Decomposition of continuum {gamma}-ray spectra using synthesized response matrix

Energy Technology Data Exchange (ETDEWEB)

Jandel, M.; Morhac, M.; Kliman, J.; Krupa, L.; Matousek, V. E-mail: vladislav.matousek@savba.sk; Hamilton, J.H.; Ramayya, A.V

2004-01-01

The efficient methods of decomposition of {gamma}-ray spectra, based on the Gold algorithm, are presented. They use a response matrix of Gammasphere, which was obtained by synthesis of simulated and interpolated response functions using a new developed interpolation algorithm. The decomposition method has been applied to the measured spectra of {sup 152}Eu and {sup 56}Co. The results show a very effective removal of the background counts and their concentration into the corresponding photopeaks. The peak-to-total ratio in the spectra achieved after applying the decomposition method is in the interval 0.95-0.99. In addition, a new advanced algorithm of the 'boosted' decomposition has been proposed. In the spectra obtained after applying the boosted decomposition to the measured spectra, very narrow photopeaks are observed with the counts concentrated to several channels.

Approximate L0 constrained Non-negative Matrix and Tensor Factorization

DEFF Research Database (Denmark)

Mørup, Morten; Madsen, Kristoffer Hougaard; Hansen, Lars Kai

2008-01-01

Non-negative matrix factorization (NMF), i.e. V = WH where both V, W and H are non-negative has become a widely used blind source separation technique due to its part based representation. The NMF decomposition is not in general unique and a part based representation not guaranteed. However...... constraint. In general, solving for a given L0 norm is an NP hard problem thus convex relaxatin to regularization by the L1 norm is often considered, i.e., minimizing ( 1/2 ||V-WHk||^2+lambda|H|_1). An open problem is to control the degree of sparsity imposed. We here demonstrate that a full regularization......, the L1 regularization strength lambda that best approximates a given L0 can be directly accessed and in effect used to control the sparsity of H. The MATLAB code for the NLARS algorithm is available for download....

An analogue of Wagner's theorem for decompositions of matrix algebras

International Nuclear Information System (INIS)

Ivanov, D N

2004-01-01

Wagner's celebrated theorem states that a finite affine plane whose collineation group is transitive on lines is a translation plane. The notion of an orthogonal decomposition (OD) of a classically semisimple associative algebra introduced by the author allows one to draw an analogy between finite affine planes of order n and ODs of the matrix algebra M n (C) into a sum of subalgebras conjugate to the diagonal subalgebra. These ODs are called WP-decompositions and are equivalent to the well-known ODs of simple Lie algebras of type A n-1 into a sum of Cartan subalgebras. In this paper we give a detailed and improved proof of the analogue of Wagner's theorem for WP-decompositions of the matrix algebra of odd non-square order an outline of which was earlier published in a short note in 'Russian Math. Surveys' in 1994. In addition, in the framework of the theory of ODs of associative algebras, based on the method of idempotent bases, we obtain an elementary proof of the well-known Kostrikin-Tiep theorem on irreducible ODs of Lie algebras of type A n-1 in the case where n is a prime-power.

A domian Decomposition Method for Transient Neutron Transport with Pomrning-Eddington Approximation

International Nuclear Information System (INIS)

Hendi, A.A.; Abulwafa, E.E.

2008-01-01

The time-dependent neutron transport problem is approximated using the Pomraning-Eddington approximation. This approximation is two-flux approximation that expands the angular intensity in terms of the energy density and the net flux. This approximation converts the integro-differential Boltzmann equation into two first order differential equations. The A domian decomposition method that used to solve the linear or nonlinear differential equations is used to solve the resultant two differential equations to find the neutron energy density and net flux, which can be used to calculate the neutron angular intensity through the Pomraning-Eddington approximation

Hierarchical Decompositions for the Computation of High-Dimensional Multivariate Normal Probabilities

KAUST Repository

Genton, Marc G.

2017-09-07

We present a hierarchical decomposition scheme for computing the n-dimensional integral of multivariate normal probabilities that appear frequently in statistics. The scheme exploits the fact that the formally dense covariance matrix can be approximated by a matrix with a hierarchical low rank structure. It allows the reduction of the computational complexity per Monte Carlo sample from O(n2) to O(mn+knlog(n/m)), where k is the numerical rank of off-diagonal matrix blocks and m is the size of small diagonal blocks in the matrix that are not well-approximated by low rank factorizations and treated as dense submatrices. This hierarchical decomposition leads to substantial efficiencies in multivariate normal probability computations and allows integrations in thousands of dimensions to be practical on modern workstations.

Hierarchical Decompositions for the Computation of High-Dimensional Multivariate Normal Probabilities

KAUST Repository

Genton, Marc G.; Keyes, David E.; Turkiyyah, George

2017-01-01

We present a hierarchical decomposition scheme for computing the n-dimensional integral of multivariate normal probabilities that appear frequently in statistics. The scheme exploits the fact that the formally dense covariance matrix can be approximated by a matrix with a hierarchical low rank structure. It allows the reduction of the computational complexity per Monte Carlo sample from O(n2) to O(mn+knlog(n/m)), where k is the numerical rank of off-diagonal matrix blocks and m is the size of small diagonal blocks in the matrix that are not well-approximated by low rank factorizations and treated as dense submatrices. This hierarchical decomposition leads to substantial efficiencies in multivariate normal probability computations and allows integrations in thousands of dimensions to be practical on modern workstations.

A Taxonomy of Latent Structure Assumptions for Probability Matrix Decomposition Models.

Science.gov (United States)

Meulders, Michel; De Boeck, Paul; Van Mechelen, Iven

2003-01-01

Proposed a taxonomy of latent structure assumptions for probability matrix decomposition (PMD) that includes the original PMD model and a three-way extension of the multiple classification latent class model. Simulation study results show the usefulness of the taxonomy. (SLD)

Subspace-Based Noise Reduction for Speech Signals via Diagonal and Triangular Matrix Decompositions

DEFF Research Database (Denmark)

Hansen, Per Christian; Jensen, Søren Holdt

We survey the definitions and use of rank-revealing matrix decompositions in single-channel noise reduction algorithms for speech signals. Our algorithms are based on the rank-reduction paradigm and, in particular, signal subspace techniques. The focus is on practical working algorithms, using both...... diagonal (eigenvalue and singular value) decompositions and rank-revealing triangular decompositions (ULV, URV, VSV, ULLV and ULLIV). In addition we show how the subspace-based algorithms can be evaluated and compared by means of simple FIR filter interpretations. The algorithms are illustrated...... with working Matlab code and applications in speech processing....

An additive matrix preconditioning method with application for domain decomposition and two-level matrix partitionings

Czech Academy of Sciences Publication Activity Database

Axelsson, Owe

2010-01-01

Roč. 5910, - (2010), s. 76-83 ISSN 0302-9743. [International Conference on Large-Scale Scientific Computations, LSSC 2009 /7./. Sozopol, 04.06.2009-08.06.2009] R&D Projects: GA AV ČR 1ET400300415 Institutional research plan: CEZ:AV0Z30860518 Keywords : additive matrix * condition number * domain decomposition Subject RIV: BA - General Mathematics www.springerlink.com

Solving network design problems via decomposition, aggregation and approximation

CERN Document Server

Bärmann, Andreas

2016-01-01

Andreas Bärmann develops novel approaches for the solution of network design problems as they arise in various contexts of applied optimization. At the example of an optimal expansion of the German railway network until 2030, the author derives a tailor-made decomposition technique for multi-period network design problems. Next, he develops a general framework for the solution of network design problems via aggregation of the underlying graph structure. This approach is shown to save much computation time as compared to standard techniques. Finally, the author devises a modelling framework for the approximation of the robust counterpart under ellipsoidal uncertainty, an often-studied case in the literature. Each of these three approaches opens up a fascinating branch of research which promises a better theoretical understanding of the problem and an increasing range of solvable application settings at the same time. Contents Decomposition for Multi-Period Network Design Solving Network Design Problems via Ag...

Rules for matrix element evaluations in JWKB approximation

International Nuclear Information System (INIS)

Giler, S.

1990-01-01

Using the properties of the so-called fundamental solutions to the one-dimensional Schroedinger equation having Froeman and Froeman form the rules are formulated which allow one to evaluate matrix elements in the JWKB approximation and its generalizations. The rules apply to operators M(x, d/dx), M being polynomial functions of their arguments. The applicability of the rules depends on the properties of the so-called canonical indices introduced in this paper. The canonical indices are global characteristics of underlying Stokes graphs. If sufficiently small in comparison with unity they allow one to apply safely the JWKB approximation within the so-called ε-reduced canonical domains of a given Stokes graph. The Oth canonical index for the nth energy level Stokes graph corresponding to the harmonic oscillator potential is found to be ε CAN = 0.678/(2n+1). If the application of the rules is allowed then approximated matrix elements are obtained in an unambiguous way and with an accuracy controlled by corresponding canonical indices. Several examples of matrix elements are considered to illustrate how the rules should be used. Limitations to the rules are also discussed with the aid of suitably chosen examples. (author)

Dielectric Matrix Formulation of Correlation Energies in the Random Phase Approximation: Inclusion of Exchange Effects.

Science.gov (United States)

Mussard, Bastien; Rocca, Dario; Jansen, Georg; Ángyán, János G

2016-05-10

Starting from the general expression for the ground state correlation energy in the adiabatic-connection fluctuation-dissipation theorem (ACFDT) framework, it is shown that the dielectric matrix formulation, which is usually applied to calculate the direct random phase approximation (dRPA) correlation energy, can be used for alternative RPA expressions including exchange effects. Within this famework, the ACFDT analog of the second order screened exchange (SOSEX) approximation leads to a logarithmic formula for the correlation energy similar to the direct RPA expression. Alternatively, the contribution of the exchange can be included in the kernel used to evaluate the response functions. In this case, the use of an approximate kernel is crucial to simplify the formalism and to obtain a correlation energy in logarithmic form. Technical details of the implementation of these methods are discussed, and it is shown that one can take advantage of density fitting or Cholesky decomposition techniques to improve the computational efficiency; a discussion on the numerical quadrature made on the frequency variable is also provided. A series of test calculations on atomic correlation energies and molecular reaction energies shows that exchange effects are instrumental for improvement over direct RPA results.

On low-rank updates to the singular value and Tucker decompositions

Energy Technology Data Exchange (ETDEWEB)

O' Hara, M J

2009-10-06

The singular value decomposition is widely used in signal processing and data mining. Since the data often arrives in a stream, the problem of updating matrix decompositions under low-rank modification has been widely studied. Brand developed a technique in 2006 that has many advantages. However, the technique does not directly approximate the updated matrix, but rather its previous low-rank approximation added to the new update, which needs justification. Further, the technique is still too slow for large information processing problems. We show that the technique minimizes the change in error per update, so if the error is small initially it remains small. We show that an updating algorithm for large sparse matrices should be sub-linear in the matrix dimension in order to be practical for large problems, and demonstrate a simple modification to the original technique that meets the requirements.

The genealogical decomposition of a matrix population model with applications to the aggregation of stages.

Science.gov (United States)

Bienvenu, François; Akçay, Erol; Legendre, Stéphane; McCandlish, David M

2017-06-01

Matrix projection models are a central tool in many areas of population biology. In most applications, one starts from the projection matrix to quantify the asymptotic growth rate of the population (the dominant eigenvalue), the stable stage distribution, and the reproductive values (the dominant right and left eigenvectors, respectively). Any primitive projection matrix also has an associated ergodic Markov chain that contains information about the genealogy of the population. In this paper, we show that these facts can be used to specify any matrix population model as a triple consisting of the ergodic Markov matrix, the dominant eigenvalue and one of the corresponding eigenvectors. This decomposition of the projection matrix separates properties associated with lineages from those associated with individuals. It also clarifies the relationships between many quantities commonly used to describe such models, including the relationship between eigenvalue sensitivities and elasticities. We illustrate the utility of such a decomposition by introducing a new method for aggregating classes in a matrix population model to produce a simpler model with a smaller number of classes. Unlike the standard method, our method has the advantage of preserving reproductive values and elasticities. It also has conceptually satisfying properties such as commuting with changes of units. Copyright © 2017 Elsevier Inc. All rights reserved.

Approximate rational Jacobi elliptic function solutions of the fractional differential equations via the enhanced Adomian decomposition method

International Nuclear Information System (INIS)

Song Lina; Wang Weiguo

2010-01-01

In this Letter, an enhanced Adomian decomposition method which introduces the h-curve of the homotopy analysis method into the standard Adomian decomposition method is proposed. Some examples prove that this method can derive successfully approximate rational Jacobi elliptic function solutions of the fractional differential equations.

Approximate Solution of LR Fuzzy Sylvester Matrix Equations

Directory of Open Access Journals (Sweden)

Xiaobin Guo

2013-01-01

Full Text Available The fuzzy Sylvester matrix equation AX~+X~B=C~ in which A,B are m×m and n×n crisp matrices, respectively, and C~ is an m×n LR fuzzy numbers matrix is investigated. Based on the Kronecker product of matrices, we convert the fuzzy Sylvester matrix equation into an LR fuzzy linear system. Then we extend the fuzzy linear system into two systems of linear equations according to the arithmetic operations of LR fuzzy numbers. The fuzzy approximate solution of the original fuzzy matrix equation is obtained by solving the crisp linear systems. The existence condition of the LR fuzzy solution is also discussed. Some examples are given to illustrate the proposed method.

Hierarchical matrix approximation of large covariance matrices

KAUST Repository

Litvinenko, Alexander; Genton, Marc G.; Sun, Ying

2015-01-01

We approximate large non-structured Matérn covariance matrices of size n×n in the H-matrix format with a log-linear computational cost and storage O(kn log n), where rank k ≪ n is a small integer. Applications are: spatial statistics, machine learning and image analysis, kriging and optimal design.

Hierarchical matrix approximation of large covariance matrices

KAUST Repository

Litvinenko, Alexander

2015-11-30

We approximate large non-structured Matérn covariance matrices of size n×n in the H-matrix format with a log-linear computational cost and storage O(kn log n), where rank k ≪ n is a small integer. Applications are: spatial statistics, machine learning and image analysis, kriging and optimal design.

Unambiguous results from variational matrix Pade approximants

International Nuclear Information System (INIS)

Pindor, Maciej.

1979-10-01

Variational Matrix Pade Approximants are studied as a nonlinear variational problem. It is shown that although a stationary value of the Schwinger functional is a stationary value of VMPA, the latter has also another stationary value. It is therefore proposed that instead of looking for a stationary point of VMPA, one minimizes some non-negative functional and then one calculates VMPA at the point where the former has the absolute minimum. This approach, which we call the Method of the Variational Gradient (MVG) gives unambiguous results and is also shown to minimize a distance between the approximate and the exact stationary values of the Schwinger functional

Subspace-Based Noise Reduction for Speech Signals via Diagonal and Triangular Matrix Decompositions

DEFF Research Database (Denmark)

Hansen, Per Christian; Jensen, Søren Holdt

2007-01-01

We survey the definitions and use of rank-revealing matrix decompositions in single-channel noise reduction algorithms for speech signals. Our algorithms are based on the rank-reduction paradigm and, in particular, signal subspace techniques. The focus is on practical working algorithms, using both...... with working Matlab code and applications in speech processing....

Decomposition of spectra in EPR dosimetry using the matrix method

International Nuclear Information System (INIS)

Sholom, S.V.; Chumak, V.V.

2003-01-01

The matrix method of EPR spectra decomposition is developed and adapted for routine application in retrospective EPR dosimetry with teeth. According to this method, the initial EPR spectra are decomposed (using methods of matrix algebra) into several reference components (reference matrices) that are specific for each material. Proposed procedure has been tested on the example of tooth enamel. Reference spectra were a spectrum of an empty sample tube and three standard signals of enamel (two at g=2.0045, both for the native signal and one at g perpendicular =2.0018, g parallel =1.9973 for the dosimetric signal). Values of dosimetric signals obtained using the given method have been compared with data obtained by manual manipulation of spectra, and good coincidence was observed. This allows considering the proposed method as potent for application in routine EPR dosimetry

Least-Squares Approximation of an Improper Correlation Matrix by a Proper One.

Science.gov (United States)

Knol, Dirk L.; ten Berge, Jos M. F.

1989-01-01

An algorithm, based on a solution for C. I. Mosier's oblique Procrustes rotation problem, is presented for the best least-squares fitting correlation matrix approximating a given missing value or improper correlation matrix. Results are of interest for missing value and tetrachoric correlation, indefinite matrix correlation, and constrained…

Multidisciplinary Product Decomposition and Analysis Based on Design Structure Matrix Modeling

DEFF Research Database (Denmark)

Habib, Tufail

2014-01-01

Design structure matrix (DSM) modeling in complex system design supports to define physical and logical configuration of subsystems, components, and their relationships. This modeling includes product decomposition, identification of interfaces, and structure analysis to increase the architectural...... interactions across subsystems and components. For this purpose, Cambridge advanced modeler (CAM) software tool is used to develop the system matrix. The analysis of the product (printer) architecture includes clustering, partitioning as well as structure analysis of the system. The DSM analysis is helpful...... understanding of the system. Since product architecture has broad implications in relation to product life cycle issues, in this paper, mechatronic product is decomposed into subsystems and components, and then, DSM model is developed to examine the extent of modularity in the system and to manage multiple...

A variational approach to operator and matrix Pade approximation. Applications to potential scattering and field theory

International Nuclear Information System (INIS)

Mery, P.

1977-01-01

The operator and matrix Pade approximation are defined. The fact that these approximants can be derived from the Schwinger variational principle is emphasized. In potential theory, using this variational aspect it is shown that the matrix Pade approximation allow to reproduce the exact solution of the Lippman-Schwinger equation with any required accuracy taking only into account the knowledge of the first two coefficients in the Born expansion. The deep analytic structure of this variational matrix Pade approximation (hyper Pade approximation) is discussed

On Best Approximations of Polynomials in Matrices in the Matrix 2-Norm

Czech Academy of Sciences Publication Activity Database

Liesen, J.; Tichý, Petr

2009-01-01

Roč. 31, č. 2 (2009), s. 853-863 ISSN 0895-4798 R&D Projects: GA AV ČR IAA100300802 Institutional research plan: CEZ:AV0Z10300504 Keywords : matrix approximation problems * polynomials in matrices * matrix functions * matrix 2-norm * GMRES * Arnoldi's method Subject RIV: BA - General Mathematics Impact factor: 2.411, year: 2009

Error Decomposition and Adaptivity for Response Surface Approximations from PDEs with Parametric Uncertainty

KAUST Repository

Bryant, C. M.; Prudhomme, S.; Wildey, T.

2015-01-01

In this work, we investigate adaptive approaches to control errors in response surface approximations computed from numerical approximations of differential equations with uncertain or random data and coefficients. The adaptivity of the response surface approximation is based on a posteriori error estimation, and the approach relies on the ability to decompose the a posteriori error estimate into contributions from the physical discretization and the approximation in parameter space. Errors are evaluated in terms of linear quantities of interest using adjoint-based methodologies. We demonstrate that a significant reduction in the computational cost required to reach a given error tolerance can be achieved by refining the dominant error contributions rather than uniformly refining both the physical and stochastic discretization. Error decomposition is demonstrated for a two-dimensional flow problem, and adaptive procedures are tested on a convection-diffusion problem with discontinuous parameter dependence and a diffusion problem, where the diffusion coefficient is characterized by a 10-dimensional parameter space.

Finding all real roots of a polynomial by matrix algebra and the Adomian decomposition method

Directory of Open Access Journals (Sweden)

Hooman Fatoorehchi

2014-10-01

Full Text Available In this paper, we put forth a combined method for calculation of all real zeroes of a polynomial equation through the Adomian decomposition method equipped with a number of developed theorems from matrix algebra. These auxiliary theorems are associated with eigenvalues of matrices and enable convergence of the Adomian decomposition method toward different real roots of the target polynomial equation. To further improve the computational speed of our technique, a nonlinear convergence accelerator known as the Shanks transform has optionally been employed. For the sake of illustration, a number of numerical examples are given.

Grassmann integral and Balian–Brézin decomposition in Hartree–Fock–Bogoliubov matrix elements

Energy Technology Data Exchange (ETDEWEB)

Mizusaki, Takahiro, E-mail: mizusaki@isc.senshu-u.ac.jp [Institute of Natural Sciences, Senshu University, 3-8-1 Kanda-Jinbocho, Chiyoda-ku, Tokyo 101-8425 (Japan); Oi, Makito [Institute of Natural Sciences, Senshu University, 3-8-1 Kanda-Jinbocho, Chiyoda-ku, Tokyo 101-8425 (Japan); Chen, Fang-Qi [Department of Physics and Astronomy, Shanghai Jiao Tong University, Shanghai 200240 (China); Sun, Yang [Department of Physics and Astronomy, Shanghai Jiao Tong University, Shanghai 200240 (China); Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou 730000 (China)

2013-08-09

We present a new formula to calculate matrix elements of a general unitary operator with respect to Hartree–Fock–Bogoliubov states allowing multiple quasi-particle excitations. The Balian–Brézin decomposition of the unitary operator [R. Balian, E. Brézin, Il Nuovo Cimento B 64 (1969) 37] is employed in the derivation. We found that this decomposition is extremely suitable for an application of Fermion coherent state and Grassmann integrals in the quasi-particle basis. The resultant formula is compactly expressed in terms of the Pfaffian, and shows the similar bipartite structure to the formula that we have previously derived in the bare-particles basis [T. Mizusaki, M. Oi, Phys. Lett. B 715 (2012) 219].

S-AMP: Approximate Message Passing for General Matrix Ensembles

DEFF Research Database (Denmark)

Cakmak, Burak; Winther, Ole; Fleury, Bernard H.

2014-01-01

the approximate message-passing (AMP) algorithm to general matrix ensembles with a well-defined large system size limit. The generalization is based on the S-transform (in free probability) of the spectrum of the measurement matrix. Furthermore, we show that the optimality of S-AMP follows directly from its......We propose a novel iterative estimation algorithm for linear observation models called S-AMP. The fixed points of S-AMP are the stationary points of the exact Gibbs free energy under a set of (first- and second-) moment consistency constraints in the large system limit. S-AMP extends...

Least-squares approximation of an improper correlation matrix by a proper one

NARCIS (Netherlands)

Knol, Dirk L.; ten Berge, Jos M.F.

1989-01-01

An algorithm is presented for the best least-squares fitting correlation matrix approximating a given missing value or improper correlation matrix. The proposed algorithm is based upon a solution for Mosier's oblique Procrustes rotation problem offered by ten Berge and Nevels. A necessary and

Systems-based decomposition schemes for the approximate solution of multi-term fractional differential equations

Science.gov (United States)

Ford, Neville J.; Connolly, Joseph A.

2009-07-01

We give a comparison of the efficiency of three alternative decomposition schemes for the approximate solution of multi-term fractional differential equations using the Caputo form of the fractional derivative. The schemes we compare are based on conversion of the original problem into a system of equations. We review alternative approaches and consider how the most appropriate numerical scheme may be chosen to solve a particular equation.

Approximate Analytic Solutions for the Two-Phase Stefan Problem Using the Adomian Decomposition Method

Directory of Open Access Journals (Sweden)

Xiao-Ying Qin

2014-01-01

Full Text Available An Adomian decomposition method (ADM is applied to solve a two-phase Stefan problem that describes the pure metal solidification process. In contrast to traditional analytical methods, ADM avoids complex mathematical derivations and does not require coordinate transformation for elimination of the unknown moving boundary. Based on polynomial approximations for some known and unknown boundary functions, approximate analytic solutions for the model with undetermined coefficients are obtained using ADM. Substitution of these expressions into other equations and boundary conditions of the model generates some function identities with the undetermined coefficients. By determining these coefficients, approximate analytic solutions for the model are obtained. A concrete example of the solution shows that this method can easily be implemented in MATLAB and has a fast convergence rate. This is an efficient method for finding approximate analytic solutions for the Stefan and the inverse Stefan problems.

Extended Krylov subspaces approximations of matrix functions. Application to computational electromagnetics

Energy Technology Data Exchange (ETDEWEB)

Druskin, V.; Lee, Ping [Schlumberger-Doll Research, Ridgefield, CT (United States); Knizhnerman, L. [Central Geophysical Expedition, Moscow (Russian Federation)

1996-12-31

There is now a growing interest in the area of using Krylov subspace approximations to compute the actions of matrix functions. The main application of this approach is the solution of ODE systems, obtained after discretization of partial differential equations by method of lines. In the event that the cost of computing the matrix inverse is relatively inexpensive, it is sometimes attractive to solve the ODE using the extended Krylov subspaces, originated by actions of both positive and negative matrix powers. Examples of such problems can be found frequently in computational electromagnetics.

Number-conserving random phase approximation with analytically integrated matrix elements

International Nuclear Information System (INIS)

Kyotoku, M.; Schmid, K.W.; Gruemmer, F.; Faessler, A.

1990-01-01

In the present paper a number conserving random phase approximation is derived as a special case of the recently developed random phase approximation in general symmetry projected quasiparticle mean fields. All the occurring integrals induced by the number projection are performed analytically after writing the various overlap and energy matrices in the random phase approximation equation as polynomials in the gauge angle. In the limit of a large number of particles the well-known pairing vibration matrix elements are recovered. We also present a new analytically number projected variational equation for the number conserving pairing problem

Random matrix theory and acoustic resonances in plates with an approximate symmetry

DEFF Research Database (Denmark)

Andersen, Anders Peter; Ellegaard, C.; Jackson, A.D.

2001-01-01

We discuss a random matrix model of systems with an approximate symmetry and present the spectral fluctuation statistics and eigenvector characteristics for the model. An acoustic resonator like, e.g., an aluminum plate may have an approximate symmetry. We have measured the frequency spectrum and...

Multilinear operators for higher-order decompositions.

Energy Technology Data Exchange (ETDEWEB)

Kolda, Tamara Gibson

2006-04-01

We propose two new multilinear operators for expressing the matrix compositions that are needed in the Tucker and PARAFAC (CANDECOMP) decompositions. The first operator, which we call the Tucker operator, is shorthand for performing an n-mode matrix multiplication for every mode of a given tensor and can be employed to concisely express the Tucker decomposition. The second operator, which we call the Kruskal operator, is shorthand for the sum of the outer-products of the columns of N matrices and allows a divorce from a matricized representation and a very concise expression of the PARAFAC decomposition. We explore the properties of the Tucker and Kruskal operators independently of the related decompositions. Additionally, we provide a review of the matrix and tensor operations that are frequently used in the context of tensor decompositions.

Approximate Analytical Solutions for Mathematical Model of Tumour Invasion and Metastasis Using Modified Adomian Decomposition and Homotopy Perturbation Methods

Directory of Open Access Journals (Sweden)

Norhasimah Mahiddin

2014-01-01

Full Text Available The modified decomposition method (MDM and homotopy perturbation method (HPM are applied to obtain the approximate solution of the nonlinear model of tumour invasion and metastasis. The study highlights the significant features of the employed methods and their ability to handle nonlinear partial differential equations. The methods do not need linearization and weak nonlinearity assumptions. Although the main difference between MDM and Adomian decomposition method (ADM is a slight variation in the definition of the initial condition, modification eliminates massive computation work. The approximate analytical solution obtained by MDM logically contains the solution obtained by HPM. It shows that HPM does not involve the Adomian polynomials when dealing with nonlinear problems.

Four-Component Scattering Power Decomposition Algorithm with Rotation of Covariance Matrix Using ALOS-PALSAR Polarimetric Data

Directory of Open Access Journals (Sweden)

Yasuhiro Nakamura

2012-07-01

Full Text Available The present study introduces the four-component scattering power decomposition (4-CSPD algorithm with rotation of covariance matrix, and presents an experimental proof of the equivalence between the 4-CSPD algorithms based on rotation of covariance matrix and coherency matrix. From a theoretical point of view, the 4-CSPD algorithms with rotation of the two matrices are identical. Although it seems obvious, no experimental evidence has yet been presented. In this paper, using polarimetric synthetic aperture radar (POLSAR data acquired by Phased Array L-band SAR (PALSAR on board of Advanced Land Observing Satellite (ALOS, an experimental proof is presented to show that both algorithms indeed produce identical results.

Note on Symplectic SVD-Like Decomposition

Directory of Open Access Journals (Sweden)

AGOUJIL Said

2016-02-01

Full Text Available The aim of this study was to introduce a constructive method to compute a symplectic singular value decomposition (SVD-like decomposition of a 2n-by-m rectangular real matrix A, based on symplectic refectors.This approach used a canonical Schur form of skew-symmetric matrix and it allowed us to compute eigenvalues for the structured matrices as Hamiltonian matrix JAA^T.

Implementation of the CCGM approximation for surface diffraction using Wigner R-matrix theory

International Nuclear Information System (INIS)

Lauderdale, J.G.; McCurdy, C.W.

1983-01-01

The CCGM approximation for surface scattering proposed by Cabrera, Celli, Goodman, and Manson [Surf. Sci. 19, 67 (1970)] is implemented for realistic surface interaction potentials using Wigner R-matrix theory. The resulting procedure is highly efficient computationally and is in no way limited to hard wall or purely repulsive potentials. Comparison is made with the results of close-coupling calculations of other workers which include the same diffraction channels in order to fairly evaluate the CCGM approximation which is an approximation to the coupled channels Lippman--Schwinger equation for the T matrix. The shapes of selective adsorption features, whether maxima or minima, in the scattered intensity are well represented in this approach for cases in which the surface corrugation is not too strong

Singular value decomposition for collaborative filtering on a GPU

Science.gov (United States)

Kato, Kimikazu; Hosino, Tikara

2010-06-01

A collaborative filtering predicts customers' unknown preferences from known preferences. In a computation of the collaborative filtering, a singular value decomposition (SVD) is needed to reduce the size of a large scale matrix so that the burden for the next phase computation will be decreased. In this application, SVD means a roughly approximated factorization of a given matrix into smaller sized matrices. Webb (a.k.a. Simon Funk) showed an effective algorithm to compute SVD toward a solution of an open competition called "Netflix Prize". The algorithm utilizes an iterative method so that the error of approximation improves in each step of the iteration. We give a GPU version of Webb's algorithm. Our algorithm is implemented in the CUDA and it is shown to be efficient by an experiment.

Singular value decomposition for collaborative filtering on a GPU

International Nuclear Information System (INIS)

Kato, Kimikazu; Hosino, Tikara

2010-01-01

A collaborative filtering predicts customers' unknown preferences from known preferences. In a computation of the collaborative filtering, a singular value decomposition (SVD) is needed to reduce the size of a large scale matrix so that the burden for the next phase computation will be decreased. In this application, SVD means a roughly approximated factorization of a given matrix into smaller sized matrices. Webb (a.k.a. Simon Funk) showed an effective algorithm to compute SVD toward a solution of an open competition called 'Netflix Prize'. The algorithm utilizes an iterative method so that the error of approximation improves in each step of the iteration. We give a GPU version of Webb's algorithm. Our algorithm is implemented in the CUDA and it is shown to be efficient by an experiment.

Calculations of the properties of superconducting alloys via the average T-matrix approximation

International Nuclear Information System (INIS)

Chatterjee, P.

1980-01-01

The theoretical formula of McMillan, modified via the multiple-scattering theory by Gomersall and Gyorffy, has been very successful in computing the electron-phonon coupling constant (lambda) and the transition temperature (Tsub(c)) of many superconducting elements and compounds. For disordered solids, such as substitutional alloys, however, this theory fails because of the breakdown of the translational symmetry used in the multiple-scattering theory. Under these conditions the problem can still be solved if the t-matrix is averaged in the random phase approximation (average T-matrix approximation). Gomersall and Gyorffy's expression is reformulated for lambda in the random phase approximation. This theory is applied to calculate lambda and Tsub(c) of the binary substitutional NbMo alloy system at different concentrations. The results appear to be in fair agreement with experiments. (author)

Case report: Time of death estimation of a buried body by modeling a decomposition matrix for a pig carcass.

Science.gov (United States)

Niederegger, Senta; Schermer, Julia; Höfig, Juliane; Mall, Gita

2015-01-01

Estimating time of death of buried human bodies is a very difficult task. Casper's rule from 1860 is still widely used which illustrates the lack of suitable methods. In this case study excavations in an arbor revealed the crouching body of a human being, dressed only in boxer shorts and socks. Witnesses were not able to generate a concise answer as to when the person in question was last seen alive; the pieces of information opened a window of 2-6 weeks for the possible time of death. To determine the post mortem interval (PMI) an experiment using a pig carcass was conducted to set up a decomposition matrix. Fitting the autopsy findings of the victim into the decomposition matrix yielded a time of death estimation of 2-3 weeks. This time frame was later confirmed by a new witness. The authors feel confident that a widespread conduction of decomposition matrices using pig carcasses can lead to a great increase of experience and knowledge in PMI estimation of buried bodies and will eventually lead to applicable new methods. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Improving residue-residue contact prediction via low-rank and sparse decomposition of residue correlation matrix.

Science.gov (United States)

Zhang, Haicang; Gao, Yujuan; Deng, Minghua; Wang, Chao; Zhu, Jianwei; Li, Shuai Cheng; Zheng, Wei-Mou; Bu, Dongbo

2016-03-25

Strategies for correlation analysis in protein contact prediction often encounter two challenges, namely, the indirect coupling among residues, and the background correlations mainly caused by phylogenetic biases. While various studies have been conducted on how to disentangle indirect coupling, the removal of background correlations still remains unresolved. Here, we present an approach for removing background correlations via low-rank and sparse decomposition (LRS) of a residue correlation matrix. The correlation matrix can be constructed using either local inference strategies (e.g., mutual information, or MI) or global inference strategies (e.g., direct coupling analysis, or DCA). In our approach, a correlation matrix was decomposed into two components, i.e., a low-rank component representing background correlations, and a sparse component representing true correlations. Finally the residue contacts were inferred from the sparse component of correlation matrix. We trained our LRS-based method on the PSICOV dataset, and tested it on both GREMLIN and CASP11 datasets. Our experimental results suggested that LRS significantly improves the contact prediction precision. For example, when equipped with the LRS technique, the prediction precision of MI and mfDCA increased from 0.25 to 0.67 and from 0.58 to 0.70, respectively (Top L/10 predicted contacts, sequence separation: 5 AA, dataset: GREMLIN). In addition, our LRS technique also consistently outperforms the popular denoising technique APC (average product correction), on both local (MI_LRS: 0.67 vs MI_APC: 0.34) and global measures (mfDCA_LRS: 0.70 vs mfDCA_APC: 0.67). Interestingly, we found out that when equipped with our LRS technique, local inference strategies performed in a comparable manner to that of global inference strategies, implying that the application of LRS technique narrowed down the performance gap between local and global inference strategies. Overall, our LRS technique greatly facilitates

Algorithm 589. SICEDR: a FORTRAN subroutine for improving the accuracy of computed matrix eigenvalues

International Nuclear Information System (INIS)

Dongarra, J.J.

1982-01-01

SICEDR is a FORTRAN subroutine for improving the accuracy of a computed real eigenvalue and improving or computing the associated eigenvector. It is first used to generate information during the determination of the eigenvalues by the Schur decomposition technique. In particular, the Schur decomposition technique results in an orthogonal matrix Q and an upper quasi-triangular matrix T, such that A = QTQ/sup T/. Matrices A, Q, and T and the approximate eigenvalue, say lambda, are then used in the improvement phase. SICEDR uses an iterative method similar to iterative improvement for linear systems to improve the accuracy of lambda and improve or compute the eigenvector x in O(n 2 ) work, where n is the order of the matrix A

Technique for information retrieval using enhanced latent semantic analysis generating rank approximation matrix by factorizing the weighted morpheme-by-document matrix

Science.gov (United States)

Chew, Peter A; Bader, Brett W

2012-10-16

A technique for information retrieval includes parsing a corpus to identify a number of wordform instances within each document of the corpus. A weighted morpheme-by-document matrix is generated based at least in part on the number of wordform instances within each document of the corpus and based at least in part on a weighting function. The weighted morpheme-by-document matrix separately enumerates instances of stems and affixes. Additionally or alternatively, a term-by-term alignment matrix may be generated based at least in part on the number of wordform instances within each document of the corpus. At least one lower rank approximation matrix is generated by factorizing the weighted morpheme-by-document matrix and/or the term-by-term alignment matrix.

Representing Matrix Cracks Through Decomposition of the Deformation Gradient Tensor in Continuum Damage Mechanics Methods

Science.gov (United States)

Leone, Frank A., Jr.

2015-01-01

A method is presented to represent the large-deformation kinematics of intraply matrix cracks and delaminations in continuum damage mechanics (CDM) constitutive material models. The method involves the additive decomposition of the deformation gradient tensor into 'crack' and 'bulk material' components. The response of the intact bulk material is represented by a reduced deformation gradient tensor, and the opening of an embedded cohesive interface is represented by a normalized cohesive displacement-jump vector. The rotation of the embedded interface is tracked as the material deforms and as the crack opens. The distribution of the total local deformation between the bulk material and the cohesive interface components is determined by minimizing the difference between the cohesive stress and the bulk material stress projected onto the cohesive interface. The improvements to the accuracy of CDM models that incorporate the presented method over existing approaches are demonstrated for a single element subjected to simple shear deformation and for a finite element model of a unidirectional open-hole tension specimen. The material model is implemented as a VUMAT user subroutine for the Abaqus/Explicit finite element software. The presented deformation gradient decomposition method reduces the artificial load transfer across matrix cracks subjected to large shearing deformations, and avoids the spurious secondary failure modes that often occur in analyses based on conventional progressive damage models.

Correlation effects beyond coupled cluster singles and doubles approximation through Fock matrix dressing.

Science.gov (United States)

Maitra, Rahul; Nakajima, Takahito

2017-11-28

We present an accurate single reference coupled cluster theory in which the conventional Fock operator matrix is suitably dressed to simulate the effect of triple and higher excitations within a singles and doubles framework. The dressing thus invoked originates from a second-order perturbative approximation of a similarity transformed Hamiltonian and induces higher rank excitations through local renormalization of individual occupied and unoccupied orbital lines. Such a dressing is able to recover a significant amount of correlation effects beyond singles and doubles approximation, but only with an economic n 5 additional cost. Due to the inclusion of higher rank excitations via the Fock matrix dressing, this method is a natural improvement over conventional coupled cluster theory with singles and doubles approximation, and this method would be demonstrated via applications on some challenging systems. This highly promising scheme has a conceptually simple structure which is also easily generalizable to a multi-reference coupled cluster scheme for treating strong degeneracy. We shall demonstrate that this method is a natural lowest order perturbative approximation to the recently developed iterative n-body excitation inclusive coupled cluster singles and doubles scheme [R. Maitra et al., J. Chem. Phys. 147, 074103 (2017)].

Real-time dynamics of matrix quantum mechanics beyond the classical approximation

Science.gov (United States)

Buividovich, Pavel; Hanada, Masanori; Schäfer, Andreas

2018-03-01

We describe a numerical method which allows to go beyond the classical approximation for the real-time dynamics of many-body systems by approximating the many-body Wigner function by the most general Gaussian function with time-dependent mean and dispersion. On a simple example of a classically chaotic system with two degrees of freedom we demonstrate that this Gaussian state approximation is accurate for significantly smaller field strengths and longer times than the classical one. Applying this approximation to matrix quantum mechanics, we demonstrate that the quantum Lyapunov exponents are in general smaller than their classical counterparts, and even seem to vanish below some temperature. This behavior resembles the finite-temperature phase transition which was found for this system in Monte-Carlo simulations, and ensures that the system does not violate the Maldacena-Shenker-Stanford bound λL < 2πT, which inevitably happens for classical dynamics at sufficiently small temperatures.

A rational approximation to Reich-Moore collision matrix of non-fissile nuclides

International Nuclear Information System (INIS)

Devan, K.; Keshavamurthy, R.S.

1999-01-01

The cross sections of many important nuclides are represented in Reich-Moore (RM) formalism in the recent American Evaluated Nuclear Data file, ENDF/B-VI. Processing of cross sections with RM resonance parameters is much more difficult than the other multilevel formalisms such as MLBW and Adler-Adler. In this paper, we derive a rational approximation to the RM collision matrix in the vicinity of a resonance. This simplifies the cross section processing. The energy range of the validity of this approximation in the vicinity of a resonance is also derived. Choosing Ni 58 as an example, results of our approximation for a non-fissile nuclide are given for two typical s-wave resonances. Our rational approximation method is found to work with good accuracies in the vicinity of resonances

Sparse and smooth canonical correlation analysis through rank-1 matrix approximation

Science.gov (United States)

Aïssa-El-Bey, Abdeldjalil; Seghouane, Abd-Krim

2017-12-01

Canonical correlation analysis (CCA) is a well-known technique used to characterize the relationship between two sets of multidimensional variables by finding linear combinations of variables with maximal correlation. Sparse CCA and smooth or regularized CCA are two widely used variants of CCA because of the improved interpretability of the former and the better performance of the later. So far, the cross-matrix product of the two sets of multidimensional variables has been widely used for the derivation of these variants. In this paper, two new algorithms for sparse CCA and smooth CCA are proposed. These algorithms differ from the existing ones in their derivation which is based on penalized rank-1 matrix approximation and the orthogonal projectors onto the space spanned by the two sets of multidimensional variables instead of the simple cross-matrix product. The performance and effectiveness of the proposed algorithms are tested on simulated experiments. On these results, it can be observed that they outperform the state of the art sparse CCA algorithms.

Domain decomposition method for nonconforming finite element approximations of anisotropic elliptic problems on nonmatching grids

Energy Technology Data Exchange (ETDEWEB)

Maliassov, S.Y. [Texas A& M Univ., College Station, TX (United States)

1996-12-31

An approach to the construction of an iterative method for solving systems of linear algebraic equations arising from nonconforming finite element discretizations with nonmatching grids for second order elliptic boundary value problems with anisotropic coefficients is considered. The technique suggested is based on decomposition of the original domain into nonoverlapping subdomains. The elliptic problem is presented in the macro-hybrid form with Lagrange multipliers at the interfaces between subdomains. A block diagonal preconditioner is proposed which is spectrally equivalent to the original saddle point matrix and has the optimal order of arithmetical complexity. The preconditioner includes blocks for preconditioning subdomain and interface problems. It is shown that constants of spectral equivalence axe independent of values of coefficients and mesh step size.

Canonical polyadic decomposition of third-order semi-nonnegative semi-symmetric tensors using LU and QR matrix factorizations

Science.gov (United States)

Wang, Lu; Albera, Laurent; Kachenoura, Amar; Shu, Huazhong; Senhadji, Lotfi

2014-12-01

Semi-symmetric three-way arrays are essential tools in blind source separation (BSS) particularly in independent component analysis (ICA). These arrays can be built by resorting to higher order statistics of the data. The canonical polyadic (CP) decomposition of such semi-symmetric three-way arrays allows us to identify the so-called mixing matrix, which contains the information about the intensities of some latent source signals present in the observation channels. In addition, in many applications, such as the magnetic resonance spectroscopy (MRS), the columns of the mixing matrix are viewed as relative concentrations of the spectra of the chemical components. Therefore, the two loading matrices of the three-way array, which are equal to the mixing matrix, are nonnegative. Most existing CP algorithms handle the symmetry and the nonnegativity separately. Up to now, very few of them consider both the semi-nonnegativity and the semi-symmetry structure of the three-way array. Nevertheless, like all the methods based on line search, trust region strategies, and alternating optimization, they appear to be dependent on initialization, requiring in practice a multi-initialization procedure. In order to overcome this drawback, we propose two new methods, called [InlineEquation not available: see fulltext.] and [InlineEquation not available: see fulltext.], to solve the problem of CP decomposition of semi-nonnegative semi-symmetric three-way arrays. Firstly, we rewrite the constrained optimization problem as an unconstrained one. In fact, the nonnegativity constraint of the two symmetric modes is ensured by means of a square change of variable. Secondly, a Jacobi-like optimization procedure is adopted because of its good convergence property. More precisely, the two new methods use LU and QR matrix factorizations, respectively, which consist in formulating high-dimensional optimization problems into several sequential polynomial and rational subproblems. By using both LU

Separable decompositions of bipartite mixed states

Science.gov (United States)

Li, Jun-Li; Qiao, Cong-Feng

2018-04-01

We present a practical scheme for the decomposition of a bipartite mixed state into a sum of direct products of local density matrices, using the technique developed in Li and Qiao (Sci. Rep. 8:1442, 2018). In the scheme, the correlation matrix which characterizes the bipartite entanglement is first decomposed into two matrices composed of the Bloch vectors of local states. Then, we show that the symmetries of Bloch vectors are consistent with that of the correlation matrix, and the magnitudes of the local Bloch vectors are lower bounded by the correlation matrix. Concrete examples for the separable decompositions of bipartite mixed states are presented for illustration.

Eigenvalue Decomposition-Based Modified Newton Algorithm

Directory of Open Access Journals (Sweden)

Wen-jun Wang

2013-01-01

Full Text Available When the Hessian matrix is not positive, the Newton direction may not be the descending direction. A new method named eigenvalue decomposition-based modified Newton algorithm is presented, which first takes the eigenvalue decomposition of the Hessian matrix, then replaces the negative eigenvalues with their absolute values, and finally reconstructs the Hessian matrix and modifies the searching direction. The new searching direction is always the descending direction. The convergence of the algorithm is proven and the conclusion on convergence rate is presented qualitatively. Finally, a numerical experiment is given for comparing the convergence domains of the modified algorithm and the classical algorithm.

Exchange-correlation energy from pairing matrix fluctuation and the particle-particle random phase approximation.

Science.gov (United States)

van Aggelen, Helen; Yang, Yang; Yang, Weitao

2014-05-14

Despite their unmatched success for many applications, commonly used local, semi-local, and hybrid density functionals still face challenges when it comes to describing long-range interactions, static correlation, and electron delocalization. Density functionals of both the occupied and virtual orbitals are able to address these problems. The particle-hole (ph-) Random Phase Approximation (RPA), a functional of occupied and virtual orbitals, has recently known a revival within the density functional theory community. Following up on an idea introduced in our recent communication [H. van Aggelen, Y. Yang, and W. Yang, Phys. Rev. A 88, 030501 (2013)], we formulate more general adiabatic connections for the correlation energy in terms of pairing matrix fluctuations described by the particle-particle (pp-) propagator. With numerical examples of the pp-RPA, the lowest-order approximation to the pp-propagator, we illustrate the potential of density functional approximations based on pairing matrix fluctuations. The pp-RPA is size-extensive, self-interaction free, fully anti-symmetric, describes the strong static correlation limit in H2, and eliminates delocalization errors in H2(+) and other single-bond systems. It gives surprisingly good non-bonded interaction energies--competitive with the ph-RPA--with the correct R(-6) asymptotic decay as a function of the separation R, which we argue is mainly attributable to its correct second-order energy term. While the pp-RPA tends to underestimate absolute correlation energies, it gives good relative energies: much better atomization energies than the ph-RPA, as it has no tendency to underbind, and reaction energies of similar quality. The adiabatic connection in terms of pairing matrix fluctuation paves the way for promising new density functional approximations.

Exchange-correlation energy from pairing matrix fluctuation and the particle-particle random phase approximation

International Nuclear Information System (INIS)

Aggelen, Helen van; Yang, Yang; Yang, Weitao

2014-01-01

Despite their unmatched success for many applications, commonly used local, semi-local, and hybrid density functionals still face challenges when it comes to describing long-range interactions, static correlation, and electron delocalization. Density functionals of both the occupied and virtual orbitals are able to address these problems. The particle-hole (ph-) Random Phase Approximation (RPA), a functional of occupied and virtual orbitals, has recently known a revival within the density functional theory community. Following up on an idea introduced in our recent communication [H. van Aggelen, Y. Yang, and W. Yang, Phys. Rev. A 88, 030501 (2013)], we formulate more general adiabatic connections for the correlation energy in terms of pairing matrix fluctuations described by the particle-particle (pp-) propagator. With numerical examples of the pp-RPA, the lowest-order approximation to the pp-propagator, we illustrate the potential of density functional approximations based on pairing matrix fluctuations. The pp-RPA is size-extensive, self-interaction free, fully anti-symmetric, describes the strong static correlation limit in H 2 , and eliminates delocalization errors in H 2 + and other single-bond systems. It gives surprisingly good non-bonded interaction energies – competitive with the ph-RPA – with the correct R −6 asymptotic decay as a function of the separation R, which we argue is mainly attributable to its correct second-order energy term. While the pp-RPA tends to underestimate absolute correlation energies, it gives good relative energies: much better atomization energies than the ph-RPA, as it has no tendency to underbind, and reaction energies of similar quality. The adiabatic connection in terms of pairing matrix fluctuation paves the way for promising new density functional approximations

A Parallel Non-Overlapping Domain-Decomposition Algorithm for Compressible Fluid Flow Problems on Triangulated Domains

Science.gov (United States)

Barth, Timothy J.; Chan, Tony F.; Tang, Wei-Pai

1998-01-01

This paper considers an algebraic preconditioning algorithm for hyperbolic-elliptic fluid flow problems. The algorithm is based on a parallel non-overlapping Schur complement domain-decomposition technique for triangulated domains. In the Schur complement technique, the triangulation is first partitioned into a number of non-overlapping subdomains and interfaces. This suggests a reordering of triangulation vertices which separates subdomain and interface solution unknowns. The reordering induces a natural 2 x 2 block partitioning of the discretization matrix. Exact LU factorization of this block system yields a Schur complement matrix which couples subdomains and the interface together. The remaining sections of this paper present a family of approximate techniques for both constructing and applying the Schur complement as a domain-decomposition preconditioner. The approximate Schur complement serves as an algebraic coarse space operator, thus avoiding the known difficulties associated with the direct formation of a coarse space discretization. In developing Schur complement approximations, particular attention has been given to improving sequential and parallel efficiency of implementations without significantly degrading the quality of the preconditioner. A computer code based on these developments has been tested on the IBM SP2 using MPI message passing protocol. A number of 2-D calculations are presented for both scalar advection-diffusion equations as well as the Euler equations governing compressible fluid flow to demonstrate performance of the preconditioning algorithm.

Time dependent mean field approximation to the many-body S-matrix

International Nuclear Information System (INIS)

Alhassid, Y.; Koonin, S.E.

1980-01-01

Time-dependent Hartree-Fock (TDHF) calculations are a good description of some inclusive properties of deep inelastic heavy-ion collisions. The first steps toward a mean-field theory that approximates specific elements of the many-body S matrix are presented. A many-body system with pairwise interactions excited by an external, time-dependent one-body field is considered. The methods are used to solve the forced Lipkin model. The moduli of elastic and excitation amplitudes are plotted. 3 figures

Clustering via Kernel Decomposition

DEFF Research Database (Denmark)

Have, Anna Szynkowiak; Girolami, Mark A.; Larsen, Jan

2006-01-01

Methods for spectral clustering have been proposed recently which rely on the eigenvalue decomposition of an affinity matrix. In this work it is proposed that the affinity matrix is created based on the elements of a non-parametric density estimator. This matrix is then decomposed to obtain...... posterior probabilities of class membership using an appropriate form of nonnegative matrix factorization. The troublesome selection of hyperparameters such as kernel width and number of clusters can be obtained using standard cross-validation methods as is demonstrated on a number of diverse data sets....

Numerical solution of matrix exponential in burn-up equation using mini-max polynomial approximation

International Nuclear Information System (INIS)

Kawamoto, Yosuke; Chiba, Go; Tsuji, Masashi; Narabayashi, Tadashi

2015-01-01

Highlights: • We propose a new numerical solution of matrix exponential in burn-up depletion calculations. • The depletion calculation with extremely short half-lived nuclides can be done numerically stable with this method. • The computational time is shorter than the other conventional methods. - Abstract: Nuclear fuel burn-up depletion calculations are essential to compute the nuclear fuel composition transition. In the burn-up calculations, the matrix exponential method has been widely used. In the present paper, we propose a new numerical solution of the matrix exponential, a Mini-Max Polynomial Approximation (MMPA) method. This method is numerically stable for burn-up matrices with extremely short half-lived nuclides as the Chebyshev Rational Approximation Method (CRAM), and it has several advantages over CRAM. We also propose a multi-step calculation, a computational time reduction scheme of the MMPA method, which can perform simultaneously burn-up calculations with several time periods. The applicability of these methods has been theoretically and numerically proved for general burn-up matrices. The numerical verification has been performed, and it has been shown that these methods have high precision equivalent to CRAM

Indecomposability of polynomials via Jacobian matrix

International Nuclear Information System (INIS)

Cheze, G.; Najib, S.

2007-12-01

Uni-multivariate decomposition of polynomials is a special case of absolute factorization. Recently, thanks to the Ruppert's matrix some effective results about absolute factorization have been improved. Here we show that with a jacobian matrix we can get sharper bounds for the special case of uni-multivariate decomposition. (author)

Least-squares approximation of an improper by a proper correlation matrix using a semi-infinite convex program

NARCIS (Netherlands)

Knol, Dirk L.; ten Berge, Jos M.F.

1987-01-01

An algorithm is presented for the best least-squares fitting correlation matrix approximating a given missing value or improper correlation matrix. The proposed algorithm is based on a solution for C. I. Mosier's oblique Procrustes rotation problem offered by J. M. F. ten Berge and K. Nevels (1977).

Correlated random-phase approximation from densities and in-medium matrix elements

Energy Technology Data Exchange (ETDEWEB)

Trippel, Richard; Roth, Robert [Institut fuer Kernphysik, Technische Universitaet Darmstadt (Germany)

2016-07-01

The random-phase approximation (RPA) as well as the second RPA (SRPA) are established tools for the study of collective excitations in nuclei. Addressing the well known lack of correlations, we derived a universal framework for a fully correlated RPA based on the use of one- and two-body densities. We apply densities from coupled cluster theory and investigate the impact of correlations. As an alternative approach to correlations we use matrix elements transformed via in-medium similarity renormalization group (IM-SRG) in combination with RPA and SRPA. We find that within SRPA the use of IM-SRG matrix elements leads to the disappearance of instabilities of low-lying states. For the calculations we use normal-ordered two- plus three-body interactions derived from chiral effective field theory. We apply different Hamiltonians to a number of doubly-magic nuclei and calculate electric transition strengths.

Investigation of bar system modal characteristics using Dynamic Stiffness Matrix polynomial approximations

Czech Academy of Sciences Publication Activity Database

Náprstek, Jiří; Fischer, Cyril

2017-01-01

Roč. 180, February (2017), s. 3-12 ISSN 0045-7949 R&D Projects: GA ČR(CZ) GA15-01035S Institutional support: RVO:68378297 Keywords : Dynamic Stiffness Matrix * lambda matrices * self-adjoint operators * approximation in frequency domain * Wittrick-Williams algorithm Subject RIV: JM - Building Engineering OBOR OECD: Construction engineering, Municipal and structural engineering Impact factor: 2.847, year: 2016 http://www.sciencedirect.com/science/article/pii/S0045794916310495

Matrix model approximations of fuzzy scalar field theories and their phase diagrams

Energy Technology Data Exchange (ETDEWEB)

Tekel, Juraj [Department of Theoretical Physics, Faculty of Mathematics, Physics and Informatics, Comenius University, Mlynska Dolina, Bratislava, 842 48 (Slovakia)

2015-12-29

We present an analysis of two different approximations to the scalar field theory on the fuzzy sphere, a nonperturbative and a perturbative one, which are both multitrace matrix models. We show that the former reproduces a phase diagram with correct features in a qualitative agreement with the previous numerical studies and that the latter gives a phase diagram with features not expected in the phase diagram of the field theory.

High Performance Polar Decomposition on Distributed Memory Systems

KAUST Repository

Sukkari, Dalal E.; Ltaief, Hatem; Keyes, David E.

2016-01-01

The polar decomposition of a dense matrix is an important operation in linear algebra. It can be directly calculated through the singular value decomposition (SVD) or iteratively using the QR dynamically-weighted Halley algorithm (QDWH). The former

Decomposition methods for unsupervised learning

DEFF Research Database (Denmark)

Mørup, Morten

2008-01-01

This thesis presents the application and development of decomposition methods for Unsupervised Learning. It covers topics from classical factor analysis based decomposition and its variants such as Independent Component Analysis, Non-negative Matrix Factorization and Sparse Coding...... methods and clustering problems is derived both in terms of classical point clustering but also in terms of community detection in complex networks. A guiding principle throughout this thesis is the principle of parsimony. Hence, the goal of Unsupervised Learning is here posed as striving for simplicity...... in the decompositions. Thus, it is demonstrated how a wide range of decomposition methods explicitly or implicitly strive to attain this goal. Applications of the derived decompositions are given ranging from multi-media analysis of image and sound data, analysis of biomedical data such as electroencephalography...

Accurate Quasiparticle Spectra from the T-Matrix Self-Energy and the Particle-Particle Random Phase Approximation.

Science.gov (United States)

Zhang, Du; Su, Neil Qiang; Yang, Weitao

2017-07-20

The GW self-energy, especially G 0 W 0 based on the particle-hole random phase approximation (phRPA), is widely used to study quasiparticle (QP) energies. Motivated by the desirable features of the particle-particle (pp) RPA compared to the conventional phRPA, we explore the pp counterpart of GW, that is, the T-matrix self-energy, formulated with the eigenvectors and eigenvalues of the ppRPA matrix. We demonstrate the accuracy of the T-matrix method for molecular QP energies, highlighting the importance of the pp channel for calculating QP spectra.

HLIBCov: Parallel Hierarchical Matrix Approximation of Large Covariance Matrices and Likelihoods with Applications in Parameter Identification

KAUST Repository

Litvinenko, Alexander

2017-09-26

The main goal of this article is to introduce the parallel hierarchical matrix library HLIBpro to the statistical community. We describe the HLIBCov package, which is an extension of the HLIBpro library for approximating large covariance matrices and maximizing likelihood functions. We show that an approximate Cholesky factorization of a dense matrix of size $2M\\\\times 2M$ can be computed on a modern multi-core desktop in few minutes. Further, HLIBCov is used for estimating the unknown parameters such as the covariance length, variance and smoothness parameter of a Mat\\\\\\'ern covariance function by maximizing the joint Gaussian log-likelihood function. The computational bottleneck here is expensive linear algebra arithmetics due to large and dense covariance matrices. Therefore covariance matrices are approximated in the hierarchical ($\\\\H$-) matrix format with computational cost $\\\\mathcal{O}(k^2n \\\\log^2 n/p)$ and storage $\\\\mathcal{O}(kn \\\\log n)$, where the rank $k$ is a small integer (typically $k<25$), $p$ the number of cores and $n$ the number of locations on a fairly general mesh. We demonstrate a synthetic example, where the true values of known parameters are known. For reproducibility we provide the C++ code, the documentation, and the synthetic data.

HLIBCov: Parallel Hierarchical Matrix Approximation of Large Covariance Matrices and Likelihoods with Applications in Parameter Identification

KAUST Repository

Litvinenko, Alexander

2017-09-24

The main goal of this article is to introduce the parallel hierarchical matrix library HLIBpro to the statistical community. We describe the HLIBCov package, which is an extension of the HLIBpro library for approximating large covariance matrices and maximizing likelihood functions. We show that an approximate Cholesky factorization of a dense matrix of size $2M\\\\times 2M$ can be computed on a modern multi-core desktop in few minutes. Further, HLIBCov is used for estimating the unknown parameters such as the covariance length, variance and smoothness parameter of a Mat\\\\\\'ern covariance function by maximizing the joint Gaussian log-likelihood function. The computational bottleneck here is expensive linear algebra arithmetics due to large and dense covariance matrices. Therefore covariance matrices are approximated in the hierarchical ($\\\\mathcal{H}$-) matrix format with computational cost $\\\\mathcal{O}(k^2n \\\\log^2 n/p)$ and storage $\\\\mathcal{O}(kn \\\\log n)$, where the rank $k$ is a small integer (typically $k<25$), $p$ the number of cores and $n$ the number of locations on a fairly general mesh. We demonstrate a synthetic example, where the true values of known parameters are known. For reproducibility we provide the C++ code, the documentation, and the synthetic data.

The Microbial Efficiency-Matrix Stabilization (MEMS) framework integrates plant litter decomposition with soil organic matter stabilization: do labile plant inputs form stable soil organic matter?

Science.gov (United States)

Cotrufo, M Francesca; Wallenstein, Matthew D; Boot, Claudia M; Denef, Karolien; Paul, Eldor

2013-04-01

The decomposition and transformation of above- and below-ground plant detritus (litter) is the main process by which soil organic matter (SOM) is formed. Yet, research on litter decay and SOM formation has been largely uncoupled, failing to provide an effective nexus between these two fundamental processes for carbon (C) and nitrogen (N) cycling and storage. We present the current understanding of the importance of microbial substrate use efficiency and C and N allocation in controlling the proportion of plant-derived C and N that is incorporated into SOM, and of soil matrix interactions in controlling SOM stabilization. We synthesize this understanding into the Microbial Efficiency-Matrix Stabilization (MEMS) framework. This framework leads to the hypothesis that labile plant constituents are the dominant source of microbial products, relative to input rates, because they are utilized more efficiently by microbes. These microbial products of decomposition would thus become the main precursors of stable SOM by promoting aggregation and through strong chemical bonding to the mineral soil matrix. © 2012 Blackwell Publishing Ltd.

A Class of Weighted Low Rank Approximation of the Positive Semidefinite Hankel Matrix

Directory of Open Access Journals (Sweden)

Jianchao Bai

2015-01-01

Full Text Available We consider the weighted low rank approximation of the positive semidefinite Hankel matrix problem arising in signal processing. By using the Vandermonde representation, we firstly transform the problem into an unconstrained optimization problem and then use the nonlinear conjugate gradient algorithm with the Armijo line search to solve the equivalent unconstrained optimization problem. Numerical examples illustrate that the new method is feasible and effective.

Dynamic mode decomposition for plasma diagnostics and validation

Science.gov (United States)

Taylor, Roy; Kutz, J. Nathan; Morgan, Kyle; Nelson, Brian A.

2018-05-01

We demonstrate the application of the Dynamic Mode Decomposition (DMD) for the diagnostic analysis of the nonlinear dynamics of a magnetized plasma in resistive magnetohydrodynamics. The DMD method is an ideal spatio-temporal matrix decomposition that correlates spatial features of computational or experimental data while simultaneously associating the spatial activity with periodic temporal behavior. DMD can produce low-rank, reduced order surrogate models that can be used to reconstruct the state of the system with high fidelity. This allows for a reduction in the computational cost and, at the same time, accurate approximations of the problem, even if the data are sparsely sampled. We demonstrate the use of the method on both numerical and experimental data, showing that it is a successful mathematical architecture for characterizing the helicity injected torus with steady inductive (HIT-SI) magnetohydrodynamics. Importantly, the DMD produces interpretable, dominant mode structures, including a stationary mode consistent with our understanding of a HIT-SI spheromak accompanied by a pair of injector-driven modes. In combination, the 3-mode DMD model produces excellent dynamic reconstructions across the domain of analyzed data.

Vanishing-Overhead Linear-Scaling Random Phase Approximation by Cholesky Decomposition and an Attenuated Coulomb-Metric.

Science.gov (United States)

Luenser, Arne; Schurkus, Henry F; Ochsenfeld, Christian

2017-04-11

A reformulation of the random phase approximation within the resolution-of-the-identity (RI) scheme is presented, that is competitive to canonical molecular orbital RI-RPA already for small- to medium-sized molecules. For electronically sparse systems drastic speedups due to the reduced scaling behavior compared to the molecular orbital formulation are demonstrated. Our reformulation is based on two ideas, which are independently useful: First, a Cholesky decomposition of density matrices that reduces the scaling with basis set size for a fixed-size molecule by one order, leading to massive performance improvements. Second, replacement of the overlap RI metric used in the original AO-RPA by an attenuated Coulomb metric. Accuracy is significantly improved compared to the overlap metric, while locality and sparsity of the integrals are retained, as is the effective linear scaling behavior.

Finite-dimensional approximations of the resolvent of an infinite band matrix and continued fractions

International Nuclear Information System (INIS)

Barrios, Dolores; Lopez, Guillermo L; Martinez-Finkelshtein, A; Torrano, Emilio

1999-01-01

The approximability of the resolvent of an operator induced by a band matrix by the resolvents of its finite-dimensional sections is studied. For bounded perturbations of self-adjoint matrices a positive result is obtained. The convergence domain of the sequence of resolvents can be described in this case in terms of matrices involved in the representation. This result is applied to tridiagonal complex matrices to establish conditions for the convergence of Chebyshev continued fractions on sets in the complex domain. In the particular case of compact perturbations this result is improved and a connection between the poles of the limit function and the eigenvalues of the tridiagonal matrix is established

TRUST MODEL FOR SOCIAL NETWORK USING SINGULAR VALUE DECOMPOSITION

Directory of Open Access Journals (Sweden)

Davis Bundi Ntwiga

2016-06-01

Full Text Available For effective interactions to take place in a social network, trust is important. We model trust of agents using the peer to peer reputation ratings in the network that forms a real valued matrix. Singular value decomposition discounts the reputation ratings to estimate the trust levels as trust is the subjective probability of future expectations based on current reputation ratings. Reputation and trust are closely related and singular value decomposition can estimate trust using the real valued matrix of the reputation ratings of the agents in the network. Singular value decomposition is an ideal technique in error elimination when estimating trust from reputation ratings. Reputation estimation of trust is optimal at the discounting of 20 %.

QR-decomposition based SENSE reconstruction using parallel architecture.

Science.gov (United States)

Ullah, Irfan; Nisar, Habab; Raza, Haseeb; Qasim, Malik; Inam, Omair; Omer, Hammad

2018-04-01

Magnetic Resonance Imaging (MRI) is a powerful medical imaging technique that provides essential clinical information about the human body. One major limitation of MRI is its long scan time. Implementation of advance MRI algorithms on a parallel architecture (to exploit inherent parallelism) has a great potential to reduce the scan time. Sensitivity Encoding (SENSE) is a Parallel Magnetic Resonance Imaging (pMRI) algorithm that utilizes receiver coil sensitivities to reconstruct MR images from the acquired under-sampled k-space data. At the heart of SENSE lies inversion of a rectangular encoding matrix. This work presents a novel implementation of GPU based SENSE algorithm, which employs QR decomposition for the inversion of the rectangular encoding matrix. For a fair comparison, the performance of the proposed GPU based SENSE reconstruction is evaluated against single and multicore CPU using openMP. Several experiments against various acceleration factors (AFs) are performed using multichannel (8, 12 and 30) phantom and in-vivo human head and cardiac datasets. Experimental results show that GPU significantly reduces the computation time of SENSE reconstruction as compared to multi-core CPU (approximately 12x speedup) and single-core CPU (approximately 53x speedup) without any degradation in the quality of the reconstructed images. Copyright © 2018 Elsevier Ltd. All rights reserved.

Analysis of Nonlinear Dynamics by Square Matrix Method

Energy Technology Data Exchange (ETDEWEB)

Yu, Li Hua [Brookhaven National Lab. (BNL), Upton, NY (United States). Energy and Photon Sciences Directorate. National Synchrotron Light Source II

2016-07-25

The nonlinear dynamics of a system with periodic structure can be analyzed using a square matrix. In this paper, we show that because the special property of the square matrix constructed for nonlinear dynamics, we can reduce the dimension of the matrix from the original large number for high order calculation to low dimension in the first step of the analysis. Then a stable Jordan decomposition is obtained with much lower dimension. The transformation to Jordan form provides an excellent action-angle approximation to the solution of the nonlinear dynamics, in good agreement with trajectories and tune obtained from tracking. And more importantly, the deviation from constancy of the new action-angle variable provides a measure of the stability of the phase space trajectories and their tunes. Thus the square matrix provides a novel method to optimize the nonlinear dynamic system. The method is illustrated by many examples of comparison between theory and numerical simulation. Finally, in particular, we show that the square matrix method can be used for optimization to reduce the nonlinearity of a system.

Nonlocal low-rank and sparse matrix decomposition for spectral CT reconstruction

Science.gov (United States)

Niu, Shanzhou; Yu, Gaohang; Ma, Jianhua; Wang, Jing

2018-02-01

Spectral computed tomography (CT) has been a promising technique in research and clinics because of its ability to produce improved energy resolution images with narrow energy bins. However, the narrow energy bin image is often affected by serious quantum noise because of the limited number of photons used in the corresponding energy bin. To address this problem, we present an iterative reconstruction method for spectral CT using nonlocal low-rank and sparse matrix decomposition (NLSMD), which exploits the self-similarity of patches that are collected in multi-energy images. Specifically, each set of patches can be decomposed into a low-rank component and a sparse component, and the low-rank component represents the stationary background over different energy bins, while the sparse component represents the rest of the different spectral features in individual energy bins. Subsequently, an effective alternating optimization algorithm was developed to minimize the associated objective function. To validate and evaluate the NLSMD method, qualitative and quantitative studies were conducted by using simulated and real spectral CT data. Experimental results show that the NLSMD method improves spectral CT images in terms of noise reduction, artifact suppression and resolution preservation.

Integral transport multiregion geometrical shadowing factor for the approximate collision probability matrix calculation of infinite closely packed lattices

International Nuclear Information System (INIS)

Jowzani-Moghaddam, A.

1981-01-01

An integral transport method of calculating the geometrical shadowing factor in multiregion annular cells for infinite closely packed lattices in cylindrical geometry is developed. This analytical method has been programmed in the TPGS code. This method is based upon a consideration of the properties of the integral transport method for a nonuniform body, which together with Bonalumi's approximations allows the determination of the approximate multiregion collision probability matrix for infinite closely packed lattices with sufficient accuracy. The multiregion geometrical shadowing factors have been calculated for variations in fuel pin annular segment rings in a geometry of annular cells. These shadowing factors can then be used in the calculation of neutron transport from one annulus to another in an infinite lattice. The result of this new geometrical shadowing and collision probability matrix are compared with the Dancoff-Ginsburg correction and the probability matrix using constant shadowing on Yankee fuel elements in an infinite lattice. In these cases the Dancoff-Ginsburg correction factor and collision probability matrix using constant shadowing are in difference by at most 6.2% and 6%, respectively

Matrix with Prescribed Eigenvectors

Science.gov (United States)

Ahmad, Faiz

2011-01-01

It is a routine matter for undergraduates to find eigenvalues and eigenvectors of a given matrix. But the converse problem of finding a matrix with prescribed eigenvalues and eigenvectors is rarely discussed in elementary texts on linear algebra. This problem is related to the "spectral" decomposition of a matrix and has important technical…

Integration of large chemical kinetic mechanisms via exponential methods with Krylov approximations to Jacobian matrix functions

KAUST Repository

Bisetti, Fabrizio

2012-01-01

with the computational cost associated with the time integration of stiff, large chemical systems, a novel approach is proposed. The approach combines an exponential integrator and Krylov subspace approximations to the exponential function of the Jacobian matrix

Application of spectral Lanczos decomposition method to large scale problems arising geophysics

Energy Technology Data Exchange (ETDEWEB)

Tamarchenko, T. [Western Atlas Logging Services, Houston, TX (United States)

1996-12-31

This paper presents an application of Spectral Lanczos Decomposition Method (SLDM) to numerical modeling of electromagnetic diffusion and elastic waves propagation in inhomogeneous media. SLDM approximates an action of a matrix function as a linear combination of basis vectors in Krylov subspace. I applied the method to model electromagnetic fields in three-dimensions and elastic waves in two dimensions. The finite-difference approximation of the spatial part of differential operator reduces the initial boundary-value problem to a system of ordinary differential equations with respect to time. The solution to this system requires calculating exponential and sine/cosine functions of the stiffness matrices. Large scale numerical examples are in a good agreement with the theoretical error bounds and stability estimates given by Druskin, Knizhnerman, 1987.

Optimal matrix product states for the Heisenberg spin chain

International Nuclear Information System (INIS)

Latorre, Jose I; Pico, Vicent

2009-01-01

We present some exact results for the optimal matrix product state (MPS) approximation to the ground state of the infinite isotropic Heisenberg spin-1/2 chain. Our approach is based on the systematic use of Schmidt decompositions to reduce the problem of approximating for the ground state of a spin chain to an analytical minimization. This allows one to show that results of standard simulations, e.g. density matrix renormalization group and infinite time evolving block decimation, do correspond to the result obtained by this minimization strategy and, thus, both methods deliver optimal MPS with the same energy but, otherwise, different properties. We also find that translational and rotational symmetries cannot be maintained simultaneously by the MPS ansatz of minimum energy and present explicit constructions for each case. Furthermore, we analyze symmetry restoration and quantify it to uncover new scaling relations. The method we propose can be extended to any translational invariant Hamiltonian

Modified truncated randomized singular value decomposition (MTRSVD) algorithms for large scale discrete ill-posed problems with general-form regularization

Science.gov (United States)

Jia, Zhongxiao; Yang, Yanfei

2018-05-01

In this paper, we propose new randomization based algorithms for large scale linear discrete ill-posed problems with general-form regularization: subject to , where L is a regularization matrix. Our algorithms are inspired by the modified truncated singular value decomposition (MTSVD) method, which suits only for small to medium scale problems, and randomized SVD (RSVD) algorithms that generate good low rank approximations to A. We use rank-k truncated randomized SVD (TRSVD) approximations to A by truncating the rank- RSVD approximations to A, where q is an oversampling parameter. The resulting algorithms are called modified TRSVD (MTRSVD) methods. At every step, we use the LSQR algorithm to solve the resulting inner least squares problem, which is proved to become better conditioned as k increases so that LSQR converges faster. We present sharp bounds for the approximation accuracy of the RSVDs and TRSVDs for severely, moderately and mildly ill-posed problems, and substantially improve a known basic bound for TRSVD approximations. We prove how to choose the stopping tolerance for LSQR in order to guarantee that the computed and exact best regularized solutions have the same accuracy. Numerical experiments illustrate that the best regularized solutions by MTRSVD are as accurate as the ones by the truncated generalized singular value decomposition (TGSVD) algorithm, and at least as accurate as those by some existing truncated randomized generalized singular value decomposition (TRGSVD) algorithms. This work was supported in part by the National Science Foundation of China (Nos. 11771249 and 11371219).

Biomass pyrolysis: Thermal decomposition mechanisms of furfural and benzaldehyde

Science.gov (United States)

Vasiliou, AnGayle K.; Kim, Jong Hyun; Ormond, Thomas K.; Piech, Krzysztof M.; Urness, Kimberly N.; Scheer, Adam M.; Robichaud, David J.; Mukarakate, Calvin; Nimlos, Mark R.; Daily, John W.; Guan, Qi; Carstensen, Hans-Heinrich; Ellison, G. Barney

2013-09-01

The thermal decompositions of furfural and benzaldehyde have been studied in a heated microtubular flow reactor. The pyrolysis experiments were carried out by passing a dilute mixture of the aromatic aldehydes (roughly 0.1%-1%) entrained in a stream of buffer gas (either He or Ar) through a pulsed, heated SiC reactor that is 2-3 cm long and 1 mm in diameter. Typical pressures in the reactor are 75-150 Torr with the SiC tube wall temperature in the range of 1200-1800 K. Characteristic residence times in the reactor are 100-200 μsec after which the gas mixture emerges as a skimmed molecular beam at a pressure of approximately 10 μTorr. Products were detected using matrix infrared absorption spectroscopy, 118.2 nm (10.487 eV) photoionization mass spectroscopy and resonance enhanced multiphoton ionization. The initial steps in the thermal decomposition of furfural and benzaldehyde have been identified. Furfural undergoes unimolecular decomposition to furan + CO: C4H3O-CHO (+ M) → CO + C4H4O. Sequential decomposition of furan leads to the production of HC≡CH, CH2CO, CH3C≡CH, CO, HCCCH2, and H atoms. In contrast, benzaldehyde resists decomposition until higher temperatures when it fragments to phenyl radical plus H atoms and CO: C6H5CHO (+ M) → C6H5CO + H → C6H5 + CO + H. The H atoms trigger a chain reaction by attacking C6H5CHO: H + C6H5CHO → [C6H6CHO]* → C6H6 + CO + H. The net result is the decomposition of benzaldehyde to produce benzene and CO.

Low-rank matrix approximation with manifold regularization.

Science.gov (United States)

Zhang, Zhenyue; Zhao, Keke

2013-07-01

This paper proposes a new model of low-rank matrix factorization that incorporates manifold regularization to the matrix factorization. Superior to the graph-regularized nonnegative matrix factorization, this new regularization model has globally optimal and closed-form solutions. A direct algorithm (for data with small number of points) and an alternate iterative algorithm with inexact inner iteration (for large scale data) are proposed to solve the new model. A convergence analysis establishes the global convergence of the iterative algorithm. The efficiency and precision of the algorithm are demonstrated numerically through applications to six real-world datasets on clustering and classification. Performance comparison with existing algorithms shows the effectiveness of the proposed method for low-rank factorization in general.

Reduced-rank approximations to the far-field transform in the gridded fast multipole method

Science.gov (United States)

Hesford, Andrew J.; Waag, Robert C.

2011-05-01

The fast multipole method (FMM) has been shown to have a reduced computational dependence on the size of finest-level groups of elements when the elements are positioned on a regular grid and FFT convolution is used to represent neighboring interactions. However, transformations between plane-wave expansions used for FMM interactions and pressure distributions used for neighboring interactions remain significant contributors to the cost of FMM computations when finest-level groups are large. The transformation operators, which are forward and inverse Fourier transforms with the wave space confined to the unit sphere, are smooth and well approximated using reduced-rank decompositions that further reduce the computational dependence of the FMM on finest-level group size. The adaptive cross approximation (ACA) is selected to represent the forward and adjoint far-field transformation operators required by the FMM. However, the actual error of the ACA is found to be greater than that predicted using traditional estimates, and the ACA generally performs worse than the approximation resulting from a truncated singular-value decomposition (SVD). To overcome these issues while avoiding the cost of a full-scale SVD, the ACA is employed with more stringent accuracy demands and recompressed using a reduced, truncated SVD. The results show a greatly reduced approximation error that performs comparably to the full-scale truncated SVD without degrading the asymptotic computational efficiency associated with ACA matrix assembly.

Detection of Copper (II) and Cadmium (II) binding to dissolved organic matter from macrophyte decomposition by fluorescence excitation-emission matrix spectra combined with parallel factor analysis

International Nuclear Information System (INIS)

Yuan, Dong-hai; Guo, Xu-jing; Wen, Li; He, Lian-sheng; Wang, Jing-gang; Li, Jun-qi

2015-01-01

Fluorescence excitation-emission matrix (EEM) spectra coupled with parallel factor analysis (PARAFAC) was used to characterize dissolved organic matter (DOM) derived from macrophyte decomposition, and to study its complexation with Cu (II) and Cd (II). Both the protein-like and the humic-like components showed a marked quenching effect by Cu (II). Negligible quenching effects were found for Cd (II) by components 1, 5 and 6. The stability constants and the fraction of the binding fluorophores for humic-like components and Cu (II) can be influenced by macrophyte decomposition of various weight gradients in aquatic plants. Macrophyte decomposition within the scope of the appropriate aquatic phytomass can maximize the stability constant of DOM-metal complexes. A large amount of organic matter was introduced into the aquatic environment by macrophyte decomposition, suggesting that the potential risk of DOM as a carrier of heavy metal contamination in macrophytic lakes should not be ignored. - Highlights: • Macrophyte decomposition increases fluorescent DOM components in the upper sediment. • Protein-like components are quenched or enhanced by adding Cu (II) and Cd (II). • Macrophyte decomposition DOM can impact the affinity of Cu (II) and Cd (II). • The log K M and f values showed a marked change due to macrophyte decomposition. • Macrophyte decomposition can maximize the stability constant of DOM-Cu (II) complexes. - Macrophyte decomposition DOM can influence on the binding affinity of metal ions in macrophytic lakes

CVD-MPFA full pressure support, coupled unstructured discrete fracture-matrix Darcy-flux approximations

Science.gov (United States)

Ahmed, Raheel; Edwards, Michael G.; Lamine, Sadok; Huisman, Bastiaan A. H.; Pal, Mayur

2017-11-01

Two novel control-volume methods are presented for flow in fractured media, and involve coupling the control-volume distributed multi-point flux approximation (CVD-MPFA) constructed with full pressure support (FPS), to two types of discrete fracture-matrix approximation for simulation on unstructured grids; (i) involving hybrid grids and (ii) a lower dimensional fracture model. Flow is governed by Darcy's law together with mass conservation both in the matrix and the fractures, where large discontinuities in permeability tensors can occur. Finite-volume FPS schemes are more robust than the earlier CVD-MPFA triangular pressure support (TPS) schemes for problems involving highly anisotropic homogeneous and heterogeneous full-tensor permeability fields. We use a cell-centred hybrid-grid method, where fractures are modelled by lower-dimensional interfaces between matrix cells in the physical mesh but expanded to equi-dimensional cells in the computational domain. We present a simple procedure to form a consistent hybrid-grid locally for a dual-cell. We also propose a novel hybrid-grid for intersecting fractures, for the FPS method, which reduces the condition number of the global linear system and leads to larger time steps for tracer transport. The transport equation for tracer flow is coupled with the pressure equation and provides flow parameter assessment of the fracture models. Transport results obtained via TPS and FPS hybrid-grid formulations are compared with the corresponding results of fine-scale explicit equi-dimensional formulations. The results show that the hybrid-grid FPS method applies to general full-tensor fields and provides improved robust approximations compared to the hybrid-grid TPS method for fractured domains, for both weakly anisotropic permeability fields and very strong anisotropic full-tensor permeability fields where the TPS scheme exhibits spurious oscillations. The hybrid-grid FPS formulation is extended to compressible flow and the

HLIBCov: Parallel Hierarchical Matrix Approximation of Large Covariance Matrices and Likelihoods with Applications in Parameter Identification

KAUST Repository

Litvinenko, Alexander

2017-01-01

and maximizing likelihood functions. We show that an approximate Cholesky factorization of a dense matrix of size $2M\\times 2M$ can be computed on a modern multi-core desktop in few minutes. Further, HLIBCov is used for estimating the unknown parameters

HLIBCov: Parallel Hierarchical Matrix Approximation of Large Covariance Matrices and Likelihoods with Applications in Parameter Identification

KAUST Repository

Litvinenko, Alexander

2017-01-01

matrices. Therefore covariance matrices are approximated in the hierarchical ($\\H$-) matrix format with computational cost $\\mathcal{O}(k^2n \\log^2 n/p)$ and storage $\\mathcal{O}(kn \\log n)$, where the rank $k$ is a small integer (typically $k<25$), $p

M3: Matrix Multiplication on MapReduce

DEFF Research Database (Denmark)

Silvestri, Francesco; Ceccarello, Matteo

2015-01-01

M3 is an Hadoop library for performing dense and sparse matrix multiplication in MapReduce. The library is based on multi-round algorithms exploiting the 3D decomposition of the problem.......M3 is an Hadoop library for performing dense and sparse matrix multiplication in MapReduce. The library is based on multi-round algorithms exploiting the 3D decomposition of the problem....

A S-matrix-like approximation in the charged particle scattering by the hydrogen atom

International Nuclear Information System (INIS)

Mignaco, J.A.; Tort, A.C.

1979-01-01

The Born approximation for charged particle scattering by the hydrogen atom is unfit at low energies. From a S-matrix-like consideration on the dominance of the neighbour singularities, the calculation of other contributions is suggested. The inclusion of bound states is made, following Eden's and his colaborators' ideas, which are described by their interest and likeness with procedures in the intermediate energy physics. (Author) [pt

High Performance Polar Decomposition on Distributed Memory Systems

KAUST Repository

Sukkari, Dalal E.

2016-08-08

The polar decomposition of a dense matrix is an important operation in linear algebra. It can be directly calculated through the singular value decomposition (SVD) or iteratively using the QR dynamically-weighted Halley algorithm (QDWH). The former is difficult to parallelize due to the preponderant number of memory-bound operations during the bidiagonal reduction. We investigate the latter scenario, which performs more floating-point operations but exposes at the same time more parallelism, and therefore, runs closer to the theoretical peak performance of the system, thanks to more compute-bound matrix operations. Profiling results show the performance scalability of QDWH for calculating the polar decomposition using around 9200 MPI processes on well and ill-conditioned matrices of 100K×100K problem size. We study then the performance impact of the QDWH-based polar decomposition as a pre-processing step toward calculating the SVD itself. The new distributed-memory implementation of the QDWH-SVD solver achieves up to five-fold speedup against current state-of-the-art vendor SVD implementations. © Springer International Publishing Switzerland 2016.

Efficient approximation of random fields for numerical applications

KAUST Repository

Harbrecht, Helmut; Peters, Michael; Siebenmorgen, Markus

2015-01-01

We consider the rapid computation of separable expansions for the approximation of random fields. We compare approaches based on techniques from the approximation of non-local operators on the one hand and based on the pivoted Cholesky decomposition on the other hand. We provide an a-posteriori error estimate for the pivoted Cholesky decomposition in terms of the trace. Numerical examples validate and quantify the considered methods.

Efficient approximation of random fields for numerical applications

KAUST Repository

Harbrecht, Helmut

2015-01-07

We consider the rapid computation of separable expansions for the approximation of random fields. We compare approaches based on techniques from the approximation of non-local operators on the one hand and based on the pivoted Cholesky decomposition on the other hand. We provide an a-posteriori error estimate for the pivoted Cholesky decomposition in terms of the trace. Numerical examples validate and quantify the considered methods.

Structured decomposition design of partial Mueller matrix polarimeters.

Science.gov (United States)

Alenin, Andrey S; Scott Tyo, J

2015-07-01

Partial Mueller matrix polarimeters (pMMPs) are active sensing instruments that probe a scattering process with a set of polarization states and analyze the scattered light with a second set of polarization states. Unlike conventional Mueller matrix polarimeters, pMMPs do not attempt to reconstruct the entire Mueller matrix. With proper choice of generator and analyzer states, a subset of the Mueller matrix space can be reconstructed with fewer measurements than that of the full Mueller matrix polarimeter. In this paper we consider the structure of the Mueller matrix and our ability to probe it using a reduced number of measurements. We develop analysis tools that allow us to relate the particular choice of generator and analyzer polarization states to the portion of Mueller matrix space that the instrument measures, as well as develop an optimization method that is based on balancing the signal-to-noise ratio of the resulting instrument with the ability of that instrument to accurately measure a particular set of desired polarization components with as few measurements as possible. In the process, we identify 10 classes of pMMP systems, for which the space coverage is immediately known. We demonstrate the theory with a numerical example that designs partial polarimeters for the task of monitoring the damage state of a material as presented earlier by Hoover and Tyo [Appl. Opt.46, 8364 (2007)10.1364/AO.46.008364APOPAI1559-128X]. We show that we can reduce the polarimeter to making eight measurements while still covering the Mueller matrix subspace spanned by the objects.

Attractive electron-electron interactions within robust local fitting approximations.

Science.gov (United States)

Merlot, Patrick; Kjærgaard, Thomas; Helgaker, Trygve; Lindh, Roland; Aquilante, Francesco; Reine, Simen; Pedersen, Thomas Bondo

2013-06-30

An analysis of Dunlap's robust fitting approach reveals that the resulting two-electron integral matrix is not manifestly positive semidefinite when local fitting domains or non-Coulomb fitting metrics are used. We present a highly local approximate method for evaluating four-center two-electron integrals based on the resolution-of-the-identity (RI) approximation and apply it to the construction of the Coulomb and exchange contributions to the Fock matrix. In this pair-atomic resolution-of-the-identity (PARI) approach, atomic-orbital (AO) products are expanded in auxiliary functions centered on the two atoms associated with each product. Numerical tests indicate that in 1% or less of all Hartree-Fock and Kohn-Sham calculations, the indefinite integral matrix causes nonconvergence in the self-consistent-field iterations. In these cases, the two-electron contribution to the total energy becomes negative, meaning that the electronic interaction is effectively attractive, and the total energy is dramatically lower than that obtained with exact integrals. In the vast majority of our test cases, however, the indefiniteness does not interfere with convergence. The total energy accuracy is comparable to that of the standard Coulomb-metric RI method. The speed-up compared with conventional algorithms is similar to the RI method for Coulomb contributions; exchange contributions are accelerated by a factor of up to eight with a triple-zeta quality basis set. A positive semidefinite integral matrix is recovered within PARI by introducing local auxiliary basis functions spanning the full AO product space, as may be achieved by using Cholesky-decomposition techniques. Local completion, however, slows down the algorithm to a level comparable with or below conventional calculations. Copyright © 2013 Wiley Periodicals, Inc.

Decomposing Nekrasov decomposition

International Nuclear Information System (INIS)

Morozov, A.; Zenkevich, Y.

2016-01-01

AGT relations imply that the four-point conformal block admits a decomposition into a sum over pairs of Young diagrams of essentially rational Nekrasov functions — this is immediately seen when conformal block is represented in the form of a matrix model. However, the q-deformation of the same block has a deeper decomposition — into a sum over a quadruple of Young diagrams of a product of four topological vertices. We analyze the interplay between these two decompositions, their properties and their generalization to multi-point conformal blocks. In the latter case we explain how Dotsenko-Fateev all-with-all (star) pair “interaction” is reduced to the quiver model nearest-neighbor (chain) one. We give new identities for q-Selberg averages of pairs of generalized Macdonald polynomials. We also translate the slicing invariance of refined topological strings into the language of conformal blocks and interpret it as abelianization of generalized Macdonald polynomials.

Decomposing Nekrasov decomposition

Energy Technology Data Exchange (ETDEWEB)

Morozov, A. [ITEP,25 Bolshaya Cheremushkinskaya, Moscow, 117218 (Russian Federation); Institute for Information Transmission Problems,19-1 Bolshoy Karetniy, Moscow, 127051 (Russian Federation); National Research Nuclear University MEPhI,31 Kashirskoe highway, Moscow, 115409 (Russian Federation); Zenkevich, Y. [ITEP,25 Bolshaya Cheremushkinskaya, Moscow, 117218 (Russian Federation); National Research Nuclear University MEPhI,31 Kashirskoe highway, Moscow, 115409 (Russian Federation); Institute for Nuclear Research of Russian Academy of Sciences,6a Prospekt 60-letiya Oktyabrya, Moscow, 117312 (Russian Federation)

2016-02-16

AGT relations imply that the four-point conformal block admits a decomposition into a sum over pairs of Young diagrams of essentially rational Nekrasov functions — this is immediately seen when conformal block is represented in the form of a matrix model. However, the q-deformation of the same block has a deeper decomposition — into a sum over a quadruple of Young diagrams of a product of four topological vertices. We analyze the interplay between these two decompositions, their properties and their generalization to multi-point conformal blocks. In the latter case we explain how Dotsenko-Fateev all-with-all (star) pair “interaction” is reduced to the quiver model nearest-neighbor (chain) one. We give new identities for q-Selberg averages of pairs of generalized Macdonald polynomials. We also translate the slicing invariance of refined topological strings into the language of conformal blocks and interpret it as abelianization of generalized Macdonald polynomials.

On the correspondence between data revision and trend-cycle decomposition

NARCIS (Netherlands)

Dungey, M.; Jacobs, J. P. A. M.; Tian, J.; van Norden, S.

2013-01-01

This article places the data revision model of Jacobs and van Norden (2011) within a class of trend-cycle decompositions relating directly to the Beveridge-Nelson decomposition. In both these approaches, identifying restrictions on the covariance matrix under simple and realistic conditions may

Trace Norm Regularized CANDECOMP/PARAFAC Decomposition With Missing Data.

Science.gov (United States)

Liu, Yuanyuan; Shang, Fanhua; Jiao, Licheng; Cheng, James; Cheng, Hong

2015-11-01

In recent years, low-rank tensor completion (LRTC) problems have received a significant amount of attention in computer vision, data mining, and signal processing. The existing trace norm minimization algorithms for iteratively solving LRTC problems involve multiple singular value decompositions of very large matrices at each iteration. Therefore, they suffer from high computational cost. In this paper, we propose a novel trace norm regularized CANDECOMP/PARAFAC decomposition (TNCP) method for simultaneous tensor decomposition and completion. We first formulate a factor matrix rank minimization model by deducing the relation between the rank of each factor matrix and the mode- n rank of a tensor. Then, we introduce a tractable relaxation of our rank function, and then achieve a convex combination problem of much smaller-scale matrix trace norm minimization. Finally, we develop an efficient algorithm based on alternating direction method of multipliers to solve our problem. The promising experimental results on synthetic and real-world data validate the effectiveness of our TNCP method. Moreover, TNCP is significantly faster than the state-of-the-art methods and scales to larger problems.

Biclustering via Sparse Singular Value Decomposition

KAUST Repository

Lee, Mihee

2010-02-16

Sparse singular value decomposition (SSVD) is proposed as a new exploratory analysis tool for biclustering or identifying interpretable row-column associations within high-dimensional data matrices. SSVD seeks a low-rank, checkerboard structured matrix approximation to data matrices. The desired checkerboard structure is achieved by forcing both the left- and right-singular vectors to be sparse, that is, having many zero entries. By interpreting singular vectors as regression coefficient vectors for certain linear regressions, sparsity-inducing regularization penalties are imposed to the least squares regression to produce sparse singular vectors. An efficient iterative algorithm is proposed for computing the sparse singular vectors, along with some discussion of penalty parameter selection. A lung cancer microarray dataset and a food nutrition dataset are used to illustrate SSVD as a biclustering method. SSVD is also compared with some existing biclustering methods using simulated datasets. © 2010, The International Biometric Society.

Implementation of QR-decomposition based on CORDIC for unitary MUSIC algorithm

Science.gov (United States)

Lounici, Merwan; Luan, Xiaoming; Saadi, Wahab

2013-07-01

The DOA (Direction Of Arrival) estimation with subspace methods such as MUSIC (MUltiple SIgnal Classification) and ESPRIT (Estimation of Signal Parameters via Rotational Invariance Technique) is based on an accurate estimation of the eigenvalues and eigenvectors of covariance matrix. QR decomposition is implemented with the Coordinate Rotation DIgital Computer (CORDIC) algorithm. QRD requires only additions and shifts [6], so it is faster and more regular than other methods. In this article the hardware architecture of an EVD (Eigen Value Decomposition) processor based on TSA (triangular systolic array) for QR decomposition is proposed. Using Xilinx System Generator (XSG), the design is implemented and the estimated logic device resource values are presented for different matrix sizes.

Integration of large chemical kinetic mechanisms via exponential methods with Krylov approximations to Jacobian matrix functions

KAUST Repository

Bisetti, Fabrizio

2012-06-01

Recent trends in hydrocarbon fuel research indicate that the number of species and reactions in chemical kinetic mechanisms is rapidly increasing in an effort to provide predictive capabilities for fuels of practical interest. In order to cope with the computational cost associated with the time integration of stiff, large chemical systems, a novel approach is proposed. The approach combines an exponential integrator and Krylov subspace approximations to the exponential function of the Jacobian matrix. The components of the approach are described in detail and applied to the ignition of stoichiometric methane-air and iso-octane-air mixtures, here described by two widely adopted chemical kinetic mechanisms. The approach is found to be robust even at relatively large time steps and the global error displays a nominal third-order convergence. The performance of the approach is improved by utilising an adaptive algorithm for the selection of the Krylov subspace size, which guarantees an approximation to the matrix exponential within user-defined error tolerance. The Krylov projection of the Jacobian matrix onto a low-dimensional space is interpreted as a local model reduction with a well-defined error control strategy. Finally, the performance of the approach is discussed with regard to the optimal selection of the parameters governing the accuracy of its individual components. © 2012 Copyright Taylor and Francis Group, LLC.

Decomposing tensors with structured matrix factors reduces to rank-1 approximations

DEFF Research Database (Denmark)

Comon, Pierre; Sørensen, Mikael; Tsigaridas, Elias

2010-01-01

Tensor decompositions permit to estimate in a deterministic way the parameters in a multi-linear model. Applications have been already pointed out in antenna array processing and digital communications, among others, and are extremely attractive provided some diversity at the receiver is availabl....... As opposed to the widely used ALS algorithm, non-iterative algorithms are proposed in this paper to compute the required tensor decomposition into a sum of rank-1 terms, when some factor matrices enjoy some structure, such as block-Hankel, triangular, band, etc....

Nuclear Matrix Elements for the $\\beta\\beta$ Decay of the $^{76}$Ge

CERN Document Server

Brown, B A; Horoi, M

2015-01-01

The nuclear matrix elements for two-neutrino double-beta (2 n$\\beta\\beta$ ) and zero-neutrino double-beta (0 n$\\beta\\beta$) decay of 76 Ge are evaluated in terms of the configuration interaction (CI), quasiparticle random phase approximation (QRPA) and interacting boson model (IBM) methods. We show that the decomposition of the matrix elements in terms of interemediate states in 74 Ge is dominated by ground state of this nucleus. We consider corrections to the CI results that arise from configurations admixtures involving orbitals out-side of the CI configuration space by using results from QRPA, many-body-perturbation theory, and the connections to related observables. The CI two-neutrino matrix element is reduced due to the inclusion of spin-orbit partners, and to many-body correlations connected with Gamow-Teller beta decay. The CI zero-neutrino matrix element for the heavy neutrino is enhanced due to particle-particle correlations that are connected with the odd-even oscillations in the nuclear masse...

Matrix completion via a low rank factorization model and an Augmented Lagrangean Succesive Overrelaxation Algorithm

Directory of Open Access Journals (Sweden)

Hugo Lara

2014-12-01

Full Text Available The matrix completion problem (MC has been approximated by using the nuclear norm relaxation. Some algorithms based on this strategy require the computationally expensive singular value decomposition (SVD at each iteration. One way to avoid SVD calculations is to use alternating methods, which pursue the completion through matrix factorization with a low rank condition. In this work an augmented Lagrangean-type alternating algorithm is proposed. The new algorithm uses duality information to define the iterations, in contrast to the solely primal LMaFit algorithm, which employs a Successive Over Relaxation scheme. The convergence result is studied. Some numerical experiments are given to compare numerical performance of both proposals.

Spectral Tensor-Train Decomposition

DEFF Research Database (Denmark)

Bigoni, Daniele; Engsig-Karup, Allan Peter; Marzouk, Youssef M.

2016-01-01

The accurate approximation of high-dimensional functions is an essential task in uncertainty quantification and many other fields. We propose a new function approximation scheme based on a spectral extension of the tensor-train (TT) decomposition. We first define a functional version of the TT...... adaptive Smolyak approach. The method is also used to approximate the solution of an elliptic PDE with random input data. The open source software and examples presented in this work are available online (http://pypi.python.org/pypi/TensorToolbox/)....

ARMA Cholesky Factor Models for the Covariance Matrix of Linear Models.

Science.gov (United States)

Lee, Keunbaik; Baek, Changryong; Daniels, Michael J

2017-11-01

In longitudinal studies, serial dependence of repeated outcomes must be taken into account to make correct inferences on covariate effects. As such, care must be taken in modeling the covariance matrix. However, estimation of the covariance matrix is challenging because there are many parameters in the matrix and the estimated covariance matrix should be positive definite. To overcomes these limitations, two Cholesky decomposition approaches have been proposed: modified Cholesky decomposition for autoregressive (AR) structure and moving average Cholesky decomposition for moving average (MA) structure, respectively. However, the correlations of repeated outcomes are often not captured parsimoniously using either approach separately. In this paper, we propose a class of flexible, nonstationary, heteroscedastic models that exploits the structure allowed by combining the AR and MA modeling of the covariance matrix that we denote as ARMACD. We analyze a recent lung cancer study to illustrate the power of our proposed methods.

Applications of tensor (multiway array) factorizations and decompositions in data mining

DEFF Research Database (Denmark)

Mørup, Morten

2011-01-01

Tensor (multiway array) factorization and decomposition has become an important tool for data mining. Fueled by the computational power of modern computer researchers can now analyze large-scale tensorial structured data that only a few years ago would have been impossible. Tensor factorizations...... have several advantages over two-way matrix factorizations including uniqueness of the optimal solution and component identification even when most of the data is missing. Furthermore, multiway decomposition techniques explicitly exploit the multiway structure that is lost when collapsing some...... of the modes of the tensor in order to analyze the data by regular matrix factorization approaches. Multiway decomposition is being applied to new fields every year and there is no doubt that the future will bring many exciting new applications. The aim of this overview is to introduce the basic concepts...

Approximating the imbibition and absorption behavior of a distribution of matrix blocks by an equivalent spherical block

International Nuclear Information System (INIS)

Zimmerman, R.W.; Bodvarsson, G.S.

1994-03-01

A theoretical study is presented of the effect of matrix block shape and matrix block size distribution on liquid imbibition and solute absorption in a fractured rock mass. It is shown that the behavior of an individual irregularly-shaped matrix block can be modeled with reasonable accuracy by using the results for a spherical matrix block, if one uses an effective radius a = 3V/A, where V is the volume of the block and A is its surface area. In the early-time regime of matrix imbibition, it is shown that a collection of blocks of different sizes can be modeled by a single equivalent block, with an equivalent radius of -1 > -1 , where the average is taken on a volumetrically-weighted basis. In an intermediate time regime, it is shown for the case where the radii are normally distributed that the equivalent radius is reasonably well approximated by the mean radius . In the long-time limit, where no equivalent radius can be rigorously defined, an asymptotic expression is derived for the cumulative diffusion as a function of the mean and the standard deviation of the radius distribution function

Eigenvalue-eigenvector decomposition (EED) analysis of dissimilarity and covariance matrix obtained from total synchronous fluorescence spectral (TSFS) data sets of herbal preparations: Optimizing the classification approach

Science.gov (United States)

Tarai, Madhumita; Kumar, Keshav; Divya, O.; Bairi, Partha; Mishra, Kishor Kumar; Mishra, Ashok Kumar

2017-09-01

The present work compares the dissimilarity and covariance based unsupervised chemometric classification approaches by taking the total synchronous fluorescence spectroscopy data sets acquired for the cumin and non-cumin based herbal preparations. The conventional decomposition method involves eigenvalue-eigenvector analysis of the covariance of the data set and finds the factors that can explain the overall major sources of variation present in the data set. The conventional approach does this irrespective of the fact that the samples belong to intrinsically different groups and hence leads to poor class separation. The present work shows that classification of such samples can be optimized by performing the eigenvalue-eigenvector decomposition on the pair-wise dissimilarity matrix.

Lie bialgebras with triangular decomposition

International Nuclear Information System (INIS)

Andruskiewitsch, N.; Levstein, F.

1992-06-01

Lie bialgebras originated in a triangular decomposition of the underlying Lie algebra are discussed. The explicit formulas for the quantization of the Heisenberg Lie algebra and some motion Lie algebras are given, as well as the algebra of rational functions on the quantum Heisenberg group and the formula for the universal R-matrix. (author). 17 refs

Eigenvalue-eigenvector decomposition (EED) analysis of dissimilarity and covariance matrix obtained from total synchronous fluorescence spectral (TSFS) data sets of herbal preparations: Optimizing the classification approach.

Science.gov (United States)

Tarai, Madhumita; Kumar, Keshav; Divya, O; Bairi, Partha; Mishra, Kishor Kumar; Mishra, Ashok Kumar

2017-09-05

The present work compares the dissimilarity and covariance based unsupervised chemometric classification approaches by taking the total synchronous fluorescence spectroscopy data sets acquired for the cumin and non-cumin based herbal preparations. The conventional decomposition method involves eigenvalue-eigenvector analysis of the covariance of the data set and finds the factors that can explain the overall major sources of variation present in the data set. The conventional approach does this irrespective of the fact that the samples belong to intrinsically different groups and hence leads to poor class separation. The present work shows that classification of such samples can be optimized by performing the eigenvalue-eigenvector decomposition on the pair-wise dissimilarity matrix. Copyright © 2017 Elsevier B.V. All rights reserved.

Characteristics of Decomposition Powers of L-Band Multi-Polarimetric SAR in Assessing Tree Growth of Industrial Plantation Forests in the Tropics

Directory of Open Access Journals (Sweden)

Yoshio Yamaguchi

2012-10-01

Full Text Available A decomposition scheme was applied to ALOS/PALSAR data obtained from a fast-growing tree plantation in Sumatra, Indonesia to extract tree stem information and then estimate the forest stand volume. The scattering power decomposition of the polarimetric SAR data was performed both with and without a rotation matrix and compared to the following field-measured forest biometric parameters: tree diameter, tree height and stand volume. The analytical results involving the rotation matrix correlated better than those without the rotation matrix even for natural scattering surfaces within the forests. Our primary finding was that all of the decomposition powers from the rotated matrix correlated significantly to the forest biometric parameters when divided by the total power. The surface scattering ratio of the total power markedly decreased with the forest growth, whereas the canopy and double-bounce scattering ratios increased. The observations of the decomposition powers were consistent with the tree growth characteristics. Consequently, we found a significant logarithmic relationship between the decomposition powers and the forest biometric parameters that can potentially be used to estimate the forest stand volume.

Structure and decomposition of the silver formate Ag(HCO2)

International Nuclear Information System (INIS)

Puzan, Anna N.; Baumer, Vyacheslav N.; Mateychenko, Pavel V.

2017-01-01

Crystal structure of the silver formate Ag(HCO 2 ) has been determined (orthorhombic, sp.gr. Pccn, a=7.1199(5), b=10.3737(4), c=6.4701(3)Å, V=477.88(4) Å 3 , Z=8). The structure contains isolated formate ions and the pairs Ag 2 2+ which form the layers in (001) planes (the shortest Ag–Ag distances is 2.919 in the pair and 3.421 and 3.716 Å between the nearest Ag atoms of adjacent pairs). Silver formate is unstable compound which decompose spontaneously vs time. Decomposition was studied using Rietveld analysis of the powder diffraction patterns. It was concluded that the diffusion of Ag atoms leads to the formation of plate-like metal particles as nuclei in the (100) planes which settle parallel to (001) planes of the silver formate matrix. - Highlights: • Silver formate Ag(HCO 2 ) was synthesized and characterized. • Layered packing of Ag-Ag pairs in the structure was found. • Decomposition of Ag(HCO 2 ) and formation of metal phase were studied. • Rietveld-refined micro-structural characteristics during decomposition reveal the space relationship between the matrix structure and forming Ag phase REPLACE with: Space relationship between the matrix structure and forming Ag phase.

The Matrix Cookbook

DEFF Research Database (Denmark)

Petersen, Kaare Brandt; Pedersen, Michael Syskind

Matrix identities, relations and approximations. A desktop reference for quick overview of mathematics of matrices.......Matrix identities, relations and approximations. A desktop reference for quick overview of mathematics of matrices....

Multilevel domain decomposition for electronic structure calculations

International Nuclear Information System (INIS)

Barrault, M.; Cances, E.; Hager, W.W.; Le Bris, C.

2007-01-01

We introduce a new multilevel domain decomposition method (MDD) for electronic structure calculations within semi-empirical and density functional theory (DFT) frameworks. This method iterates between local fine solvers and global coarse solvers, in the spirit of domain decomposition methods. Using this approach, calculations have been successfully performed on several linear polymer chains containing up to 40,000 atoms and 200,000 atomic orbitals. Both the computational cost and the memory requirement scale linearly with the number of atoms. Additional speed-up can easily be obtained by parallelization. We show that this domain decomposition method outperforms the density matrix minimization (DMM) method for poor initial guesses. Our method provides an efficient preconditioner for DMM and other linear scaling methods, variational in nature, such as the orbital minimization (OM) procedure

Fluorescence Intrinsic Characterization of Excitation-Emission Matrix Using Multi-Dimensional Ensemble Empirical Mode Decomposition

Directory of Open Access Journals (Sweden)

Tzu-Chien Hsiao

2013-11-01

Full Text Available Excitation-emission matrix (EEM fluorescence spectroscopy is a noninvasive method for tissue diagnosis and has become important in clinical use. However, the intrinsic characterization of EEM fluorescence remains unclear. Photobleaching and the complexity of the chemical compounds make it difficult to distinguish individual compounds due to overlapping features. Conventional studies use principal component analysis (PCA for EEM fluorescence analysis, and the relationship between the EEM features extracted by PCA and diseases has been examined. The spectral features of different tissue constituents are not fully separable or clearly defined. Recently, a non-stationary method called multi-dimensional ensemble empirical mode decomposition (MEEMD was introduced; this method can extract the intrinsic oscillations on multiple spatial scales without loss of information. The aim of this study was to propose a fluorescence spectroscopy system for EEM measurements and to describe a method for extracting the intrinsic characteristics of EEM by MEEMD. The results indicate that, although PCA provides the principal factor for the spectral features associated with chemical compounds, MEEMD can provide additional intrinsic features with more reliable mapping of the chemical compounds. MEEMD has the potential to extract intrinsic fluorescence features and improve the detection of biochemical changes.

Efficient non-linear model reduction via a least-squares Petrov-Galerkin projection and compressive tensor approximations

KAUST Repository

Carlberg, Kevin

2010-10-28

A Petrov-Galerkin projection method is proposed for reducing the dimension of a discrete non-linear static or dynamic computational model in view of enabling its processing in real time. The right reduced-order basis is chosen to be invariant and is constructed using the Proper Orthogonal Decomposition method. The left reduced-order basis is selected to minimize the two-norm of the residual arising at each Newton iteration. Thus, this basis is iteration-dependent, enables capturing of non-linearities, and leads to the globally convergent Gauss-Newton method. To avoid the significant computational cost of assembling the reduced-order operators, the residual and action of the Jacobian on the right reduced-order basis are each approximated by the product of an invariant, large-scale matrix, and an iteration-dependent, smaller one. The invariant matrix is computed using a data compression procedure that meets proposed consistency requirements. The iteration-dependent matrix is computed to enable the least-squares reconstruction of some entries of the approximated quantities. The results obtained for the solution of a turbulent flow problem and several non-linear structural dynamics problems highlight the merit of the proposed consistency requirements. They also demonstrate the potential of this method to significantly reduce the computational cost associated with high-dimensional non-linear models while retaining their accuracy. © 2010 John Wiley & Sons, Ltd.

Efficient non-linear model reduction via a least-squares Petrov-Galerkin projection and compressive tensor approximations

KAUST Repository

Carlberg, Kevin; Bou-Mosleh, Charbel; Farhat, Charbel

2010-01-01

A Petrov-Galerkin projection method is proposed for reducing the dimension of a discrete non-linear static or dynamic computational model in view of enabling its processing in real time. The right reduced-order basis is chosen to be invariant and is constructed using the Proper Orthogonal Decomposition method. The left reduced-order basis is selected to minimize the two-norm of the residual arising at each Newton iteration. Thus, this basis is iteration-dependent, enables capturing of non-linearities, and leads to the globally convergent Gauss-Newton method. To avoid the significant computational cost of assembling the reduced-order operators, the residual and action of the Jacobian on the right reduced-order basis are each approximated by the product of an invariant, large-scale matrix, and an iteration-dependent, smaller one. The invariant matrix is computed using a data compression procedure that meets proposed consistency requirements. The iteration-dependent matrix is computed to enable the least-squares reconstruction of some entries of the approximated quantities. The results obtained for the solution of a turbulent flow problem and several non-linear structural dynamics problems highlight the merit of the proposed consistency requirements. They also demonstrate the potential of this method to significantly reduce the computational cost associated with high-dimensional non-linear models while retaining their accuracy. © 2010 John Wiley & Sons, Ltd.

Thermal decomposition of biphenyl (1963); Decomposition thermique du biphenyle (1963)

Energy Technology Data Exchange (ETDEWEB)

Clerc, M [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires

1962-06-15

The rates of formation of the decomposition products of biphenyl; hydrogen, methane, ethane, ethylene, as well as triphenyl have been measured in the vapour and liquid phases at 460 deg. C. The study of the decomposition products of biphenyl at different temperatures between 400 and 460 deg. C has provided values of the activation energies of the reactions yielding the main products of pyrolysis in the vapour phase. Product and Activation energy: Hydrogen 73 {+-} 2 kCal/Mole; Benzene 76 {+-} 2 kCal/Mole; Meta-triphenyl 53 {+-} 2 kCal/Mole; Biphenyl decomposition 64 {+-} 2 kCal/Mole; The rate of disappearance of biphenyl is only very approximately first order. These results show the major role played at the start of the decomposition by organic impurities which are not detectable by conventional physico-chemical analysis methods and the presence of which accelerates noticeably the decomposition rate. It was possible to eliminate these impurities by zone-melting carried out until the initial gradient of the formation curves for the products became constant. The composition of the high-molecular weight products (over 250) was deduced from the mean molecular weight and the dosage of the aromatic C - H bonds by infrared spectrophotometry. As a result the existence in tars of hydrogenated tetra, penta and hexaphenyl has been demonstrated. (author) [French] Les vitesses de formation des produits de decomposition du biphenyle: hydrogene, methane, ethane, ethylene, ainsi que des triphenyles, ont ete mesurees en phase vapeur et en phase liquide a 460 deg. C. L'etude des produits de decomposition du biphenyle a differentes temperatures comprises entre 400 et 460 deg. C, a fourni les valeurs des energies d'activation des reactions conduisant aux principaux produits de la pyrolyse en phase vapeur. Produit et Energie d'activation: Hydrogene 73 {+-} 2 kcal/Mole; Benzene 76 {+-} 2 kcal/Mole; Metatriphenyle, 53 {+-} 2 kcal/Mole; Decomposition du biphenyle 64 {+-} 2 kcal/Mole; La

Sparse Localization with a Mobile Beacon Based on LU Decomposition in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Chunhui Zhao

2015-09-01

Full Text Available Node localization is the core in wireless sensor network. It can be solved by powerful beacons, which are equipped with global positioning system devices to know their location information. In this article, we present a novel sparse localization approach with a mobile beacon based on LU decomposition. Our scheme firstly translates node localization problem into a 1-sparse vector recovery problem by establishing sparse localization model. Then, LU decomposition pre-processing is adopted to solve the problem that measurement matrix does not meet the re¬stricted isometry property. Later, the 1-sparse vector can be exactly recovered by compressive sensing. Finally, as the 1-sparse vector is approximate sparse, weighted Cen¬troid scheme is introduced to accurately locate the node. Simulation and analysis show that our scheme has better localization performance and lower requirement for the mobile beacon than MAP+GC, MAP-M, and MAP-MN schemes. In addition, the obstacles and DOI have little effect on the novel scheme, and it has great localization performance under low SNR, thus, the scheme proposed is robust.

Exact and approximate exchange potentials investigated in terms of their matrix elements with the Kohn-Sham orbitals

International Nuclear Information System (INIS)

Holas, A.; Cinal, M.

2005-01-01

Three approximate exchange potentials of high accuracy v x Y (r), Y=A,B,C, for the density-functional theory applications are obtained by replacing the matrix elements of the exact potential between the Kohn-Sham (KS) orbitals with such elements of the Fock exchange operator (within the virtual-occupied subset only) in three representations found for any local potential. A common identity is the base of these representations. The potential v x C happens to be the same as that derived by Harbola and Sahni, and v x A as that derived by Gritsenko and Baerends, and Della Sala and Goerling. The potentials obtained can be expressed in terms of occupied KS orbitals only. At large r, their asymptotic form -1/r is the same as that of the exact potential. The high quality of these three approximations is demonstrated by direct comparison with the exact potential and using various consistency tests. A common root established for the three approximations could be helpful in finding new and better approximations via modification of identities employed in the present investigation

Near-infrared Mueller matrix imaging for colonic cancer detection

Science.gov (United States)

Wang, Jianfeng; Zheng, Wei; Lin, Kan; Huang, Zhiwei

2016-03-01

Mueller matrix imaging along with polar decomposition method was employed for the colonic cancer detection by polarized light in the near-infrared spectral range (700-1100 nm). A high-speed (colonic tissues (i.e., normal and caner) were acquired. Polar decomposition was further implemented on the 16 images to derive the diattentuation, depolarization, and the retardance images. The decomposed images showed clear margin between the normal and cancerous colon tissue samples. The work shows the potential of near-infrared Mueller matrix imaging for the early diagnosis and detection of malignant lesions in the colon.

Thermal decomposition of nano-enabled thermoplastics: Possible environmental health and safety implications

International Nuclear Information System (INIS)

Sotiriou, Georgios A.; Singh, Dilpreet; Zhang, Fang; Chalbot, Marie-Cecile G.; Spielman-Sun, Eleanor; Hoering, Lutz; Kavouras, Ilias G.; Lowry, Gregory V.; Wohlleben, Wendel; Demokritou, Philip

2016-01-01

Highlights: • Nano-enabled products might reach their end-of-life by thermal decomposition. • Thermal decomposition provides two by-products: released aerosol and residual ash. • Is there any nanofiller release in byproducts? • Risk assessment of potential environmental health implications. - Abstract: Nano-enabled products (NEPs) are currently part of our life prompting for detailed investigation of potential nano-release across their life-cycle. Particularly interesting is their end-of-life thermal decomposition scenario. Here, we examine the thermal decomposition of widely used NEPs, namely thermoplastic nanocomposites, and assess the properties of the byproducts (released aerosol and residual ash) and possible environmental health and safety implications. We focus on establishing a fundamental understanding on the effect of thermal decomposition parameters, such as polymer matrix, nanofiller properties, decomposition temperature, on the properties of byproducts using a recently-developed lab-based experimental integrated platform. Our results indicate that thermoplastic polymer matrix strongly influences size and morphology of released aerosol, while there was minimal but detectable nano-release, especially when inorganic nanofillers were used. The chemical composition of the released aerosol was found not to be strongly influenced by the presence of nanofiller at least for the low, industry-relevant loadings assessed here. Furthermore, the morphology and composition of residual ash was found to be strongly influenced by the presence of nanofiller. The findings presented here on thermal decomposition/incineration of NEPs raise important questions and concerns regarding the potential fate and transport of released engineered nanomaterials in environmental media and potential environmental health and safety implications.

Thermal decomposition of nano-enabled thermoplastics: Possible environmental health and safety implications

Energy Technology Data Exchange (ETDEWEB)

Sotiriou, Georgios A.; Singh, Dilpreet; Zhang, Fang [Center for Nanotechnology and Nanotoxicology, Department of Environmental Health, T.H. Chan School of Public Health, Harvard University, 665 Huntington Ave., Boston, MA 02115 (United States); Chalbot, Marie-Cecile G. [Department of Environmental and Occupational Health, College of Public Health, University of Arkansas for Medical Sciences, Little Rock, AR 72205 (United States); Spielman-Sun, Eleanor [Department of Civil and Environmental Engineering, Carnegie Mellon University, Pittsburgh, PA 15213 (United States); Hoering, Lutz [BASF SE, Material Physics, 67056 Ludwigshafen (Germany); Kavouras, Ilias G. [Department of Environmental and Occupational Health, College of Public Health, University of Arkansas for Medical Sciences, Little Rock, AR 72205 (United States); Lowry, Gregory V. [Department of Civil and Environmental Engineering, Carnegie Mellon University, Pittsburgh, PA 15213 (United States); Wohlleben, Wendel [Center for Nanotechnology and Nanotoxicology, Department of Environmental Health, T.H. Chan School of Public Health, Harvard University, 665 Huntington Ave., Boston, MA 02115 (United States); BASF SE, Material Physics, 67056 Ludwigshafen (Germany); Demokritou, Philip, E-mail: pdemokri@hsph.harvard.edu [Center for Nanotechnology and Nanotoxicology, Department of Environmental Health, T.H. Chan School of Public Health, Harvard University, 665 Huntington Ave., Boston, MA 02115 (United States)

2016-03-15

Highlights: • Nano-enabled products might reach their end-of-life by thermal decomposition. • Thermal decomposition provides two by-products: released aerosol and residual ash. • Is there any nanofiller release in byproducts? • Risk assessment of potential environmental health implications. - Abstract: Nano-enabled products (NEPs) are currently part of our life prompting for detailed investigation of potential nano-release across their life-cycle. Particularly interesting is their end-of-life thermal decomposition scenario. Here, we examine the thermal decomposition of widely used NEPs, namely thermoplastic nanocomposites, and assess the properties of the byproducts (released aerosol and residual ash) and possible environmental health and safety implications. We focus on establishing a fundamental understanding on the effect of thermal decomposition parameters, such as polymer matrix, nanofiller properties, decomposition temperature, on the properties of byproducts using a recently-developed lab-based experimental integrated platform. Our results indicate that thermoplastic polymer matrix strongly influences size and morphology of released aerosol, while there was minimal but detectable nano-release, especially when inorganic nanofillers were used. The chemical composition of the released aerosol was found not to be strongly influenced by the presence of nanofiller at least for the low, industry-relevant loadings assessed here. Furthermore, the morphology and composition of residual ash was found to be strongly influenced by the presence of nanofiller. The findings presented here on thermal decomposition/incineration of NEPs raise important questions and concerns regarding the potential fate and transport of released engineered nanomaterials in environmental media and potential environmental health and safety implications.

Approximate Implicitization Using Linear Algebra

Directory of Open Access Journals (Sweden)

Oliver J. D. Barrowclough

2012-01-01

Full Text Available We consider a family of algorithms for approximate implicitization of rational parametric curves and surfaces. The main approximation tool in all of the approaches is the singular value decomposition, and they are therefore well suited to floating-point implementation in computer-aided geometric design (CAGD systems. We unify the approaches under the names of commonly known polynomial basis functions and consider various theoretical and practical aspects of the algorithms. We offer new methods for a least squares approach to approximate implicitization using orthogonal polynomials, which tend to be faster and more numerically stable than some existing algorithms. We propose several simple propositions relating the properties of the polynomial bases to their implicit approximation properties.

Structure and decomposition of the silver formate Ag(HCO{sub 2})

Energy Technology Data Exchange (ETDEWEB)

Puzan, Anna N., E-mail: anna_puzan@mail.ru; Baumer, Vyacheslav N.; Mateychenko, Pavel V.

2017-02-15

Crystal structure of the silver formate Ag(HCO{sub 2}) has been determined (orthorhombic, sp.gr. Pccn, a=7.1199(5), b=10.3737(4), c=6.4701(3)Å, V=477.88(4) Å{sup 3}, Z=8). The structure contains isolated formate ions and the pairs Ag{sub 2}{sup 2+} which form the layers in (001) planes (the shortest Ag–Ag distances is 2.919 in the pair and 3.421 and 3.716 Å between the nearest Ag atoms of adjacent pairs). Silver formate is unstable compound which decompose spontaneously vs time. Decomposition was studied using Rietveld analysis of the powder diffraction patterns. It was concluded that the diffusion of Ag atoms leads to the formation of plate-like metal particles as nuclei in the (100) planes which settle parallel to (001) planes of the silver formate matrix. - Highlights: • Silver formate Ag(HCO{sub 2}) was synthesized and characterized. • Layered packing of Ag-Ag pairs in the structure was found. • Decomposition of Ag(HCO{sub 2}) and formation of metal phase were studied. • Rietveld-refined micro-structural characteristics during decomposition reveal the space relationship between the matrix structure and forming Ag phase REPLACE with: Space relationship between the matrix structure and forming Ag phase.

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.

An approximate method for calculating electron-phonon matrix element of a disordered transition metal and relevant comments on superconductivity

International Nuclear Information System (INIS)

Zhang, L.

1981-08-01

A method based on the tight-binding approximation is developed to calculate the electron-phonon matrix element for the disordered transition metals. With the method as a basis the experimental Tsub(c) data of the amorphous transition metal superconductors are re-analysed. Some comments on the superconductivity of the disordered materials are given

Parallel decompositions of Mueller matrices and polarimetric subtraction

Directory of Open Access Journals (Sweden)

Gil J.J.

2010-06-01

Full Text Available From a general formulation of the physically realizable parallel decompositions of the Mueller matrix M of a given depolarizing system, a procedure for determining the set of pure Mueller matrices susceptible to be subtracted from M is presented. This procedure provides a way to check if a given pure Mueller matrix N can be subtracted from M or not. If this check is positive, the value of the relative cross section of the subtracted component is also determined.

Square well approximation to the optical potential

International Nuclear Information System (INIS)

Jain, A.K.; Gupta, M.C.; Marwadi, P.R.

1976-01-01

Approximations for obtaining T-matrix elements for a sum of several potentials in terms of T-matrices for individual potentials are studied. Based on model calculations for S-wave for a sum of two separable non-local potentials of Yukawa type form factors and a sum of two delta function potentials, it is shown that the T-matrix for a sum of several potentials can be approximated satisfactorily over all the energy regions by the sum of T-matrices for individual potentials. Based on this, an approximate method for finding T-matrix for any local potential by approximating it by a sum of suitable number of square wells is presented. This provides an interesting way to calculate the T-matrix for any arbitary potential in terms of Bessel functions to a good degree of accuracy. The method is applied to the Saxon-Wood potentials and good agreement with exact results is found. (author)

Tensor decomposition in electronic structure calculations on 3D Cartesian grids

International Nuclear Information System (INIS)

Khoromskij, B.N.; Khoromskaia, V.; Chinnamsetty, S.R.; Flad, H.-J.

2009-01-01

In this paper, we investigate a novel approach based on the combination of Tucker-type and canonical tensor decomposition techniques for the efficient numerical approximation of functions and operators in electronic structure calculations. In particular, we study applicability of tensor approximations for the numerical solution of Hartree-Fock and Kohn-Sham equations on 3D Cartesian grids. We show that the orthogonal Tucker-type tensor approximation of electron density and Hartree potential of simple molecules leads to low tensor rank representations. This enables an efficient tensor-product convolution scheme for the computation of the Hartree potential using a collocation-type approximation via piecewise constant basis functions on a uniform nxnxn grid. Combined with the Richardson extrapolation, our approach exhibits O(h 3 ) convergence in the grid-size h=O(n -1 ). Moreover, this requires O(3rn+r 3 ) storage, where r denotes the Tucker rank of the electron density with r=O(logn), almost uniformly in n. For example, calculations of the Coulomb matrix and the Hartree-Fock energy for the CH 4 molecule, with a pseudopotential on the C atom, achieved accuracies of the order of 10 -6 hartree with a grid-size n of several hundreds. Since the tensor-product convolution in 3D is performed via 1D convolution transforms, our scheme markedly outperforms the 3D-FFT in both the computing time and storage requirements.

EISPACK, Subroutines for Eigenvalues, Eigenvectors, Matrix Operations

International Nuclear Information System (INIS)

Garbow, Burton S.; Cline, A.K.; Meyering, J.

1993-01-01

: Driver subroutine for a nonsym. tridiag. matrix; SVD: Singular value decomposition of rectangular matrix; TINVIT: Find some vectors of sym. tridiag. matrix; TQLRAT: Find all values of sym. tridiag. matrix; TQL1: Find all values of sym. tridiag. matrix; TQL2: Find all values/vectors of sym. tridiag. matrix; TRBAK1: Back transform vectors of matrix formed by TRED1; TRBAK3: Back transform vectors of matrix formed by TRED3; TRED1: Reduce sym. matrix to sym. tridiag. matrix; TRED2: Reduce sym. matrix to sym. tridiag. matrix; TRED3: Reduce sym. packed matrix to sym. tridiag. matrix; TRIDIB: Find some values of sym. tridiag. matrix; TSTURM: Find some values/vectors of sym. tridiag. matrix. 2 - Method of solution: Almost all the algorithms used in EISPACK are based on similarity transformations. Similarity transformations based on orthogonal and unitary matrices are particularly attractive from a numerical point of view because they do not magnify any errors present in the input data or introduced during the computation. Most of the techniques employed are constructive realizations of variants of Schur's theorem, 'Any matrix can be triangularized by a unitary similarity transformation'. It is usually not possible to compute Schur's transformation with a finite number of rational arithmetic operations. Instead, the algorithms employ a potentially infinite sequence of similarity transformations in which the resultant matrix approaches an upper triangular matrix. The sequence is terminated when all of the sub-diagonal elements of the resulting matrix are less than the roundoff errors involved in the computation. The diagonal elements are then the desired approximations to the eigenvalues of the original matrix and the corresponding eigenvectors can be calculated. Special algorithms deal with symmetric matrices. QR, LR, QL, rational QR, bisection QZ, and inverse iteration methods are used

Electrochemical and Infrared Absorption Spectroscopy Detection of SF₆ Decomposition Products.

Science.gov (United States)

Dong, Ming; Zhang, Chongxing; Ren, Ming; Albarracín, Ricardo; Ye, Rixin

2017-11-15

Sulfur hexafluoride (SF₆) gas-insulated electrical equipment is widely used in high-voltage (HV) and extra-high-voltage (EHV) power systems. Partial discharge (PD) and local heating can occur in the electrical equipment because of insulation faults, which results in SF₆ decomposition and ultimately generates several types of decomposition products. These SF₆ decomposition products can be qualitatively and quantitatively detected with relevant detection methods, and such detection contributes to diagnosing the internal faults and evaluating the security risks of the equipment. At present, multiple detection methods exist for analyzing the SF₆ decomposition products, and electrochemical sensing (ES) and infrared (IR) spectroscopy are well suited for application in online detection. In this study, the combination of ES with IR spectroscopy is used to detect SF₆ gas decomposition. First, the characteristics of these two detection methods are studied, and the data analysis matrix is established. Then, a qualitative and quantitative analysis ES-IR model is established by adopting a two-step approach. A SF₆ decomposition detector is designed and manufactured by combining an electrochemical sensor and IR spectroscopy technology. The detector is used to detect SF₆ gas decomposition and is verified to reliably and accurately detect the gas components and concentrations.

Parallelism in matrix computations

CERN Document Server

Gallopoulos, Efstratios; Sameh, Ahmed H

2016-01-01

This book is primarily intended as a research monograph that could also be used in graduate courses for the design of parallel algorithms in matrix computations. It assumes general but not extensive knowledge of numerical linear algebra, parallel architectures, and parallel programming paradigms. The book consists of four parts: (I) Basics; (II) Dense and Special Matrix Computations; (III) Sparse Matrix Computations; and (IV) Matrix functions and characteristics. Part I deals with parallel programming paradigms and fundamental kernels, including reordering schemes for sparse matrices. Part II is devoted to dense matrix computations such as parallel algorithms for solving linear systems, linear least squares, the symmetric algebraic eigenvalue problem, and the singular-value decomposition. It also deals with the development of parallel algorithms for special linear systems such as banded ,Vandermonde ,Toeplitz ,and block Toeplitz systems. Part III addresses sparse matrix computations: (a) the development of pa...

Vector domain decomposition schemes for parabolic equations

Science.gov (United States)

Vabishchevich, P. N.

2017-09-01

A new class of domain decomposition schemes for finding approximate solutions of timedependent problems for partial differential equations is proposed and studied. A boundary value problem for a second-order parabolic equation is used as a model problem. The general approach to the construction of domain decomposition schemes is based on partition of unity. Specifically, a vector problem is set up for solving problems in individual subdomains. Stability conditions for vector regionally additive schemes of first- and second-order accuracy are obtained.

Model-free method for isothermal and non-isothermal decomposition kinetics analysis of PET sample

International Nuclear Information System (INIS)

Saha, B.; Maiti, A.K.; Ghoshal, A.K.

2006-01-01

Pyrolysis, one possible alternative to recover valuable products from waste plastics, has recently been the subject of renewed interest. In the present study, the isoconversion methods, i.e., Vyazovkin model-free approach is applied to study non-isothermal decomposition kinetics of waste PET samples using various temperature integral approximations such as Coats and Redfern, Gorbachev, and Agrawal and Sivasubramanian approximation and direct integration (recursive adaptive Simpson quadrature scheme) to analyze the decomposition kinetics. The results show that activation energy (E α ) is a weak but increasing function of conversion (α) in case of non-isothermal decomposition and strong and decreasing function of conversion in case of isothermal decomposition. This indicates possible existence of nucleation, nuclei growth and gas diffusion mechanism during non-isothermal pyrolysis and nucleation and gas diffusion mechanism during isothermal pyrolysis. Optimum E α dependencies on α obtained for non-isothermal data showed similar nature for all the types of temperature integral approximations

Effects of calibration methods on quantitative material decomposition in photon-counting spectral computed tomography using a maximum a posteriori estimator.

Science.gov (United States)

Curtis, Tyler E; Roeder, Ryan K

2017-10-01

Advances in photon-counting detectors have enabled quantitative material decomposition using multi-energy or spectral computed tomography (CT). Supervised methods for material decomposition utilize an estimated attenuation for each material of interest at each photon energy level, which must be calibrated based upon calculated or measured values for known compositions. Measurements using a calibration phantom can advantageously account for system-specific noise, but the effect of calibration methods on the material basis matrix and subsequent quantitative material decomposition has not been experimentally investigated. Therefore, the objective of this study was to investigate the influence of the range and number of contrast agent concentrations within a modular calibration phantom on the accuracy of quantitative material decomposition in the image domain. Gadolinium was chosen as a model contrast agent in imaging phantoms, which also contained bone tissue and water as negative controls. The maximum gadolinium concentration (30, 60, and 90 mM) and total number of concentrations (2, 4, and 7) were independently varied to systematically investigate effects of the material basis matrix and scaling factor calibration on the quantitative (root mean squared error, RMSE) and spatial (sensitivity and specificity) accuracy of material decomposition. Images of calibration and sample phantoms were acquired using a commercially available photon-counting spectral micro-CT system with five energy bins selected to normalize photon counts and leverage the contrast agent k-edge. Material decomposition of gadolinium, calcium, and water was performed for each calibration method using a maximum a posteriori estimator. Both the quantitative and spatial accuracy of material decomposition were most improved by using an increased maximum gadolinium concentration (range) in the basis matrix calibration; the effects of using a greater number of concentrations were relatively small in

Fragmentation of extracellular matrix by hypochlorous acid

DEFF Research Database (Denmark)

Woods, Alan A; Davies, Michael Jonathan

2003-01-01

/chloramide decomposition, with copper and iron ions being effective catalysts, and decreased by compounds which scavenge chloramines/chloramides, or species derived from them. The effect of such matrix modifications on cellular behaviour is poorly understood, though it is known that changes in matrix materials can have...... profound effects on cell adhesion, proliferation, growth and phenotype. The observed matrix modifications reported here may therefore modulate cellular behaviour in diseases such as atherosclerosis where MPO-derived oxidants are generated....

Transfer matrix in the quasiclassical approximation with constant and position-dependent mass, resonant tunneling

International Nuclear Information System (INIS)

Perez-Alvarez, R.; Rodriguez-Coppola, H.; Lopez-Gondar, J.; Izquierdo, M.L.

1987-11-01

We develop the quasiclassical approximation for the effective Hamiltonians describing nonhomogeneous systems and we deduce the wave function, the applicability conditions and the connection rules around the turning points. Based on the transfer matrix (TM) formalism we obtain expressions for the transmission coefficient of multiple barriers, the energy levels of multiple wells and the quasistationary levels of a well open by one, and by the two sides. The dispersion relation of a periodic potential profile with variable mass problem is also given. We discuss resonant tunneling for a system of multiple barriers. The transmission coefficient of such a barrier is maximum at energies close to the levels of the inner well when the end barriers are high enough and symmetric. (author). 20 refs, 1 fig

An optimization approach for fitting canonical tensor decompositions.

Energy Technology Data Exchange (ETDEWEB)

Dunlavy, Daniel M. (Sandia National Laboratories, Albuquerque, NM); Acar, Evrim; Kolda, Tamara Gibson

2009-02-01

Tensor decompositions are higher-order analogues of matrix decompositions and have proven to be powerful tools for data analysis. In particular, we are interested in the canonical tensor decomposition, otherwise known as the CANDECOMP/PARAFAC decomposition (CPD), which expresses a tensor as the sum of component rank-one tensors and is used in a multitude of applications such as chemometrics, signal processing, neuroscience, and web analysis. The task of computing the CPD, however, can be difficult. The typical approach is based on alternating least squares (ALS) optimization, which can be remarkably fast but is not very accurate. Previously, nonlinear least squares (NLS) methods have also been recommended; existing NLS methods are accurate but slow. In this paper, we propose the use of gradient-based optimization methods. We discuss the mathematical calculation of the derivatives and further show that they can be computed efficiently, at the same cost as one iteration of ALS. Computational experiments demonstrate that the gradient-based optimization methods are much more accurate than ALS and orders of magnitude faster than NLS.

Five- and six-electron harmonium atoms: Highly accurate electronic properties and their application to benchmarking of approximate 1-matrix functionals

Science.gov (United States)

Cioslowski, Jerzy; Strasburger, Krzysztof

2018-04-01

Electronic properties of several states of the five- and six-electron harmonium atoms are obtained from large-scale calculations employing explicitly correlated basis functions. The high accuracy of the computed energies (including their components), natural spinorbitals, and their occupation numbers makes them suitable for testing, calibration, and benchmarking of approximate formalisms of quantum chemistry and solid state physics. In the case of the five-electron species, the availability of the new data for a wide range of the confinement strengths ω allows for confirmation and generalization of the previously reached conclusions concerning the performance of the presently known approximations for the electron-electron repulsion energy in terms of the 1-matrix that are at heart of the density matrix functional theory (DMFT). On the other hand, the properties of the three low-lying states of the six-electron harmonium atom, computed at ω = 500 and ω = 1000, uncover deficiencies of the 1-matrix functionals not revealed by previous studies. In general, the previously published assessment of the present implementations of DMFT being of poor accuracy is found to hold. Extending the present work to harmonically confined systems with even more electrons is most likely counterproductive as the steep increase in computational cost required to maintain sufficient accuracy of the calculated properties is not expected to be matched by the benefits of additional information gathered from the resulting benchmarks.

Robust estimation of the correlation matrix of longitudinal data

KAUST Repository

Maadooliat, Mehdi

2011-09-23

We propose a double-robust procedure for modeling the correlation matrix of a longitudinal dataset. It is based on an alternative Cholesky decomposition of the form Σ=DLL⊤D where D is a diagonal matrix proportional to the square roots of the diagonal entries of Σ and L is a unit lower-triangular matrix determining solely the correlation matrix. The first robustness is with respect to model misspecification for the innovation variances in D, and the second is robustness to outliers in the data. The latter is handled using heavy-tailed multivariate t-distributions with unknown degrees of freedom. We develop a Fisher scoring algorithm for computing the maximum likelihood estimator of the parameters when the nonredundant and unconstrained entries of (L,D) are modeled parsimoniously using covariates. We compare our results with those based on the modified Cholesky decomposition of the form LD2L⊤ using simulations and a real dataset. © 2011 Springer Science+Business Media, LLC.

Nonlinear QR code based optical image encryption using spiral phase transform, equal modulus decomposition and singular value decomposition

Science.gov (United States)

Kumar, Ravi; Bhaduri, Basanta; Nishchal, Naveen K.

2018-01-01

In this study, we propose a quick response (QR) code based nonlinear optical image encryption technique using spiral phase transform (SPT), equal modulus decomposition (EMD) and singular value decomposition (SVD). First, the primary image is converted into a QR code and then multiplied with a spiral phase mask (SPM). Next, the product is spiral phase transformed with particular spiral phase function, and further, the EMD is performed on the output of SPT, which results into two complex images, Z 1 and Z 2. Among these, Z 1 is further Fresnel propagated with distance d, and Z 2 is reserved as a decryption key. Afterwards, SVD is performed on Fresnel propagated output to get three decomposed matrices i.e. one diagonal matrix and two unitary matrices. The two unitary matrices are modulated with two different SPMs and then, the inverse SVD is performed using the diagonal matrix and modulated unitary matrices to get the final encrypted image. Numerical simulation results confirm the validity and effectiveness of the proposed technique. The proposed technique is robust against noise attack, specific attack, and brutal force attack. Simulation results are presented in support of the proposed idea.

Representation of discrete Steklov-Poincare operator arising in domain decomposition methods in wavelet basis

Energy Technology Data Exchange (ETDEWEB)

Jemcov, A.; Matovic, M.D. [Queen`s Univ., Kingston, Ontario (Canada)

1996-12-31

This paper examines the sparse representation and preconditioning of a discrete Steklov-Poincare operator which arises in domain decomposition methods. A non-overlapping domain decomposition method is applied to a second order self-adjoint elliptic operator (Poisson equation), with homogeneous boundary conditions, as a model problem. It is shown that the discrete Steklov-Poincare operator allows sparse representation with a bounded condition number in wavelet basis if the transformation is followed by thresholding and resealing. These two steps combined enable the effective use of Krylov subspace methods as an iterative solution procedure for the system of linear equations. Finding the solution of an interface problem in domain decomposition methods, known as a Schur complement problem, has been shown to be equivalent to the discrete form of Steklov-Poincare operator. A common way to obtain Schur complement matrix is by ordering the matrix of discrete differential operator in subdomain node groups then block eliminating interface nodes. The result is a dense matrix which corresponds to the interface problem. This is equivalent to reducing the original problem to several smaller differential problems and one boundary integral equation problem for the subdomain interface.

Frozen Gaussian approximation based domain decomposition methods for the linear Schrödinger equation beyond the semi-classical regime

Science.gov (United States)

Lorin, E.; Yang, X.; Antoine, X.

2016-06-01

The paper is devoted to develop efficient domain decomposition methods for the linear Schrödinger equation beyond the semiclassical regime, which does not carry a small enough rescaled Planck constant for asymptotic methods (e.g. geometric optics) to produce a good accuracy, but which is too computationally expensive if direct methods (e.g. finite difference) are applied. This belongs to the category of computing middle-frequency wave propagation, where neither asymptotic nor direct methods can be directly used with both efficiency and accuracy. Motivated by recent works of the authors on absorbing boundary conditions (Antoine et al. (2014) [13] and Yang and Zhang (2014) [43]), we introduce Semiclassical Schwarz Waveform Relaxation methods (SSWR), which are seamless integrations of semiclassical approximation to Schwarz Waveform Relaxation methods. Two versions are proposed respectively based on Herman-Kluk propagation and geometric optics, and we prove the convergence and provide numerical evidence of efficiency and accuracy of these methods.

Decomposition of pyrite and the interaction of pyrite with coal organic matrix in pyrolysis and hydropyrolysis

Energy Technology Data Exchange (ETDEWEB)

Chen, H.; Li, B.; Zhang, B. [Chinese Academy of Sciences, Taiyuan (China). Institute of Coal Chemistry

1999-07-01

The thermal decomposition and reduction behaviour of pure pyrite crystals were studied under nitrogen and hydrogen atmospheres. Decomposition of pyrite in coal during pyrolysis and hydropyrolysis, and the behaviour of organic sulphur, are discussed. Temperature and pressure effects are considered. 7 refs., 6 figs., 1 tab.

Convergence of the standard RLS method and UDUT factorisation of covariance matrix for solving the algebraic Riccati equation of the DLQR via heuristic approximate dynamic programming

Science.gov (United States)

Moraes Rêgo, Patrícia Helena; Viana da Fonseca Neto, João; Ferreira, Ernesto M.

2015-08-01

The main focus of this article is to present a proposal to solve, via UDUT factorisation, the convergence and numerical stability problems that are related to the covariance matrix ill-conditioning of the recursive least squares (RLS) approach for online approximations of the algebraic Riccati equation (ARE) solution associated with the discrete linear quadratic regulator (DLQR) problem formulated in the actor-critic reinforcement learning and approximate dynamic programming context. The parameterisations of the Bellman equation, utility function and dynamic system as well as the algebra of Kronecker product assemble a framework for the solution of the DLQR problem. The condition number and the positivity parameter of the covariance matrix are associated with statistical metrics for evaluating the approximation performance of the ARE solution via RLS-based estimators. The performance of RLS approximators is also evaluated in terms of consistence and polarisation when associated with reinforcement learning methods. The used methodology contemplates realisations of online designs for DLQR controllers that is evaluated in a multivariable dynamic system model.

Numerical CP Decomposition of Some Difficult Tensors

Czech Academy of Sciences Publication Activity Database

Tichavský, Petr; Phan, A. H.; Cichocki, A.

2017-01-01

Roč. 317, č. 1 (2017), s. 362-370 ISSN 0377-0427 R&D Projects: GA ČR(CZ) GA14-13713S Institutional support: RVO:67985556 Keywords : Small matrix multiplication * Canonical polyadic tensor decomposition * Levenberg-Marquardt method Subject RIV: BB - Applied Statistics, Operational Research OBOR OECD: Applied mathematics Impact factor: 1.357, year: 2016 http://library.utia.cas.cz/separaty/2017/SI/tichavsky-0468385. pdf

Massively Parallel Polar Decomposition on Distributed-Memory Systems

KAUST Repository

Ltaief, Hatem; Sukkari, Dalal E.; Esposito, Aniello; Nakatsukasa, Yuji; Keyes, David E.

2018-01-01

We present a high-performance implementation of the Polar Decomposition (PD) on distributed-memory systems. Building upon on the QR-based Dynamically Weighted Halley (QDWH) algorithm, the key idea lies in finding the best rational approximation

Low Rank Approximation Algorithms, Implementation, Applications

CERN Document Server

Markovsky, Ivan

2012-01-01

Matrix low-rank approximation is intimately related to data modelling; a problem that arises frequently in many different fields. Low Rank Approximation: Algorithms, Implementation, Applications is a comprehensive exposition of the theory, algorithms, and applications of structured low-rank approximation. Local optimization methods and effective suboptimal convex relaxations for Toeplitz, Hankel, and Sylvester structured problems are presented. A major part of the text is devoted to application of the theory. Applications described include: system and control theory: approximate realization, model reduction, output error, and errors-in-variables identification; signal processing: harmonic retrieval, sum-of-damped exponentials, finite impulse response modeling, and array processing; machine learning: multidimensional scaling and recommender system; computer vision: algebraic curve fitting and fundamental matrix estimation; bioinformatics for microarray data analysis; chemometrics for multivariate calibration; ...

Electrochemical and Infrared Absorption Spectroscopy Detection of SF6 Decomposition Products

Directory of Open Access Journals (Sweden)

Ming Dong

2017-11-01

Full Text Available Sulfur hexafluoride (SF6 gas-insulated electrical equipment is widely used in high-voltage (HV and extra-high-voltage (EHV power systems. Partial discharge (PD and local heating can occur in the electrical equipment because of insulation faults, which results in SF6 decomposition and ultimately generates several types of decomposition products. These SF6 decomposition products can be qualitatively and quantitatively detected with relevant detection methods, and such detection contributes to diagnosing the internal faults and evaluating the security risks of the equipment. At present, multiple detection methods exist for analyzing the SF6 decomposition products, and electrochemical sensing (ES and infrared (IR spectroscopy are well suited for application in online detection. In this study, the combination of ES with IR spectroscopy is used to detect SF6 gas decomposition. First, the characteristics of these two detection methods are studied, and the data analysis matrix is established. Then, a qualitative and quantitative analysis ES-IR model is established by adopting a two-step approach. A SF6 decomposition detector is designed and manufactured by combining an electrochemical sensor and IR spectroscopy technology. The detector is used to detect SF6 gas decomposition and is verified to reliably and accurately detect the gas components and concentrations.

Electrochemical and Infrared Absorption Spectroscopy Detection of SF6 Decomposition Products

Science.gov (United States)

Dong, Ming; Ren, Ming; Ye, Rixin

2017-01-01

Sulfur hexafluoride (SF6) gas-insulated electrical equipment is widely used in high-voltage (HV) and extra-high-voltage (EHV) power systems. Partial discharge (PD) and local heating can occur in the electrical equipment because of insulation faults, which results in SF6 decomposition and ultimately generates several types of decomposition products. These SF6 decomposition products can be qualitatively and quantitatively detected with relevant detection methods, and such detection contributes to diagnosing the internal faults and evaluating the security risks of the equipment. At present, multiple detection methods exist for analyzing the SF6 decomposition products, and electrochemical sensing (ES) and infrared (IR) spectroscopy are well suited for application in online detection. In this study, the combination of ES with IR spectroscopy is used to detect SF6 gas decomposition. First, the characteristics of these two detection methods are studied, and the data analysis matrix is established. Then, a qualitative and quantitative analysis ES-IR model is established by adopting a two-step approach. A SF6 decomposition detector is designed and manufactured by combining an electrochemical sensor and IR spectroscopy technology. The detector is used to detect SF6 gas decomposition and is verified to reliably and accurately detect the gas components and concentrations. PMID:29140268

Xylanase and cellulase activities during anaerobic decomposition of three aquatic macrophytes.

Science.gov (United States)

Nunes, Maíra F; da Cunha-Santino, Marcela B; Bianchini, Irineu

2011-01-01

Enzymatic activity during decomposition is extremely important to hydrolyze molecules that are assimilated by microorganisms. During aquatic macrophytes decomposition, enzymes act mainly in the breakdown of lignocellulolytic matrix fibers (i.e. cellulose, hemicellulose and lignin) that encompass the refractory fraction from organic matter. Considering the importance of enzymatic activities role in decomposition processes, this study aimed to describe the temporal changes of xylanase and cellulose activities during anaerobic decomposition of Ricciocarpus natans (freely-floating), Oxycaryum cubense (emergent) and Cabomba furcata (submersed). The aquatic macrophytes were collected in Óleo Lagoon, Luiz Antonio, São Paulo, Brazil and bioassays were accomplished.  Decomposition chambers from each species (n = 10) were set up with dried macrophyte fragments and filtered Óleo Lagoon water. The chambers were incubated at 22.5°C, in the dark and under anaerobic conditions. Enzymatic activities and remaining organic matter were measured periodically during 90 days. The temporal variation of enzymes showed that C. furcata presented the highest decay and the highest maximum enzyme production. Xylanase production was higher than cellulase production for the decomposition of the three aquatic macrophytes species.

A PARALLEL NONOVERLAPPING DOMAIN DECOMPOSITION METHOD FOR STOKES PROBLEMS

Institute of Scientific and Technical Information of China (English)

Mei-qun Jiang; Pei-liang Dai

2006-01-01

A nonoverlapping domain decomposition iterative procedure is developed and analyzed for generalized Stokes problems and their finite element approximate problems in RN(N=2,3). The method is based on a mixed-type consistency condition with two parameters as a transmission condition together with a derivative-free transmission data updating technique on the artificial interfaces. The method can be applied to a general multi-subdomain decomposition and implemented on parallel machines with local simple communications naturally.

Quantitative assessment of submicron scale anisotropy in tissue multifractality by scattering Mueller matrix in the framework of Born approximation

Science.gov (United States)

Das, Nandan Kumar; Dey, Rajib; Chakraborty, Semanti; Panigrahi, Prasanta K.; Meglinski, Igor; Ghosh, Nirmalya

2018-04-01

A number of tissue-like disordered media exhibit local anisotropy of scattering in the scaling behavior. Scaling behavior contains wealth of fractal or multifractal properties. We demonstrate that the spatial dielectric fluctuations in a sample of biological tissue exhibit multifractal anisotropy. Multifractal anisotropy encoded in the wavelength variation of the light scattering Mueller matrix and manifesting as an intriguing spectral diattenuation effect. We developed an inverse method for the quantitative assessment of the multifractal anisotropy. The method is based on the processing of relevant Mueller matrix elements in Fourier domain by using Born approximation, followed by the multifractal analysis. The approach promises for probing subtle micro-structural changes in biological tissues associated with the cancer and precancer, as well as for non-destructive characterization of a wide range of scattering materials.

Randomized interpolative decomposition of separated representations

Science.gov (United States)

Biagioni, David J.; Beylkin, Daniel; Beylkin, Gregory

2015-01-01

We introduce an algorithm to compute tensor interpolative decomposition (dubbed CTD-ID) for the reduction of the separation rank of Canonical Tensor Decompositions (CTDs). Tensor ID selects, for a user-defined accuracy ɛ, a near optimal subset of terms of a CTD to represent the remaining terms via a linear combination of the selected terms. CTD-ID can be used as an alternative to or in combination with the Alternating Least Squares (ALS) algorithm. We present examples of its use within a convergent iteration to compute inverse operators in high dimensions. We also briefly discuss the spectral norm as a computational alternative to the Frobenius norm in estimating approximation errors of tensor ID. We reduce the problem of finding tensor IDs to that of constructing interpolative decompositions of certain matrices. These matrices are generated via randomized projection of the terms of the given tensor. We provide cost estimates and several examples of the new approach to the reduction of separation rank.

Approximate Inverse Preconditioners with Adaptive Dropping

Czech Academy of Sciences Publication Activity Database

Kopal, J.; Rozložník, Miroslav; Tůma, Miroslav

2015-01-01

Roč. 84, June (2015), s. 13-20 ISSN 0965-9978 R&D Projects: GA ČR(CZ) GAP108/11/0853; GA ČR GA13-06684S Institutional support: RVO:67985807 Keywords : approximate inverse * Gram-Schmidt orthogonalization * incomplete decomposition * preconditioned conjugate gradient method * algebraic preconditioning * pivoting Subject RIV: BA - General Mathematics Impact factor: 1.673, year: 2015

Three-Component Decomposition Based on Stokes Vector for Compact Polarimetric SAR

Directory of Open Access Journals (Sweden)

Hanning Wang

2015-09-01

Full Text Available In this paper, a three-component decomposition algorithm is proposed for processing compact polarimetric SAR images. By using the correspondence between the covariance matrix and the Stokes vector, three-component scattering models for CTLR and DCP modes are established. The explicit expression of decomposition results is then derived by setting the contribution of volume scattering as a free parameter. The degree of depolarization is taken as the upper bound of the free parameter, for the constraint that the weighting factor of each scattering component should be nonnegative. Several methods are investigated to estimate the free parameter suitable for decomposition. The feasibility of this algorithm is validated by AIRSAR data over San Francisco and RADARSAT-2 data over Flevoland.

Modal analysis of fluid flows using variants of proper orthogonal decomposition

Science.gov (United States)

Rowley, Clarence; Dawson, Scott

2017-11-01

This talk gives an overview of several methods for analyzing fluid flows, based on variants of proper orthogonal decomposition. These methods may be used to determine simplified, approximate models that capture the essential features of these flows, in order to better understand the dominant physical mechanisms, and potentially to develop appropriate strategies for model-based flow control. We discuss balanced proper orthogonal decomposition as an approximation of balanced truncation, and explain connections with system identification methods such as the eigensystem realization algorithm. We demonstrate the methods on several canonical examples, including a linearized channel flow and the flow past a circular cylinder. Supported by AFOSR, Grant FA9550-14-1-0289.

Stability of 4-dimensional space-time from the IIB matrix model via the improved mean field approximation

International Nuclear Information System (INIS)

Aoyama, Tatsumi; Kawai, Hikaru; Shibusa, Yuuichiro

2006-01-01

We investigate the origin of our four-dimensional space-time by considering dynamical aspects of the IIB matrix model using the improved mean field approximation. Previous works have focused on the specific choices of configurations as ansatz which preserve SO(d) rotational symmetry. In this report, an extended ansatz is proposed and examined up to a third-order approximation which includes both the SO(4) ansatz and the SO(7) ansatz in their respective limits. From the solutions of the self-consistency condition represented by the extrema of the free energy of the system, it is found that some of the solutions found in the SO(4) or SO(7) ansatz disappear in the extended ansatz. This implies that the extension of ansatz can be used to distinguish stable solutions from unstable solutions. It is also found that there is a non-trivial accumulation of extrema including the SO(4)-preserving solution, which may lead to the formation of a plateau. (author)

Exact Markov chain and approximate diffusion solution for haploid genetic drift with one-way mutation.

Science.gov (United States)

Hössjer, Ola; Tyvand, Peder A; Miloh, Touvia

2016-02-01

The classical Kimura solution of the diffusion equation is investigated for a haploid random mating (Wright-Fisher) model, with one-way mutations and initial-value specified by the founder population. The validity of the transient diffusion solution is checked by exact Markov chain computations, using a Jordan decomposition of the transition matrix. The conclusion is that the one-way diffusion model mostly works well, although the rate of convergence depends on the initial allele frequency and the mutation rate. The diffusion approximation is poor for mutation rates so low that the non-fixation boundary is regular. When this happens we perturb the diffusion solution around the non-fixation boundary and obtain a more accurate approximation that takes quasi-fixation of the mutant allele into account. The main application is to quantify how fast a specific genetic variant of the infinite alleles model is lost. We also discuss extensions of the quasi-fixation approach to other models with small mutation rates. Copyright © 2015 Elsevier Inc. All rights reserved.

Non-negative Matrix Factorization for Binary Data

DEFF Research Database (Denmark)

Larsen, Jacob Søgaard; Clemmensen, Line Katrine Harder

We propose the Logistic Non-negative Matrix Factorization for decomposition of binary data. Binary data are frequently generated in e.g. text analysis, sensory data, market basket data etc. A common method for analysing non-negative data is the Non-negative Matrix Factorization, though...... this is in theory not appropriate for binary data, and thus we propose a novel Non-negative Matrix Factorization based on the logistic link function. Furthermore we generalize the method to handle missing data. The formulation of the method is compared to a previously proposed method (Tome et al., 2015). We compare...... the performance of the Logistic Non-negative Matrix Factorization to Least Squares Non-negative Matrix Factorization and Kullback-Leibler (KL) Non-negative Matrix Factorization on sets of binary data: a synthetic dataset, a set of student comments on their professors collected in a binary term-document matrix...

The matrix-elements of two-particle residual interaction in the shell-model formalism with the M.S.D.I. approximation. Part 2

International Nuclear Information System (INIS)

Jasielska, A.; Wiktor, S.

1977-01-01

The table of two-particle matrix elements calculated according to the formalism of MSDI approximation for the orbits 1fsub(7/2), 2psub(3/2), 2psub(1/2) and 1fsub(5/2) and published previously is now supplemented by inclusion of the 1gsub(9/2) orbit. (author)

MATLAB matrix algebra

CERN Document Server

Pérez López, César

2014-01-01

MATLAB is a high-level language and environment for numerical computation, visualization, and programming. Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming languages, such as C/C++ or Java. MATLAB Matrix Algebra introduces you to the MATLAB language with practical hands-on instructions and results, allowing you to quickly achieve your goals. Starting with a look at symbolic and numeric variables, with an emphasis on vector and matrix variables, you will go on to examine functions and operations that support vectors and matrices as arguments, including those based on analytic parent functions. Computational methods for finding eigenvalues and eigenvectors of matrices are detailed, leading to various matrix decompositions. Applications such as change of bases, the classification of quadratic forms and ...

A Rank-Constrained Matrix Representation for Hypergraph-Based Subspace Clustering

Directory of Open Access Journals (Sweden)

Yubao Sun

2015-01-01

Full Text Available This paper presents a novel, rank-constrained matrix representation combined with hypergraph spectral analysis to enable the recovery of the original subspace structures of corrupted data. Real-world data are frequently corrupted with both sparse error and noise. Our matrix decomposition model separates the low-rank, sparse error, and noise components from the data in order to enhance robustness to the corruption. In order to obtain the desired rank representation of the data within a dictionary, our model directly utilizes rank constraints by restricting the upper bound of the rank range. An alternative projection algorithm is proposed to estimate the low-rank representation and separate the sparse error from the data matrix. To further capture the complex relationship between data distributed in multiple subspaces, we use hypergraph to represent the data by encapsulating multiple related samples into one hyperedge. The final clustering result is obtained by spectral decomposition of the hypergraph Laplacian matrix. Validation experiments on the Extended Yale Face Database B, AR, and Hopkins 155 datasets show that the proposed method is a promising tool for subspace clustering.

Approximating the constellation constrained capacity of the MIMO channel with discrete input

DEFF Research Database (Denmark)

Yankov, Metodi Plamenov; Forchhammer, Søren; Larsen, Knud J.

2015-01-01

In this paper the capacity of a Multiple Input Multiple Output (MIMO) channel is considered, subject to average power constraint, for multi-dimensional discrete input, in the case when no channel state information is available at the transmitter. We prove that when the constellation size grows, t...... for the equivalent orthogonal channel, obtained by the singular value decomposition. Furthermore, lower bounds on the constrained capacity are derived for the cases of square and tall MIMO matrix, by optimizing the constellation for the equivalent channel, obtained by QR decomposition....

Role of electrodes in ambient electrolytic decomposition of hydroxylammonium nitrate (HAN solutions

Directory of Open Access Journals (Sweden)

Kai Seng Koh

2013-09-01

Full Text Available Decomposition of hydroxylammonium nitrate (HAN solution with electrolytic decomposition method has attracted much attention in recent years due to its efficiencies and practicability. However, the phenomenon has not been well-studied till now. By utilizing mathematical model currently available, the effect of water content and power used for decomposition was studied. Experiment data shows that sacrificial material such as copper or aluminum outperforms inert electrodes in the decomposition of HAN solution. In the case of using copper wire to electrolyse HAN solutions, approximately 10 seconds is required to reach 100 °C regardless of concentration of HAN. In term of power consumption, 100 W–300 W was found to be the range in which decomposition could be triggered effectively using copper wire as electrodes.

Efficient solution of parabolic equations by Krylov approximation methods

Science.gov (United States)

Gallopoulos, E.; Saad, Y.

1990-01-01

Numerical techniques for solving parabolic equations by the method of lines is addressed. The main motivation for the proposed approach is the possibility of exploiting a high degree of parallelism in a simple manner. The basic idea of the method is to approximate the action of the evolution operator on a given state vector by means of a projection process onto a Krylov subspace. Thus, the resulting approximation consists of applying an evolution operator of a very small dimension to a known vector which is, in turn, computed accurately by exploiting well-known rational approximations to the exponential. Because the rational approximation is only applied to a small matrix, the only operations required with the original large matrix are matrix-by-vector multiplications, and as a result the algorithm can easily be parallelized and vectorized. Some relevant approximation and stability issues are discussed. We present some numerical experiments with the method and compare its performance with a few explicit and implicit algorithms.

Thermal Decomposition of Radiation-Damaged Polystyrene

International Nuclear Information System (INIS)

J Abrefah, J.; Klinger, G.S.

2000-01-01

The radiation-damaged polystyrene material (''polycube'') used in this study was synthesized by mixing a high-density polystyrene (''Dylene Fines No. 100'') with plutonium and uranium oxides. The polycubes were used on the Hanford Site in the 1960s for criticality studies to determine the hydrogen-to-fissile atom ratios for neutron moderation during processing of spent nuclear fuel. Upon completion of the studies, two methods were developed to reclaim the transuranic (TRU) oxides from the polymer matrix: (1) burning the polycubes in air at 873 K; and (2) heating the polycubes in the absence of oxygen and scrubbing the released monomer and other volatile organics using carbon tetrachloride. Neither of these methods was satisfactory in separating the TRU oxides from the polystyrene. Consequently, the remaining polycubes were sent to the Hanford Plutonium Finishing Plant (PFP) for storage. Over time, the high dose of alpha and gamma radiation has resulted in a polystyrene matrix that is highly cross-linked and hydrogen deficient and a stabilization process is being developed in support of Defense Nuclear Facility Safety Board Recommendation 94-1. Baseline processes involve thermal treatment to pyrolyze the polycubes in a furnace to decompose the polystyrene and separate out the TRU oxides. Thermal decomposition products from this degraded polystyrene matrix were characterized by Pacific Northwest National Laboratory to provide information for determining the environmental impact of the process and for optimizing the process parameters. A gas chromatography/mass spectrometry (GC/MS) system coupled to a horizontal tube furnace was used for the characterization studies. The decomposition studies were performed both in air and helium atmospheres at 773 K, the planned processing temperature. The volatile and semi-volatile organic products identified for the radiation-damaged polystyrene were different from those observed for virgin polystyrene. The differences were in the

Transition matrices and orbitals from reduced density matrix theory

Energy Technology Data Exchange (ETDEWEB)

Etienne, Thibaud [Université de Lorraine – Nancy, Théorie-Modélisation-Simulation, SRSMC, Boulevard des Aiguillettes 54506, Vandoeuvre-lès-Nancy (France); CNRS, Théorie-Modélisation-Simulation, SRSMC, Boulevard des Aiguillettes 54506, Vandoeuvre-lès-Nancy (France); Unité de Chimie Physique Théorique et Structurale, Université de Namur, Rue de Bruxelles 61, 5000 Namur (Belgium)

2015-06-28

In this contribution, we report two different methodologies for characterizing the electronic structure reorganization occurring when a chromophore undergoes an electronic transition. For the first method, we start by setting the theoretical background necessary to the reinterpretation through simple tensor analysis of (i) the transition density matrix and (ii) the natural transition orbitals in the scope of reduced density matrix theory. This novel interpretation is made more clear thanks to a short compendium of the one-particle reduced density matrix theory in a Fock space. The formalism is further applied to two different classes of excited states calculation methods, both requiring a single-determinant reference, that express an excited state as a hole-particle mono-excited configurations expansion, to which particle-hole correlation is coupled (time-dependent Hartree-Fock/time-dependent density functional theory) or not (configuration interaction single/Tamm-Dancoff approximation). For the second methodology presented in this paper, we introduce a novel and complementary concept related to electronic transitions with the canonical transition density matrix and the canonical transition orbitals. Their expression actually reflects the electronic cloud polarisation in the orbital space with a decomposition based on the actual contribution of one-particle excitations from occupied canonical orbitals to virtual ones. This approach validates our novel interpretation of the transition density matrix elements in terms of the Euclidean norm of elementary transition vectors in a linear tensor space. A proper use of these new concepts leads to the conclusion that despite the different principles underlying their construction, they provide two equivalent excited states topological analyses. This connexion is evidenced through simple illustrations of (in)organic dyes electronic transitions analysis.

Option Price Decomposition in Spot-Dependent Volatility Models and Some Applications

Directory of Open Access Journals (Sweden)

Raúl Merino

2017-01-01

Full Text Available We obtain a Hull and White type option price decomposition for a general local volatility model. We apply the obtained formula to CEV model. As an application we give an approximated closed formula for the call option price under a CEV model and an approximated short term implied volatility surface. These approximated formulas are used to estimate model parameters. Numerical comparison is performed for our new method with exact and approximated formulas existing in the literature.

Fast heap transform-based QR-decomposition of real and complex matrices: algorithms and codes

Science.gov (United States)

Grigoryan, Artyom M.

2015-03-01

In this paper, we describe a new look on the application of Givens rotations to the QR-decomposition problem, which is similar to the method of Householder transformations. We apply the concept of the discrete heap transform, or signal-induced unitary transforms which had been introduced by Grigoryan (2006) and used in signal and image processing. Both cases of real and complex nonsingular matrices are considered and examples of performing QR-decomposition of square matrices are given. The proposed method of QR-decomposition for the complex matrix is novel and differs from the known method of complex Givens rotation and is based on analytical equations for the heap transforms. Many examples illustrated the proposed heap transform method of QR-decomposition are given, algorithms are described in detail, and MATLAB-based codes are included.

Robust regularized singular value decomposition with application to mortality data

KAUST Repository

Zhang, Lingsong

2013-09-01

We develop a robust regularized singular value decomposition (RobRSVD) method for analyzing two-way functional data. The research is motivated by the application of modeling human mortality as a smooth two-way function of age group and year. The RobRSVD is formulated as a penalized loss minimization problem where a robust loss function is used to measure the reconstruction error of a low-rank matrix approximation of the data, and an appropriately defined two-way roughness penalty function is used to ensure smoothness along each of the two functional domains. By viewing the minimization problem as two conditional regularized robust regressions, we develop a fast iterative reweighted least squares algorithm to implement the method. Our implementation naturally incorporates missing values. Furthermore, our formulation allows rigorous derivation of leaveone- row/column-out cross-validation and generalized cross-validation criteria, which enable computationally efficient data-driven penalty parameter selection. The advantages of the new robust method over nonrobust ones are shown via extensive simulation studies and the mortality rate application. © Institute of Mathematical Statistics, 2013.

Thermal decomposition pathways of hydroxylamine: theoretical investigation on the initial steps.

Science.gov (United States)

Wang, Qingsheng; Wei, Chunyang; Pérez, Lisa M; Rogers, William J; Hall, Michael B; Mannan, M Sam

2010-09-02

Hydroxylamine (NH(2)OH) is an unstable compound at room temperature, and it has been involved in two tragic industrial incidents. Although experimental studies have been carried out to study the thermal stability of hydroxylamine, the detailed decomposition mechanism is still in debate. In this work, several density functional and ab initio methods were used in conjunction with several basis sets to investigate the initial thermal decomposition steps of hydroxylamine, including both unimolecular and bimolecular reaction pathways. The theoretical investigation shows that simple bond dissociations and unimolecular reactions are unlikely to occur. The energetically favorable initial step of decomposition pathways was determined as a bimolecular isomerization of hydroxylamine into ammonia oxide with an activation barrier of approximately 25 kcal/mol at the MPW1K level of theory. Because hydroxylamine is available only in aqueous solutions, solvent effects on the initial decomposition pathways were also studied using water cluster methods and the polarizable continuum model (PCM). In water, the activation barrier of the bimolecular isomerization reaction decreases to approximately 16 kcal/mol. The results indicate that the bimolecular isomerization pathway of hydroxylamine is more favorable in aqueous solutions. However, the bimolecular nature of this reaction means that more dilute aqueous solution will be more stable.

Optical bistability without the rotating wave approximation

Energy Technology Data Exchange (ETDEWEB)

Sharaby, Yasser A., E-mail: Yasser_Sharaby@hotmail.co [Physics Department, Faculty of Applied Sciences, Suez Canal University, Suez (Egypt); Joshi, Amitabh, E-mail: ajoshi@eiu.ed [Department of Physics, Eastern Illinois University, Charleston, IL 61920 (United States); Hassan, Shoukry S., E-mail: Shoukryhassan@hotmail.co [Mathematics Department, College of Science, University of Bahrain, P.O. Box 32038 (Bahrain)

2010-04-26

Optical bistability for two-level atomic system in a ring cavity is investigated outside the rotating wave approximation (RWA) using non-autonomous Maxwell-Bloch equations with Fourier decomposition up to first harmonic. The first harmonic output field component exhibits reversed or closed loop bistability simultaneously with the usual (anti-clockwise) bistability in the fundamental field component.

Optical bistability without the rotating wave approximation

International Nuclear Information System (INIS)

Sharaby, Yasser A.; Joshi, Amitabh; Hassan, Shoukry S.

2010-01-01

Optical bistability for two-level atomic system in a ring cavity is investigated outside the rotating wave approximation (RWA) using non-autonomous Maxwell-Bloch equations with Fourier decomposition up to first harmonic. The first harmonic output field component exhibits reversed or closed loop bistability simultaneously with the usual (anti-clockwise) bistability in the fundamental field component.

Surface spinodal decomposition in coherent metal-hydrogen and other alloys

International Nuclear Information System (INIS)

Kappus, W.; Horner, H.

1977-01-01

Spinodal decomposition in metal hydrides and alloys near a surface under the influence of elastic interactions is investigated. As long as the crystals remain coherent this process sets in prior to spinodal decomposition in the bulk. A statistical theory containing thermal fluctuations and nonlinear effects is developed and solutions are found in a mean field approximation. The theory is applied to niobium-hydride and a possible explanation for the appearance of quasiperiodic β-phase precipitates in quenched probes is given. (orig.) [de

The Effect of Topography on Target Decomposition of Polarimetric SAR Data

Directory of Open Access Journals (Sweden)

Sang-Eun Park

2015-04-01

Full Text Available Polarimetric target decomposition enables the interpretation of radar images more easily, mostly based on physical assumptions, i.e., fitting physically-based scattering models to the polarimetric SAR observations. However, the model-fitting result cannot be always successful. Particularly, the performance of model-fitting in sloping forests is still an open question. In this study, the effect of ground topography on the model-fitting-based polarimetric decomposition techniques is investigated. The estimation accuracy of each scattering component in the decomposition results are evaluated based on the simulated target matrix by using the incoherent vegetation scattering model that accounts for the tilted scattering surface beneath the forest canopy. Experimental results show that the surface and the double-bounce scattering components can be significantly misestimated due to the topographic slope, even when the volume scattering power is successfully estimated.

Reducing condition number by appropriate current decomposition on a multiplet of several wires

CSIR Research Space (South Africa)

Lysko, AA

2011-07-01

Full Text Available This paper discusses a numerical investigation in connection with the dependency of the condition number of the impedance matrix on the decomposition of current on a junction with several attached wires (multiplet). It is shown that the condition...

Dielectric matrix, dynamical matrix and phonon dispersion in hcp transition metal scandium

International Nuclear Information System (INIS)

Singh, Joginder; Singh, Natthi; Prakash, S.

1976-01-01

Complete dielectric matrix is evaluated for hcp transition metal scandium using the non-interacting s- and d-band model. The local field corrections which are consequence of the non-diagonal part of the dielectric matrix are calculated explicitly. The free electron approximation is used for the s-electrons and the simple tight-binding approximation is used for the d-electrons. The theory developed by Singh and others is used to invert the dielectric matrix and the explicit expressions for the dynamical matrix are obtained. The phonon dispersion relations are investigated by using the renormalized Animalu transition metal model potential (TMMP) for bare ion potential. The contribution due to non-central forces which arise due to local fields is found to be 20%. The results are found in resonably good agreement with the experimental values. (author)

The influence of preburial insect access on the decomposition rate.

Science.gov (United States)

Bachmann, Jutta; Simmons, Tal

2010-07-01

This study compared total body score (TBS) in buried remains (35 cm depth) with and without insect access prior to burial. Sixty rabbit carcasses were exhumed at 50 accumulated degree day (ADD) intervals. Weight loss, TBS, intra-abdominal decomposition, carcass/soil interface temperature, and below-carcass soil pH were recorded and analyzed. Results showed significant differences (p decomposition rates between carcasses with and without insect access prior to burial. An approximately 30% enhanced decomposition rate with insects was observed. TBS was the most valid tool in postmortem interval (PMI) estimation. All other variables showed only weak relationships to decomposition stages, adding little value to PMI estimation. Although progress in estimating the PMI for surface remains has been made, no previous studies have accomplished this for buried remains. This study builds a framework to which further comparable studies can contribute, to produce predictive models for PMI estimation in buried human remains.

The Products of the Thermal Decomposition of CH3CHO

Energy Technology Data Exchange (ETDEWEB)

Vasiliou, AnGayle; Piech, Krzysztof M.; Zhang, Xu; Nimlos, Mark R.; Ahmed, Musahid; Golan, Amir; Kostko, Oleg; Osborn, David L.; Daily, John W.; Stanton, John F.; Ellison, G. Barney

2011-04-06

We have used a heated 2 cm x 1 mm SiC microtubular (mu tubular) reactor to decompose acetaldehyde: CH3CHO + DELTA --> products. Thermal decomposition is followed at pressures of 75 - 150 Torr and at temperatures up to 1700 K, conditions that correspond to residence times of roughly 50 - 100 mu sec in the mu tubular reactor. The acetaldehyde decomposition products are identified by two independent techniques: VUV photoionization mass spectroscopy (PIMS) and infrared (IR) absorption spectroscopy after isolation in a cryogenic matrix. Besides CH3CHO, we have studied three isotopologues, CH3CDO, CD3CHO, and CD3CDO. We have identified the thermal decomposition products CH3(PIMS), CO (IR, PIMS), H (PIMS), H2 (PIMS), CH2CO (IR, PIMS), CH2=CHOH (IR, PIMS), H2O (IR, PIMS), and HC=CH (IR, PIMS). Plausible evidence has been found to support the idea that there are at least three different thermal decomposition pathways for CH3CHO: Radical decomposition: CH3CHO + DELTA --> CH3 + [HCO] --> CH3 + H + CO Elimination: CH3CHO + DELTA --> H2 + CH2=C=O. Isomerization/elimination: CH3CHO + DELTA --> [CH2=CH-OH] --> HC=CH + H2O. Both PIMS and IR spectroscopy show compelling evidence for the participation of vinylidene, CH2=C:, as an intermediate in the decomposition of vinyl alchohol: CH2=CH-OH + DELTA --> [CH2=C:] + H2O --> HC=CH + H2O.

Using many pilot points and singular value decomposition in groundwater model calibration

DEFF Research Database (Denmark)

Christensen, Steen; Doherty, John

2008-01-01

over the model area. Singular value decomposition (SVD) of the normal matrix is used to reduce the large number of pilot point parameters to a smaller number of so-called super parameters that can be estimated by nonlinear regression from the available observations. A number of eigenvectors...

Low rank approximation methods for MR fingerprinting with large scale dictionaries.

Science.gov (United States)

Yang, Mingrui; Ma, Dan; Jiang, Yun; Hamilton, Jesse; Seiberlich, Nicole; Griswold, Mark A; McGivney, Debra

2018-04-01

This work proposes new low rank approximation approaches with significant memory savings for large scale MR fingerprinting (MRF) problems. We introduce a compressed MRF with randomized singular value decomposition method to significantly reduce the memory requirement for calculating a low rank approximation of large sized MRF dictionaries. We further relax this requirement by exploiting the structures of MRF dictionaries in the randomized singular value decomposition space and fitting them to low-degree polynomials to generate high resolution MRF parameter maps. In vivo 1.5T and 3T brain scan data are used to validate the approaches. T 1 , T 2 , and off-resonance maps are in good agreement with that of the standard MRF approach. Moreover, the memory savings is up to 1000 times for the MRF-fast imaging with steady-state precession sequence and more than 15 times for the MRF-balanced, steady-state free precession sequence. The proposed compressed MRF with randomized singular value decomposition and dictionary fitting methods are memory efficient low rank approximation methods, which can benefit the usage of MRF in clinical settings. They also have great potentials in large scale MRF problems, such as problems considering multi-component MRF parameters or high resolution in the parameter space. Magn Reson Med 79:2392-2400, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Matrix interdiction problem

Energy Technology Data Exchange (ETDEWEB)

Pan, Feng [Los Alamos National Laboratory; Kasiviswanathan, Shiva [Los Alamos National Laboratory

2010-01-01

In the matrix interdiction problem, a real-valued matrix and an integer k is given. The objective is to remove k columns such that the sum over all rows of the maximum entry in each row is minimized. This combinatorial problem is closely related to bipartite network interdiction problem which can be applied to prioritize the border checkpoints in order to minimize the probability that an adversary can successfully cross the border. After introducing the matrix interdiction problem, we will prove the problem is NP-hard, and even NP-hard to approximate with an additive n{gamma} factor for a fixed constant {gamma}. We also present an algorithm for this problem that achieves a factor of (n-k) mUltiplicative approximation ratio.

Microlocal study of S-matrix singularity structure

International Nuclear Information System (INIS)

Kawai, Takahiro; Kyoto Univ.; Stapp, H.P.

1975-01-01

Support is adduced for two related conjectures of simplicity of the analytic structure of the S-matrix and related function; namely, Sato's conjecture that the S-matrix is a solution of a maximally over-determined system of pseudo-differential equations, and our conjecture that the singularity spectrum of any bubble diagram function has the conormal structure with respect to a canonical decomposition of the solutions of the relevant Landau equations. This latter conjecture eliminates the open sets of allowed singularities that existing procedures permit. (orig.) [de

CP decomposition approach to blind separation for DS-CDMA system using a new performance index

Science.gov (United States)

Rouijel, Awatif; Minaoui, Khalid; Comon, Pierre; Aboutajdine, Driss

2014-12-01

In this paper, we present a canonical polyadic (CP) tensor decomposition isolating the scaling matrix. This has two major implications: (i) the problem conditioning shows up explicitly and could be controlled through a constraint on the so-called coherences and (ii) a performance criterion concerning the factor matrices can be exactly calculated and is more realistic than performance metrics used in the literature. Two new algorithms optimizing the CP decomposition based on gradient descent are proposed. This decomposition is illustrated by an application to direct-sequence code division multiplexing access (DS-CDMA) systems; computer simulations are provided and demonstrate the good behavior of these algorithms, compared to others in the literature.

Microbial Signatures of Cadaver Gravesoil During Decomposition.

Science.gov (United States)

Finley, Sheree J; Pechal, Jennifer L; Benbow, M Eric; Robertson, B K; Javan, Gulnaz T

2016-04-01

Genomic studies have estimated there are approximately 10(3)-10(6) bacterial species per gram of soil. The microbial species found in soil associated with decomposing human remains (gravesoil) have been investigated and recognized as potential molecular determinants for estimates of time since death. The nascent era of high-throughput amplicon sequencing of the conserved 16S ribosomal RNA (rRNA) gene region of gravesoil microbes is allowing research to expand beyond more subjective empirical methods used in forensic microbiology. The goal of the present study was to evaluate microbial communities and identify taxonomic signatures associated with the gravesoil human cadavers. Using 16S rRNA gene amplicon-based sequencing, soil microbial communities were surveyed from 18 cadavers placed on the surface or buried that were allowed to decompose over a range of decomposition time periods (3-303 days). Surface soil microbial communities showed a decreasing trend in taxon richness, diversity, and evenness over decomposition, while buried cadaver-soil microbial communities demonstrated increasing taxon richness, consistent diversity, and decreasing evenness. The results show that ubiquitous Proteobacteria was confirmed as the most abundant phylum in all gravesoil samples. Surface cadaver-soil communities demonstrated a decrease in Acidobacteria and an increase in Firmicutes relative abundance over decomposition, while buried soil communities were consistent in their community composition throughout decomposition. Better understanding of microbial community structure and its shifts over time may be important for advancing general knowledge of decomposition soil ecology and its potential use during forensic investigations.

Microwave-assisted versus conventional decomposition procedures applied to a ceramic potsherd standard reference material by inductively coupled plasma atomic emission spectrometry

Energy Technology Data Exchange (ETDEWEB)

Papadopoulou, D.N.; Zachariadis, G.A.; Anthemidis, A.N.; Tsirliganis, N.C.; Stratis, J.A

2004-03-03

Inductively coupled plasma atomic emission spectrometry (ICP-AES) is a powerful, sensitive analytical technique with numerous applications in chemical characterization including that of ancient pottery, mainly due to its multi-element character, and the relatively short time required for the analysis. A critical step in characterization studies of ancient pottery is the selection of a suitable decomposition procedure for the ceramic matrix. The current work presents the results of a comparative study of six decomposition procedures applied on a standard ceramic potsherd reference material, SARM 69. The investigated decomposition procedures included three microwave-assisted decomposition procedures, one wet decomposition (WD) procedure by conventional heating, one combined microwave-assisted and conventional heating WD procedure, and one fusion procedure. Chemical analysis was carried out by ICP-AES. Five major (Si, Al, Fe, Ca, Mg), three minor (Mn, Ba, Ti) and two trace (Cu, Co) elements were determined and compared with their certified values. Quantitation was performed at two different spectral lines for each element and multi-element matrix-matched calibration standards were used. The recovery values for the six decomposition procedures ranged between 75 and 110% with a few notable exceptions. Data were processed statistically in order to evaluate the investigated decomposition procedures in terms of recovery, accuracy and precision, and eventually select the most appropriate one for ancient pottery analysis.

Performance of Scattering Matrix Decomposition and Color Spaces for Synthetic Aperture Radar Imagery

Science.gov (United States)

2010-03-01

Color Spaces and Synthetic Aperture Radar (SAR) Multicolor Imaging. 15 2.3.1 Colorimetry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 2.3.2...III. Decomposition Techniques on SAR Polarimetry and Colorimetry applied to SAR Imagery...space polarimetric SAR systems. Colorimetry is also introduced in this chapter, presenting the fundamentals of the RGB and CMY color spaces, defined for

Decoupling the direct and indirect effects of climate on plant litter decomposition: Accounting for stress-induced modifications in plant chemistry.

Science.gov (United States)

Suseela, Vidya; Tharayil, Nishanth

2018-04-01

Decomposition of plant litter is a fundamental ecosystem process that can act as a feedback to climate change by simultaneously influencing both the productivity of ecosystems and the flux of carbon dioxide from the soil. The influence of climate on decomposition from a postsenescence perspective is relatively well known; in particular, climate is known to regulate the rate of litter decomposition via its direct influence on the reaction kinetics and microbial physiology on processes downstream of tissue senescence. Climate can alter plant metabolism during the formative stage of tissues and could shape the final chemical composition of plant litter that is available for decomposition, and thus indirectly influence decomposition; however, these indirect effects are relatively poorly understood. Climatic stress disrupts cellular homeostasis in plants and results in the reprogramming of primary and secondary metabolic pathways, which leads to changes in the quantity, composition, and organization of small molecules and recalcitrant heteropolymers, including lignins, tannins, suberins, and cuticle within the plant tissue matrix. Furthermore, by regulating metabolism during tissue senescence, climate influences the resorption of nutrients from senescing tissues. Thus, the final chemical composition of plant litter that forms the substrate of decomposition is a combined product of presenescence physiological processes through the production and resorption of metabolites. The changes in quantity, composition, and localization of the molecular construct of the litter could enhance or hinder tissue decomposition and soil nutrient cycling by altering the recalcitrance of the lignocellulose matrix, the composition of microbial communities, and the activity of microbial exo-enzymes via various complexation reactions. Also, the climate-induced changes in the molecular composition of litter could differentially influence litter decomposition and soil nutrient cycling. Compared

Approximate Method for Solving the Linear Fuzzy Delay Differential Equations

Directory of Open Access Journals (Sweden)

S. Narayanamoorthy

2015-01-01

Full Text Available We propose an algorithm of the approximate method to solve linear fuzzy delay differential equations using Adomian decomposition method. The detailed algorithm of the approach is provided. The approximate solution is compared with the exact solution to confirm the validity and efficiency of the method to handle linear fuzzy delay differential equation. To show this proper features of this proposed method, numerical example is illustrated.

Matrix calculus

CERN Document Server

Bodewig, E

1959-01-01

Matrix Calculus, Second Revised and Enlarged Edition focuses on systematic calculation with the building blocks of a matrix and rows and columns, shunning the use of individual elements. The publication first offers information on vectors, matrices, further applications, measures of the magnitude of a matrix, and forms. The text then examines eigenvalues and exact solutions, including the characteristic equation, eigenrows, extremum properties of the eigenvalues, bounds for the eigenvalues, elementary divisors, and bounds for the determinant. The text ponders on approximate solutions, as well

Tensor Decompositions for Learning Latent Variable Models

Science.gov (United States)

2012-12-08

and eigenvectors of tensors is generally significantly more complicated than their matrix counterpart (both algebraically [Qi05, CS11, Lim05] and...The reduction First, let W ∈ Rd×k be a linear transformation such that M2(W,W ) = W M2W = I where I is the k × k identity matrix (i.e., W whitens ...approximate the whitening matrix W ∈ Rd×k from second-moment matrix M2 ∈ Rd×d. To do this, one first multiplies M2 by a random matrix R ∈ Rd×k′ for some k′ ≥ k

A copyright protection scheme for digital images based on shuffled singular value decomposition and visual cryptography.

Science.gov (United States)

Devi, B Pushpa; Singh, Kh Manglem; Roy, Sudipta

2016-01-01

This paper proposes a new watermarking algorithm based on the shuffled singular value decomposition and the visual cryptography for copyright protection of digital images. It generates the ownership and identification shares of the image based on visual cryptography. It decomposes the image into low and high frequency sub-bands. The low frequency sub-band is further divided into blocks of same size after shuffling it and then the singular value decomposition is applied to each randomly selected block. Shares are generated by comparing one of the elements in the first column of the left orthogonal matrix with its corresponding element in the right orthogonal matrix of the singular value decomposition of the block of the low frequency sub-band. The experimental results show that the proposed scheme clearly verifies the copyright of the digital images, and is robust to withstand several image processing attacks. Comparison with the other related visual cryptography-based algorithms reveals that the proposed method gives better performance. The proposed method is especially resilient against the rotation attack.

Fast wavelet based sparse approximate inverse preconditioner

Energy Technology Data Exchange (ETDEWEB)

Wan, W.L. [Univ. of California, Los Angeles, CA (United States)

1996-12-31

Incomplete LU factorization is a robust preconditioner for both general and PDE problems but unfortunately not easy to parallelize. Recent study of Huckle and Grote and Chow and Saad showed that sparse approximate inverse could be a potential alternative while readily parallelizable. However, for special class of matrix A that comes from elliptic PDE problems, their preconditioners are not optimal in the sense that independent of mesh size. A reason may be that no good sparse approximate inverse exists for the dense inverse matrix. Our observation is that for this kind of matrices, its inverse entries typically have piecewise smooth changes. We can take advantage of this fact and use wavelet compression techniques to construct a better sparse approximate inverse preconditioner. We shall show numerically that our approach is effective for this kind of matrices.

Big geo data surface approximation using radial basis functions: A comparative study

Science.gov (United States)

Majdisova, Zuzana; Skala, Vaclav

2017-12-01

Approximation of scattered data is often a task in many engineering problems. The Radial Basis Function (RBF) approximation is appropriate for big scattered datasets in n-dimensional space. It is a non-separable approximation, as it is based on the distance between two points. This method leads to the solution of an overdetermined linear system of equations. In this paper the RBF approximation methods are briefly described, a new approach to the RBF approximation of big datasets is presented, and a comparison for different Compactly Supported RBFs (CS-RBFs) is made with respect to the accuracy of the computation. The proposed approach uses symmetry of a matrix, partitioning the matrix into blocks and data structures for storage of the sparse matrix. The experiments are performed for synthetic and real datasets.

Four-level time decomposition quasi-static power flow and successive disturbances analysis. [Power system disturbances

Energy Technology Data Exchange (ETDEWEB)

Jovanovic, S M [Nikola Tesla Inst., Belgrade (YU)

1990-01-01

This paper presents a model and an appropriate numerical procedure for a four-level time decomposition quasi-static power flow and successive disturbances analysis of power systems. The analysis consists of the sequential computation of the zero, primary, secondary and tertiary quasi-static states and of the estimation of successive structural disturbances during the 1200 s dynamics after a structural disturbance. The model is developed by detailed inspection of the time decomposition characteristics of automatic protection and control devices. Adequate speed of the numerical procedure is attained by a specific application of the inversion matrix lemma and the decoupled model constant coefficient matrices. The four-level time decomposition quasi-static method is intended for security and emergency analysis. (author).

Radioactivity computation of steady-state and pulsed fusion reactors operation

International Nuclear Information System (INIS)

Attaya, H.

1994-06-01

Different mathematical methods are used to calculate the nuclear transmutation in steady-state and pulsed neutron irradiation. These methods are the Schuer decomposition, the eigenvector decomposition, and the Pade approximation of the matrix exponential function. In the case of the linear decay chain approximation, a simple algorithm is used to evaluate the transition matrices

Decomposition of orthogonal polygons in a set of rectanglеs

OpenAIRE

Shestakov, E.; Voronov, A.

2009-01-01

Algorithm for covering orthogonal integrated circuit layout objects is considered. Objects of the research are special single-connected orthogonal polygons which are generated during decomposition of any multiply connected polygon in a set of single-connected orthogonal polygons. Developed algorithm for covering polygons based on the mathematical techinque of logic matrix transformation. Results described in this paper, can be applied in computer geometry and image analysis.

Asynchronous Task-Based Polar Decomposition on Manycore Architectures

KAUST Repository

Sukkari, Dalal

2016-10-25

This paper introduces the first asynchronous, task-based implementation of the polar decomposition on manycore architectures. Based on a new formulation of the iterative QR dynamically-weighted Halley algorithm (QDWH) for the calculation of the polar decomposition, the proposed implementation replaces the original and hostile LU factorization for the condition number estimator by the more adequate QR factorization to enable software portability across various architectures. Relying on fine-grained computations, the novel task-based implementation is also capable of taking advantage of the identity structure of the matrix involved during the QDWH iterations, which decreases the overall algorithmic complexity. Furthermore, the artifactual synchronization points have been severely weakened compared to previous implementations, unveiling look-ahead opportunities for better hardware occupancy. The overall QDWH-based polar decomposition can then be represented as a directed acyclic graph (DAG), where nodes represent computational tasks and edges define the inter-task data dependencies. The StarPU dynamic runtime system is employed to traverse the DAG, to track the various data dependencies and to asynchronously schedule the computational tasks on the underlying hardware resources, resulting in an out-of-order task scheduling. Benchmarking experiments show significant improvements against existing state-of-the-art high performance implementations (i.e., Intel MKL and Elemental) for the polar decomposition on latest shared-memory vendors\\' systems (i.e., Intel Haswell/Broadwell/Knights Landing, NVIDIA K80/P100 GPUs and IBM Power8), while maintaining high numerical accuracy.

Decomposition of forest products buried in landfills

International Nuclear Information System (INIS)

Wang, Xiaoming; Padgett, Jennifer M.; Powell, John S.; Barlaz, Morton A.

2013-01-01

Highlights: • This study tracked chemical changes of wood and paper in landfills. • A decomposition index was developed to quantify carbohydrate biodegradation. • Newsprint biodegradation as measured here is greater than previous reports. • The field results correlate well with previous laboratory measurements. - Abstract: The objective of this study was to investigate the decomposition of selected wood and paper products in landfills. The decomposition of these products under anaerobic landfill conditions results in the generation of biogenic carbon dioxide and methane, while the un-decomposed portion represents a biogenic carbon sink. Information on the decomposition of these municipal waste components is used to estimate national methane emissions inventories, for attribution of carbon storage credits, and to assess the life-cycle greenhouse gas impacts of wood and paper products. Hardwood (HW), softwood (SW), plywood (PW), oriented strand board (OSB), particleboard (PB), medium-density fiberboard (MDF), newsprint (NP), corrugated container (CC) and copy paper (CP) were buried in landfills operated with leachate recirculation, and were excavated after approximately 1.5 and 2.5 yr. Samples were analyzed for cellulose (C), hemicellulose (H), lignin (L), volatile solids (VS), and organic carbon (OC). A holocellulose decomposition index (HOD) and carbon storage factor (CSF) were calculated to evaluate the extent of solids decomposition and carbon storage. Samples of OSB made from HW exhibited cellulose plus hemicellulose (C + H) loss of up to 38%, while loss for the other wood types was 0–10% in most samples. The C + H loss was up to 81%, 95% and 96% for NP, CP and CC, respectively. The CSFs for wood and paper samples ranged from 0.34 to 0.47 and 0.02 to 0.27 g OC g −1 dry material, respectively. These results, in general, correlated well with an earlier laboratory-scale study, though NP and CC decomposition measured in this study were higher than

Decomposition of forest products buried in landfills

Energy Technology Data Exchange (ETDEWEB)

Wang, Xiaoming, E-mail: xwang25@ncsu.edu [Department of Civil, Construction, and Environmental Engineering, Campus Box 7908, North Carolina State University, Raleigh, NC 27695-7908 (United States); Padgett, Jennifer M. [Department of Civil, Construction, and Environmental Engineering, Campus Box 7908, North Carolina State University, Raleigh, NC 27695-7908 (United States); Powell, John S. [Department of Chemical and Biomolecular Engineering, Campus Box 7905, North Carolina State University, Raleigh, NC 27695-7905 (United States); Barlaz, Morton A. [Department of Civil, Construction, and Environmental Engineering, Campus Box 7908, North Carolina State University, Raleigh, NC 27695-7908 (United States)

2013-11-15

Highlights: • This study tracked chemical changes of wood and paper in landfills. • A decomposition index was developed to quantify carbohydrate biodegradation. • Newsprint biodegradation as measured here is greater than previous reports. • The field results correlate well with previous laboratory measurements. - Abstract: The objective of this study was to investigate the decomposition of selected wood and paper products in landfills. The decomposition of these products under anaerobic landfill conditions results in the generation of biogenic carbon dioxide and methane, while the un-decomposed portion represents a biogenic carbon sink. Information on the decomposition of these municipal waste components is used to estimate national methane emissions inventories, for attribution of carbon storage credits, and to assess the life-cycle greenhouse gas impacts of wood and paper products. Hardwood (HW), softwood (SW), plywood (PW), oriented strand board (OSB), particleboard (PB), medium-density fiberboard (MDF), newsprint (NP), corrugated container (CC) and copy paper (CP) were buried in landfills operated with leachate recirculation, and were excavated after approximately 1.5 and 2.5 yr. Samples were analyzed for cellulose (C), hemicellulose (H), lignin (L), volatile solids (VS), and organic carbon (OC). A holocellulose decomposition index (HOD) and carbon storage factor (CSF) were calculated to evaluate the extent of solids decomposition and carbon storage. Samples of OSB made from HW exhibited cellulose plus hemicellulose (C + H) loss of up to 38%, while loss for the other wood types was 0–10% in most samples. The C + H loss was up to 81%, 95% and 96% for NP, CP and CC, respectively. The CSFs for wood and paper samples ranged from 0.34 to 0.47 and 0.02 to 0.27 g OC g{sup −1} dry material, respectively. These results, in general, correlated well with an earlier laboratory-scale study, though NP and CC decomposition measured in this study were higher than

Asynchronous Task-Based Polar Decomposition on Single Node Manycore Architectures

KAUST Repository

Sukkari, Dalal E.; Ltaief, Hatem; Faverge, Mathieu; Keyes, David E.

2017-01-01

This paper introduces the first asynchronous, task-based formulation of the polar decomposition and its corresponding implementation on manycore architectures. Based on a formulation of the iterative QR dynamically-weighted Halley algorithm (QDWH) for the calculation of the polar decomposition, the proposed implementation replaces the original LU factorization for the condition number estimator by the more adequate QR factorization to enable software portability across various architectures. Relying on fine-grained computations, the novel task-based implementation is capable of taking advantage of the identity structure of the matrix involved during the QDWH iterations, which decreases the overall algorithmic complexity. Furthermore, the artifactual synchronization points have been weakened compared to previous implementations, unveiling look-ahead opportunities for better hardware occupancy. The overall QDWH-based polar decomposition can then be represented as a directed acyclic graph (DAG), where nodes represent computational tasks and edges define the inter-task data dependencies. The StarPU dynamic runtime system is employed to traverse the DAG, to track the various data dependencies and to asynchronously schedule the computational tasks on the underlying hardware resources, resulting in an out-of-order task scheduling. Benchmarking experiments show significant improvements against existing state-of-the-art high performance implementations for the polar decomposition on latest shared-memory vendors' systems, while maintaining numerical accuracy.

Asynchronous Task-Based Polar Decomposition on Single Node Manycore Architectures

KAUST Repository

Sukkari, Dalal E.

2017-09-29

This paper introduces the first asynchronous, task-based formulation of the polar decomposition and its corresponding implementation on manycore architectures. Based on a formulation of the iterative QR dynamically-weighted Halley algorithm (QDWH) for the calculation of the polar decomposition, the proposed implementation replaces the original LU factorization for the condition number estimator by the more adequate QR factorization to enable software portability across various architectures. Relying on fine-grained computations, the novel task-based implementation is capable of taking advantage of the identity structure of the matrix involved during the QDWH iterations, which decreases the overall algorithmic complexity. Furthermore, the artifactual synchronization points have been weakened compared to previous implementations, unveiling look-ahead opportunities for better hardware occupancy. The overall QDWH-based polar decomposition can then be represented as a directed acyclic graph (DAG), where nodes represent computational tasks and edges define the inter-task data dependencies. The StarPU dynamic runtime system is employed to traverse the DAG, to track the various data dependencies and to asynchronously schedule the computational tasks on the underlying hardware resources, resulting in an out-of-order task scheduling. Benchmarking experiments show significant improvements against existing state-of-the-art high performance implementations for the polar decomposition on latest shared-memory vendors\\' systems, while maintaining numerical accuracy.

DOLOMITE THERMAL-DECOMPOSITION MACROKINETIC MODELS FOR EVALUATION OF THE GASGENERATORS SORBENT SYSTEMS

Directory of Open Access Journals (Sweden)

K. V. Dobrego

2015-01-01

Full Text Available Employing dolomite in the capacity of a sorbent for generator gas purification is of considerable interest nowadays, as it is the impurity of generator gas that causes the major problem for creating cheep and effective co-generator plants. Designing gas purification systems employs simple but physically adequate macrokinetic models of dolomite thermal decomposition.  The  paper  analyzes  peculiarities  of  several  contemporaneous  models  of  dolomite and calcite thermal decomposition and infers on reasonable practicality for creating compact engineering dolomite-decomposition macrokinetic models and universal techniques of these models parameter reconstruction for specific dolomite samples. Such technics can be founded on thermogravimetric data and standard approximation error minimizing algorithms.The author assumes that CO2  evacuation from the reaction zone within the particle may proceed by diffusion mechanism and/or by the Darcy filtration and indicates that functional dependence of the thermal-decomposition rate from the particle sizes and the temperature differs for the specified mechanisms. The paper formulates four macrokinetic models whose correspondence verification is grounded on the experimental data. The author concludes that further work in this direction should proceed with the dolomite samples investigation and selecting the best approximation model describing experimental data in wide range of temperatures, warming up rates and the particle sizes.

Symbolic computation of analytic approximate solutions for nonlinear fractional differential equations

Science.gov (United States)

Lin, Yezhi; Liu, Yinping; Li, Zhibin

2013-01-01

The Adomian decomposition method (ADM) is one of the most effective methods to construct analytic approximate solutions for nonlinear differential equations. In this paper, based on the new definition of the Adomian polynomials, Rach (2008) [22], the Adomian decomposition method and the Padé approximants technique, a new algorithm is proposed to construct analytic approximate solutions for nonlinear fractional differential equations with initial or boundary conditions. Furthermore, a MAPLE software package is developed to implement this new algorithm, which is user-friendly and efficient. One only needs to input the system equation, initial or boundary conditions and several necessary parameters, then our package will automatically deliver the analytic approximate solutions within a few seconds. Several different types of examples are given to illustrate the scope and demonstrate the validity of our package, especially for non-smooth initial value problems. Our package provides a helpful and easy-to-use tool in science and engineering simulations. Program summaryProgram title: ADMP Catalogue identifier: AENE_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AENE_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 12011 No. of bytes in distributed program, including test data, etc.: 575551 Distribution format: tar.gz Programming language: MAPLE R15. Computer: PCs. Operating system: Windows XP/7. RAM: 2 Gbytes Classification: 4.3. Nature of problem: Constructing analytic approximate solutions of nonlinear fractional differential equations with initial or boundary conditions. Non-smooth initial value problems can be solved by this program. Solution method: Based on the new definition of the Adomian polynomials [1], the Adomian decomposition method and the Pad

Ab initio study of spinodal decomposition in (Zn,Cr)Te

International Nuclear Information System (INIS)

Fukushima, T.; Sato, K.; Katayama-Yoshida, H.; Dederichs, P.H.

2006-01-01

The spinodal decomposition in (Zn,Cr)Te is simulated by using first principles calculations and Monte Carlo simulation. It is found that the chemical pair interaction between Cr atoms in (Zn,Cr)Te is attractive interaction and leads to spinodal decomposition. Curie temperatures in decomposed situation are estimated by the random phase approximation with taking the magnetic percolation effect into account. This decomposed phase makes the random pattern of high concentration regions which connect each other and have possibility to realize high Curie temperature. (copyright 2006 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (Abstract Copyright [2006], Wiley Periodicals, Inc.)

Ozone decomposition

Directory of Open Access Journals (Sweden)

Batakliev Todor

2014-06-01

Full Text Available Catalytic ozone decomposition is of great significance because ozone is a toxic substance commonly found or generated in human environments (aircraft cabins, offices with photocopiers, laser printers, sterilizers. Considerable work has been done on ozone decomposition reported in the literature. This review provides a comprehensive summary of the literature, concentrating on analysis of the physico-chemical properties, synthesis and catalytic decomposition of ozone. This is supplemented by a review on kinetics and catalyst characterization which ties together the previously reported results. Noble metals and oxides of transition metals have been found to be the most active substances for ozone decomposition. The high price of precious metals stimulated the use of metal oxide catalysts and particularly the catalysts based on manganese oxide. It has been determined that the kinetics of ozone decomposition is of first order importance. A mechanism of the reaction of catalytic ozone decomposition is discussed, based on detailed spectroscopic investigations of the catalytic surface, showing the existence of peroxide and superoxide surface intermediates

TH-A-18C-07: Noise Suppression in Material Decomposition for Dual-Energy CT

International Nuclear Information System (INIS)

Dong, X; Petrongolo, M; Wang, T; Zhu, L

2014-01-01

Purpose: A general problem of dual-energy CT (DECT) is that the decomposition is sensitive to noise in the two sets of dual-energy projection data, resulting in severely degraded qualities of decomposed images. We have previously proposed an iterative denoising method for DECT. Using a linear decomposition function, the method does not gain the full benefits of DECT on beam-hardening correction. In this work, we expand the framework of our iterative method to include non-linear decomposition models for noise suppression in DECT. Methods: We first obtain decomposed projections, which are free of beam-hardening artifacts, using a lookup table pre-measured on a calibration phantom. First-pass material images with high noise are reconstructed from the decomposed projections using standard filter-backprojection reconstruction. Noise on the decomposed images is then suppressed by an iterative method, which is formulated in the form of least-square estimation with smoothness regularization. Based on the design principles of a best linear unbiased estimator, we include the inverse of the estimated variance-covariance matrix of the decomposed images as the penalty weight in the least-square term. Analytical formulae are derived to compute the variance-covariance matrix from the measured decomposition lookup table. Results: We have evaluated the proposed method via phantom studies. Using non-linear decomposition, our method effectively suppresses the streaking artifacts of beam-hardening and obtains more uniform images than our previous approach based on a linear model. The proposed method reduces the average noise standard deviation of two basis materials by one order of magnitude without sacrificing the spatial resolution. Conclusion: We propose a general framework of iterative denoising for material decomposition of DECT. Preliminary phantom studies have shown the proposed method improves the image uniformity and reduces noise level without resolution loss. In the future

Thermal decomposition of potassium metaperiodate doped with trivalent ions

Energy Technology Data Exchange (ETDEWEB)

Muraleedharan, K., E-mail: kmuralika@gmail.com [Department of Chemistry, University of Calicut, Calicut, Kerala 673 635 (India); Kannan, M.P.; Gangadevi, T. [Department of Chemistry, University of Calicut, Calicut, Kerala 673 635 (India)

2010-04-20

The kinetics of isothermal decomposition of potassium metaperiodate (KIO{sub 4}), doped with phosphate and aluminium has been studied by thermogravimetry (TG). We introduced a custom-made thermobalance that is able to record weight decrease with time under pure isothermal conditions. The decomposition proceeds mainly through two stages: an acceleratory stages up to {alpha} = 0.50 and the decay stage beyond. The decomposition data for aluminium and phosphate doped KIO{sub 4} were found to be best described by the Prout-Tompkins equation. Separate kinetic analyses of the {alpha}-t data corresponding to the acceleratory region and decay region showed that the acceleratory stage gave the best fit with Prout-Tompkins equation itself whereas the decay stage fitted better to the contracting area equation. The rate of decomposition of phosphate doped KIO{sub 4} increases approximately linearly with an increase in the dopant concentration. In the case of aluminium doped KIO{sub 4}, the rate passes through a maximum with increase in the dopant concentration. The {alpha}-t data of pure and doped KIO{sub 4} were also subjected to isoconversional studies for the determination of activation energy values. Doping did not change the activation energy of the reaction. The results favour an electron-transfer mechanism for the isothermal decomposition of KIO{sub 4}, agreeing well with our earlier observations.

The coupled-channel T-matrix: its lowest-order Born + Lanczos approximants

International Nuclear Information System (INIS)

Znojil, M.

1995-01-01

Three iterative methods of solution of the Lippmann-Schwinger equations (viz., the method of continued fractions by J.Horacek and T.Sasakawa), its Born-remainder modification and a coupled-channel matrix-continued-fraction generalization are all interpreted as special cases of a common iterative matrix prescription. Firstly, in terms of certain asymmetric projectors P≠P + , we re-derive the three particular older methods as different realizations of the well-known Lanczos inversion. Then, a generalized iteration method is proposed as a Born-like re-arrangement of any intermediate Lanczos iteration step. A maximal flexibility is achieved in the formalism which might compete with the standard Pade re-summations in practice. Its first few truncations are listed, therefore. 26 refs., 1 tab

General factorization relations and consistency conditions in the sudden approximation via infinite matrix inversion

International Nuclear Information System (INIS)

Chan, C.K.; Hoffman, D.K.; Evans, J.W.

1985-01-01

Local, i.e., multiplicative, operators satisfy well-known linear factorization relations wherein matrix elements (between states associated with a complete set of wave functions) can be obtained as a linear combination of those out of the ground state (the input data). Analytic derivation of factorization relations for general state input data results in singular integral expressions for the coefficients, which can, however, be regularized using consistency conditions between matrix elements out of a single (nonground) state. Similar results hold for suitable ''symmetry class'' averaged matrix elements where the symmetry class projection operators are ''complete.'' In several cases where the wave functions or projection operators incorporate orthogonal polynomial dependence, we show that the ground state factorization relations have a simplified structure allowing an alternative derivation of the general factorization relations via an infinite matrix inversion procedure. This form is shown to have some advantages over previous versions. In addition, this matrix inversion procedure obtains all consistency conditions (which is not always the case from regularization of singular integrals)

Speech Denoising in White Noise Based on Signal Subspace Low-rank Plus Sparse Decomposition

Directory of Open Access Journals (Sweden)

yuan Shuai

2017-01-01

Full Text Available In this paper, a new subspace speech enhancement method using low-rank and sparse decomposition is presented. In the proposed method, we firstly structure the corrupted data as a Toeplitz matrix and estimate its effective rank for the underlying human speech signal. Then the low-rank and sparse decomposition is performed with the guidance of speech rank value to remove the noise. Extensive experiments have been carried out in white Gaussian noise condition, and experimental results show the proposed method performs better than conventional speech enhancement methods, in terms of yielding less residual noise and lower speech distortion.

Approximate motion integrals and the quantum chaos problem

International Nuclear Information System (INIS)

Bunakov, V.E.; Ivanov, I.B.

2001-01-01

One discusses the problem of occurrence and seek for the motion integrals in the stationary quantum mechanics and its relation to the quantum chaos. One studies decomposition of quantum numbers and derives the criterion of chaos. To seek the motion integrals one applies the convergence method. One derived the approximate integrals in the Hennone-Hales problem. One discusses the problem of compatibility of chaos and integrability [ru

A cluster approximation for the transfer-matrix method

International Nuclear Information System (INIS)

Surda, A.

1990-08-01

A cluster approximation for the transfer-method is formulated. The calculation of the partition function of lattice models is transformed to a nonlinear mapping problem. The method yields the free energy, correlation functions and the phase diagrams for a large class of lattice models. The high accuracy of the method is exemplified by the calculation of the critical temperature of the Ising model. (author). 14 refs, 2 figs, 1 tab

Likelihood Approximation With Hierarchical Matrices For Large Spatial Datasets

KAUST Repository

Litvinenko, Alexander

2017-09-03

We use available measurements to estimate the unknown parameters (variance, smoothness parameter, and covariance length) of a covariance function by maximizing the joint Gaussian log-likelihood function. To overcome cubic complexity in the linear algebra, we approximate the discretized covariance function in the hierarchical (H-) matrix format. The H-matrix format has a log-linear computational cost and storage O(kn log n), where the rank k is a small integer and n is the number of locations. The H-matrix technique allows us to work with general covariance matrices in an efficient way, since H-matrices can approximate inhomogeneous covariance functions, with a fairly general mesh that is not necessarily axes-parallel, and neither the covariance matrix itself nor its inverse have to be sparse. We demonstrate our method with Monte Carlo simulations and an application to soil moisture data. The C, C++ codes and data are freely available.

Subtracting a best rank-1 approximation may increase tensor rank

NARCIS (Netherlands)

Stegeman, Alwin; Comon, Pierre

2010-01-01

It has been shown that a best rank-R approximation of an order-k tensor may not exist when R >= 2 and k >= 3. This poses a serious problem to data analysts using tensor decompositions it has been observed numerically that, generally, this issue cannot be solved by consecutively computing and

A Hybrid Model Based on Wavelet Decomposition-Reconstruction in Track Irregularity State Forecasting

Directory of Open Access Journals (Sweden)

Chaolong Jia

2015-01-01

Full Text Available Wavelet is able to adapt to the requirements of time-frequency signal analysis automatically and can focus on any details of the signal and then decompose the function into the representation of a series of simple basis functions. It is of theoretical and practical significance. Therefore, this paper does subdivision on track irregularity time series based on the idea of wavelet decomposition-reconstruction and tries to find the best fitting forecast model of detail signal and approximate signal obtained through track irregularity time series wavelet decomposition, respectively. On this ideology, piecewise gray-ARMA recursive based on wavelet decomposition and reconstruction (PG-ARMARWDR and piecewise ANN-ARMA recursive based on wavelet decomposition and reconstruction (PANN-ARMARWDR models are proposed. Comparison and analysis of two models have shown that both these models can achieve higher accuracy.

Multivariate Padé Approximation for Solving Nonlinear Partial Differential Equations of Fractional Order

Directory of Open Access Journals (Sweden)

Veyis Turut

2013-01-01

Full Text Available Two tecHniques were implemented, the Adomian decomposition method (ADM and multivariate Padé approximation (MPA, for solving nonlinear partial differential equations of fractional order. The fractional derivatives are described in Caputo sense. First, the fractional differential equation has been solved and converted to power series by Adomian decomposition method (ADM, then power series solution of fractional differential equation was put into multivariate Padé series. Finally, numerical results were compared and presented in tables and figures.

Simultaneous tensor decomposition and completion using factor priors.

Science.gov (United States)

Chen, Yi-Lei; Hsu, Chiou-Ting; Liao, Hong-Yuan Mark

2014-03-01

The success of research on matrix completion is evident in a variety of real-world applications. Tensor completion, which is a high-order extension of matrix completion, has also generated a great deal of research interest in recent years. Given a tensor with incomplete entries, existing methods use either factorization or completion schemes to recover the missing parts. However, as the number of missing entries increases, factorization schemes may overfit the model because of incorrectly predefined ranks, while completion schemes may fail to interpret the model factors. In this paper, we introduce a novel concept: complete the missing entries and simultaneously capture the underlying model structure. To this end, we propose a method called simultaneous tensor decomposition and completion (STDC) that combines a rank minimization technique with Tucker model decomposition. Moreover, as the model structure is implicitly included in the Tucker model, we use factor priors, which are usually known a priori in real-world tensor objects, to characterize the underlying joint-manifold drawn from the model factors. By exploiting this auxiliary information, our method leverages two classic schemes and accurately estimates the model factors and missing entries. We conducted experiments to empirically verify the convergence of our algorithm on synthetic data and evaluate its effectiveness on various kinds of real-world data. The results demonstrate the efficacy of the proposed method and its potential usage in tensor-based applications. It also outperforms state-of-the-art methods on multilinear model analysis and visual data completion tasks.

Uniform analytic approximation of Wigner rotation matrices

Science.gov (United States)

Hoffmann, Scott E.

2018-02-01

We derive the leading asymptotic approximation, for low angle θ, of the Wigner rotation matrix elements, dm1m2 j(θ ) , uniform in j, m1, and m2. The result is in terms of a Bessel function of integer order. We numerically investigate the error for a variety of cases and find that the approximation can be useful over a significant range of angles. This approximation has application in the partial wave analysis of wavepacket scattering.

Muonic molecules as three-body Coulomb problem in adiabatic approximation

International Nuclear Information System (INIS)

Decker, M.

1994-04-01

The three-body Coulomb problem is treated within the framework of the hyperspherical adiabatic approach. The surface functions are expanded into Faddeev-type components in order to ensure the equivalent representation of all possible two-body contributions. It is shown that this decomposition reduces the numerical effort considerably. The remaining radial equations are solved both in the extreme and the uncoupled adiabatic approximation to determine the binding energies of the systems (dtμ) and (d 3 Heμ). Whereas the ground state is described very well in the uncoupled adiabatic approximation, the excited states should be treated within the coupled adiabatic approximation to obtain good agreement with variational calculations. (orig.)

3D quantitative analysis of early decomposition changes of the human face.

Science.gov (United States)

Caplova, Zuzana; Gibelli, Daniele Maria; Poppa, Pasquale; Cummaudo, Marco; Obertova, Zuzana; Sforza, Chiarella; Cattaneo, Cristina

2018-03-01

Decomposition of the human body and human face is influenced, among other things, by environmental conditions. The early decomposition changes that modify the appearance of the face may hamper the recognition and identification of the deceased. Quantitative assessment of those changes may provide important information for forensic identification. This report presents a pilot 3D quantitative approach of tracking early decomposition changes of a single cadaver in controlled environmental conditions by summarizing the change with weekly morphological descriptions. The root mean square (RMS) value was used to evaluate the changes of the face after death. The results showed a high correlation (r = 0.863) between the measured RMS and the time since death. RMS values of each scan are presented, as well as the average weekly RMS values. The quantification of decomposition changes could improve the accuracy of antemortem facial approximation and potentially could allow the direct comparisons of antemortem and postmortem 3D scans.

Paths correlation matrix.

Science.gov (United States)

Qian, Weixian; Zhou, Xiaojun; Lu, Yingcheng; Xu, Jiang

2015-09-15

Both the Jones and Mueller matrices encounter difficulties when physically modeling mixed materials or rough surfaces due to the complexity of light-matter interactions. To address these issues, we derived a matrix called the paths correlation matrix (PCM), which is a probabilistic mixture of Jones matrices of every light propagation path. Because PCM is related to actual light propagation paths, it is well suited for physical modeling. Experiments were performed, and the reflection PCM of a mixture of polypropylene and graphite was measured. The PCM of the mixed sample was accurately decomposed into pure polypropylene's single reflection, pure graphite's single reflection, and depolarization caused by multiple reflections, which is consistent with the theoretical derivation. Reflection parameters of rough surface can be calculated from PCM decomposition, and the results fit well with the theoretical calculations provided by the Fresnel equations. These theoretical and experimental analyses verify that PCM is an efficient way to physically model light-matter interactions.

Decomposition techniques

Science.gov (United States)

Chao, T.T.; Sanzolone, R.F.

1992-01-01

Sample decomposition is a fundamental and integral step in the procedure of geochemical analysis. It is often the limiting factor to sample throughput, especially with the recent application of the fast and modern multi-element measurement instrumentation. The complexity of geological materials makes it necessary to choose the sample decomposition technique that is compatible with the specific objective of the analysis. When selecting a decomposition technique, consideration should be given to the chemical and mineralogical characteristics of the sample, elements to be determined, precision and accuracy requirements, sample throughput, technical capability of personnel, and time constraints. This paper addresses these concerns and discusses the attributes and limitations of many techniques of sample decomposition along with examples of their application to geochemical analysis. The chemical properties of reagents as to their function as decomposition agents are also reviewed. The section on acid dissolution techniques addresses the various inorganic acids that are used individually or in combination in both open and closed systems. Fluxes used in sample fusion are discussed. The promising microwave-oven technology and the emerging field of automation are also examined. A section on applications highlights the use of decomposition techniques for the determination of Au, platinum group elements (PGEs), Hg, U, hydride-forming elements, rare earth elements (REEs), and multi-elements in geological materials. Partial dissolution techniques used for geochemical exploration which have been treated in detail elsewhere are not discussed here; nor are fire-assaying for noble metals and decomposition techniques for X-ray fluorescence or nuclear methods be discussed. ?? 1992.

Likelihood Approximation With Hierarchical Matrices For Large Spatial Datasets

KAUST Repository

Litvinenko, Alexander; Sun, Ying; Genton, Marc G.; Keyes, David E.

2017-01-01

algebra, we approximate the discretized covariance function in the hierarchical (H-) matrix format. The H-matrix format has a log-linear computational cost and storage O(kn log n), where the rank k is a small integer and n is the number of locations. The H

Solvation effect on decomposition rate of 10-methyl-10-phenylphenoxarsonium iodide in some alcohols and ketones

International Nuclear Information System (INIS)

Gavrilov, V.I.; Gumerov, N.S.; Rakhmatullin, R.R.

1989-01-01

By the method of conductometry decomposition kinetics of 10-methyl-10phenylphenoxarsonium iodide in methanol, ethanol, 2-propanol, 1-butanol, 1-pentanol and methyl ethyl ketone at initial concentration of the salt 0.00024-0.003 mol/l, is studied. It is shown that at the temperatures up to 80-95 deg C practically no decomposition of arsonium salt in methanol and ethanol is observed. With an increase in the length of alcohol alkyl radical the decomposition rate increases. The values of activation enrgy both for alcohols and ketone are approximately the same. At the same time, decomposition rate in alcohol proved much slower than in ketone, which is related to iodide-ion solvation in protic solvents

Solvation effect on decomposition rate of 10-methyl-10-phenylphenoxarsonium iodide in some alcohols and ketones

Energy Technology Data Exchange (ETDEWEB)

Gavrilov, V I; Gumerov, N S; Rakhmatullin, R R [Kazanskij Khimiko-Tekhnologicheskij Inst., Kazan (USSR)

1989-03-01

By the method of conductometry decomposition kinetics of 10-methyl-10phenylphenoxarsonium iodide in methanol, ethanol, 2-propanol, 1-butanol, 1-pentanol and methyl ethyl ketone at initial concentration of the salt 0.00024-0.003 mol/l, is studied. It is shown that at the temperatures up to 80-95 deg C practically no decomposition of arsonium salt in methanol and ethanol is observed. With an increase in the length of alcohol alkyl radical the decomposition rate increases. The values of activation enrgy both for alcohols and ketone are approximately the same. At the same time, decomposition rate in alcohol proved much slower than in ketone, which is related to iodide-ion solvation in protic solvents.

A Longitudinal Study of Decomposition Odour in Soil Using Sorbent Tubes and Solid Phase Microextraction

Directory of Open Access Journals (Sweden)

Katelynn A. Perrault

2014-07-01

Full Text Available Odour profiling of decomposed remains is important for understanding the mechanisms that cadaver dogs and forensically-relevant insects use to locate decomposed remains. The decomposition odour profile is complex and has been documented in outdoor terrestrial environments. The purpose of this study was to perform longitudinal analysis of the volatile organic compound (VOC profile in soils associated with decomposed remains across all stages of decomposition. Two VOC collection techniques (sorbent tubes and solid phase microextraction were used to collect a wider analyte range and to investigate differences in collection techniques. Pig carcasses were placed in an outdoor research facility in Australia to model the decomposition process and VOCs were collected intermittently over two months. VOCs of interest were identified over the duration of the trial, showing distinct trends in compound evolution and disappearance. The collection techniques were complementary, representing different subsets of VOCs from the overall profile. Sorbent tubes collected more decomposition-specific VOCs and these compounds were more effective at characterising the matrix over an extended period. Using both collection techniques improves the likelihood of identifying the complete VOC profile of decomposition odour. Such information is important for the search and recovery of victim remains in various stages of decomposition.

A counterexample and a modification to the adiabatic approximation theorem in quantum mechanics

Science.gov (United States)

Gingold, H.

1991-01-01

A counterexample to the adiabatic approximation theorem is given when degeneracies are present. A formulation of an alternative version is proposed. A complete asymptotic decomposition for n dimensional self-adjoint Hamiltonian systems is restated and used.

Distance descending ordering method: An O(n) algorithm for inverting the mass matrix in simulation of macromolecules with long branches

Science.gov (United States)

Xu, Xiankun; Li, Peiwen

2017-11-01

Fixman's work in 1974 and the follow-up studies have developed a method that can factorize the inverse of mass matrix into an arithmetic combination of three sparse matrices-one of them is positive definite and needs to be further factorized by using the Cholesky decomposition or similar methods. When the molecule subjected to study is of serial chain structure, this method can achieve O (n) time complexity. However, for molecules with long branches, Cholesky decomposition about the corresponding positive definite matrix will introduce massive fill-in due to its nonzero structure. Although there are several methods can be used to reduce the number of fill-in, none of them could strictly guarantee for zero fill-in for all molecules according to our test, and thus cannot obtain O (n) time complexity by using these traditional methods. In this paper we present a new method that can guarantee for no fill-in in doing the Cholesky decomposition, which was developed based on the correlations between the mass matrix and the geometrical structure of molecules. As a result, the inverting of mass matrix will remain the O (n) time complexity, no matter the molecule structure has long branches or not.

Limited-memory adaptive snapshot selection for proper orthogonal decomposition

Energy Technology Data Exchange (ETDEWEB)

Oxberry, Geoffrey M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Kostova-Vassilevska, Tanya [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Arrighi, Bill [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Chand, Kyle [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

2015-04-02

Reduced order models are useful for accelerating simulations in many-query contexts, such as optimization, uncertainty quantification, and sensitivity analysis. However, offline training of reduced order models can have prohibitively expensive memory and floating-point operation costs in high-performance computing applications, where memory per core is limited. To overcome this limitation for proper orthogonal decomposition, we propose a novel adaptive selection method for snapshots in time that limits offline training costs by selecting snapshots according an error control mechanism similar to that found in adaptive time-stepping ordinary differential equation solvers. The error estimator used in this work is related to theory bounding the approximation error in time of proper orthogonal decomposition-based reduced order models, and memory usage is minimized by computing the singular value decomposition using a single-pass incremental algorithm. Results for a viscous Burgers’ test problem demonstrate convergence in the limit as the algorithm error tolerances go to zero; in this limit, the full order model is recovered to within discretization error. The resulting method can be used on supercomputers to generate proper orthogonal decomposition-based reduced order models, or as a subroutine within hyperreduction algorithms that require taking snapshots in time, or within greedy algorithms for sampling parameter space.

An approximation method for diffusion based leaching models

International Nuclear Information System (INIS)

Shukla, B.S.; Dignam, M.J.

1987-01-01

In connection with the fixation of nuclear waste in a glassy matrix equations have been derived for leaching models based on a uniform concentration gradient approximation, and hence a uniform flux, therefore requiring the use of only Fick's first law. In this paper we improve on the uniform flux approximation, developing and justifying the approach. The resulting set of equations are solved to a satisfactory approximation for a matrix dissolving at a constant rate in a finite volume of leachant to give analytical expressions for the time dependence of the thickness of the leached layer, the diffusional and dissolutional contribution to the flux, and the leachant composition. Families of curves are presented which cover the full range of all the physical parameters for this system. The same procedure can be readily extended to more complex systems. (author)

Incremental Nonnegative Matrix Factorization for Face Recognition

Directory of Open Access Journals (Sweden)

Wen-Sheng Chen

2008-01-01

Full Text Available Nonnegative matrix factorization (NMF is a promising approach for local feature extraction in face recognition tasks. However, there are two major drawbacks in almost all existing NMF-based methods. One shortcoming is that the computational cost is expensive for large matrix decomposition. The other is that it must conduct repetitive learning, when the training samples or classes are updated. To overcome these two limitations, this paper proposes a novel incremental nonnegative matrix factorization (INMF for face representation and recognition. The proposed INMF approach is based on a novel constraint criterion and our previous block strategy. It thus has some good properties, such as low computational complexity, sparse coefficient matrix. Also, the coefficient column vectors between different classes are orthogonal. In particular, it can be applied to incremental learning. Two face databases, namely FERET and CMU PIE face databases, are selected for evaluation. Compared with PCA and some state-of-the-art NMF-based methods, our INMF approach gives the best performance.

Discrete Ordinates Approximations to the First- and Second-Order Radiation Transport Equations

International Nuclear Information System (INIS)

FAN, WESLEY C.; DRUMM, CLIFTON R.; POWELL, JENNIFER L. email wcfan@sandia.gov

2002-01-01

The conventional discrete ordinates approximation to the Boltzmann transport equation can be described in a matrix form. Specifically, the within-group scattering integral can be represented by three components: a moment-to-discrete matrix, a scattering cross-section matrix and a discrete-to-moment matrix. Using and extending these entities, we derive and summarize the matrix representations of the second-order transport equations

Discrete Ordinates Approximations to the First- and Second-Order Radiation Transport Equations

CERN Document Server

Fan, W C; Powell, J L

2002-01-01

The conventional discrete ordinates approximation to the Boltzmann transport equation can be described in a matrix form. Specifically, the within-group scattering integral can be represented by three components: a moment-to-discrete matrix, a scattering cross-section matrix and a discrete-to-moment matrix. Using and extending these entities, we derive and summarize the matrix representations of the second-order transport equations.

Analysis of Optical Fiber Complex Propagation Matrix on the Basis of Vortex Modes

DEFF Research Database (Denmark)

Lyubopytov, Vladimir S.; Tatarczak, Anna; Lu, Xiaofeng

2016-01-01

We propose and experimentally demonstrate a novel method for reconstruction of the complex propagation matrix of optical fibers supporting propagation of multiple vortex modes. This method is based on the azimuthal decomposition approach and allows the complex matrix elements to be determined...... by direct calculations. We apply the proposed method to demonstrate the feasibility of optical compensation for coupling between vortex modes in optical fiber....

Polarimetric SAR interferometry-based decomposition modelling for reliable scattering retrieval

Science.gov (United States)

Agrawal, Neeraj; Kumar, Shashi; Tolpekin, Valentyn

2016-05-01

Fully Polarimetric SAR (PolSAR) data is used for scattering information retrieval from single SAR resolution cell. Single SAR resolution cell may contain contribution from more than one scattering objects. Hence, single or dual polarized data does not provide all the possible scattering information. So, to overcome this problem fully Polarimetric data is used. It was observed in previous study that fully Polarimetric data of different dates provide different scattering values for same object and coefficient of determination obtained from linear regression between volume scattering and aboveground biomass (AGB) shows different values for the SAR dataset of different dates. Scattering values are important input elements for modelling of forest aboveground biomass. In this research work an approach is proposed to get reliable scattering from interferometric pair of fully Polarimetric RADARSAT-2 data. The field survey for data collection was carried out for Barkot forest during November 10th to December 5th, 2014. Stratified random sampling was used to collect field data for circumference at breast height (CBH) and tree height measurement. Field-measured AGB was compared with the volume scattering elements obtained from decomposition modelling of individual PolSAR images and PolInSAR coherency matrix. Yamaguchi 4-component decomposition was implemented to retrieve scattering elements from SAR data. PolInSAR based decomposition was the great challenge in this work and it was implemented with certain assumptions to create Hermitian coherency matrix with co-registered polarimetric interferometric pair of SAR data. Regression analysis between field-measured AGB and volume scattering element obtained from PolInSAR data showed highest (0.589) coefficient of determination. The same regression with volume scattering elements of individual SAR images showed 0.49 and 0.50 coefficients of determination for master and slave images respectively. This study recommends use of

Direct formulation to Cholesky decomposition of a general nonsingular correlation matrix.

Science.gov (United States)

Madar, Vered

2015-08-01

We present two novel and explicit parametrizations of Cholesky factor of a nonsingular correlation matrix. One that uses semi-partial correlation coefficients, and a second that utilizes differences between the successive ratios of two determinants. To each, we offer a useful application.

Linking temperature sensitivity of soil organic matter decomposition to its molecular structure, accessibility, and microbial physiology.

Science.gov (United States)

Wagai, Rota; Kishimoto-Mo, Ayaka W; Yonemura, Seiichiro; Shirato, Yasuhito; Hiradate, Syuntaro; Yagasaki, Yasumi

2013-04-01

Temperature sensitivity of soil organic matter (SOM) decomposition may have a significant impact on global warming. Enzyme-kinetic hypothesis suggests that decomposition of low-quality substrate (recalcitrant molecular structure) requires higher activation energy and thus has greater temperature sensitivity than that of high-quality, labile substrate. Supporting evidence, however, relies largely on indirect indices of substrate quality. Furthermore, the enzyme-substrate reactions that drive decomposition may be regulated by microbial physiology and/or constrained by protective effects of soil mineral matrix. We thus tested the kinetic hypothesis by directly assessing the carbon molecular structure of low-density fraction (LF) which represents readily accessible, mineral-free SOM pool. Using five mineral soil samples of contrasting SOM concentrations, we conducted 30-days incubations (15, 25, and 35 °C) to measure microbial respiration and quantified easily soluble C as well as microbial biomass C pools before and after the incubations. Carbon structure of LFs (soil was measured by solid-state (13) C-NMR. Decomposition Q10 was significantly correlated with the abundance of aromatic plus alkyl-C relative to O-alkyl-C groups in LFs but not in bulk soil fraction or with the indirect C quality indices based on microbial respiration or biomass. The warming did not significantly change the concentration of biomass C or the three types of soluble C despite two- to three-fold increase in respiration. Thus, enhanced microbial maintenance respiration (reduced C-use efficiency) especially in the soils rich in recalcitrant LF might lead to the apparent equilibrium between SOM solubilization and microbial C uptake. Our results showed physical fractionation coupled with direct assessment of molecular structure as an effective approach and supported the enzyme-kinetic interpretation of widely observed C quality-temperature relationship for short-term decomposition. Factors

An Approximate Approach to Automatic Kernel Selection.

Science.gov (United States)

Ding, Lizhong; Liao, Shizhong

2016-02-02

Kernel selection is a fundamental problem of kernel-based learning algorithms. In this paper, we propose an approximate approach to automatic kernel selection for regression from the perspective of kernel matrix approximation. We first introduce multilevel circulant matrices into automatic kernel selection, and develop two approximate kernel selection algorithms by exploiting the computational virtues of multilevel circulant matrices. The complexity of the proposed algorithms is quasi-linear in the number of data points. Then, we prove an approximation error bound to measure the effect of the approximation in kernel matrices by multilevel circulant matrices on the hypothesis and further show that the approximate hypothesis produced with multilevel circulant matrices converges to the accurate hypothesis produced with kernel matrices. Experimental evaluations on benchmark datasets demonstrate the effectiveness of approximate kernel selection.

Finite-rank potential that reproduces the Pade approximant

International Nuclear Information System (INIS)

Tani, S.

1979-01-01

If a scattering potential is of a finite rank, say N, the exact solution of the problem can be obtained from the Born series, if the potential strength is within the radius of convergence; the exact solution can be obtained from the analytical continuation of the formal Born series outside the radius of convergence. Beyond the first 2N terms of the Born series, an individual term of the Born series depends on the first 2N terms, and the [N/N] Pade approximant and the exact solution agree with each other. The above-mentioned features of a finite-rank problem are relevant to scattering theory in general, because most scattering problems may be handled as an extension of the rank-N problem, in which the rank N tends to infinity. The foregoing aspects of scattering theory will be studied in depth in the present paper, and in so doing we proceed in the opposite direction. Namely, given a potential, we calculate the first 2N terms of the Born series for the K matrix and the first N terms of the Born series for the wave function. Using these data, a special rank-N potential is constructed in such a way that it reproduces the [N/N] Pade approximant of the K matrix of the original scattering problem. One great advantage of obtaining such a rank-N potential is that the wave function of the system may be approximated in the same spirit as done for the K matrix; hence, we can introduce a new approximation method for dealing with an off-shell T matrix. A part of the mathematical work is incomplete, but the physical aspects are thoroughly discussed

Preparation of explosive nanoparticles in a porous chromium(III) oxide matrix: a first attempt to control the reactivity of explosives

International Nuclear Information System (INIS)

Comet, M; Siegert, B; Pichot, V; Gibot, P; Spitzer, D

2008-01-01

This paper reports the first attempt to control the combustion and the detonation properties of a high explosive through its structure. A porous chromium(III) oxide matrix produced by the combustion of ammonium dichromate was infiltrated by hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX). The structure of the Cr 2 O 3 matrix was studied by both scanning and transmission electron microscopy (SEM, TEM); the Cr 2 O 3 /RDX nanocomposites were characterized by nitrogen adsorption. A mathematical model based on these techniques was used to demonstrate that the Cr 2 O 3 matrix encloses and stabilizes RDX particles at the nanoscale. The decomposition process of the nanocomposites was investigated by atomic force microscopy (AFM). The reactivity and sensitivity of the nanocomposites were studied by impact and friction tests, differential scanning calorimetry (DSC), time-resolved cinematography and detonation experiments, and were correlated with their structure. The size of RDX nanoparticles and their distribution in the Cr 2 O 3 matrix have an important influence on their reactivity. The reactive properties of nanostructured RDX differ significantly from those of classical micron-sized RDX. For instance, the melting point disappears and the decomposition temperature is significantly lowered. The quantization of the explosive particles in the Cr 2 O 3 matrix decreases the sensitivity to mechanical stress and allows controlling the decomposition mode-i.e. combustion versus detonation

Identification method for gas-liquid two-phase flow regime based on singular value decomposition and least square support vector machine

International Nuclear Information System (INIS)

Sun Bin; Zhou Yunlong; Zhao Peng; Guan Yuebo

2007-01-01

Aiming at the non-stationary characteristics of differential pressure fluctuation signals of gas-liquid two-phase flow, and the slow convergence of learning and liability of dropping into local minima for BP neural networks, flow regime identification method based on Singular Value Decomposition (SVD) and Least Square Support Vector Machine (LS-SVM) is presented. First of all, the Empirical Mode Decomposition (EMD) method is used to decompose the differential pressure fluctuation signals of gas-liquid two-phase flow into a number of stationary Intrinsic Mode Functions (IMFs) components from which the initial feature vector matrix is formed. By applying the singular vale decomposition technique to the initial feature vector matrixes, the singular values are obtained. Finally, the singular values serve as the flow regime characteristic vector to be LS-SVM classifier and flow regimes are identified by the output of the classifier. The identification result of four typical flow regimes of air-water two-phase flow in horizontal pipe has shown that this method achieves a higher identification rate. (authors)

Underdetermined Blind Audio Source Separation Using Modal Decomposition

Directory of Open Access Journals (Sweden)

Abdeldjalil Aïssa-El-Bey

2007-03-01

Full Text Available This paper introduces new algorithms for the blind separation of audio sources using modal decomposition. Indeed, audio signals and, in particular, musical signals can be well approximated by a sum of damped sinusoidal (modal components. Based on this representation, we propose a two-step approach consisting of a signal analysis (extraction of the modal components followed by a signal synthesis (grouping of the components belonging to the same source using vector clustering. For the signal analysis, two existing algorithms are considered and compared: namely the EMD (empirical mode decomposition algorithm and a parametric estimation algorithm using ESPRIT technique. A major advantage of the proposed method resides in its validity for both instantaneous and convolutive mixtures and its ability to separate more sources than sensors. Simulation results are given to compare and assess the performance of the proposed algorithms.

Underdetermined Blind Audio Source Separation Using Modal Decomposition

Directory of Open Access Journals (Sweden)

Aïssa-El-Bey Abdeldjalil

2007-01-01

Full Text Available This paper introduces new algorithms for the blind separation of audio sources using modal decomposition. Indeed, audio signals and, in particular, musical signals can be well approximated by a sum of damped sinusoidal (modal components. Based on this representation, we propose a two-step approach consisting of a signal analysis (extraction of the modal components followed by a signal synthesis (grouping of the components belonging to the same source using vector clustering. For the signal analysis, two existing algorithms are considered and compared: namely the EMD (empirical mode decomposition algorithm and a parametric estimation algorithm using ESPRIT technique. A major advantage of the proposed method resides in its validity for both instantaneous and convolutive mixtures and its ability to separate more sources than sensors. Simulation results are given to compare and assess the performance of the proposed algorithms.

Nuclear power plant risk assembly and decomposition for risk management

International Nuclear Information System (INIS)

Iden, D.C.

1985-01-01

The state-of-the-art method for analyzing the risk from nuclear power plants is probabilistic risk assessment (PRA). The intermediate results of a PRA are first assembled to quantify the risk from operating a nuclear power plant in the form of (1) core damage (or core melt) frequency, (2) plant damage state frequencies, (3) release category frequencies, and (4) the frequency of exceeding specific levels of offsite consequences. Once the overall PRA results have been quantified, the next step is to decompose those results into the individual contributors to each of the four forms of risk in some rank order. The way in which the PRA model is set up to assemble and decompose the plant risk determines the ease and usefulness of the PRA model as a risk management tool for evaluating perturbations to the PRA model. These perturbations can take the form of technical specification changes, hardware modifications, procedural changes, etc. The matrix formalism developed by Dr. Stan Kaplan for risk assembly and decomposition represents a significant breakthrough in making the PRA model an effective risk management tool. The key to understanding the matrix formalism and making it a useful tool for managing nuclear power plant risk is the structure of the PRA model. PRA risk model structure and decomposition of the risk results are discussed with the Seabrook PRA as an example

Analytical approximations to the Hotelling trace for digital x-ray detectors

Science.gov (United States)

Clarkson, Eric; Pineda, Angel R.; Barrett, Harrison H.

2001-06-01

The Hotelling trace is the signal-to-noise ratio for the ideal linear observer in a detection task. We provide an analytical approximation for this figure of merit when the signal is known exactly and the background is generated by a stationary random process, and the imaging system is an ideal digital x-ray detector. This approximation is based on assuming that the detector is infinite in extent. We test this approximation for finite-size detectors by comparing it to exact calculations using matrix inversion of the data covariance matrix. After verifying the validity of the approximation under a variety of circumstances, we use it to generate plots of the Hotelling trace as a function of pairs of parameters of the system, the signal and the background.

Efficient Matrix Models for Relational Learning

Science.gov (United States)

2009-10-01

base learners and h1:r is the ensemble learner. For example, consider the case where h1, . . . , hr are linear discriminants. The weighted vote of...a multilinear form naturally leads one to consider tensor factorization: e.g., UAV T is a special case of Tucker decomposition [129] on a 2D- tensor , a...matrix. Our five modeling choices can also be used to differentiate tensor factorizations, but the choices may be subtler for tensors than for

Neutrino mass matrix

International Nuclear Information System (INIS)

Strobel, E.L.

1985-01-01

Given the many conflicting experimental results, examination is made of the neutrino mass matrix in order to determine possible masses and mixings. It is assumed that the Dirac mass matrix for the electron, muon, and tau neutrinos is similar in form to those of the quarks and charged leptons, and that the smallness of the observed neutrino masses results from the Gell-Mann-Ramond-Slansky mechanism. Analysis of masses and mixings for the neutrinos is performed using general structures for the Majorana mass matrix. It is shown that if certain tentative experimental results concerning the neutrino masses and mixing angles are confirmed, significant limitations may be placed on the Majorana mass matrix. The most satisfactory simple assumption concerning the Majorana mass matrix is that it is approximately proportional to the Dirac mass matrix. A very recent experimental neutrino mass result and its implications are discussed. Some general properties of matrices with structure similar to the Dirac mass matrices are discussed

Zero-Sum Matrix Game with Payoffs of Dempster-Shafer Belief Structures and Its Applications on Sensors

Science.gov (United States)

Deng, Xinyang; Jiang, Wen; Zhang, Jiandong

2017-01-01

The zero-sum matrix game is one of the most classic game models, and it is widely used in many scientific and engineering fields. In the real world, due to the complexity of the decision-making environment, sometimes the payoffs received by players may be inexact or uncertain, which requires that the model of matrix games has the ability to represent and deal with imprecise payoffs. To meet such a requirement, this paper develops a zero-sum matrix game model with Dempster–Shafer belief structure payoffs, which effectively represents the ambiguity involved in payoffs of a game. Then, a decomposition method is proposed to calculate the value of such a game, which is also expressed with belief structures. Moreover, for the possible computation-intensive issue in the proposed decomposition method, as an alternative solution, a Monte Carlo simulation approach is presented, as well. Finally, the proposed zero-sum matrix games with payoffs of Dempster–Shafer belief structures is illustratively applied to the sensor selection and intrusion detection of sensor networks, which shows its effectiveness and application process. PMID:28430156

Single-particle density matrix of liquid 4He

International Nuclear Information System (INIS)

Vakarchuk, I.A.

2008-01-01

The density single-particle matrix in the coordinate notation was calculated based on the expression for the interacting Bose-particle N system density matrix. Under the low temperatures the mentioned matrix in the first approximation enables to reproduce the Bogoliubov theory results. In the classical terms the mentioned theory enables to reproduce the results of the theory of the classical fluids in the approximation of the chaotic phases. On the basis of the density single-particle matrix one managed to obtain the function of the pulse distribution of the particles, the Bose-liquid average kinetic energy, and to study the Bose-Einstein condensation phenomenon [ru

Decomposition cross-correlation for analysis of collagen matrix deformation by single smooth muscle cells

NARCIS (Netherlands)

van den Akker, Jeroen; Pistea, Adrian; Bakker, Erik N. T. P.; VanBavel, Ed

2008-01-01

Microvascular remodeling is known to depend on cellular interactions with matrix tissue. However, it is difficult to study the role of specific cells or matrix elements in an in vivo setting. The aim of this study is to develop an automated technique that can be employed to obtain and analyze local

A Tensor Decomposition-Based Approach for Detecting Dynamic Network States From EEG.

Science.gov (United States)

Mahyari, Arash Golibagh; Zoltowski, David M; Bernat, Edward M; Aviyente, Selin

2017-01-01

Functional connectivity (FC), defined as the statistical dependency between distinct brain regions, has been an important tool in understanding cognitive brain processes. Most of the current works in FC have focused on the assumption of temporally stationary networks. However, recent empirical work indicates that FC is dynamic due to cognitive functions. The purpose of this paper is to understand the dynamics of FC for understanding the formation and dissolution of networks of the brain. In this paper, we introduce a two-step approach to characterize the dynamics of functional connectivity networks (FCNs) by first identifying change points at which the network connectivity across subjects shows significant changes and then summarizing the FCNs between consecutive change points. The proposed approach is based on a tensor representation of FCNs across time and subjects yielding a four-mode tensor. The change points are identified using a subspace distance measure on low-rank approximations to the tensor at each time point. The network summarization is then obtained through tensor-matrix projections across the subject and time modes. The proposed framework is applied to electroencephalogram (EEG) data collected during a cognitive control task. The detected change-points are consistent with a priori known ERN interval. The results show significant connectivities in medial-frontal regions which are consistent with widely observed ERN amplitude measures. The tensor-based method outperforms conventional matrix-based methods such as singular value decomposition in terms of both change-point detection and state summarization. The proposed tensor-based method captures the topological structure of FCNs which provides more accurate change-point-detection and state summarization.

Proper Orthogonal Decomposition and Dynamic Mode Decomposition in the Right Ventricle after Repair of Tetralogy of Fallot

Science.gov (United States)

Mikhail, Amanda; Kadem, Lyes; di Labbio, Giuseppe

2017-11-01

Tetralogy of Fallot accounts for 5% of all cyanotic congenital heart defects, making it the most predominant today. Approximately 1660 cases per year are seen in the United States alone. Once repaired at a very young age, symptoms such as pulmonary valve regurgitation seem to arise two to three decades after the initial operation. Currently, not much is understood about the blood flow in the right ventricle of the heart when regurgitation is present. In this study, the interaction between the diastolic interventricular flow and the regurgitating pulmonary valve are investigated. This experimental work aims to simulate and characterize this detrimental flow in a right heart simulator using time-resolved particle image velocimetry. Seven severities of regurgitation were simulated. Proper Orthogonal Decomposition (POD) and Dynamic Mode Decomposition (DMD) revealed intricate coherent flow structures. With regurgitation severity, the modal energies from POD are more distributed among the modes while DMD reveals more unstable modes. This study can contribute to the further investigation of the detrimental effects of right ventricle regurgitation.

Solving Fokker-Planck Equations on Cantor Sets Using Local Fractional Decomposition Method

Directory of Open Access Journals (Sweden)

Shao-Hong Yan

2014-01-01

Full Text Available The local fractional decomposition method is applied to approximate the solutions for Fokker-Planck equations on Cantor sets with local fractional derivative. The obtained results give the present method that is very effective and simple for solving the differential equations on Cantor set.

Modeling of ferric sulfate decomposition and sulfation of potassium chloride during grate‐firing of biomass

DEFF Research Database (Denmark)

Wu, Hao; Jespersen, Jacob Boll; Jappe Frandsen, Flemming

2013-01-01

Ferric sulfate is used as an additive in biomass combustion to convert the released potassium chloride to the less harmful potassium sulfate. The decomposition of ferric sulfate is studied in a fast heating rate thermogravimetric analyzer and a volumetric reaction model is proposed to describe...... the process. The yields of sulfur oxides from ferric sulfate decomposition under boiler conditions are investigated experimentally, revealing a distribution of approximately 40% SO3 and 60% SO2. The ferric sulfate decomposition model is combined with a detailed kinetic model of gas‐phase KCl sulfation...... and a model of K2SO4 condensation to simulate the sulfation of KCl by ferric sulfate addition. The simulation results show good agreements with experiments conducted in a biomass grate‐firing reactor. The results indicate that the SO3 released from ferric sulfate decomposition is the main contributor to KCl...

A practical material decomposition method for x-ray dual spectral computed tomography.

Science.gov (United States)

Hu, Jingjing; Zhao, Xing

2016-03-17

X-ray dual spectral CT (DSCT) scans the measured object with two different x-ray spectra, and the acquired rawdata can be used to perform the material decomposition of the object. Direct calibration methods allow a faster material decomposition for DSCT and can be separated in two groups: image-based and rawdata-based. The image-based method is an approximative method, and beam hardening artifacts remain in the resulting material-selective images. The rawdata-based method generally obtains better image quality than the image-based method, but this method requires geometrically consistent rawdata. However, today's clinical dual energy CT scanners usually measure different rays for different energy spectra and acquire geometrically inconsistent rawdata sets, and thus cannot meet the requirement. This paper proposes a practical material decomposition method to perform rawdata-based material decomposition in the case of inconsistent measurement. This method first yields the desired consistent rawdata sets from the measured inconsistent rawdata sets, and then employs rawdata-based technique to perform material decomposition and reconstruct material-selective images. The proposed method was evaluated by use of simulated FORBILD thorax phantom rawdata and dental CT rawdata, and simulation results indicate that this method can produce highly quantitative DSCT images in the case of inconsistent DSCT measurements.

Reduced density matrix functional theory via a wave function based approach

Energy Technology Data Exchange (ETDEWEB)

Schade, Robert; Bloechl, Peter [Institute for Theoretical Physics, Clausthal University of Technology, Clausthal (Germany); Pruschke, Thomas [Institute for Theoretical Physics, University of Goettingen, Goettingen (Germany)

2016-07-01

We propose a new method for the calculation of the electronic and atomic structure of correlated electron systems based on reduced density matrix functional theory (rDMFT). The density-matrix functional is evaluated on the fly using Levy's constrained search formalism. The present implementation rests on a local approximation of the interaction reminiscent to that of dynamical mean field theory (DMFT). We focus here on additional approximations to the exact density-matrix functional in the local approximation and evaluate their performance.

Direct application of Padé approximant for solving nonlinear differential equations.

Science.gov (United States)

Vazquez-Leal, Hector; Benhammouda, Brahim; Filobello-Nino, Uriel; Sarmiento-Reyes, Arturo; Jimenez-Fernandez, Victor Manuel; Garcia-Gervacio, Jose Luis; Huerta-Chua, Jesus; Morales-Mendoza, Luis Javier; Gonzalez-Lee, Mario

2014-01-01

This work presents a direct procedure to apply Padé method to find approximate solutions for nonlinear differential equations. Moreover, we present some cases study showing the strength of the method to generate highly accurate rational approximate solutions compared to other semi-analytical methods. The type of tested nonlinear equations are: a highly nonlinear boundary value problem, a differential-algebraic oscillator problem, and an asymptotic problem. The high accurate handy approximations obtained by the direct application of Padé method shows the high potential if the proposed scheme to approximate a wide variety of problems. What is more, the direct application of the Padé approximant aids to avoid the previous application of an approximative method like Taylor series method, homotopy perturbation method, Adomian Decomposition method, homotopy analysis method, variational iteration method, among others, as tools to obtain a power series solutions to post-treat with the Padé approximant. 34L30.

Implementation of domain decomposition and data decomposition algorithms in RMC code

International Nuclear Information System (INIS)

Liang, J.G.; Cai, Y.; Wang, K.; She, D.

2013-01-01

The applications of Monte Carlo method in reactor physics analysis is somewhat restricted due to the excessive memory demand in solving large-scale problems. Memory demand in MC simulation is analyzed firstly, it concerns geometry data, data of nuclear cross-sections, data of particles, and data of tallies. It appears that tally data is dominant in memory cost and should be focused on in solving the memory problem. Domain decomposition and tally data decomposition algorithms are separately designed and implemented in the reactor Monte Carlo code RMC. Basically, the domain decomposition algorithm is a strategy of 'divide and rule', which means problems are divided into different sub-domains to be dealt with separately and some rules are established to make sure the whole results are correct. Tally data decomposition consists in 2 parts: data partition and data communication. Two algorithms with differential communication synchronization mechanisms are proposed. Numerical tests have been executed to evaluate performance of the new algorithms. Domain decomposition algorithm shows potentials to speed up MC simulation as a space parallel method. As for tally data decomposition algorithms, memory size is greatly reduced

Singular Value Decomposition and Ligand Binding Analysis

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André Luiz Galo

2013-01-01

Full Text Available Singular values decomposition (SVD is one of the most important computations in linear algebra because of its vast application for data analysis. It is particularly useful for resolving problems involving least-squares minimization, the determination of matrix rank, and the solution of certain problems involving Euclidean norms. Such problems arise in the spectral analysis of ligand binding to macromolecule. Here, we present a spectral data analysis method using SVD (SVD analysis and nonlinear fitting to determine the binding characteristics of intercalating drugs to DNA. This methodology reduces noise and identifies distinct spectral species similar to traditional principal component analysis as well as fitting nonlinear binding parameters. We applied SVD analysis to investigate the interaction of actinomycin D and daunomycin with native DNA. This methodology does not require prior knowledge of ligand molar extinction coefficients (free and bound, which potentially limits binding analysis. Data are acquired simply by reconstructing the experimental data and by adjusting the product of deconvoluted matrices and the matrix of model coefficients determined by the Scatchard and McGee and von Hippel equation.

Central limit theorems for large graphs: Method of quantum decomposition

International Nuclear Information System (INIS)

Hashimoto, Yukihiro; Hora, Akihito; Obata, Nobuaki

2003-01-01

A new method is proposed for investigating spectral distribution of the combinatorial Laplacian (adjacency matrix) of a large regular graph on the basis of quantum decomposition and quantum central limit theorem. General results are proved for Cayley graphs of discrete groups and for distance-regular graphs. The Coxeter groups and the Johnson graphs are discussed in detail by way of illustration. In particular, the limit distributions obtained from the Johnson graphs are characterized by the Meixner polynomials which form a one-parameter deformation of the Laguerre polynomials

Seismic wave extrapolation using lowrank symbol approximation

KAUST Repository

Fomel, Sergey

2012-04-30

We consider the problem of constructing a wave extrapolation operator in a variable and possibly anisotropic medium. Our construction involves Fourier transforms in space combined with the help of a lowrank approximation of the space-wavenumber wave-propagator matrix. A lowrank approximation implies selecting a small set of representative spatial locations and a small set of representative wavenumbers. We present a mathematical derivation of this method, a description of the lowrank approximation algorithm and numerical examples that confirm the validity of the proposed approach. Wave extrapolation using lowrank approximation can be applied to seismic imaging by reverse-time migration in 3D heterogeneous isotropic or anisotropic media. © 2012 European Association of Geoscientists & Engineers.

High-purity Cu nanocrystal synthesis by a dynamic decomposition method

Science.gov (United States)

Jian, Xian; Cao, Yu; Chen, Guozhang; Wang, Chao; Tang, Hui; Yin, Liangjun; Luan, Chunhong; Liang, Yinglin; Jiang, Jing; Wu, Sixin; Zeng, Qing; Wang, Fei; Zhang, Chengui

2014-12-01

Cu nanocrystals are applied extensively in several fields, particularly in the microelectron, sensor, and catalysis. The catalytic behavior of Cu nanocrystals depends mainly on the structure and particle size. In this work, formation of high-purity Cu nanocrystals is studied using a common chemical vapor deposition precursor of cupric tartrate. This process is investigated through a combined experimental and computational approach. The decomposition kinetics is researched via differential scanning calorimetry and thermogravimetric analysis using Flynn-Wall-Ozawa, Kissinger, and Starink methods. The growth was found to be influenced by the factors of reaction temperature, protective gas, and time. And microstructural and thermal characterizations were performed by X-ray diffraction, scanning electron microscopy, transmission electron microscopy, and differential scanning calorimetry. Decomposition of cupric tartrate at different temperatures was simulated by density functional theory calculations under the generalized gradient approximation. High crystalline Cu nanocrystals without floccules were obtained from thermal decomposition of cupric tartrate at 271°C for 8 h under Ar. This general approach paves a way to controllable synthesis of Cu nanocrystals with high purity.

Preparation of explosive nanoparticles in a porous chromium(III) oxide matrix: a first attempt to control the reactivity of explosives

Energy Technology Data Exchange (ETDEWEB)

Comet, M; Siegert, B; Pichot, V; Gibot, P; Spitzer, D [Laboratoire ISL/CNRS ' Nanomateriaux pour les Systemes Sous Sollicitations Extremes' (NS3E), FRE 3026, French-German Research Institute of Saint-Louis (ISL), 5 rue du General Cassagnou, 68301 Saint-Louis (France)], E-mail: comet@isl.tm.fr

2008-07-16

This paper reports the first attempt to control the combustion and the detonation properties of a high explosive through its structure. A porous chromium(III) oxide matrix produced by the combustion of ammonium dichromate was infiltrated by hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX). The structure of the Cr{sub 2}O{sub 3} matrix was studied by both scanning and transmission electron microscopy (SEM, TEM); the Cr{sub 2}O{sub 3}/RDX nanocomposites were characterized by nitrogen adsorption. A mathematical model based on these techniques was used to demonstrate that the Cr{sub 2}O{sub 3} matrix encloses and stabilizes RDX particles at the nanoscale. The decomposition process of the nanocomposites was investigated by atomic force microscopy (AFM). The reactivity and sensitivity of the nanocomposites were studied by impact and friction tests, differential scanning calorimetry (DSC), time-resolved cinematography and detonation experiments, and were correlated with their structure. The size of RDX nanoparticles and their distribution in the Cr{sub 2}O{sub 3} matrix have an important influence on their reactivity. The reactive properties of nanostructured RDX differ significantly from those of classical micron-sized RDX. For instance, the melting point disappears and the decomposition temperature is significantly lowered. The quantization of the explosive particles in the Cr{sub 2}O{sub 3} matrix decreases the sensitivity to mechanical stress and allows controlling the decomposition mode-i.e. combustion versus detonation.

The nuclear reaction matrix

International Nuclear Information System (INIS)

Krenciglowa, E.M.; Kung, C.L.; Kuo, T.T.S.; Osnes, E.; and Department of Physics, State University of New York at Stony Brook, Stony Brook, New York 11794)

1976-01-01

Different definitions of the reaction matrix G appropriate to the calculation of nuclear structure are reviewed and discussed. Qualitative physical arguments are presented in support of a two-step calculation of the G-matrix for finite nuclei. In the first step the high-energy excitations are included using orthogonalized plane-wave intermediate states, and in the second step the low-energy excitations are added in, using harmonic oscillator intermediate states. Accurate calculations of G-matrix elements for nuclear structure calculations in the Aapprox. =18 region are performed following this procedure and treating the Pauli exclusion operator Q 2 /sub p/ by the method of Tsai and Kuo. The treatment of Q 2 /sub p/, the effect of the intermediate-state spectrum and the energy dependence of the reaction matrix are investigated in detail. The present matrix elements are compared with various matrix elements given in the literature. In particular, close agreement is obtained with the matrix elements calculated by Kuo and Brown using approximate methods

Type II collagen peptide is able to accelerate embryonic chondrocyte differentiation: an association with articular cartilage matrix resorption in osteoarthrosis

Directory of Open Access Journals (Sweden)

Elena Vasil'evna Chetina

2010-01-01

Conclusion. The effect of CP on gene expression and collagen decomposition activity depends on the morphotype of embryonic chondrocytes. Lack of effect of CP on collagen decomposition activity in both the embryonic hypertrophic chondrocytes and the cartilage explants from OA patients supports the hypothesis that the hypertrophic morphotype is a dominant morphotype of articular chondrocytes in OA. Moreover, collagen decomposition products can be involved in the resorption of matrix in OA and in the maintenance of chronic nature of the pathology.

Approximate kernel competitive learning.

Science.gov (United States)

Wu, Jian-Sheng; Zheng, Wei-Shi; Lai, Jian-Huang

2015-03-01

Kernel competitive learning has been successfully used to achieve robust clustering. However, kernel competitive learning (KCL) is not scalable for large scale data processing, because (1) it has to calculate and store the full kernel matrix that is too large to be calculated and kept in the memory and (2) it cannot be computed in parallel. In this paper we develop a framework of approximate kernel competitive learning for processing large scale dataset. The proposed framework consists of two parts. First, it derives an approximate kernel competitive learning (AKCL), which learns kernel competitive learning in a subspace via sampling. We provide solid theoretical analysis on why the proposed approximation modelling would work for kernel competitive learning, and furthermore, we show that the computational complexity of AKCL is largely reduced. Second, we propose a pseudo-parallelled approximate kernel competitive learning (PAKCL) based on a set-based kernel competitive learning strategy, which overcomes the obstacle of using parallel programming in kernel competitive learning and significantly accelerates the approximate kernel competitive learning for large scale clustering. The empirical evaluation on publicly available datasets shows that the proposed AKCL and PAKCL can perform comparably as KCL, with a large reduction on computational cost. Also, the proposed methods achieve more effective clustering performance in terms of clustering precision against related approximate clustering approaches. Copyright © 2014 Elsevier Ltd. All rights reserved.

Adaptive Hybrid Visual Servo Regulation of Mobile Robots Based on Fast Homography Decomposition

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Chunfu Wu

2015-01-01

Full Text Available For the monocular camera-based mobile robot system, an adaptive hybrid visual servo regulation algorithm which is based on a fast homography decomposition method is proposed to drive the mobile robot to its desired position and orientation, even when object’s imaging depth and camera’s position extrinsic parameters are unknown. Firstly, the homography’s particular properties caused by mobile robot’s 2-DOF motion are taken into account to induce a fast homography decomposition method. Secondly, the homography matrix and the extracted orientation error, incorporated with the desired view’s single feature point, are utilized to form an error vector and its open-loop error function. Finally, Lyapunov-based techniques are exploited to construct an adaptive regulation control law, followed by the experimental verification. The experimental results show that the proposed fast homography decomposition method is not only simple and efficient, but also highly precise. Meanwhile, the designed control law can well enable mobile robot position and orientation regulation despite the lack of depth information and camera’s position extrinsic parameters.

Parallelizable approximate solvers for recursions arising in preconditioning

Energy Technology Data Exchange (ETDEWEB)

Shapira, Y. [Israel Inst. of Technology, Haifa (Israel)

1996-12-31

For the recursions used in the Modified Incomplete LU (MILU) preconditioner, namely, the incomplete decomposition, forward elimination and back substitution processes, a parallelizable approximate solver is presented. The present analysis shows that the solutions of the recursions depend only weakly on their initial conditions and may be interpreted to indicate that the inexact solution is close, in some sense, to the exact one. The method is based on a domain decomposition approach, suitable for parallel implementations with message passing architectures. It requires a fixed number of communication steps per preconditioned iteration, independently of the number of subdomains or the size of the problem. The overlapping subdomains are either cubes (suitable for mesh-connected arrays of processors) or constructed by the data-flow rule of the recursions (suitable for line-connected arrays with possibly SIMD or vector processors). Numerical examples show that, in both cases, the overhead in the number of iterations required for convergence of the preconditioned iteration is small relatively to the speed-up gained.

Recovery and removal of nutrients from swine wastewater by using a novel integrated reactor for struvite decomposition and recycling

Science.gov (United States)

Huang, Haiming; Xiao, Dean; Liu, Jiahui; Hou, Li; Ding, Li

2015-01-01

In the present study, struvite decomposition was performed by air stripping for ammonia release and a novel integrated reactor was designed for the simultaneous removal and recovery of total ammonia-nitrogen (TAN) and total orthophosphate (PT) from swine wastewater by internal struvite recycling. Decomposition of struvite by air stripping was found to be feasible. Without supplementation with additional magnesium and phosphate sources, the removal ratio of TAN from synthetic wastewater was maintained at >80% by recycling of the struvite decomposition product formed under optimal conditions, six times. Continuous operation of the integrated reactor indicated that approximately 91% TAN and 97% PT in the swine wastewater could be removed and recovered by the proposed recycling process with the supplementation of bittern. Economic evaluation of the proposed system showed that struvite precipitation cost can be saved by approximately 54% by adopting the proposed recycling process in comparison with no recycling method. PMID:25960246

Impact of the Choice of Normalization Method on Molecular Cancer Class Discovery Using Nonnegative Matrix Factorization.

Science.gov (United States)

Yang, Haixuan; Seoighe, Cathal

2016-01-01

Nonnegative Matrix Factorization (NMF) has proved to be an effective method for unsupervised clustering analysis of gene expression data. By the nonnegativity constraint, NMF provides a decomposition of the data matrix into two matrices that have been used for clustering analysis. However, the decomposition is not unique. This allows different clustering results to be obtained, resulting in different interpretations of the decomposition. To alleviate this problem, some existing methods directly enforce uniqueness to some extent by adding regularization terms in the NMF objective function. Alternatively, various normalization methods have been applied to the factor matrices; however, the effects of the choice of normalization have not been carefully investigated. Here we investigate the performance of NMF for the task of cancer class discovery, under a wide range of normalization choices. After extensive evaluations, we observe that the maximum norm showed the best performance, although the maximum norm has not previously been used for NMF. Matlab codes are freely available from: http://maths.nuigalway.ie/~haixuanyang/pNMF/pNMF.htm.

Vegetation exerts a greater control on litter decomposition than climate warming in peatlands.

Science.gov (United States)

Ward, Susan E; Orwin, Kate H; Ostle, Nicholas J; Briones, J I; Thomson, Bruce C; Griffiths, Robert I; Oakley, Simon; Quirk, Helen; Bardget, Richard D

2015-01-01

Historically, slow decomposition rates have resulted in the accumulation of large amounts of carbon in northern peatlands. Both climate warming and vegetation change can alter rates of decomposition, and hence affect rates of atmospheric CO2 exchange, with consequences for climate change feedbacks. Although warming and vegetation change are happening concurrently, little is known about their relative and interactive effects on decomposition processes. To test the effects of warming and vegetation change on decomposition rates, we placed litter of three dominant species (Calluna vulgaris, Eriophorum vaginatum, Hypnum jutlandicum) into a peatland field experiment that combined warming.with plant functional group removals, and measured mass loss over two years. To identify potential mechanisms behind effects, we also measured nutrient cycling and soil biota. We found that plant functional group removals exerted a stronger control over short-term litter decomposition than did approximately 1 degrees C warming, and that the plant removal effect depended on litter species identity. Specifically, rates of litter decomposition were faster when shrubs were removed from the plant community, and these effects were strongest for graminoid and bryophyte litter. Plant functional group removals also had strong effects on soil biota and nutrient cycling associated with decomposition, whereby shrub removal had cascading effects on soil fungal community composition, increased enchytraeid abundance, and increased rates of N mineralization. Our findings demonstrate that, in addition to litter quality, changes in vegetation composition play a significant role in regulating short-term litter decomposition and belowground communities in peatland, and that these impacts can be greater than moderate warming effects. Our findings, albeit from a relatively short-term study, highlight the need to consider both vegetation change and its impacts below ground alongside climatic effects when

The sagitta and lens thickness: the exact solution and a matrix approximation for lenses with toric, spherical, and cylindrical surfaces.

Science.gov (United States)

Harris, W F

1989-03-01

The exact equation for sagitta of spherical surfaces is generalized to toric surfaces which include spherical and cylindrical surfaces as special cases. Lens thickness, therefore, can be calculated accurately anywhere on a lens even in cases of extreme spherical and cylindrical powers and large diameters. The sagittae of tire- and barrel-form toric surfaces differ off the principal meridians, as is shown by a numerical example. The same holds for pulley- and capstan-form toric surfaces. A general expression is given for thickness at an arbitrary point on a toric lens. Approximate expressions are derived and re-expressed in terms of matrices. The matrix provides an elegant means of generalizing equations for spherical surfaces and lenses to toric surfaces and lenses.

On the Equivalence of Nonnegative Matrix Factorization and K-means- Spectral Clustering

Energy Technology Data Exchange (ETDEWEB)

Ding, Chris; He, Xiaofeng; Simon, Horst D.; Jin, Rong

2005-12-04

We provide a systematic analysis of nonnegative matrix factorization (NMF) relating to data clustering. We generalize the usual X = FG{sup T} decomposition to the symmetric W = HH{sup T} and W = HSH{sup T} decompositions. We show that (1) W = HH{sup T} is equivalent to Kernel K-means clustering and the Laplacian-based spectral clustering. (2) X = FG{sup T} is equivalent to simultaneous clustering of rows and columns of a bipartite graph. We emphasizes the importance of orthogonality in NMF and soft clustering nature of NMF. These results are verified with experiments on face images and newsgroups.

Ranking Support Vector Machine with Kernel Approximation.

Science.gov (United States)

Chen, Kai; Li, Rongchun; Dou, Yong; Liang, Zhengfa; Lv, Qi

2017-01-01

Learning to rank algorithm has become important in recent years due to its successful application in information retrieval, recommender system, and computational biology, and so forth. Ranking support vector machine (RankSVM) is one of the state-of-art ranking models and has been favorably used. Nonlinear RankSVM (RankSVM with nonlinear kernels) can give higher accuracy than linear RankSVM (RankSVM with a linear kernel) for complex nonlinear ranking problem. However, the learning methods for nonlinear RankSVM are still time-consuming because of the calculation of kernel matrix. In this paper, we propose a fast ranking algorithm based on kernel approximation to avoid computing the kernel matrix. We explore two types of kernel approximation methods, namely, the Nyström method and random Fourier features. Primal truncated Newton method is used to optimize the pairwise L2-loss (squared Hinge-loss) objective function of the ranking model after the nonlinear kernel approximation. Experimental results demonstrate that our proposed method gets a much faster training speed than kernel RankSVM and achieves comparable or better performance over state-of-the-art ranking algorithms.

Ranking Support Vector Machine with Kernel Approximation

Directory of Open Access Journals (Sweden)

Kai Chen

2017-01-01

Full Text Available Learning to rank algorithm has become important in recent years due to its successful application in information retrieval, recommender system, and computational biology, and so forth. Ranking support vector machine (RankSVM is one of the state-of-art ranking models and has been favorably used. Nonlinear RankSVM (RankSVM with nonlinear kernels can give higher accuracy than linear RankSVM (RankSVM with a linear kernel for complex nonlinear ranking problem. However, the learning methods for nonlinear RankSVM are still time-consuming because of the calculation of kernel matrix. In this paper, we propose a fast ranking algorithm based on kernel approximation to avoid computing the kernel matrix. We explore two types of kernel approximation methods, namely, the Nyström method and random Fourier features. Primal truncated Newton method is used to optimize the pairwise L2-loss (squared Hinge-loss objective function of the ranking model after the nonlinear kernel approximation. Experimental results demonstrate that our proposed method gets a much faster training speed than kernel RankSVM and achieves comparable or better performance over state-of-the-art ranking algorithms.

Eigenvector decomposition of full-spectrum x-ray computed tomography.

Science.gov (United States)

Gonzales, Brian J; Lalush, David S

2012-03-07

Energy-discriminated x-ray computed tomography (CT) data were projected onto a set of basis functions to suppress the noise in filtered back-projection (FBP) reconstructions. The x-ray CT data were acquired using a novel x-ray system which incorporated a single-pixel photon-counting x-ray detector to measure the x-ray spectrum for each projection ray. A matrix of the spectral response of different materials was decomposed using eigenvalue decomposition to form the basis functions. Projection of FBP onto basis functions created a de facto image segmentation of multiple contrast agents. Final reconstructions showed significant noise suppression while preserving important energy-axis data. The noise suppression was demonstrated by a marked improvement in the signal-to-noise ratio (SNR) along the energy axis for multiple regions of interest in the reconstructed images. Basis functions used on a more coarsely sampled energy axis still showed an improved SNR. We conclude that the noise-resolution trade off along the energy axis was significantly improved using the eigenvalue decomposition basis functions.

A parallel algorithm for solving the multidimensional within-group discrete ordinates equations with spatial domain decomposition - 104

International Nuclear Information System (INIS)

Zerr, R.J.; Azmy, Y.Y.

2010-01-01

A spatial domain decomposition with a parallel block Jacobi solution algorithm has been developed based on the integral transport matrix formulation of the discrete ordinates approximation for solving the within-group transport equation. The new methodology abandons the typical source iteration scheme and solves directly for the fully converged scalar flux. Four matrix operators are constructed based upon the integral form of the discrete ordinates equations. A single differential mesh sweep is performed to construct these operators. The method is parallelized by decomposing the problem domain into several smaller sub-domains, each treated as an independent problem. The scalar flux of each sub-domain is solved exactly given incoming angular flux boundary conditions. Sub-domain boundary conditions are updated iteratively, and convergence is achieved when the scalar flux error in all cells meets a pre-specified convergence criterion. The method has been implemented in a computer code that was then employed for strong scaling studies of the algorithm's parallel performance via a fixed-size problem in tests ranging from one domain up to one cell per sub-domain. Results indicate that the best parallel performance compared to source iterations occurs for optically thick, highly scattering problems, the variety that is most difficult for the traditional SI scheme to solve. Moreover, the minimum execution time occurs when each sub-domain contains a total of four cells. (authors)

Detection and identification of concealed weapons using matrix pencil

Science.gov (United States)

Adve, Raviraj S.; Thayaparan, Thayananthan

2011-06-01

The detection and identification of concealed weapons is an extremely hard problem due to the weak signature of the target buried within the much stronger signal from the human body. This paper furthers the automatic detection and identification of concealed weapons by proposing the use of an effective approach to obtain the resonant frequencies in a measurement. The technique, based on Matrix Pencil, a scheme for model based parameter estimation also provides amplitude information, hence providing a level of confidence in the results. Of specific interest is the fact that Matrix Pencil is based on a singular value decomposition, making the scheme robust against noise.

A Type-2 Block-Component-Decomposition Based 2D AOA Estimation Algorithm for an Electromagnetic Vector Sensor Array

Directory of Open Access Journals (Sweden)

Yu-Fei Gao

2017-04-01

Full Text Available This paper investigates a two-dimensional angle of arrival (2D AOA estimation algorithm for the electromagnetic vector sensor (EMVS array based on Type-2 block component decomposition (BCD tensor modeling. Such a tensor decomposition method can take full advantage of the multidimensional structural information of electromagnetic signals to accomplish blind estimation for array parameters with higher resolution. However, existing tensor decomposition methods encounter many restrictions in applications of the EMVS array, such as the strict requirement for uniqueness conditions of decomposition, the inability to handle partially-polarized signals, etc. To solve these problems, this paper investigates tensor modeling for partially-polarized signals of an L-shaped EMVS array. The 2D AOA estimation algorithm based on rank- ( L 1 , L 2 , · BCD is developed, and the uniqueness condition of decomposition is analyzed. By means of the estimated steering matrix, the proposed algorithm can automatically achieve angle pair-matching. Numerical experiments demonstrate that the present algorithm has the advantages of both accuracy and robustness of parameter estimation. Even under the conditions of lower SNR, small angular separation and limited snapshots, the proposed algorithm still possesses better performance than subspace methods and the canonical polyadic decomposition (CPD method.

Excluding Noise from Short Krylov Subspace Approximations to the Truncated Singular Value Decomposition (SVD)

Science.gov (United States)

2017-09-27

100 times larger for the minimal Krylov subspace. 0 5 10 15 20 25 Krylov subspace dimension 10-2 10-1 100 101 102 103 104 jjĜ ¡ 1 jj F SVD...approximation Kn (G;u(0) ) 0 5 10 15 20 25 Krylov subspace dimension 10-2 10-1 100 101 102 103 104 jjx jj fo r m in x jjĜ x ¡ bjj SVD approximation Kn (G;u(0

Symbolic computation of analytic approximate solutions for nonlinear differential equations with initial conditions

Science.gov (United States)

Lin, Yezhi; Liu, Yinping; Li, Zhibin

2012-01-01

The Adomian decomposition method (ADM) is one of the most effective methods for constructing analytic approximate solutions of nonlinear differential equations. In this paper, based on the new definition of the Adomian polynomials, and the two-step Adomian decomposition method (TSADM) combined with the Padé technique, a new algorithm is proposed to construct accurate analytic approximations of nonlinear differential equations with initial conditions. Furthermore, a MAPLE package is developed, which is user-friendly and efficient. One only needs to input a system, initial conditions and several necessary parameters, then our package will automatically deliver analytic approximate solutions within a few seconds. Several different types of examples are given to illustrate the validity of the package. Our program provides a helpful and easy-to-use tool in science and engineering to deal with initial value problems. Program summaryProgram title: NAPA Catalogue identifier: AEJZ_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEJZ_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 4060 No. of bytes in distributed program, including test data, etc.: 113 498 Distribution format: tar.gz Programming language: MAPLE R13 Computer: PC Operating system: Windows XP/7 RAM: 2 Gbytes Classification: 4.3 Nature of problem: Solve nonlinear differential equations with initial conditions. Solution method: Adomian decomposition method and Padé technique. Running time: Seconds at most in routine uses of the program. Special tasks may take up to some minutes.

Blip decomposition of the path integral: exponential acceleration of real-time calculations on quantum dissipative systems.

Science.gov (United States)

Makri, Nancy

2014-10-07

The real-time path integral representation of the reduced density matrix for a discrete system in contact with a dissipative medium is rewritten in terms of the number of blips, i.e., elementary time intervals over which the forward and backward paths are not identical. For a given set of blips, it is shown that the path sum with respect to the coordinates of all remaining time points is isomorphic to that for the wavefunction of a system subject to an external driving term and thus can be summed by an inexpensive iterative procedure. This exact decomposition reduces the number of terms by a factor that increases exponentially with propagation time. Further, under conditions (moderately high temperature and/or dissipation strength) that lead primarily to incoherent dynamics, the "fully incoherent limit" zero-blip term of the series provides a reasonable approximation to the dynamics, and the blip series converges rapidly to the exact result. Retention of only the blips required for satisfactory convergence leads to speedup of full-memory path integral calculations by many orders of magnitude.

A mathematical formulation of the Mahaux-Weidenmueller formula for the scattering matrix

International Nuclear Information System (INIS)

Christiansen, T J; Zworski, M

2009-01-01

This paper gives a mathematical exposition of a formula for the scattering matrix for a manifold with infinite cylindrical ends or a waveguide. This formula is well known in the physics literature and we show that a variant of this formula gives the scattering matrix of the mathematics literature. Moreover, we bound the difference between the scattering matrix and an approximation of it computed using a finite rank approximation of the interaction matrix.

Extraction Method of Driver’s Mental Component Based on Empirical Mode Decomposition and Approximate Entropy Statistic Characteristic in Vehicle Running State

Directory of Open Access Journals (Sweden)

Shuan-Feng Zhao

2017-01-01

Full Text Available In the driver fatigue monitoring technology, the essence is to capture and analyze the driver behavior information, such as eyes, face, heart, and EEG activity during driving. However, ECG and EEG monitoring are limited by the installation electrodes and are not commercially available. The most common fatigue detection method is the analysis of driver behavior, that is, to determine whether the driver is tired by recording and analyzing the behavior characteristics of steering wheel and brake. The driver usually adjusts his or her actions based on the observed road conditions. Obviously the road path information is directly contained in the vehicle driving state; if you want to judge the driver’s driving behavior by vehicle driving status information, the first task is to remove the road information from the vehicle driving state data. Therefore, this paper proposes an effective intrinsic mode function selection method for the approximate entropy of empirical mode decomposition considering the characteristics of the frequency distribution of road and vehicle information and the unsteady and nonlinear characteristics of the driver closed-loop driving system in vehicle driving state data. The objective is to extract the effective component of the driving behavior information and to weaken the road information component. Finally the effectiveness of the proposed method is verified by simulating driving experiments.

FESA class for off-momentum lossmaps and decomposition of beam losses at LHC

CERN Document Server

Wyszynski, Michal Jakub; Pojer, Mirko; Salvachua Ferrando, Belen Maria; Valentino, Gianluca; CERN. Geneva. ATS Department

2016-01-01

The project consisted of two main parts. The first part was to build a FESA class which would serve as lossmap feedback controller for off-momentum lossmaps, capable of handling 100 Hz BLM data, contrary to existing controller. Thanks to the efficient management RF frequency, beam dumps during this procedure would be avoided and machine availability would improve by shortening the duration of machine validation after technical stops. The second part concerned identification of beam losses at the LHC. It was a continuation of author’s work done as Summer Student project. The aim was to identify issues with the existing losses decomposition matrix for flat top, apply necessary corrections and construct analogous matrix for injection.

LINPACK, Subroutine Library for Linear Equation System Solution and Matrix Calculation

International Nuclear Information System (INIS)

Dongarra, J.J.

1979-01-01

1 - Description of problem or function: LINPACK is a collection of FORTRAN subroutines which analyze and solve various classes of systems of simultaneous linear algebraic equations. The collection deals with general, banded, symmetric indefinite, symmetric positive definite, triangular, and tridiagonal square matrices, as well as with least squares problems and the QR and singular value decompositions of rectangular matrices. A subroutine-naming convention is employed in which each subroutine name consists of five letters which represent a coded specification (TXXYY) of the computation done by that subroutine. The first letter, T, indicates the matrix data type. Standard FORTRAN allows the use of three such types: S REAL, D DOUBLE PRECISION, and C COMPLEX. In addition, some FORTRAN systems allow a double-precision complex type: Z COMPLEX*16. The second and third letters of the subroutine name, XX, indicate the form of the matrix or its decomposition: GE: General, GB: General band, PO: Positive definite, PP: Positive definite packed, PB: Positive definite band, SI: Symmetric indefinite, SP: Symmetric indefinite packed, HI: Hermitian indefinite, HP: Hermitian indefinite packed, TR: Triangular, GT: General tridiagonal, PT: Positive definite tridiagonal, CH: Cholesky decomposition, QR: Orthogonal-triangular decomposition, SV: Singular value decomposition. The final two letters, YY, indicate the computation done by the particular subroutine: FA: Factor, CO: Factor and estimate condition, SL: Solve, DI: Determinant and/or inverse and/or inertia, DC: Decompose, UD: Update, DD: Down-date, EX Exchange. The following chart shows all the LINPACK subroutines. The initial 'S' in the names may be replaced by D, C or Z and the initial 'C' in the complex-only names may be replaced by a Z. SGE: FA, CO, SL, DI; SGB: FA, CO, SL, DI; SPO: FA, CO, SL, DI; SPP: FA, CO, SL, DI; SPB: FA, CO, SL, DI; SSI: FA, CO, SL, DI; SSP: FA, CO, SL, DI; CHI: FA, CO, SL, DI; CHP: FA, CO, SL, DI; STR

Extended quasiparticle approximation for relativistic electrons in plasmas

Directory of Open Access Journals (Sweden)

V.G.Morozov

2006-01-01

Full Text Available Starting with Dyson equations for the path-ordered Green's function, it is shown that the correlation functions for relativistic electrons (positrons in a weakly coupled non-equilibrium plasmas can be decomposed into sharply peaked quasiparticle parts and off-shell parts in a rather general form. To leading order in the electromagnetic coupling constant, this decomposition yields the extended quasiparticle approximation for the correlation functions, which can be used for the first principle calculation of the radiation scattering rates in QED plasmas.

Global sensitivity analysis by polynomial dimensional decomposition

Energy Technology Data Exchange (ETDEWEB)

Rahman, Sharif, E-mail: rahman@engineering.uiowa.ed [College of Engineering, The University of Iowa, Iowa City, IA 52242 (United States)

2011-07-15

This paper presents a polynomial dimensional decomposition (PDD) method for global sensitivity analysis of stochastic systems subject to independent random input following arbitrary probability distributions. The method involves Fourier-polynomial expansions of lower-variate component functions of a stochastic response by measure-consistent orthonormal polynomial bases, analytical formulae for calculating the global sensitivity indices in terms of the expansion coefficients, and dimension-reduction integration for estimating the expansion coefficients. Due to identical dimensional structures of PDD and analysis-of-variance decomposition, the proposed method facilitates simple and direct calculation of the global sensitivity indices. Numerical results of the global sensitivity indices computed for smooth systems reveal significantly higher convergence rates of the PDD approximation than those from existing methods, including polynomial chaos expansion, random balance design, state-dependent parameter, improved Sobol's method, and sampling-based methods. However, for non-smooth functions, the convergence properties of the PDD solution deteriorate to a great extent, warranting further improvements. The computational complexity of the PDD method is polynomial, as opposed to exponential, thereby alleviating the curse of dimensionality to some extent.

Google matrix, dynamical attractors, and Ulam networks.

Science.gov (United States)

Shepelyansky, D L; Zhirov, O V

2010-03-01

We study the properties of the Google matrix generated by a coarse-grained Perron-Frobenius operator of the Chirikov typical map with dissipation. The finite-size matrix approximant of this operator is constructed by the Ulam method. This method applied to the simple dynamical model generates directed Ulam networks with approximate scale-free scaling and characteristics being in certain features similar to those of the world wide web with approximate scale-free degree distributions as well as two characteristics similar to the web: a power-law decay in PageRank that mirrors the decay of PageRank on the world wide web and a sensitivity to the value alpha in PageRank. The simple dynamical attractors play here the role of popular websites with a strong concentration of PageRank. A variation in the Google parameter alpha or other parameters of the dynamical map can drive the PageRank of the Google matrix to a delocalized phase with a strange attractor where the Google search becomes inefficient.

Adaptive ACMS: A robust localized Approximated Component Mode Synthesis Method

OpenAIRE

Madureira, Alexandre L.; Sarkis, Marcus

2017-01-01

We consider finite element methods of multiscale type to approximate solutions for two-dimensional symmetric elliptic partial differential equations with heterogeneous $L^\\infty$ coefficients. The methods are of Galerkin type and follows the Variational Multiscale and Localized Orthogonal Decomposition--LOD approaches in the sense that it decouples spaces into multiscale and fine subspaces. In a first method, the multiscale basis functions are obtained by mapping coarse basis functions, based...

The TRUPACT-II Matrix Depleton Program

International Nuclear Information System (INIS)

Connolly, M.J.; Djordjevic, S.M.; Loehr, C.A.; Smith, M.C.; Banjac, V.; Lyon, W.F.

1995-01-01

Contact-handled transuranic (CH-TRU) wastes will be shipped and disposed at the Waste Isolation Pilot Plant (WIPP) repository in the Transuranic Package Transporter-II (TRUPACT-II) shipping package. A primary transportation requirement for the TRUPACT-II is that the concentration of potentially flammable gases (i.e., hydrogen and methane) must not exceed 5 percent by volume in the package or the payload during a 60-day shipping period. Decomposition of waste materials by radiation, or radiolysis, is the predominant mechanism of gas generation during transport. The gas generation potential of a target waste material is characterized by a G-value, which is the number of molecules of gas generated per 100 eV of ionizing radiation absorbed by the target material. To demonstrate compliance with the flammable gas concentration requirement, theoretical worst-case calculations were performed to establish allowable wattage (decay heat) limits for waste containers. The calculations were based on the G-value for the waste material with the highest potential for flammable gas generation. The calculations also made no allowances for decreases of the G-value over time due to matrix depletion phenomena that have been observed by many experimenters. Matrix depletion occurs over time when an alpha-generating source particle alters the target material (by evaporation, reaction, or decomposition) into a material of lower gas generating potential. The net effect of these alterations is represented by the ''effective G-value.''

Correction of failure in antenna array using matrix pencil technique

International Nuclear Information System (INIS)

Khan, SU; Rahim, MKA

2017-01-01

In this paper a non-iterative technique is developed for the correction of faulty antenna array based on matrix pencil technique (MPT). The failure of a sensor in antenna array can damage the radiation power pattern in terms of sidelobes level and nulls. In the developed technique, the radiation pattern of the array is sampled to form discrete power pattern information set. Then this information set can be arranged in the form of Hankel matrix (HM) and execute the singular value decomposition (SVD). By removing nonprincipal values, we obtain an optimum lower rank estimation of HM. This lower rank matrix corresponds to the corrected pattern. Then the proposed technique is employed to recover the weight excitation and position allocations from the estimated matrix. Numerical simulations confirm the efficiency of the proposed technique, which is compared with the available techniques in terms of sidelobes level and nulls. (paper)

Interacting effects of insects and flooding on wood decomposition.

Directory of Open Access Journals (Sweden)

Michael D Ulyshen

Full Text Available Saproxylic arthropods are thought to play an important role in wood decomposition but very few efforts have been made to quantify their contributions to the process and the factors controlling their activities are not well understood. In the current study, mesh exclusion bags were used to quantify how arthropods affect loblolly pine (Pinus taeda L. decomposition rates in both seasonally flooded and unflooded forests over a 31-month period in the southeastern United States. Wood specific gravity (based on initial wood volume was significantly lower in bolts placed in unflooded forests and for those unprotected from insects. Approximately 20.5% and 13.7% of specific gravity loss after 31 months was attributable to insect activity in flooded and unflooded forests, respectively. Importantly, minimal between-treatment differences in water content and the results from a novel test carried out separately suggest the mesh bags had no significant impact on wood mass loss beyond the exclusion of insects. Subterranean termites (Isoptera: Rhinotermitidae: Reticulitermes spp. were 5-6 times more active below-ground in unflooded forests compared to flooded forests based on wooden monitoring stakes. They were also slightly more active above-ground in unflooded forests but these differences were not statistically significant. Similarly, seasonal flooding had no detectable effect on above-ground beetle (Coleoptera richness or abundance. Although seasonal flooding strongly reduced Reticulitermes activity below-ground, it can be concluded from an insignificant interaction between forest type and exclusion treatment that reduced above-ground decomposition rates in seasonally flooded forests were due largely to suppressed microbial activity at those locations. The findings from this study indicate that southeastern U.S. arthropod communities accelerate above-ground wood decomposition significantly and to a similar extent in both flooded and unflooded forests

Calculation of the Cholesky factor directly from the stiffness matrix of the structural element

International Nuclear Information System (INIS)

Prates, C.L.M.; Soriano, H.L.

1978-01-01

The analysis of the structures of nuclear power plants requires the evaluation of the internal forces. This is attained by the solution of a system of equations. This solution takes most of the computing time and memory. One of the ways it can be achieved is based on the Cholesky factor. The structural matrix of the coeficients is transformed into an upper triangular matrix by the Cholesky decomposition. Cholesky factor can be obtained directly from the stiffness matrix of the structural element. The result can thus be obtained in a more precise and quick way. (Author)

Coulomb matrix elements in multi-orbital Hubbard models.

Science.gov (United States)

Bünemann, Jörg; Gebhard, Florian

2017-04-26

Coulomb matrix elements are needed in all studies in solid-state theory that are based on Hubbard-type multi-orbital models. Due to symmetries, the matrix elements are not independent. We determine a set of independent Coulomb parameters for a d-shell and an f-shell and all point groups with up to 16 elements (O h , O, T d , T h , D 6h , and D 4h ). Furthermore, we express all other matrix elements as a function of the independent Coulomb parameters. Apart from the solution of the general point-group problem we investigate in detail the spherical approximation and first-order corrections to the spherical approximation.

Synthesis of transparent ZnO/PMMA nanocomposite films through free-radical copolymerization of asymmetric zinc methacrylate acetate and in-situ thermal decomposition

Energy Technology Data Exchange (ETDEWEB)

Zhang Lin [Department of Chemistry, Nanchang University, 999 Xuefu Avenue, Nanchang 330031 (China); Institute of Polymers, Nanchang University, 999 Xuefu Avenue, Nanchang 330031 (China); Li Fan, E-mail: lfan@ncu.edu.cn [Institute of Polymers, Nanchang University, 999 Xuefu Avenue, Nanchang 330031 (China); Chen Yiwang, E-mail: ywchen@ncu.edu.cn [Department of Chemistry, Nanchang University, 999 Xuefu Avenue, Nanchang 330031 (China); Institute of Polymers, Nanchang University, 999 Xuefu Avenue, Nanchang 330031 (China); Wang Xiaofeng [Institute of Polymers, Nanchang University, 999 Xuefu Avenue, Nanchang 330031 (China)

2011-08-15

In this paper, a new and simple approach for in-situ preparation of transparent ZnO/poly(metyl methacrylate) (ZnO/PMMA) nanocomposite films was developed. Poly(methyl methacrylate)-co-poly(zinc methacrylate acetate) (PMMA-co-PZnMAAc) copolymer was synthesized via free-radical polymerization between methyl methacrylate (MMA) and zinc methacrylate acetate (ZnMAAc), where asymmetric ZnMAAc with only one terminal double bond (C=C) was applied to act as the precursor for ZnO nanocrystals and could avoid cross-link. Subsequently, transparent ZnO/PMMA nanocomposite films were obtained by in-situ thermal decomposition. Scanning electron microscope (SEM) image revealed that ZnO nanocrystals were homogeneously dispersed in PMMA matrix. With thermal decomposition time increasing, the absorption intensity in UV region and photoluminescence intensity of ZnO/PMMA nanocomposite films enhanced. However, the optical properties diminished when the thermal decomposition temperature increased. The TGA measurement displayed ZnO/PMMA nanocomposite films prepared by the in-situ synthesis method possessed better thermal stability compared with those prepared by the physical blending method and pristine PMMA films. - Highlights: > ZnO/PMMA hybrid films were prepared via free-radical polymerization and in-situ thermal decomposition. > ZnO NCs are homogeneously dispersed in the PMMA matrix and these films have good optical properties. > Thermal stability of these films is improved compared with those of physically blending ones.

Synthesis of transparent ZnO/PMMA nanocomposite films through free-radical copolymerization of asymmetric zinc methacrylate acetate and in-situ thermal decomposition

International Nuclear Information System (INIS)

Zhang Lin; Li Fan; Chen Yiwang; Wang Xiaofeng

2011-01-01

In this paper, a new and simple approach for in-situ preparation of transparent ZnO/poly(metyl methacrylate) (ZnO/PMMA) nanocomposite films was developed. Poly(methyl methacrylate)-co-poly(zinc methacrylate acetate) (PMMA-co-PZnMAAc) copolymer was synthesized via free-radical polymerization between methyl methacrylate (MMA) and zinc methacrylate acetate (ZnMAAc), where asymmetric ZnMAAc with only one terminal double bond (C=C) was applied to act as the precursor for ZnO nanocrystals and could avoid cross-link. Subsequently, transparent ZnO/PMMA nanocomposite films were obtained by in-situ thermal decomposition. Scanning electron microscope (SEM) image revealed that ZnO nanocrystals were homogeneously dispersed in PMMA matrix. With thermal decomposition time increasing, the absorption intensity in UV region and photoluminescence intensity of ZnO/PMMA nanocomposite films enhanced. However, the optical properties diminished when the thermal decomposition temperature increased. The TGA measurement displayed ZnO/PMMA nanocomposite films prepared by the in-situ synthesis method possessed better thermal stability compared with those prepared by the physical blending method and pristine PMMA films. - Highlights: → ZnO/PMMA hybrid films were prepared via free-radical polymerization and in-situ thermal decomposition. → ZnO NCs are homogeneously dispersed in the PMMA matrix and these films have good optical properties. → Thermal stability of these films is improved compared with those of physically blending ones.

Characteristic analysis on UAV-MIMO channel based on normalized correlation matrix.

Science.gov (United States)

Gao, Xi jun; Chen, Zi li; Hu, Yong Jiang

2014-01-01

Based on the three-dimensional GBSBCM (geometrically based double bounce cylinder model) channel model of MIMO for unmanned aerial vehicle (UAV), the simple form of UAV space-time-frequency channel correlation function which includes the LOS, SPE, and DIF components is presented. By the methods of channel matrix decomposition and coefficient normalization, the analytic formula of UAV-MIMO normalized correlation matrix is deduced. This formula can be used directly to analyze the condition number of UAV-MIMO channel matrix, the channel capacity, and other characteristic parameters. The simulation results show that this channel correlation matrix can be applied to describe the changes of UAV-MIMO channel characteristics under different parameter settings comprehensively. This analysis method provides a theoretical basis for improving the transmission performance of UAV-MIMO channel. The development of MIMO technology shows practical application value in the field of UAV communication.

A simple, rapid and eco friendly method for determination of uranium in geological samples of low silicate matrix by ICP-OES

International Nuclear Information System (INIS)

Hanuman, V.V.; Chakrapani, G.; Singh, A.K.

2013-01-01

A simple, rapid, cost effective and eco friendly decomposition and dissolution method is developed for the determination of uranium (U 3 O 8 ) by Inductively Coupled Plasma - Optical Emission Spectrometer (ICP-OES) in low silicate geological samples. The salts of Sodium di-hydrogen phosphate monohydrate and Sodium pyrophosphate deca hydrate are used in the ratio of 1:1 (phosphate flux) for the decomposition of low silicate matrix geological samples. Samples are decomposed by fusion with the phosphate flux after ignition and the dissolution is carried out using distilled water. If the samples contain >10% silica, they have been treated with little amount of (HF+HNO 3 ) prior to fusion with phosphate flux. These samples, are analysed by ICP-OES directly without any separation from the matrix. The spectral interferences of major matrix elements (Al, Ti, Fe, Mn, etc present in the sample) on uranium are studied and it is observed that their interferences are negligible, as dilution is required to bring uranium concentration into calibration range of instrument. This is the first time, the phosphate flux is used for decomposition of low silicate geological samples for uranium determination by ICP-OES

Decomposition and particle release of a carbon nanotube/epoxy nanocomposite at elevated temperatures

International Nuclear Information System (INIS)

Schlagenhauf, Lukas; Kuo, Yu-Ying; Bahk, Yeon Kyoung; Nüesch, Frank; Wang, Jing

2015-01-01

Carbon nanotubes (CNTs) as fillers in nanocomposites have attracted significant attention, and one of the applications is to use the CNTs as flame retardants. For such nanocomposites, possible release of CNTs at elevated temperatures after decomposition of the polymer matrix poses potential health threats. We investigated the airborne particle release from a decomposing multi-walled carbon nanotube (MWCNT)/epoxy nanocomposite in order to measure a possible release of MWCNTs. An experimental set-up was established that allows decomposing the samples in a furnace by exposure to increasing temperatures at a constant heating rate and under ambient air or nitrogen atmosphere. The particle analysis was performed by aerosol measurement devices and by transmission electron microscopy (TEM) of collected particles. Further, by the application of a thermal denuder, it was also possible to measure non-volatile particles only. Characterization of the tested samples and the decomposition kinetics were determined by the usage of thermogravimetric analysis (TGA). The particle release of different samples was investigated, of a neat epoxy, nanocomposites with 0.1 and 1 wt% MWCNTs, and nanocomposites with functionalized MWCNTs. The results showed that the added MWCNTs had little effect on the decomposition kinetics of the investigated samples, but the weight of the remaining residues after decomposition was influenced significantly. The measurements with decomposition in different atmospheres showed a release of a higher number of particles at temperatures below 300 °C when air was used. Analysis of collected particles by TEM revealed that no detectable amount of MWCNTs was released, but micrometer-sized fibrous particles were collected

Decomposition and particle release of a carbon nanotube/epoxy nanocomposite at elevated temperatures

Science.gov (United States)

Schlagenhauf, Lukas; Kuo, Yu-Ying; Bahk, Yeon Kyoung; Nüesch, Frank; Wang, Jing

2015-11-01

Carbon nanotubes (CNTs) as fillers in nanocomposites have attracted significant attention, and one of the applications is to use the CNTs as flame retardants. For such nanocomposites, possible release of CNTs at elevated temperatures after decomposition of the polymer matrix poses potential health threats. We investigated the airborne particle release from a decomposing multi-walled carbon nanotube (MWCNT)/epoxy nanocomposite in order to measure a possible release of MWCNTs. An experimental set-up was established that allows decomposing the samples in a furnace by exposure to increasing temperatures at a constant heating rate and under ambient air or nitrogen atmosphere. The particle analysis was performed by aerosol measurement devices and by transmission electron microscopy (TEM) of collected particles. Further, by the application of a thermal denuder, it was also possible to measure non-volatile particles only. Characterization of the tested samples and the decomposition kinetics were determined by the usage of thermogravimetric analysis (TGA). The particle release of different samples was investigated, of a neat epoxy, nanocomposites with 0.1 and 1 wt% MWCNTs, and nanocomposites with functionalized MWCNTs. The results showed that the added MWCNTs had little effect on the decomposition kinetics of the investigated samples, but the weight of the remaining residues after decomposition was influenced significantly. The measurements with decomposition in different atmospheres showed a release of a higher number of particles at temperatures below 300 °C when air was used. Analysis of collected particles by TEM revealed that no detectable amount of MWCNTs was released, but micrometer-sized fibrous particles were collected.

Decomposition and particle release of a carbon nanotube/epoxy nanocomposite at elevated temperatures

Energy Technology Data Exchange (ETDEWEB)

Schlagenhauf, Lukas [Empa - Swiss Federal Laboratories for Materials Science and Technology, Laboratory for Functional Polymers (Switzerland); Kuo, Yu-Ying; Bahk, Yeon Kyoung [Empa - Swiss Federal Laboratories for Materials Science and Technology, Laboratory for Advanced Analytical Technologies (Switzerland); Nüesch, Frank [Empa - Swiss Federal Laboratories for Materials Science and Technology, Laboratory for Functional Polymers (Switzerland); Wang, Jing, E-mail: Jing.Wang@ifu.baug.ethz.ch [Empa - Swiss Federal Laboratories for Materials Science and Technology, Laboratory for Advanced Analytical Technologies (Switzerland)

2015-11-15

Carbon nanotubes (CNTs) as fillers in nanocomposites have attracted significant attention, and one of the applications is to use the CNTs as flame retardants. For such nanocomposites, possible release of CNTs at elevated temperatures after decomposition of the polymer matrix poses potential health threats. We investigated the airborne particle release from a decomposing multi-walled carbon nanotube (MWCNT)/epoxy nanocomposite in order to measure a possible release of MWCNTs. An experimental set-up was established that allows decomposing the samples in a furnace by exposure to increasing temperatures at a constant heating rate and under ambient air or nitrogen atmosphere. The particle analysis was performed by aerosol measurement devices and by transmission electron microscopy (TEM) of collected particles. Further, by the application of a thermal denuder, it was also possible to measure non-volatile particles only. Characterization of the tested samples and the decomposition kinetics were determined by the usage of thermogravimetric analysis (TGA). The particle release of different samples was investigated, of a neat epoxy, nanocomposites with 0.1 and 1 wt% MWCNTs, and nanocomposites with functionalized MWCNTs. The results showed that the added MWCNTs had little effect on the decomposition kinetics of the investigated samples, but the weight of the remaining residues after decomposition was influenced significantly. The measurements with decomposition in different atmospheres showed a release of a higher number of particles at temperatures below 300 °C when air was used. Analysis of collected particles by TEM revealed that no detectable amount of MWCNTs was released, but micrometer-sized fibrous particles were collected.

Decompositions of manifolds

CERN Document Server

Daverman, Robert J

2007-01-01

Decomposition theory studies decompositions, or partitions, of manifolds into simple pieces, usually cell-like sets. Since its inception in 1929, the subject has become an important tool in geometric topology. The main goal of the book is to help students interested in geometric topology to bridge the gap between entry-level graduate courses and research at the frontier as well as to demonstrate interrelations of decomposition theory with other parts of geometric topology. With numerous exercises and problems, many of them quite challenging, the book continues to be strongly recommended to eve

Newton-Raphson based modified Laplace Adomian decomposition method for solving quadratic Riccati differential equations

Directory of Open Access Journals (Sweden)

Mishra Vinod

2016-01-01

Full Text Available Numerical Laplace transform method is applied to approximate the solution of nonlinear (quadratic Riccati differential equations mingled with Adomian decomposition method. A new technique is proposed in this work by reintroducing the unknown function in Adomian polynomial with that of well known Newton-Raphson formula. The solutions obtained by the iterative algorithm are exhibited in an infinite series. The simplicity and efficacy of method is manifested with some examples in which comparisons are made among the exact solutions, ADM (Adomian decomposition method, HPM (Homotopy perturbation method, Taylor series method and the proposed scheme.

Thermal decomposition of pyrite

International Nuclear Information System (INIS)

Music, S.; Ristic, M.; Popovic, S.

1992-01-01

Thermal decomposition of natural pyrite (cubic, FeS 2 ) has been investigated using X-ray diffraction and 57 Fe Moessbauer spectroscopy. X-ray diffraction analysis of pyrite ore from different sources showed the presence of associated minerals, such as quartz, szomolnokite, stilbite or stellerite, micas and hematite. Hematite, maghemite and pyrrhotite were detected as thermal decomposition products of natural pyrite. The phase composition of the thermal decomposition products depends on the terature, time of heating and starting size of pyrite chrystals. Hematite is the end product of the thermal decomposition of natural pyrite. (author) 24 refs.; 6 figs.; 2 tabs

Danburite decomposition by sulfuric acid

International Nuclear Information System (INIS)

Mirsaidov, U.; Mamatov, E.D.; Ashurov, N.A.

2011-01-01

Present article is devoted to decomposition of danburite of Ak-Arkhar Deposit of Tajikistan by sulfuric acid. The process of decomposition of danburite concentrate by sulfuric acid was studied. The chemical nature of decomposition process of boron containing ore was determined. The influence of temperature on the rate of extraction of boron and iron oxides was defined. The dependence of decomposition of boron and iron oxides on process duration, dosage of H 2 SO 4 , acid concentration and size of danburite particles was determined. The kinetics of danburite decomposition by sulfuric acid was studied as well. The apparent activation energy of the process of danburite decomposition by sulfuric acid was calculated. The flowsheet of danburite processing by sulfuric acid was elaborated.

Localized motion in random matrix decomposition of complex financial systems

Science.gov (United States)

Jiang, Xiong-Fei; Zheng, Bo; Ren, Fei; Qiu, Tian

2017-04-01

With the random matrix theory, we decompose the multi-dimensional time series of complex financial systems into a set of orthogonal eigenmode functions, which are classified into the market mode, sector mode, and random mode. In particular, the localized motion generated by the business sectors, plays an important role in financial systems. Both the business sectors and their impact on the stock market are identified from the localized motion. We clarify that the localized motion induces different characteristics of the time correlations for the stock-market index and individual stocks. With a variation of a two-factor model, we reproduce the return-volatility correlations of the eigenmodes.

A novel method for EMG decomposition based on matched filters

Directory of Open Access Journals (Sweden)

Ailton Luiz Dias Siqueira Júnior

Full Text Available Introduction Decomposition of electromyography (EMG signals into the constituent motor unit action potentials (MUAPs can allow for deeper insights into the underlying processes associated with the neuromuscular system. The vast majority of the methods for EMG decomposition found in the literature depend on complex algorithms and specific instrumentation. As an attempt to contribute to solving these issues, we propose a method based on a bank of matched filters for the decomposition of EMG signals. Methods Four main units comprise our method: a bank of matched filters, a peak detector, a motor unit classifier and an overlapping resolution module. The system’s performance was evaluated with simulated and real EMG data. Classification accuracy was measured by comparing the responses of the system with known data from the simulator and with the annotations of a human expert. Results The results show that decomposition of non-overlapping MUAPs can be achieved with up to 99% accuracy for signals with up to 10 active motor units and a signal-to-noise ratio (SNR of 10 dB. For overlapping MUAPs with up to 10 motor units per signal and a SNR of 20 dB, the technique allows for correct classification of approximately 71% of the MUAPs. The method is capable of processing, decomposing and classifying a 50 ms window of data in less than 5 ms using a standard desktop computer. Conclusion This article contributes to the ongoing research on EMG decomposition by describing a novel technique capable of delivering high rates of success by means of a fast algorithm, suggesting its possible use in future real-time embedded applications, such as myoelectric prostheses control and biofeedback systems.

Data-Driven Model Reduction and Transfer Operator Approximation

Science.gov (United States)

Klus, Stefan; Nüske, Feliks; Koltai, Péter; Wu, Hao; Kevrekidis, Ioannis; Schütte, Christof; Noé, Frank

2018-06-01

In this review paper, we will present different data-driven dimension reduction techniques for dynamical systems that are based on transfer operator theory as well as methods to approximate transfer operators and their eigenvalues, eigenfunctions, and eigenmodes. The goal is to point out similarities and differences between methods developed independently by the dynamical systems, fluid dynamics, and molecular dynamics communities such as time-lagged independent component analysis, dynamic mode decomposition, and their respective generalizations. As a result, extensions and best practices developed for one particular method can be carried over to other related methods.

On practical challenges of decomposition-based hybrid forecasting algorithms for wind speed and solar irradiation

International Nuclear Information System (INIS)

Wang, Yamin; Wu, Lei

2016-01-01

This paper presents a comprehensive analysis on practical challenges of empirical mode decomposition (EMD) based algorithms on wind speed and solar irradiation forecasts that have been largely neglected in literature, and proposes an alternative approach to mitigate such challenges. Specifically, the challenges are: (1) Decomposed sub-series are very sensitive to the original time series data. That is, sub-series of the new time series, consisting of the original one plus a limit number of new data samples, may significantly differ from those used in training forecasting models. In turn, forecasting models established by original sub-series may not be suitable for newly decomposed sub-series and have to be trained more frequently; and (2) Key environmental factors usually play a critical role in non-decomposition based methods for forecasting wind speed and solar irradiation. However, it is difficult to incorporate such critical environmental factors into forecasting models of individual decomposed sub-series, because the correlation between the original data and environmental factors is lost after decomposition. Numerical case studies on wind speed and solar irradiation forecasting show that the performance of existing EMD-based forecasting methods could be worse than the non-decomposition based forecasting model, and are not effective in practical cases. Finally, the approximated forecasting model based on EMD is proposed to mitigate the challenges and achieve better forecasting results than existing EMD-based forecasting algorithms and the non-decomposition based forecasting models on practical wind speed and solar irradiation forecasting cases. - Highlights: • Two challenges of existing EMD-based forecasting methods are discussed. • Significant changes of sub-series in each step of the rolling forecast procedure. • Difficulties in incorporating environmental factors into sub-series forecasting models. • The approximated forecasting method is proposed to

Variance decomposition-based sensitivity analysis via neural networks

International Nuclear Information System (INIS)

Marseguerra, Marzio; Masini, Riccardo; Zio, Enrico; Cojazzi, Giacomo

2003-01-01

This paper illustrates a method for efficiently performing multiparametric sensitivity analyses of the reliability model of a given system. These analyses are of great importance for the identification of critical components in highly hazardous plants, such as the nuclear or chemical ones, thus providing significant insights for their risk-based design and management. The technique used to quantify the importance of a component parameter with respect to the system model is based on a classical decomposition of the variance. When the model of the system is realistically complicated (e.g. by aging, stand-by, maintenance, etc.), its analytical evaluation soon becomes impractical and one is better off resorting to Monte Carlo simulation techniques which, however, could be computationally burdensome. Therefore, since the variance decomposition method requires a large number of system evaluations, each one to be performed by Monte Carlo, the need arises for possibly substituting the Monte Carlo simulation model with a fast, approximated, algorithm. Here we investigate an approach which makes use of neural networks appropriately trained on the results of a Monte Carlo system reliability/availability evaluation to quickly provide with reasonable approximation, the values of the quantities of interest for the sensitivity analyses. The work was a joint effort between the Department of Nuclear Engineering of the Polytechnic of Milan, Italy, and the Institute for Systems, Informatics and Safety, Nuclear Safety Unit of the Joint Research Centre in Ispra, Italy which sponsored the project

Efficient morse decompositions of vector fields.

Science.gov (United States)

Chen, Guoning; Mischaikow, Konstantin; Laramee, Robert S; Zhang, Eugene

2008-01-01

Existing topology-based vector field analysis techniques rely on the ability to extract the individual trajectories such as fixed points, periodic orbits, and separatrices that are sensitive to noise and errors introduced by simulation and interpolation. This can make such vector field analysis unsuitable for rigorous interpretations. We advocate the use of Morse decompositions, which are robust with respect to perturbations, to encode the topological structures of a vector field in the form of a directed graph, called a Morse connection graph (MCG). While an MCG exists for every vector field, it need not be unique. Previous techniques for computing MCG's, while fast, are overly conservative and usually results in MCG's that are too coarse to be useful for the applications. To address this issue, we present a new technique for performing Morse decomposition based on the concept of tau-maps, which typically provides finer MCG's than existing techniques. Furthermore, the choice of tau provides a natural tradeoff between the fineness of the MCG's and the computational costs. We provide efficient implementations of Morse decomposition based on tau-maps, which include the use of forward and backward mapping techniques and an adaptive approach in constructing better approximations of the images of the triangles in the meshes used for simulation.. Furthermore, we propose the use of spatial tau-maps in addition to the original temporal tau-maps. These techniques provide additional trade-offs between the quality of the MCGs and the speed of computation. We demonstrate the utility of our technique with various examples in the plane and on surfaces including engine simulation data sets.

Economic and environmental efficiency using a social accounting matrix

International Nuclear Information System (INIS)

Morilla, Carmen Rodriguez; Diaz-Salazar, Gaspar Llanes; Cardenete, M. Alejandro

2007-01-01

This paper aims to show the utility of the so-called Social Accounting Matrix and Environmental Accounts (SAMEA) for economic and environmental efficiency analysis. The article uses the SAMEA for Spain in 2000, applied to water resources and greenhouse gas emissions. This matrix is used as a central core of a multisectorial model of economic and environmental performance, and it calculates the denominated 'domestics SAMEA multipliers' and their decomposition into characteristic, direct, indirect and induced effects. These multipliers show some evaluation of economic and environmental efficiency. Also, we present an application of these multipliers that demonstrates that there is no causal interrelation between those sectors with higher economic backward linkages and those with higher environmental deterioration backward linkages. (author)

Simulating propagation of decomposed elastic waves using low-rank approximate mixed-domain integral operators for heterogeneous transversely isotropic media

KAUST Repository

Cheng, Jiubing

2014-08-05

In elastic imaging, the extrapolated vector fields are decomposed into pure wave modes, such that the imaging condition produces interpretable images, which characterize reflectivity of different reflection types. Conventionally, wavefield decomposition in anisotropic media is costly as the operators involved is dependent on the velocity, and thus not stationary. In this abstract, we propose an efficient approach to directly extrapolate the decomposed elastic waves using lowrank approximate mixed space/wavenumber domain integral operators for heterogeneous transverse isotropic (TI) media. The low-rank approximation is, thus, applied to the pseudospectral extrapolation and decomposition at the same time. The pseudo-spectral implementation also allows for relatively large time steps in which the low-rank approximation is applied. Synthetic examples show that it can yield dispersionfree extrapolation of the decomposed quasi-P (qP) and quasi- SV (qSV) modes, which can be used for imaging, as well as the total elastic wavefields.

Azimuthal decomposition of optical modes

CSIR Research Space (South Africa)

Dudley, Angela L

2012-07-01

Full Text Available This presentation analyses the azimuthal decomposition of optical modes. Decomposition of azimuthal modes need two steps, namely generation and decomposition. An azimuthally-varying phase (bounded by a ring-slit) placed in the spatial frequency...

A Dual Super-Element Domain Decomposition Approach for Parallel Nonlinear Finite Element Analysis

Science.gov (United States)

Jokhio, G. A.; Izzuddin, B. A.

2015-05-01

This article presents a new domain decomposition method for nonlinear finite element analysis introducing the concept of dual partition super-elements. The method extends ideas from the displacement frame method and is ideally suited for parallel nonlinear static/dynamic analysis of structural systems. In the new method, domain decomposition is realized by replacing one or more subdomains in a "parent system," each with a placeholder super-element, where the subdomains are processed separately as "child partitions," each wrapped by a dual super-element along the partition boundary. The analysis of the overall system, including the satisfaction of equilibrium and compatibility at all partition boundaries, is realized through direct communication between all pairs of placeholder and dual super-elements. The proposed method has particular advantages for matrix solution methods based on the frontal scheme, and can be readily implemented for existing finite element analysis programs to achieve parallelization on distributed memory systems with minimal intervention, thus overcoming memory bottlenecks typically faced in the analysis of large-scale problems. Several examples are presented in this article which demonstrate the computational benefits of the proposed parallel domain decomposition approach and its applicability to the nonlinear structural analysis of realistic structural systems.

Approximate analytical modeling of leptospirosis infection

Science.gov (United States)

Ismail, Nur Atikah; Azmi, Amirah; Yusof, Fauzi Mohamed; Ismail, Ahmad Izani

2017-11-01

Leptospirosis is an infectious disease carried by rodents which can cause death in humans. The disease spreads directly through contact with feces, urine or through bites of infected rodents and indirectly via water contaminated with urine and droppings from them. Significant increase in the number of leptospirosis cases in Malaysia caused by the recent severe floods were recorded during heavy rainfall season. Therefore, to understand the dynamics of leptospirosis infection, a mathematical model based on fractional differential equations have been developed and analyzed. In this paper an approximate analytical method, the multi-step Laplace Adomian decomposition method, has been used to conduct numerical simulations so as to gain insight on the spread of leptospirosis infection.

Testing Constancy of the Error Covariance Matrix in Vector Models against Parametric Alternatives using a Spectral Decomposition

DEFF Research Database (Denmark)

Yang, Yukay

I consider multivariate (vector) time series models in which the error covariance matrix may be time-varying. I derive a test of constancy of the error covariance matrix against the alternative that the covariance matrix changes over time. I design a new family of Lagrange-multiplier tests against...... to consider multivariate volatility modelling....

Thermal decomposition of lutetium propionate

DEFF Research Database (Denmark)

Grivel, Jean-Claude

2010-01-01

The thermal decomposition of lutetium(III) propionate monohydrate (Lu(C2H5CO2)3·H2O) in argon was studied by means of thermogravimetry, differential thermal analysis, IR-spectroscopy and X-ray diffraction. Dehydration takes place around 90 °C. It is followed by the decomposition of the anhydrous...... °C. Full conversion to Lu2O3 is achieved at about 1000 °C. Whereas the temperatures and solid reaction products of the first two decomposition steps are similar to those previously reported for the thermal decomposition of lanthanum(III) propionate monohydrate, the final decomposition...... of the oxycarbonate to the rare-earth oxide proceeds in a different way, which is here reminiscent of the thermal decomposition path of Lu(C3H5O2)·2CO(NH2)2·2H2O...

Analytical singular-value decomposition of three-dimensional, proximity-based SPECT systems

Energy Technology Data Exchange (ETDEWEB)

Barrett, Harrison H. [Arizona Univ., Tucson, AZ (United States). College of Optical Sciences; Arizona Univ., Tucson, AZ (United States). Center for Gamma-Ray Imaging; Holen, Roel van [Ghent Univ. (Belgium). Medical Image and Signal Processing (MEDISIP); Arizona Univ., Tucson, AZ (United States). Center for Gamma-Ray Imaging

2011-07-01

An operator formalism is introduced for the description of SPECT imaging systems that use solid-angle effects rather than pinholes or collimators, as in recent work by Mitchell and Cherry. The object is treated as a 3D function, without discretization, and the data are 2D functions on the detectors. An analytic singular-value decomposition of the resulting integral operator is performed and used to compute the measurement and null components of the objects. The results of the theory are confirmed with a Landweber algorithm that does not require a system matrix. (orig.)

Likelihood Approximation With Parallel Hierarchical Matrices For Large Spatial Datasets

KAUST Repository

Litvinenko, Alexander; Sun, Ying; Genton, Marc G.; Keyes, David E.

2017-01-01

The main goal of this article is to introduce the parallel hierarchical matrix library HLIBpro to the statistical community. We describe the HLIBCov package, which is an extension of the HLIBpro library for approximating large covariance matrices and maximizing likelihood functions. We show that an approximate Cholesky factorization of a dense matrix of size $2M\\times 2M$ can be computed on a modern multi-core desktop in few minutes. Further, HLIBCov is used for estimating the unknown parameters such as the covariance length, variance and smoothness parameter of a Matérn covariance function by maximizing the joint Gaussian log-likelihood function. The computational bottleneck here is expensive linear algebra arithmetics due to large and dense covariance matrices. Therefore covariance matrices are approximated in the hierarchical ($\\H$-) matrix format with computational cost $\\mathcal{O}(k^2n \\log^2 n/p)$ and storage $\\mathcal{O}(kn \\log n)$, where the rank $k$ is a small integer (typically $k<25$), $p$ the number of cores and $n$ the number of locations on a fairly general mesh. We demonstrate a synthetic example, where the true values of known parameters are known. For reproducibility we provide the C++ code, the documentation, and the synthetic data.

Likelihood Approximation With Parallel Hierarchical Matrices For Large Spatial Datasets

KAUST Repository

Litvinenko, Alexander

2017-11-01

The main goal of this article is to introduce the parallel hierarchical matrix library HLIBpro to the statistical community. We describe the HLIBCov package, which is an extension of the HLIBpro library for approximating large covariance matrices and maximizing likelihood functions. We show that an approximate Cholesky factorization of a dense matrix of size $2M\\\\times 2M$ can be computed on a modern multi-core desktop in few minutes. Further, HLIBCov is used for estimating the unknown parameters such as the covariance length, variance and smoothness parameter of a Matérn covariance function by maximizing the joint Gaussian log-likelihood function. The computational bottleneck here is expensive linear algebra arithmetics due to large and dense covariance matrices. Therefore covariance matrices are approximated in the hierarchical ($\\\\H$-) matrix format with computational cost $\\\\mathcal{O}(k^2n \\\\log^2 n/p)$ and storage $\\\\mathcal{O}(kn \\\\log n)$, where the rank $k$ is a small integer (typically $k<25$), $p$ the number of cores and $n$ the number of locations on a fairly general mesh. We demonstrate a synthetic example, where the true values of known parameters are known. For reproducibility we provide the C++ code, the documentation, and the synthetic data.

Large Scale Simulation of Hydrogen Dispersion by a Stabilized Balancing Domain Decomposition Method

Directory of Open Access Journals (Sweden)

Qing-He Yao

2014-01-01

Full Text Available The dispersion behaviour of leaking hydrogen in a partially open space is simulated by a balancing domain decomposition method in this work. An analogy of the Boussinesq approximation is employed to describe the connection between the flow field and the concentration field. The linear systems of Navier-Stokes equations and the convection diffusion equation are symmetrized by a pressure stabilized Lagrange-Galerkin method, and thus a balancing domain decomposition method is enabled to solve the interface problem of the domain decomposition system. Numerical results are validated by comparing with the experimental data and available numerical results. The dilution effect of ventilation is investigated, especially at the doors, where flow pattern is complicated and oscillations appear in the past research reported by other researchers. The transient behaviour of hydrogen and the process of accumulation in the partially open space are discussed, and more details are revealed by large scale computation.

Hierarchical matrices algorithms and analysis

CERN Document Server

Hackbusch, Wolfgang

2015-01-01

This self-contained monograph presents matrix algorithms and their analysis. The new technique enables not only the solution of linear systems but also the approximation of matrix functions, e.g., the matrix exponential. Other applications include the solution of matrix equations, e.g., the Lyapunov or Riccati equation. The required mathematical background can be found in the appendix. The numerical treatment of fully populated large-scale matrices is usually rather costly. However, the technique of hierarchical matrices makes it possible to store matrices and to perform matrix operations approximately with almost linear cost and a controllable degree of approximation error. For important classes of matrices, the computational cost increases only logarithmically with the approximation error. The operations provided include the matrix inversion and LU decomposition. Since large-scale linear algebra problems are standard in scientific computing, the subject of hierarchical matrices is of interest to scientists ...

Mechanistic and Kinetic Analysis of Na2SO4-Modified Laterite Decomposition by Thermogravimetry Coupled with Mass Spectrometry.

Directory of Open Access Journals (Sweden)

Song Yang

Full Text Available Nickel laterites cannot be effectively used in physical methods because of their poor crystallinity and fine grain size. Na2SO4 is the most efficient additive for grade enrichment and Ni recovery. However, how Na2SO4 affects the selective reduction of laterite ores has not been clearly investigated. This study investigated the decomposition of laterite with and without the addition of Na2SO4 in an argon atmosphere using thermogravimetry coupled with mass spectrometry (TG-MS. Approximately 25 mg of samples with 20 wt% Na2SO4 was pyrolyzed under a 100 ml/min Ar flow at a heating rate of 10°C/min from room temperature to 1300°C. The kinetic study was based on derivative thermogravimetric (DTG curves. The evolution of the pyrolysis gas composition was detected by mass spectrometry, and the decomposition products were analyzed by X-ray diffraction (XRD. The decomposition behavior of laterite with the addition of Na2SO4 was similar to that of pure laterite below 800°C during the first three stages. However, in the fourth stage, the dolomite decomposed at 897°C, which is approximately 200°C lower than the decomposition of pure laterite. In the last stage, the laterite decomposed and emitted SO2 in the presence of Na2SO4 with an activation energy of 91.37 kJ/mol. The decomposition of laterite with and without the addition of Na2SO4 can be described by one first-order reaction. Moreover, the use of Na2SO4 as the modification agent can reduce the activation energy of laterite decomposition; thus, the reaction rate can be accelerated, and the reaction temperature can be markedly reduced.

Three-pattern decomposition of global atmospheric circulation: part I—decomposition model and theorems

Science.gov (United States)

Hu, Shujuan; Chou, Jifan; Cheng, Jianbo

2018-04-01

In order to study the interactions between the atmospheric circulations at the middle-high and low latitudes from the global perspective, the authors proposed the mathematical definition of three-pattern circulations, i.e., horizontal, meridional and zonal circulations with which the actual atmospheric circulation is expanded. This novel decomposition method is proved to accurately describe the actual atmospheric circulation dynamics. The authors used the NCEP/NCAR reanalysis data to calculate the climate characteristics of those three-pattern circulations, and found that the decomposition model agreed with the observed results. Further dynamical analysis indicates that the decomposition model is more accurate to capture the major features of global three dimensional atmospheric motions, compared to the traditional definitions of Rossby wave, Hadley circulation and Walker circulation. The decomposition model for the first time realized the decomposition of global atmospheric circulation using three orthogonal circulations within the horizontal, meridional and zonal planes, offering new opportunities to study the large-scale interactions between the middle-high latitudes and low latitudes circulations.

Bessel collocation approach for approximate solutions of Hantavirus infection model

Directory of Open Access Journals (Sweden)

Suayip Yuzbasi

2017-11-01

Full Text Available In this study, a collocation method is introduced to find the approximate solutions of Hantavirus infection model which is a system of nonlinear ordinary differential equations. The method is based on the Bessel functions of the first kind, matrix operations and collocation points. This method converts Hantavirus infection model into a matrix equation in terms of the Bessel functions of first kind, matrix operations and collocation points. The matrix equation corresponds to a system of nonlinear equations with the unknown Bessel coefficients. The reliability and efficiency of the suggested scheme are demonstrated by numerical applications and all numerical calculations have been done by using a program written in Maple.

Approximating centrality in evolving graphs: toward sublinearity

Science.gov (United States)

Priest, Benjamin W.; Cybenko, George

2017-05-01

The identification of important nodes is a ubiquitous problem in the analysis of social networks. Centrality indices (such as degree centrality, closeness centrality, betweenness centrality, PageRank, and others) are used across many domains to accomplish this task. However, the computation of such indices is expensive on large graphs. Moreover, evolving graphs are becoming increasingly important in many applications. It is therefore desirable to develop on-line algorithms that can approximate centrality measures using memory sublinear in the size of the graph. We discuss the challenges facing the semi-streaming computation of many centrality indices. In particular, we apply recent advances in the streaming and sketching literature to provide a preliminary streaming approximation algorithm for degree centrality utilizing CountSketch and a multi-pass semi-streaming approximation algorithm for closeness centrality leveraging a spanner obtained through iteratively sketching the vertex-edge adjacency matrix. We also discuss possible ways forward for approximating betweenness centrality, as well as spectral measures of centrality. We provide a preliminary result using sketched low-rank approximations to approximate the output of the HITS algorithm.

CRYSTALLOGRAPHIC RELATIONS OF CEMENTITE–AUSTENITE–FERRITE IN THE DIFFUSIVE DECOMPOSITION OF AUSTENITE

Directory of Open Access Journals (Sweden)

BOLSHAKOV V. I.

2016-05-01

Full Text Available Summary. It was made a search for new and more accurate orientation relations between the crystal lattice in the pearlite and bainite austenite decomposition products. Methods. It were used the methods: transmission electron microscopy, the micro-, mathematical matrix and stereographic analysis. The purpose of the research is with theoretical, numerical and experimental methods to set up to a 0.2 degree angular orientation relations between the lattices of ferrite and cementite in the austenite decomposition products in the temperature range 400 ... 700С. Results. It was established a new, refined value for grids in the diffusion decay of γ → α + (α + θ. Practical significance. It was proposed a new oriented dependence and the corresponding double gnomonic projection with poles to planes α and θ phases, which can be used in patterns of crystallographic lattices relations studies at phase transitions, as well as the subsequent modeling of complex physical processes of structure formation in metals and binary systems.

The Speech multi features fusion perceptual hash algorithm based on tensor decomposition

Science.gov (United States)

Huang, Y. B.; Fan, M. H.; Zhang, Q. Y.

2018-03-01

With constant progress in modern speech communication technologies, the speech data is prone to be attacked by the noise or maliciously tampered. In order to make the speech perception hash algorithm has strong robustness and high efficiency, this paper put forward a speech perception hash algorithm based on the tensor decomposition and multi features is proposed. This algorithm analyses the speech perception feature acquires each speech component wavelet packet decomposition. LPCC, LSP and ISP feature of each speech component are extracted to constitute the speech feature tensor. Speech authentication is done by generating the hash values through feature matrix quantification which use mid-value. Experimental results showing that the proposed algorithm is robust for content to maintain operations compared with similar algorithms. It is able to resist the attack of the common background noise. Also, the algorithm is highly efficiency in terms of arithmetic, and is able to meet the real-time requirements of speech communication and complete the speech authentication quickly.

B-spline Collocation with Domain Decomposition Method

International Nuclear Information System (INIS)

Hidayat, M I P; Parman, S; Ariwahjoedi, B

2013-01-01

A global B-spline collocation method has been previously developed and successfully implemented by the present authors for solving elliptic partial differential equations in arbitrary complex domains. However, the global B-spline approximation, which is simply reduced to Bezier approximation of any degree p with C 0 continuity, has led to the use of B-spline basis of high order in order to achieve high accuracy. The need for B-spline bases of high order in the global method would be more prominent in domains of large dimension. For the increased collocation points, it may also lead to the ill-conditioning problem. In this study, overlapping domain decomposition of multiplicative Schwarz algorithm is combined with the global method. Our objective is two-fold that improving the accuracy with the combination technique, and also investigating influence of the combination technique to the employed B-spline basis orders with respect to the obtained accuracy. It was shown that the combination method produced higher accuracy with the B-spline basis of much lower order than that needed in implementation of the initial method. Hence, the approximation stability of the B-spline collocation method was also increased.

Matrix pentagons

Science.gov (United States)

Belitsky, A. V.

2017-10-01

The Operator Product Expansion for null polygonal Wilson loop in planar maximally supersymmetric Yang-Mills theory runs systematically in terms of multi-particle pentagon transitions which encode the physics of excitations propagating on the color flux tube ending on the sides of the four-dimensional contour. Their dynamics was unraveled in the past several years and culminated in a complete description of pentagons as an exact function of the 't Hooft coupling. In this paper we provide a solution for the last building block in this program, the SU(4) matrix structure arising from internal symmetry indices of scalars and fermions. This is achieved by a recursive solution of the Mirror and Watson equations obeyed by the so-called singlet pentagons and fixing the form of the twisted component in their tensor decomposition. The non-singlet, or charged, pentagons are deduced from these by a limiting procedure.

Matrix pentagons

Directory of Open Access Journals (Sweden)

A.V. Belitsky

2017-10-01

Full Text Available The Operator Product Expansion for null polygonal Wilson loop in planar maximally supersymmetric Yang–Mills theory runs systematically in terms of multi-particle pentagon transitions which encode the physics of excitations propagating on the color flux tube ending on the sides of the four-dimensional contour. Their dynamics was unraveled in the past several years and culminated in a complete description of pentagons as an exact function of the 't Hooft coupling. In this paper we provide a solution for the last building block in this program, the SU(4 matrix structure arising from internal symmetry indices of scalars and fermions. This is achieved by a recursive solution of the Mirror and Watson equations obeyed by the so-called singlet pentagons and fixing the form of the twisted component in their tensor decomposition. The non-singlet, or charged, pentagons are deduced from these by a limiting procedure.

Approximating the minimum cycle mean

Directory of Open Access Journals (Sweden)

Krishnendu Chatterjee

2013-07-01

Full Text Available We consider directed graphs where each edge is labeled with an integer weight and study the fundamental algorithmic question of computing the value of a cycle with minimum mean weight. Our contributions are twofold: (1 First we show that the algorithmic question is reducible in O(n^2 time to the problem of a logarithmic number of min-plus matrix multiplications of n-by-n matrices, where n is the number of vertices of the graph. (2 Second, when the weights are nonnegative, we present the first (1 + ε-approximation algorithm for the problem and the running time of our algorithm is ilde(O(n^ω log^3(nW/ε / ε, where O(n^ω is the time required for the classic n-by-n matrix multiplication and W is the maximum value of the weights.

SAM revisited: uniform semiclassical approximation with absorption

International Nuclear Information System (INIS)

Hussein, M.S.; Pato, M.P.

1986-01-01

The uniform semiclassical approximation is modified to take into account strong absorption. The resulting theory, very similar to the one developed by Frahn and Gross is used to discuss heavy-ion elastic scattering at intermediate energies. The theory permits a reasonably unambiguos separation of refractive and diffractive effects. The systems 12 C+ 12 C and 12 C+ 16 O, which seem to exhibit a remnant of a nuclear rainbow at E=20 Mev/N, are analysed with theory which is built directly on a model for the S-matrix. Simple relations between the fit S-matrix and the underlying complex potential are derived. (Author) [pt

Silver Nanoparticles and Graphitic Carbon Through Thermal Decomposition of a Silver/Acetylenedicarboxylic Salt

Directory of Open Access Journals (Sweden)

Komninou Philomela

2009-01-01

Full Text Available Abstract Spherically shaped silver nanoparticles embedded in a carbon matrix were synthesized by thermal decomposition of a Ag(I/acetylenedicarboxylic acid salt. The silver nanoparticles, which are formed either by pyrolysis at 300 °C in an autoclave or thermolysis in xylene suspension at reflux temperature, are acting catalytically for the formation of graphite layers. Both reactions proceed through in situ reduction of the silver cations and polymerization of the central acetylene triple bonds and the exact temperature of the reaction can be monitored through DTA analysis. Interestingly, the thermal decomposition of this silver salt in xylene partly leads to a minor fraction of quasicrystalline silver, as established by HR-TEM analysis. The graphitic layers covering the silver nanoparticles are clearly seen in HR-TEM images and, furthermore, established by the presence of sp2carbon at the Raman spectrum of both samples.

Approximation of reliability of direct genomic breeding values

Science.gov (United States)

Two methods to efficiently approximate theoretical genomic reliabilities are presented. The first method is based on the direct inverse of the left hand side (LHS) of mixed model equations. It uses the genomic relationship matrix for a small subset of individuals with the highest genomic relationshi...

Diagnosis of the Ill-condition of the RFM Based on Condition Index and Variance Decomposition Proportion (CIVDP)

International Nuclear Information System (INIS)

Qing, Zhou; Weili, Jiao; Tengfei, Long

2014-01-01

The Rational Function Model (RFM) is a new generalized sensor model. It does not need the physical parameters of sensors to achieve a high accuracy that is compatible to the rigorous sensor models. At present, the main method to solve RPCs is the Least Squares Estimation. But when coefficients has a large number or the distribution of the control points is not even, the classical least square method loses its superiority due to the ill-conditioning problem of design matrix. Condition Index and Variance Decomposition Proportion (CIVDP) is a reliable method for diagnosing the multicollinearity among the design matrix. It can not only detect the multicollinearity, but also can locate the parameters and show the corresponding columns in the design matrix. In this paper, the CIVDP method is used to diagnose the ill-condition problem of the RFM and to find the multicollinearity in the normal matrix

Diagnosis of the Ill-condition of the RFM Based on Condition Index and Variance Decomposition Proportion (CIVDP)

Science.gov (United States)

Qing, Zhou; Weili, Jiao; Tengfei, Long

2014-03-01

The Rational Function Model (RFM) is a new generalized sensor model. It does not need the physical parameters of sensors to achieve a high accuracy that is compatible to the rigorous sensor models. At present, the main method to solve RPCs is the Least Squares Estimation. But when coefficients has a large number or the distribution of the control points is not even, the classical least square method loses its superiority due to the ill-conditioning problem of design matrix. Condition Index and Variance Decomposition Proportion (CIVDP) is a reliable method for diagnosing the multicollinearity among the design matrix. It can not only detect the multicollinearity, but also can locate the parameters and show the corresponding columns in the design matrix. In this paper, the CIVDP method is used to diagnose the ill-condition problem of the RFM and to find the multicollinearity in the normal matrix.

Structured Matrix Completion with Applications to Genomic Data Integration.

Science.gov (United States)

Cai, Tianxi; Cai, T Tony; Zhang, Anru

2016-01-01

Matrix completion has attracted significant recent attention in many fields including statistics, applied mathematics and electrical engineering. Current literature on matrix completion focuses primarily on independent sampling models under which the individual observed entries are sampled independently. Motivated by applications in genomic data integration, we propose a new framework of structured matrix completion (SMC) to treat structured missingness by design. Specifically, our proposed method aims at efficient matrix recovery when a subset of the rows and columns of an approximately low-rank matrix are observed. We provide theoretical justification for the proposed SMC method and derive lower bound for the estimation errors, which together establish the optimal rate of recovery over certain classes of approximately low-rank matrices. Simulation studies show that the method performs well in finite sample under a variety of configurations. The method is applied to integrate several ovarian cancer genomic studies with different extent of genomic measurements, which enables us to construct more accurate prediction rules for ovarian cancer survival.

Global decomposition experiment shows soil animal impacts on decomposition are climate-dependent

Czech Academy of Sciences Publication Activity Database

Wall, D.H.; Bradford, M.A.; John, M.G.St.; Trofymow, J.A.; Behan-Pelletier, V.; Bignell, D.E.; Dangerfield, J.M.; Parton, W.J.; Rusek, Josef; Voigt, W.; Wolters, V.; Gardel, H.Z.; Ayuke, F. O.; Bashford, R.; Beljakova, O.I.; Bohlen, P.J.; Brauman, A.; Flemming, S.; Henschel, J.R.; Johnson, D.L.; Jones, T.H.; Kovářová, Marcela; Kranabetter, J.M.; Kutny, L.; Lin, K.-Ch.; Maryati, M.; Masse, D.; Pokarzhevskii, A.; Rahman, H.; Sabará, M.G.; Salamon, J.-A.; Swift, M.J.; Varela, A.; Vasconcelos, H.L.; White, D.; Zou, X.

2008-01-01

Roč. 14, č. 11 (2008), s. 2661-2677 ISSN 1354-1013 Institutional research plan: CEZ:AV0Z60660521; CEZ:AV0Z60050516 Keywords : climate decomposition index * decomposition * litter Subject RIV: EH - Ecology, Behaviour Impact factor: 5.876, year: 2008

Direct synthesis of II-VI compound nanocrystals in polymer matrix

International Nuclear Information System (INIS)

Antolini, F.; Di Luccio, T.; Laera, A.M.; Mirenghi, L.; Piscopiello, E.; Re, M.; Tapfer, L.

2007-01-01

The production of II-VI semiconductor compound - polymer matrix nanocomposites by a direct in-situ thermolysis process is described. Metal-thiolate precursor molecules embedded in a polymer matrix decompose by a thermal annealing and the nucleation of semiconductor nanocrystals occurs. It is shown that the nucleation of nanoparticles and the formation of the nanocomposite can be also achieved by laser beam irradiation; this opens the way towards a ''lithographic'' in-situ nanocomposite production process. A possible growth and nanocomposite formation mechanism, describing the structural and chemical transformation of the precursor molecules, their decomposition and the formation of the nanoparticles, is presented. (copyright 2007 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)

Sparse linear systems: Theory of decomposition, methods, technology, applications and implementation in Wolfram Mathematica

Energy Technology Data Exchange (ETDEWEB)

Pilipchuk, L. A., E-mail: pilipchik@bsu.by [Belarussian State University, 220030 Minsk, 4, Nezavisimosti avenue, Republic of Belarus (Belarus); Pilipchuk, A. S., E-mail: an.pilipchuk@gmail.com [The Natural Resources and Environmental Protestion Ministry of the Republic of Belarus, 220004 Minsk, 10 Kollektornaya Street, Republic of Belarus (Belarus)

2015-11-30

In this paper we propose the theory of decomposition, methods, technologies, applications and implementation in Wol-fram Mathematica for the constructing the solutions of the sparse linear systems. One of the applications is the Sensor Location Problem for the symmetric graph in the case when split ratios of some arc flows can be zeros. The objective of that application is to minimize the number of sensors that are assigned to the nodes. We obtain a sparse system of linear algebraic equations and research its matrix rank. Sparse systems of these types appear in generalized network flow programming problems in the form of restrictions and can be characterized as systems with a large sparse sub-matrix representing the embedded network structure.

Sparse linear systems: Theory of decomposition, methods, technology, applications and implementation in Wolfram Mathematica

International Nuclear Information System (INIS)

Pilipchuk, L. A.; Pilipchuk, A. S.

2015-01-01

In this paper we propose the theory of decomposition, methods, technologies, applications and implementation in Wol-fram Mathematica for the constructing the solutions of the sparse linear systems. One of the applications is the Sensor Location Problem for the symmetric graph in the case when split ratios of some arc flows can be zeros. The objective of that application is to minimize the number of sensors that are assigned to the nodes. We obtain a sparse system of linear algebraic equations and research its matrix rank. Sparse systems of these types appear in generalized network flow programming problems in the form of restrictions and can be characterized as systems with a large sparse sub-matrix representing the embedded network structure

Rigorous constraints on the matrix elements of the energy–momentum tensor

Directory of Open Access Journals (Sweden)

Peter Lowdon

2017-11-01

Full Text Available The structure of the matrix elements of the energy–momentum tensor play an important role in determining the properties of the form factors A(q2, B(q2 and C(q2 which appear in the Lorentz covariant decomposition of the matrix elements. In this paper we apply a rigorous frame-independent distributional-matching approach to the matrix elements of the Poincaré generators in order to derive constraints on these form factors as q→0. In contrast to the literature, we explicitly demonstrate that the vanishing of the anomalous gravitomagnetic moment B(0 and the condition A(0=1 are independent of one another, and that these constraints are not related to the specific properties or conservation of the individual Poincaré generators themselves, but are in fact a consequence of the physical on-shell requirement of the states in the matrix elements and the manner in which these states transform under Poincaré transformations.

Calculation of shielding thickness by combining the LTSN and Decomposition methods

International Nuclear Information System (INIS)

Borges, Volnei; Vilhena, Marco T. de

1997-01-01

A combination of the LTS N and Decomposition methods is reported to shielding thickness calculation. The angular flux is evaluated solving a transport problem in planar geometry considering the S N approximation, anisotropic scattering and one-group of energy. The Laplace transform is applied in the set of S N equations. The transformed angular flux is then obtained solving a transcendental equation and the angular flux is restored by the Heaviside expansion technique. The scalar flux is attained integrating the angular flux by Gaussian quadrature scheme. On the other hand, the scalar flux is linearly related to the dose rate through the mass and energy absorption coefficient. The shielding thickness is obtained solving a transcendental equation resulting from the application of the LTS N approach by the Decomposition methods. Numerical simulations are reported. (author). 6 refs., 3 tabs

Nanoscale decomposition of Nb-Ru-O

Science.gov (United States)

Music, Denis; Geyer, Richard W.; Chen, Yen-Ting

2016-11-01

A correlative theoretical and experimental methodology has been employed to explore the decomposition of amorphous Nb-Ru-O at elevated temperatures. Density functional theory based molecular dynamics simulations reveal that amorphous Nb-Ru-O is structurally modified within 10 ps at 800 K giving rise to an increase in the planar metal - oxygen and metal - metal population and hence formation of large clusters, which signifies atomic segregation. The driving force for this atomic segregation process is 0.5 eV/atom. This is validated by diffraction experiments and transmission electron microscopy of sputter-synthesized Nb-Ru-O thin films. Room temperature samples are amorphous, while at 800 K nanoscale rutile RuO2 grains, self-organized in an amorphous Nb-O matrix, are observed, which is consistent with our theoretical predictions. This amorphous/crystalline interplay may be of importance for next generation of thermoelectric devices.

Applying Novel Time-Frequency Moments Singular Value Decomposition Method and Artificial Neural Networks for Ballistocardiography

Directory of Open Access Journals (Sweden)

Koivistoinen Teemu

2007-01-01

Full Text Available As we know, singular value decomposition (SVD is designed for computing singular values (SVs of a matrix. Then, if it is used for finding SVs of an -by-1 or 1-by- array with elements representing samples of a signal, it will return only one singular value that is not enough to express the whole signal. To overcome this problem, we designed a new kind of the feature extraction method which we call ''time-frequency moments singular value decomposition (TFM-SVD.'' In this new method, we use statistical features of time series as well as frequency series (Fourier transform of the signal. This information is then extracted into a certain matrix with a fixed structure and the SVs of that matrix are sought. This transform can be used as a preprocessing stage in pattern clustering methods. The results in using it indicate that the performance of a combined system including this transform and classifiers is comparable with the performance of using other feature extraction methods such as wavelet transforms. To evaluate TFM-SVD, we applied this new method and artificial neural networks (ANNs for ballistocardiogram (BCG data clustering to look for probable heart disease of six test subjects. BCG from the test subjects was recorded using a chair-like ballistocardiograph, developed in our project. This kind of device combined with automated recording and analysis would be suitable for use in many places, such as home, office, and so forth. The results show that the method has high performance and it is almost insensitive to BCG waveform latency or nonlinear disturbance.

Applicability of point-dipoles approximation to all-dielectric metamaterials

DEFF Research Database (Denmark)

Kuznetsova, S. M.; Andryieuski, Andrei; Lavrinenko, Andrei

2015-01-01

All-dielectric metamaterials consisting of high-dielectric inclusions in a low-dielectric matrix are considered as a low-loss alternative to resonant metal-based metamaterials. In this paper we investigate the applicability of the point electric and magnetic dipoles approximation to dielectric meta......-atoms on the example of a dielectric ring metamaterial. Despite the large electrical size of high-dielectric meta-atoms, the dipole approximation allows for accurate prediction of the metamaterials properties for the rings with diameters up to approximate to 0.8 of the lattice constant. The results provide important...... guidelines for design and optimization of all-dielectric metamaterials....

Dictionary-Based Tensor Canonical Polyadic Decomposition

Science.gov (United States)

Cohen, Jeremy Emile; Gillis, Nicolas

2018-04-01

To ensure interpretability of extracted sources in tensor decomposition, we introduce in this paper a dictionary-based tensor canonical polyadic decomposition which enforces one factor to belong exactly to a known dictionary. A new formulation of sparse coding is proposed which enables high dimensional tensors dictionary-based canonical polyadic decomposition. The benefits of using a dictionary in tensor decomposition models are explored both in terms of parameter identifiability and estimation accuracy. Performances of the proposed algorithms are evaluated on the decomposition of simulated data and the unmixing of hyperspectral images.

Variational random phase approximation for the anharmonic oscillator

International Nuclear Information System (INIS)

Dukelsky, J.; Schuck, P.

1990-04-01

The recently derived Variational Random Phase Approximation is examined using the anharmonic oscillator model. Special attention is paid to the ground state RPA wave function and the convergence of the proposed truncation scheme to obtain the diagonal density matrix. Comparison with the standard Coupled Cluster method is made

A Novel Measurement Matrix Optimization Approach for Hyperspectral Unmixing

Directory of Open Access Journals (Sweden)

Su Xu

2017-01-01

Full Text Available Each pixel in the hyperspectral unmixing process is modeled as a linear combination of endmembers, which can be expressed in the form of linear combinations of a number of pure spectral signatures that are known in advance. However, the limitation of Gaussian random variables on its computational complexity or sparsity affects the efficiency and accuracy. This paper proposes a novel approach for the optimization of measurement matrix in compressive sensing (CS theory for hyperspectral unmixing. Firstly, a new Toeplitz-structured chaotic measurement matrix (TSCMM is formed by pseudo-random chaotic elements, which can be implemented by a simple hardware; secondly, rank revealing QR factorization with eigenvalue decomposition is presented to speed up the measurement time; finally, orthogonal gradient descent method for measurement matrix optimization is used to achieve optimal incoherence. Experimental results demonstrate that the proposed approach can lead to better CS reconstruction performance with low extra computational cost in hyperspectral unmixing.

Cellular decomposition in vikalloys

International Nuclear Information System (INIS)

Belyatskaya, I.S.; Vintajkin, E.Z.; Georgieva, I.Ya.; Golikov, V.A.; Udovenko, V.A.

1981-01-01

Austenite decomposition in Fe-Co-V and Fe-Co-V-Ni alloys at 475-600 deg C is investigated. The cellular decomposition in ternary alloys results in the formation of bcc (ordered) and fcc structures, and in quaternary alloys - bcc (ordered) and 12R structures. The cellular 12R structure results from the emergence of stacking faults in the fcc lattice with irregular spacing in four layers. The cellular decomposition results in a high-dispersion structure and magnetic properties approaching the level of well-known vikalloys [ru

Daily water level forecasting using wavelet decomposition and artificial intelligence techniques

Science.gov (United States)

Seo, Youngmin; Kim, Sungwon; Kisi, Ozgur; Singh, Vijay P.

2015-01-01

Reliable water level forecasting for reservoir inflow is essential for reservoir operation. The objective of this paper is to develop and apply two hybrid models for daily water level forecasting and investigate their accuracy. These two hybrid models are wavelet-based artificial neural network (WANN) and wavelet-based adaptive neuro-fuzzy inference system (WANFIS). Wavelet decomposition is employed to decompose an input time series into approximation and detail components. The decomposed time series are used as inputs to artificial neural networks (ANN) and adaptive neuro-fuzzy inference system (ANFIS) for WANN and WANFIS models, respectively. Based on statistical performance indexes, the WANN and WANFIS models are found to produce better efficiency than the ANN and ANFIS models. WANFIS7-sym10 yields the best performance among all other models. It is found that wavelet decomposition improves the accuracy of ANN and ANFIS. This study evaluates the accuracy of the WANN and WANFIS models for different mother wavelets, including Daubechies, Symmlet and Coiflet wavelets. It is found that the model performance is dependent on input sets and mother wavelets, and the wavelet decomposition using mother wavelet, db10, can further improve the efficiency of ANN and ANFIS models. Results obtained from this study indicate that the conjunction of wavelet decomposition and artificial intelligence models can be a useful tool for accurate forecasting daily water level and can yield better efficiency than the conventional forecasting models.

Subsystem density functional theory with meta-generalized gradient approximation exchange-correlation functionals.

Science.gov (United States)

Śmiga, Szymon; Fabiano, Eduardo; Laricchia, Savio; Constantin, Lucian A; Della Sala, Fabio

2015-04-21

We analyze the methodology and the performance of subsystem density functional theory (DFT) with meta-generalized gradient approximation (meta-GGA) exchange-correlation functionals for non-bonded molecular systems. Meta-GGA functionals depend on the Kohn-Sham kinetic energy density (KED), which is not known as an explicit functional of the density. Therefore, they cannot be directly applied in subsystem DFT calculations. We propose a Laplacian-level approximation to the KED which overcomes this limitation and provides a simple and accurate way to apply meta-GGA exchange-correlation functionals in subsystem DFT calculations. The so obtained density and energy errors, with respect to the corresponding supermolecular calculations, are comparable with conventional approaches, depending almost exclusively on the approximations in the non-additive kinetic embedding term. An embedding energy error decomposition explains the accuracy of our method.

Matrix Krylov subspace methods for image restoration

Directory of Open Access Journals (Sweden)

khalide jbilou

2015-09-01

Full Text Available In the present paper, we consider some matrix Krylov subspace methods for solving ill-posed linear matrix equations and in those problems coming from the restoration of blurred and noisy images. Applying the well known Tikhonov regularization procedure leads to a Sylvester matrix equation depending the Tikhonov regularized parameter. We apply the matrix versions of the well known Krylov subspace methods, namely the Least Squared (LSQR and the conjugate gradient (CG methods to get approximate solutions representing the restored images. Some numerical tests are presented to show the effectiveness of the proposed methods.

Thermal decomposition of anhydrous zinc and cadmium salicylates

International Nuclear Information System (INIS)

Kharitonov, Yu.Ya.; Tujebakhova, Z.K.

1984-01-01

On the basis of studying thermograms, thermogravigrams, IR absorption spectra, X-rayograms of anhydrous znc and cadmium salicylate complexes of the M(HSal) 2 composition, (where M=Zn, Cd; HSal is an anion of once deprotonated salicyclic acid H 2 Sal) and products of their thermal transformations, the processes are characterized of stage-by-stage thermal decomposition of these compounds under continuous heating in the air from room temperature to approximately 1000 deg C. It is shown that the Cd(HSal) 2 pyrolysis proceeds with the formation of CdSal at 170-250 deg C and CdO - at 320-460 deg C

Treatment of pauli exclusion operator in G-matrix calculations for hypernuclei

International Nuclear Information System (INIS)

Kuo, T.T.S.; Hao, Jifa

1995-01-01

We discuss a matrix-inversion method for treating the Pauli exclusion operator Q in the hyperon-nucleon G-matrix equation for hypernuclei such as Λ 16 O. A model space consisted of shell-model wave functions is employed. We discuss that it is preferable to employ a free-particle spectrum for the intermediate states of the G matrix. This leads to the difficulty that the G-matrix intermediate states are plane waves and on this representation the Pauli operator Q has a rather complicated structure. A matrix-inversion method for over-coming this difficulty is examined. To implement this method it is necessary to employ a so-called n 3Λ truncation approximation. Numerical calculations using the Juelich B tilde and A tilde potentials have been performed to study the accuracy of this approximation. (author)

Hierarchical matrix techniques for the solution of elliptic equations

KAUST Repository

Chá vez, Gustavo; Turkiyyah, George; Yokota, Rio; Keyes, David E.

2014-01-01

Hierarchical matrix approximations are a promising tool for approximating low-rank matrices given the compactness of their representation and the economy of the operations between them. Integral and differential operators have been the major

Microcausality, macrocausality and the physical region (micro)analytic S-matrix

International Nuclear Information System (INIS)

Iagolnitzer, D.

1980-01-01

Recent works on the physical region analytic structure of multiparticle collision amplitudes in relativistic quantum theory are presented. First, the structure that can be expected and which is the expression, in terms of general essential support or microanalyticity properties, of macrocausality and macrocausal factorization, is described. It is shown that, taken together, these properties are equivalent to decompositions of the S-matrix, in bounded parts of the physical region, in terms of generalized Feynman integrals. Derivations of this structure obtained recently for 3 → 3 processes below the four-particle threshold both in S-matrix theory (without recourse to the crucial ad hoc assumption of 'separation of singularities' in unitarity equations used previously) and in axiomatic field theory are then reviewed. It is finally explained how this structure applies in two-dimensional space-time and yields factorization of the multiparticle S-matrix itself for a class of models. (orig.)

Primal Decomposition-Based Method for Weighted Sum-Rate Maximization in Downlink OFDMA Systems

Directory of Open Access Journals (Sweden)

Weeraddana Chathuranga

2010-01-01

Full Text Available We consider the weighted sum-rate maximization problem in downlink Orthogonal Frequency Division Multiple Access (OFDMA systems. Motivated by the increasing popularity of OFDMA in future wireless technologies, a low complexity suboptimal resource allocation algorithm is obtained for joint optimization of multiuser subcarrier assignment and power allocation. The algorithm is based on an approximated primal decomposition-based method, which is inspired from exact primal decomposition techniques. The original nonconvex optimization problem is divided into two subproblems which can be solved independently. Numerical results are provided to compare the performance of the proposed algorithm to Lagrange relaxation based suboptimal methods as well as to optimal exhaustive search-based method. Despite its reduced computational complexity, the proposed algorithm provides close-to-optimal performance.

Colour decompositions of multi-quark one-loop QCD amplitudes

DEFF Research Database (Denmark)

Ita, Harald; Ozeren, Kemal

2012-01-01

We describe the decomposition of one-loop QCD amplitudes in terms of colour-ordered building blocks. We give new expressions for the coefficients of QCD colour structures in terms of ordered objects called primitive amplitudes, for processes with up to seven partons. These results are needed in c...... to the cross section for W+4-jet production at the Large Hadron Collider, and verify that it is very well approximated by keeping only the leading terms in an expansion around the formal limit of a large number of colours....

2016 MATRIX annals

CERN Document Server

Praeger, Cheryl; Tao, Terence

2018-01-01

MATRIX is Australia’s international, residential mathematical research institute. It facilitates new collaborations and mathematical advances through intensive residential research programs, each lasting 1-4 weeks. This book is a scientific record of the five programs held at MATRIX in its first year, 2016: Higher Structures in Geometry and Physics (Chapters 1-5 and 18-21); Winter of Disconnectedness (Chapter 6 and 22-26); Approximation and Optimisation (Chapters 7-8); Refining C*-Algebraic Invariants for Dynamics using KK-theory (Chapters 9-13); Interactions between Topological Recursion, Modularity, Quantum Invariants and Low-dimensional Topology (Chapters 14-17 and 27). The MATRIX Scientific Committee selected these programs based on their scientific excellence and the participation rate of high-profile international participants. Each program included ample unstructured time to encourage collaborative research; some of the longer programs also included an embedded conference or lecture series. The artic...

A comparison between decomposition rates of buried and surface remains in a temperate region of South Africa.

Science.gov (United States)

Marais-Werner, Anátulie; Myburgh, J; Becker, P J; Steyn, M

2018-01-01

Several studies have been conducted on decomposition patterns and rates of surface remains; however, much less are known about this process for buried remains. Understanding the process of decomposition in buried remains is extremely important and aids in criminal investigations, especially when attempting to estimate the post mortem interval (PMI). The aim of this study was to compare the rates of decomposition between buried and surface remains. For this purpose, 25 pigs (Sus scrofa; 45-80 kg) were buried and excavated at different post mortem intervals (7, 14, 33, 92, and 183 days). The observed total body scores were then compared to those of surface remains decomposing at the same location. Stages of decomposition were scored according to separate categories for different anatomical regions based on standardised methods. Variation in the degree of decomposition was considerable especially with the buried 7-day interval pigs that displayed different degrees of discolouration in the lower abdomen and trunk. At 14 and 33 days, buried pigs displayed features commonly associated with the early stages of decomposition, but with less variation. A state of advanced decomposition was reached where little change was observed in the next ±90-183 days after interment. Although the patterns of decomposition for buried and surface remains were very similar, the rates differed considerably. Based on the observations made in this study, guidelines for the estimation of PMI are proposed. This pertains to buried remains found at a depth of approximately 0.75 m in the Central Highveld of South Africa.

Domain decomposition methods for core calculations using the MINOS solver

International Nuclear Information System (INIS)

Guerin, P.; Baudron, A. M.; Lautard, J. J.

2007-01-01

Cell by cell homogenized transport calculations of an entire nuclear reactor core are currently too expensive for industrial applications, even if a simplified transport (SPn) approximation is used. In order to take advantage of parallel computers, we propose here two domain decomposition methods using the mixed dual finite element solver MINOS. The first one is a modal synthesis method on overlapping sub-domains: several Eigenmodes solutions of a local problem on each sub-domain are taken as basis functions used for the resolution of the global problem on the whole domain. The second one is an iterative method based on non-overlapping domain decomposition with Robin interface conditions. At each iteration, we solve the problem on each sub-domain with the interface conditions given by the solutions on the close sub-domains estimated at the previous iteration. For these two methods, we give numerical results which demonstrate their accuracy and their efficiency for the diffusion model on realistic 2D and 3D cores. (authors)

Pade approximants for the Saxon-Woods potential

International Nuclear Information System (INIS)

Niculescu, V.I.R.; Catana, D.

1995-01-01

In the present work central Saxon-Woods (SW) potential and a uniform sphere Coulomb potential for protons are replaced with a Pade approximants. In this way expressions of the matrix elements of this potential form can be evaluated by the theory of complex functions. The methods assures satisfactory precision in a shorter computational time. (M.I.C) 1 fig., 2 tabs., 5 refs

Approximating the Analytic Fourier Transform with the Discrete Fourier Transform

OpenAIRE

Axelrod, Jeremy

2015-01-01

The Fourier transform is approximated over a finite domain using a Riemann sum. This Riemann sum is then expressed in terms of the discrete Fourier transform, which allows the sum to be computed with a fast Fourier transform algorithm more rapidly than via a direct matrix multiplication. Advantages and limitations of using this method to approximate the Fourier transform are discussed, and prototypical MATLAB codes implementing the method are presented.

Optics of Water Microdroplets with Soot Inclusions: Exact Versus Approximate Results

Science.gov (United States)

Liu, Li; Mishchenko, Michael I.

2016-01-01

We use the recently generalized version of the multi-sphere superposition T-matrix method (STMM) to compute the scattering and absorption properties of microscopic water droplets contaminated by black carbon. The soot material is assumed to be randomly distributed throughout the droplet interior in the form of numerous small spherical inclusions. Our numerically-exact STMM results are compared with approximate ones obtained using the Maxwell-Garnett effective-medium approximation (MGA) and the Monte Carlo ray-tracing approximation (MCRTA). We show that the popular MGA can be used to calculate the droplet optical cross sections, single-scattering albedo, and asymmetry parameter provided that the soot inclusions are quasi-uniformly distributed throughout the droplet interior, but can fail in computations of the elements of the scattering matrix depending on the volume fraction of soot inclusions. The integral radiative characteristics computed with the MCRTA can deviate more significantly from their exact STMM counterparts, while accurate MCRTA computations of the phase function require droplet size parameters substantially exceeding 60.

Distance matrix-based approach to protein structure prediction.

Science.gov (United States)

Kloczkowski, Andrzej; Jernigan, Robert L; Wu, Zhijun; Song, Guang; Yang, Lei; Kolinski, Andrzej; Pokarowski, Piotr

2009-03-01

Much structural information is encoded in the internal distances; a distance matrix-based approach can be used to predict protein structure and dynamics, and for structural refinement. Our approach is based on the square distance matrix D = [r(ij)(2)] containing all square distances between residues in proteins. This distance matrix contains more information than the contact matrix C, that has elements of either 0 or 1 depending on whether the distance r (ij) is greater or less than a cutoff value r (cutoff). We have performed spectral decomposition of the distance matrices D = sigma lambda(k)V(k)V(kT), in terms of eigenvalues lambda kappa and the corresponding eigenvectors v kappa and found that it contains at most five nonzero terms. A dominant eigenvector is proportional to r (2)--the square distance of points from the center of mass, with the next three being the principal components of the system of points. By predicting r (2) from the sequence we can approximate a distance matrix of a protein with an expected RMSD value of about 7.3 A, and by combining it with the prediction of the first principal component we can improve this approximation to 4.0 A. We can also explain the role of hydrophobic interactions for the protein structure, because r is highly correlated with the hydrophobic profile of the sequence. Moreover, r is highly correlated with several sequence profiles which are useful in protein structure prediction, such as contact number, the residue-wise contact order (RWCO) or mean square fluctuations (i.e. crystallographic temperature factors). We have also shown that the next three components are related to spatial directionality of the secondary structure elements, and they may be also predicted from the sequence, improving overall structure prediction. We have also shown that the large number of available HIV-1 protease structures provides a remarkable sampling of conformations, which can be viewed as direct structural information about the

Multiresolution signal decomposition schemes

NARCIS (Netherlands)

J. Goutsias (John); H.J.A.M. Heijmans (Henk)

1998-01-01

textabstract[PNA-R9810] Interest in multiresolution techniques for signal processing and analysis is increasing steadily. An important instance of such a technique is the so-called pyramid decomposition scheme. This report proposes a general axiomatic pyramid decomposition scheme for signal analysis

Symmetric Tensor Decomposition

DEFF Research Database (Denmark)

Brachat, Jerome; Comon, Pierre; Mourrain, Bernard

2010-01-01

We present an algorithm for decomposing a symmetric tensor, of dimension n and order d, as a sum of rank-1 symmetric tensors, extending the algorithm of Sylvester devised in 1886 for binary forms. We recall the correspondence between the decomposition of a homogeneous polynomial in n variables...... of polynomial equations of small degree in non-generic cases. We propose a new algorithm for symmetric tensor decomposition, based on this characterization and on linear algebra computations with Hankel matrices. The impact of this contribution is two-fold. First it permits an efficient computation...... of the decomposition of any tensor of sub-generic rank, as opposed to widely used iterative algorithms with unproved global convergence (e.g. Alternate Least Squares or gradient descents). Second, it gives tools for understanding uniqueness conditions and for detecting the rank....

A higher-order generalized singular value decomposition for comparison of global mRNA expression from multiple organisms.

Directory of Open Access Journals (Sweden)

Sri Priya Ponnapalli

Full Text Available The number of high-dimensional datasets recording multiple aspects of a single phenomenon is increasing in many areas of science, accompanied by a need for mathematical frameworks that can compare multiple large-scale matrices with different row dimensions. The only such framework to date, the generalized singular value decomposition (GSVD, is limited to two matrices. We mathematically define a higher-order GSVD (HO GSVD for N≥2 matrices D(i∈R(m(i × n, each with full column rank. Each matrix is exactly factored as D(i=U(iΣ(iV(T, where V, identical in all factorizations, is obtained from the eigensystem SV=VΛ of the arithmetic mean S of all pairwise quotients A(iA(j(-1 of the matrices A(i=D(i(TD(i, i≠j. We prove that this decomposition extends to higher orders almost all of the mathematical properties of the GSVD. The matrix S is nondefective with V and Λ real. Its eigenvalues satisfy λ(k≥1. Equality holds if and only if the corresponding eigenvector v(k is a right basis vector of equal significance in all matrices D(i and D(j, that is σ(i,k/σ(j,k=1 for all i and j, and the corresponding left basis vector u(i,k is orthogonal to all other vectors in U(i for all i. The eigenvalues λ(k=1, therefore, define the "common HO GSVD subspace." We illustrate the HO GSVD with a comparison of genome-scale cell-cycle mRNA expression from S. pombe, S. cerevisiae and human. Unlike existing algorithms, a mapping among the genes of these disparate organisms is not required. We find that the approximately common HO GSVD subspace represents the cell-cycle mRNA expression oscillations, which are similar among the datasets. Simultaneous reconstruction in the common subspace, therefore, removes the experimental artifacts, which are dissimilar, from the datasets. In the simultaneous sequence-independent classification of the genes of the three organisms in this common subspace, genes of highly conserved sequences but significantly different cell

Thermal decomposition of beryllium perchlorate tetrahydrate

International Nuclear Information System (INIS)

Berezkina, L.G.; Borisova, S.I.; Tamm, N.S.; Novoselova, A.V.

1975-01-01

Thermal decomposition of Be(ClO 4 ) 2 x4H 2 O was studied by the differential flow technique in the helium stream. The kinetics was followed by an exchange reaction of the perchloric acid appearing by the decomposition with potassium carbonate. The rate of CO 2 liberation in this process was recorded by a heat conductivity detector. The exchange reaction yielding CO 2 is quantitative, it is not the limiting one and it does not distort the kinetics of the process of perchlorate decomposition. The solid products of decomposition were studied by infrared and NMR spectroscopy, roentgenography, thermography and chemical analysis. A mechanism suggested for the decomposition involves intermediate formation of hydroxyperchlorate: Be(ClO 4 ) 2 x4H 2 O → Be(OH)ClO 4 +HClO 4 +3H 2 O; Be(OH)ClO 4 → BeO+HClO 4 . Decomposition is accompained by melting of the sample. The mechanism of decomposition is hydrolytic. At room temperature the hydroxyperchlorate is a thick syrup-like compound crystallizing after long storing

SAM revisited: absorptive uniform semiclassical approximation and application to heavy-ion elastic scattering

International Nuclear Information System (INIS)

Pato, M.P.; Hussein, M.S.

1989-06-01

The Uniform Semiclassical Approximation is modified to take into account absorption. Symbol calculus and pseudodifferential operators techniques are employed for the purpose. The resulting theory, very similar to the one developed by Frahn and Gross permits the decomposition of the near-side and far-side amplitudes into diffractive and refractive components. Application to several heavy-ion systems at intermediate energies is made. (author) [pt

Optimization of MIMO Systems Capacity Using Large Random Matrix Methods

Directory of Open Access Journals (Sweden)

Philippe Loubaton

2012-11-01

Full Text Available This paper provides a comprehensive introduction of large random matrix methods for input covariance matrix optimization of mutual information of MIMO systems. It is first recalled informally how large system approximations of mutual information can be derived. Then, the optimization of the approximations is discussed, and important methodological points that are not necessarily covered by the existing literature are addressed, including the strict concavity of the approximation, the structure of the argument of its maximum, the accuracy of the large system approach with regard to the number of antennas, or the justification of iterative water-filling optimization algorithms. While the existing papers have developed methods adapted to a specific model, this contribution tries to provide a unified view of the large system approximation approach.

Orbital-Optimized MP3 and MP2.5 with Density-Fitting and Cholesky Decomposition Approximations.

Science.gov (United States)

Bozkaya, Uğur

2016-03-08

Efficient implementations of the orbital-optimized MP3 and MP2.5 methods with the density-fitting (DF-OMP3 and DF-OMP2.5) and Cholesky decomposition (CD-OMP3 and CD-OMP2.5) approaches are presented. The DF/CD-OMP3 and DF/CD-OMP2.5 methods are applied to a set of alkanes to compare the computational cost with the conventional orbital-optimized MP3 (OMP3) [Bozkaya J. Chem. Phys. 2011, 135, 224103] and the orbital-optimized MP2.5 (OMP2.5) [Bozkaya and Sherrill J. Chem. Phys. 2014, 141, 204105]. Our results demonstrate that the DF-OMP3 and DF-OMP2.5 methods provide considerably lower computational costs than OMP3 and OMP2.5. Further application results show that the orbital-optimized methods are very helpful for the study of open-shell noncovalent interactions, aromatic bond dissociation energies, and hydrogen transfer reactions. We conclude that the DF-OMP3 and DF-OMP2.5 methods are very promising for molecular systems with challenging electronic structures.

Exact complexity: The spectral decomposition of intrinsic computation

International Nuclear Information System (INIS)

Crutchfield, James P.; Ellison, Christopher J.; Riechers, Paul M.

2016-01-01

We give exact formulae for a wide family of complexity measures that capture the organization of hidden nonlinear processes. The spectral decomposition of operator-valued functions leads to closed-form expressions involving the full eigenvalue spectrum of the mixed-state presentation of a process's ϵ-machine causal-state dynamic. Measures include correlation functions, power spectra, past-future mutual information, transient and synchronization informations, and many others. As a result, a direct and complete analysis of intrinsic computation is now available for the temporal organization of finitary hidden Markov models and nonlinear dynamical systems with generating partitions and for the spatial organization in one-dimensional systems, including spin systems, cellular automata, and complex materials via chaotic crystallography. - Highlights: • We provide exact, closed-form expressions for a hidden stationary process' intrinsic computation. • These include information measures such as the excess entropy, transient information, and synchronization information and the entropy-rate finite-length approximations. • The method uses an epsilon-machine's mixed-state presentation. • The spectral decomposition of the mixed-state presentation relies on the recent development of meromorphic functional calculus for nondiagonalizable operators.

Spectral analysis of the SN approximations in a slab with quadratically anisotropic scattering

International Nuclear Information System (INIS)

Ourique, L.E.; Pazos, R.P.; Vilhena, M.T.; Barros, R.C.

2003-01-01

The spectral analysis of the S N approximations to the one-dimensional transport equation began with 3 and 4, following the studies of 1 and 2 about the discrete eigenvalues of the transport equation. In previous work about the influence of a parameter in the solutions of S N approximations, it was considered the total macroscopic cross section as a control parameter and was analyzed how its variation changes the nature of the eigenvalues of the S N transport matrix, in problems with linearly anisotropic scattering. It was showed the existence of bifurcations points, i.e., there exist some values of control parameters for which the S N transport matrix has only real eigenvalues while for other values the S N relation between the eigenvalues of S N transport matrix and control parameter, supposing quadratically anisotropic scattering. Numerical results are reported. (author)

Domain decomposition and multilevel integration for fermions

International Nuclear Information System (INIS)

Ce, Marco; Giusti, Leonardo; Schaefer, Stefan

2016-01-01

The numerical computation of many hadronic correlation functions is exceedingly difficult due to the exponentially decreasing signal-to-noise ratio with the distance between source and sink. Multilevel integration methods, using independent updates of separate regions in space-time, are known to be able to solve such problems but have so far been available only for pure gauge theory. We present first steps into the direction of making such integration schemes amenable to theories with fermions, by factorizing a given observable via an approximated domain decomposition of the quark propagator. This allows for multilevel integration of the (large) factorized contribution to the observable, while its (small) correction can be computed in the standard way.

Simulating propagation of decomposed elastic waves using low-rank approximate mixed-domain integral operators for heterogeneous transversely isotropic media

KAUST Repository

Cheng, Jiubing; Wu, Zedong; Alkhalifah, Tariq Ali

2014-01-01

decomposition in anisotropic media is costly as the operators involved is dependent on the velocity, and thus not stationary. In this abstract, we propose an efficient approach to directly extrapolate the decomposed elastic waves using lowrank approximate mixed

Feature fusion using kernel joint approximate diagonalization of eigen-matrices for rolling bearing fault identification

Science.gov (United States)

Liu, Yongbin; He, Bing; Liu, Fang; Lu, Siliang; Zhao, Yilei

2016-12-01

Fault pattern identification is a crucial step for the intelligent fault diagnosis of real-time health conditions in monitoring a mechanical system. However, many challenges exist in extracting the effective feature from vibration signals for fault recognition. A new feature fusion method is proposed in this study to extract new features using kernel joint approximate diagonalization of eigen-matrices (KJADE). In the method, the input space that is composed of original features is mapped into a high-dimensional feature space by nonlinear mapping. Then, the new features can be estimated through the eigen-decomposition of the fourth-order cumulative kernel matrix obtained from the feature space. Therefore, the proposed method could be used to reduce data redundancy because it extracts the inherent pattern structure of different fault classes as it is nonlinear by nature. The integration evaluation factor of between-class and within-class scatters (SS) is employed to depict the clustering performance quantitatively, and the new feature subset extracted by the proposed method is fed into a multi-class support vector machine for fault pattern identification. Finally, the effectiveness of the proposed method is verified by experimental vibration signals with different bearing fault types and severities. Results of several cases show that the KJADE algorithm is efficient in feature fusion for bearing fault identification.

An Improved Direction Finding Algorithm Based on Toeplitz Approximation

Directory of Open Access Journals (Sweden)

Qing Wang

2013-01-01

Full Text Available In this paper, a novel direction of arrival (DOA estimation algorithm called the Toeplitz fourth order cumulants multiple signal classification method (TFOC-MUSIC algorithm is proposed through combining a fast MUSIC-like algorithm termed the modified fourth order cumulants MUSIC (MFOC-MUSIC algorithm and Toeplitz approximation. In the proposed algorithm, the redundant information in the cumulants is removed. Besides, the computational complexity is reduced due to the decreased dimension of the fourth-order cumulants matrix, which is equal to the number of the virtual array elements. That is, the effective array aperture of a physical array remains unchanged. However, due to finite sampling snapshots, there exists an estimation error of the reduced-rank FOC matrix and thus the capacity of DOA estimation degrades. In order to improve the estimation performance, Toeplitz approximation is introduced to recover the Toeplitz structure of the reduced-dimension FOC matrix just like the ideal one which has the Toeplitz structure possessing optimal estimated results. The theoretical formulas of the proposed algorithm are derived, and the simulations results are presented. From the simulations, in comparison with the MFOC-MUSIC algorithm, it is concluded that the TFOC-MUSIC algorithm yields an excellent performance in both spatially-white noise and in spatially-color noise environments.

Linear models in matrix form a hands-on approach for the behavioral sciences

CERN Document Server

Brown, Jonathon D

2014-01-01

This textbook is an approachable introduction to statistical analysis using matrix algebra. Prior knowledge of matrix algebra is not necessary. Advanced topics are easy to follow through analyses that were performed on an open-source spreadsheet using a few built-in functions. These topics include ordinary linear regression, as well as maximum likelihood estimation, matrix decompositions, nonparametric smoothers and penalized cubic splines. Each data set (1) contains a limited number of observations to encourage readers to do the calculations themselves, and (2) tells a coherent story based on statistical significance and confidence intervals. In this way, students will learn how the numbers were generated and how they can be used to make cogent arguments about everyday matters. This textbook is designed for use in upper level undergraduate courses or first year graduate courses. The first chapter introduces students to linear equations, then covers matrix algebra, focusing on three essential operations: sum ...

Some nonlinear space decomposition algorithms

Energy Technology Data Exchange (ETDEWEB)

Tai, Xue-Cheng; Espedal, M. [Univ. of Bergen (Norway)

1996-12-31

Convergence of a space decomposition method is proved for a general convex programming problem. The space decomposition refers to methods that decompose a space into sums of subspaces, which could be a domain decomposition or a multigrid method for partial differential equations. Two algorithms are proposed. Both can be used for linear as well as nonlinear elliptic problems and they reduce to the standard additive and multiplicative Schwarz methods for linear elliptic problems. Two {open_quotes}hybrid{close_quotes} algorithms are also presented. They converge faster than the additive one and have better parallelism than the multiplicative method. Numerical tests with a two level domain decomposition for linear, nonlinear and interface elliptic problems are presented for the proposed algorithms.

Sequential function approximation on arbitrarily distributed point sets

Science.gov (United States)

Wu, Kailiang; Xiu, Dongbin

2018-02-01

We present a randomized iterative method for approximating unknown function sequentially on arbitrary point set. The method is based on a recently developed sequential approximation (SA) method, which approximates a target function using one data point at each step and avoids matrix operations. The focus of this paper is on data sets with highly irregular distribution of the points. We present a nearest neighbor replacement (NNR) algorithm, which allows one to sample the irregular data sets in a near optimal manner. We provide mathematical justification and error estimates for the NNR algorithm. Extensive numerical examples are also presented to demonstrate that the NNR algorithm can deliver satisfactory convergence for the SA method on data sets with high irregularity in their point distributions.

Domain decomposition parallel computing for transient two-phase flow of nuclear reactors

Energy Technology Data Exchange (ETDEWEB)

Lee, Jae Ryong; Yoon, Han Young [KAERI, Daejeon (Korea, Republic of); Choi, Hyoung Gwon [Seoul National University, Seoul (Korea, Republic of)

2016-05-15

KAERI (Korea Atomic Energy Research Institute) has been developing a multi-dimensional two-phase flow code named CUPID for multi-physics and multi-scale thermal hydraulics analysis of Light water reactors (LWRs). The CUPID code has been validated against a set of conceptual problems and experimental data. In this work, the CUPID code has been parallelized based on the domain decomposition method with Message passing interface (MPI) library. For domain decomposition, the CUPID code provides both manual and automatic methods with METIS library. For the effective memory management, the Compressed sparse row (CSR) format is adopted, which is one of the methods to represent the sparse asymmetric matrix. CSR format saves only non-zero value and its position (row and column). By performing the verification for the fundamental problem set, the parallelization of the CUPID has been successfully confirmed. Since the scalability of a parallel simulation is generally known to be better for fine mesh system, three different scales of mesh system are considered: 40000 meshes for coarse mesh system, 320000 meshes for mid-size mesh system, and 2560000 meshes for fine mesh system. In the given geometry, both single- and two-phase calculations were conducted. In addition, two types of preconditioners for a matrix solver were compared: Diagonal and incomplete LU preconditioner. In terms of enhancement of the parallel performance, the OpenMP and MPI hybrid parallel computing for a pressure solver was examined. It is revealed that the scalability of hybrid calculation was enhanced for the multi-core parallel computation.

Relaxation approximations to second-order traffic flow models by high-resolution schemes

International Nuclear Information System (INIS)

Nikolos, I.K.; Delis, A.I.; Papageorgiou, M.

2015-01-01

A relaxation-type approximation of second-order non-equilibrium traffic models, written in conservation or balance law form, is considered. Using the relaxation approximation, the nonlinear equations are transformed to a semi-linear diagonilizable problem with linear characteristic variables and stiff source terms with the attractive feature that neither Riemann solvers nor characteristic decompositions are in need. In particular, it is only necessary to provide the flux and source term functions and an estimate of the characteristic speeds. To discretize the resulting relaxation system, high-resolution reconstructions in space are considered. Emphasis is given on a fifth-order WENO scheme and its performance. The computations reported demonstrate the simplicity and versatility of relaxation schemes as numerical solvers

Approximate inverse preconditioning of iterative methods for nonsymmetric linear systems

Energy Technology Data Exchange (ETDEWEB)

Benzi, M. [Universita di Bologna (Italy); Tuma, M. [Inst. of Computer Sciences, Prague (Czech Republic)

1996-12-31

A method for computing an incomplete factorization of the inverse of a nonsymmetric matrix A is presented. The resulting factorized sparse approximate inverse is used as a preconditioner in the iterative solution of Ax = b by Krylov subspace methods.

Applying Novel Time-Frequency Moments Singular Value Decomposition Method and Artificial Neural Networks for Ballistocardiography

Directory of Open Access Journals (Sweden)

Alpo Värri

2007-01-01

Full Text Available As we know, singular value decomposition (SVD is designed for computing singular values (SVs of a matrix. Then, if it is used for finding SVs of an m-by-1 or 1-by-m array with elements representing samples of a signal, it will return only one singular value that is not enough to express the whole signal. To overcome this problem, we designed a new kind of the feature extraction method which we call ‘‘time-frequency moments singular value decomposition (TFM-SVD.’’ In this new method, we use statistical features of time series as well as frequency series (Fourier transform of the signal. This information is then extracted into a certain matrix with a fixed structure and the SVs of that matrix are sought. This transform can be used as a preprocessing stage in pattern clustering methods. The results in using it indicate that the performance of a combined system including this transform and classifiers is comparable with the performance of using other feature extraction methods such as wavelet transforms. To evaluate TFM-SVD, we applied this new method and artificial neural networks (ANNs for ballistocardiogram (BCG data clustering to look for probable heart disease of six test subjects. BCG from the test subjects was recorded using a chair-like ballistocardiograph, developed in our project. This kind of device combined with automated recording and analysis would be suitable for use in many places, such as home, office, and so forth. The results show that the method has high performance and it is almost insensitive to BCG waveform latency or nonlinear disturbance.

Applying Novel Time-Frequency Moments Singular Value Decomposition Method and Artificial Neural Networks for Ballistocardiography

Science.gov (United States)

Akhbardeh, Alireza; Junnila, Sakari; Koivuluoma, Mikko; Koivistoinen, Teemu; Värri, Alpo

2006-12-01

As we know, singular value decomposition (SVD) is designed for computing singular values (SVs) of a matrix. Then, if it is used for finding SVs of an [InlineEquation not available: see fulltext.]-by-1 or 1-by- [InlineEquation not available: see fulltext.] array with elements representing samples of a signal, it will return only one singular value that is not enough to express the whole signal. To overcome this problem, we designed a new kind of the feature extraction method which we call ''time-frequency moments singular value decomposition (TFM-SVD).'' In this new method, we use statistical features of time series as well as frequency series (Fourier transform of the signal). This information is then extracted into a certain matrix with a fixed structure and the SVs of that matrix are sought. This transform can be used as a preprocessing stage in pattern clustering methods. The results in using it indicate that the performance of a combined system including this transform and classifiers is comparable with the performance of using other feature extraction methods such as wavelet transforms. To evaluate TFM-SVD, we applied this new method and artificial neural networks (ANNs) for ballistocardiogram (BCG) data clustering to look for probable heart disease of six test subjects. BCG from the test subjects was recorded using a chair-like ballistocardiograph, developed in our project. This kind of device combined with automated recording and analysis would be suitable for use in many places, such as home, office, and so forth. The results show that the method has high performance and it is almost insensitive to BCG waveform latency or nonlinear disturbance.

Analytical approaches for the approximate solution of a nonlinear fractional ordinary differential equation

International Nuclear Information System (INIS)

Basak, K C; Ray, P C; Bera, R K

2009-01-01

The aim of the present analysis is to apply the Adomian decomposition method and He's variational method for the approximate analytical solution of a nonlinear ordinary fractional differential equation. The solutions obtained by the above two methods have been numerically evaluated and presented in the form of tables and also compared with the exact solution. It was found that the results obtained by the above two methods are in excellent agreement with the exact solution. Finally, a surface plot of the approximate solutions of the fractional differential equation by the above two methods is drawn for 0≤t≤2 and 1<α≤2.

Decomposition of Multi-player Games

Science.gov (United States)

Zhao, Dengji; Schiffel, Stephan; Thielscher, Michael

Research in General Game Playing aims at building systems that learn to play unknown games without human intervention. We contribute to this endeavour by generalising the established technique of decomposition from AI Planning to multi-player games. To this end, we present a method for the automatic decomposition of previously unknown games into independent subgames, and we show how a general game player can exploit a successful decomposition for game tree search.

Approximate Inference for Wireless Communications

DEFF Research Database (Denmark)

Hansen, Morten

This thesis investigates signal processing techniques for wireless communication receivers. The aim is to improve the performance or reduce the computationally complexity of these, where the primary focus area is cellular systems such as Global System for Mobile communications (GSM) (and extensions...... to the optimal one, which usually requires an unacceptable high complexity. Some of the treated approximate methods are based on QL-factorization of the channel matrix. In the work presented in this thesis it is proven how the QL-factorization of frequency-selective channels asymptotically provides the minimum...

A combination between Laplace transformation technique and numerical approximations to the Fokker-Planck equation solutions

International Nuclear Information System (INIS)

Monticelli, Cintia O.; Wortmann, Sergio; Segatto, Cynthia F.

2005-01-01

In this work is obtained a hybrid solution to the Fokker-Planck equation with energy dependency, very used in ion implantation problems. The main idea relies on the application of Laplace transform in the energy variable, and finite-difference in the spatial variable and in the angular variable. This procedure leads to a symbolic matrix problem for the transformed energy. To solve this system, is needed to do the Laplace inverse of the (sI+A) matrix, where s is a complex parameter, I is the identity matrix and A is a square matrix that was proceeded from the finite-difference in the spatial variable and in the angular variable. The matrix A is not defective, then is taken decomposition of A in a sum of two others matrices, where one is defective. It leads a iterative inversion method, similar the source fixed method combined with the diagonalization method, then is obtained the values to the angular flux. Hereafter we can to determine the energy deposited into the electronic system and in the nuclear system of the target. To comprove the results obtained, the simulation of implantation of B into Si at energies ranging from 1 KeV to 50 MeV was carried out and compared with the results by software SRIM2003. (author)

Detection of Water Contamination Events Using Fluorescence Spectroscopy and Alternating Trilinear Decomposition Algorithm

Directory of Open Access Journals (Sweden)

Jie Yu

2017-01-01

Full Text Available The method based on conventional index and UV-vision has been widely applied in the field of water quality abnormality detection. This paper presents a qualitative analysis approach to detect the water contamination events with unknown pollutants. Fluorescence spectra were used as water quality monitoring tools, and the detection method of unknown contaminants in water based on alternating trilinear decomposition (ATLD is proposed to analyze the excitation and emission spectra of the samples. The Delaunay triangulation interpolation method was used to make the pretreatment of three-dimensional fluorescence spectra data, in order to estimate the effect of Rayleigh and Raman scattering; ATLD model was applied to establish the model of normal water sample, and the residual matrix was obtained by subtracting the measured matrix from the model matrix; the residual sum of squares obtained from the residual matrix and threshold was used to make qualitative discrimination of test samples and distinguish drinking water samples and organic pollutant samples. The results of the study indicate that ATLD modeling with three-dimensional fluorescence spectra can provide a tool for detecting unknown organic pollutants in water qualitatively. The method based on fluorescence spectra can be complementary to the method based on conventional index and UV-vision.

An intrinsic robust rank-one-approximation approach for currencyportfolio optimization

Directory of Open Access Journals (Sweden)

Hongxuan Huang

2018-03-01

Full Text Available A currency portfolio is a special kind of wealth whose value fluctuates with foreignexchange rates over time, which possesses 3Vs (volume, variety and velocity properties of big datain the currency market. In this paper, an intrinsic robust rank one approximation (ROA approachis proposed to maximize the value of currency portfolios over time. The main results of the paperinclude four parts: Firstly, under the assumptions about the currency market, the currency portfoliooptimization problem is formulated as the basic model, in which there are two types of variablesdescribing currency amounts in portfolios and the amount of each currency exchanged into another,respectively. Secondly, the rank one approximation problem and its variants are also formulated toapproximate a foreign exchange rate matrix, whose performance is measured by the Frobenius normor the 2-norm of a residual matrix. The intrinsic robustness of the rank one approximation is provedtogether with summarizing properties of the basic ROA problem and designing a modified powermethod to search for the virtual exchange rates hidden in a foreign exchange rate matrix. Thirdly,a technique for decision variables reduction is presented to attack the currency portfolio optimization.The reduced formulation is referred to as the ROA model, which keeps only variables describingcurrency amounts in portfolios. The optimal solution to the ROA model also induces a feasible solutionto the basic model of the currency portfolio problem by integrating forex operations from the ROAmodel with practical forex rates. Finally, numerical examples are presented to verify the feasibility ande ciency of the intrinsic robust rank one approximation approach. They also indicate that there existsan objective measure for evaluating and optimizing currency portfolios over time, which is related tothe virtual standard currency and independent of any real currency selected specially for measurement.

Coherent mode decomposition using mixed Wigner functions of Hermite-Gaussian beams.

Science.gov (United States)

Tanaka, Takashi

2017-04-15

A new method of coherent mode decomposition (CMD) is proposed that is based on a Wigner-function representation of Hermite-Gaussian beams. In contrast to the well-known method using the cross spectral density (CSD), it directly determines the mode functions and their weights without solving the eigenvalue problem. This facilitates the CMD of partially coherent light whose Wigner functions (and thus CSDs) are not separable, in which case the conventional CMD requires solving an eigenvalue problem with a large matrix and thus is numerically formidable. An example is shown regarding the CMD of synchrotron radiation, one of the most important applications of the proposed method.

Retrieving the correlation matrix from a truncated PCA solution : The inverse principal component problem

NARCIS (Netherlands)

ten Berge, Jos M.F.; Kiers, Henk A.L.

When r Principal Components are available for k variables, the correlation matrix is approximated in the least squares sense by the loading matrix times its transpose. The approximation is generally not perfect unless r = k. In the present paper it is shown that, when r is at or above the Ledermann

Decomposition of diesel oil by various microorganisms

Energy Technology Data Exchange (ETDEWEB)

Suess, A; Netzsch-Lehner, A

1969-01-01

Previous experiments demonstrated the decomposition of diesel oil in different soils. In this experiment the decomposition of /sup 14/C-n-Hexadecane labelled diesel oil by special microorganisms was studied. The results were as follows: (1) In the experimental soils the microorganisms Mycoccus ruber, Mycobacterium luteum and Trichoderma hamatum are responsible for the diesel oil decomposition. (2) By adding microorganisms to the soil an increase of the decomposition rate was found only in the beginning of the experiments. (3) Maximum decomposition of diesel oil was reached 2-3 weeks after incubation.

Tomographic reconstruction of tokamak plasma light emission using wavelet-vaguelette decomposition

Science.gov (United States)

Schneider, Kai; Nguyen van Yen, Romain; Fedorczak, Nicolas; Brochard, Frederic; Bonhomme, Gerard; Farge, Marie; Monier-Garbet, Pascale

2012-10-01

Images acquired by cameras installed in tokamaks are difficult to interpret because the three-dimensional structure of the plasma is flattened in a non-trivial way. Nevertheless, taking advantage of the slow variation of the fluctuations along magnetic field lines, the optical transformation may be approximated by a generalized Abel transform, for which we proposed in Nguyen van yen et al., Nucl. Fus., 52 (2012) 013005, an inversion technique based on the wavelet-vaguelette decomposition. After validation of the new method using an academic test case and numerical data obtained with the Tokam 2D code, we present an application to an experimental movie obtained in the tokamak Tore Supra. A comparison with a classical regularization technique for ill-posed inverse problems, the singular value decomposition, allows us to assess the efficiency. The superiority of the wavelet-vaguelette technique is reflected in preserving local features, such as blobs and fronts, in the denoised emissivity map.

Accelerating Matrix-Vector Multiplication on Hierarchical Matrices Using Graphical Processing Units

KAUST Repository

Boukaram, W.

2015-03-25

Large dense matrices arise from the discretization of many physical phenomena in computational sciences. In statistics very large dense covariance matrices are used for describing random fields and processes. One can, for instance, describe distribution of dust particles in the atmosphere, concentration of mineral resources in the earth\\'s crust or uncertain permeability coefficient in reservoir modeling. When the problem size grows, storing and computing with the full dense matrix becomes prohibitively expensive both in terms of computational complexity and physical memory requirements. Fortunately, these matrices can often be approximated by a class of data sparse matrices called hierarchical matrices (H-matrices) where various sub-blocks of the matrix are approximated by low rank matrices. These matrices can be stored in memory that grows linearly with the problem size. In addition, arithmetic operations on these H-matrices, such as matrix-vector multiplication, can be completed in almost linear time. Originally the H-matrix technique was developed for the approximation of stiffness matrices coming from partial differential and integral equations. Parallelizing these arithmetic operations on the GPU has been the focus of this work and we will present work done on the matrix vector operation on the GPU using the KSPARSE library.

Batched QR and SVD Algorithms on GPUs with Applications in Hierarchical Matrix Compression

KAUST Repository

Halim Boukaram, Wajih

2017-09-14

We present high performance implementations of the QR and the singular value decomposition of a batch of small matrices hosted on the GPU with applications in the compression of hierarchical matrices. The one-sided Jacobi algorithm is used for its simplicity and inherent parallelism as a building block for the SVD of low rank blocks using randomized methods. We implement multiple kernels based on the level of the GPU memory hierarchy in which the matrices can reside and show substantial speedups against streamed cuSOLVER SVDs. The resulting batched routine is a key component of hierarchical matrix compression, opening up opportunities to perform H-matrix arithmetic efficiently on GPUs.

Batched QR and SVD Algorithms on GPUs with Applications in Hierarchical Matrix Compression

KAUST Repository

Halim Boukaram, Wajih; Turkiyyah, George; Ltaief, Hatem; Keyes, David E.

2017-01-01

We present high performance implementations of the QR and the singular value decomposition of a batch of small matrices hosted on the GPU with applications in the compression of hierarchical matrices. The one-sided Jacobi algorithm is used for its simplicity and inherent parallelism as a building block for the SVD of low rank blocks using randomized methods. We implement multiple kernels based on the level of the GPU memory hierarchy in which the matrices can reside and show substantial speedups against streamed cuSOLVER SVDs. The resulting batched routine is a key component of hierarchical matrix compression, opening up opportunities to perform H-matrix arithmetic efficiently on GPUs.

Decomposition of tetrachloroethylene by ionizing radiation

International Nuclear Information System (INIS)

Hakoda, T.; Hirota, K.; Hashimoto, S.

1998-01-01

Decomposition of tetrachloroethylene and other chloroethenes by ionizing radiation were examined to get information on treatment of industrial off-gas. Model gases, airs containing chloroethenes, were confined in batch reactors and irradiated with electron beam and gamma ray. The G-values of decomposition were larger in the order of tetrachloro- > trichloro- > trans-dichloro- > cis-dichloro- > monochloroethylene in electron beam irradiation and tetrachloro-, trichloro-, trans-dichloro- > cis-dichloro- > monochloroethylene in gamma ray irradiation. For tetrachloro-, trichloro- and trans-dichloroethylene, G-values of decomposition in EB irradiation increased with increase of chlorine atom in a molecule, while those in gamma ray irradiation were almost kept constant. The G-value of decomposition for tetrachloroethylene in EB irradiation was the largest of those for all chloroethenes. In order to examine the effect of the initial concentration on G-value of decomposition, airs containing 300 to 1,800 ppm of tetrachloroethylene were irradiated with electron beam and gamma ray. The G-values of decomposition in both irradiation increased with the initial concentration. Those in electron beam irradiation were two times larger than those in gamma ray irradiation

Pade approximants in field theory: pion and kaon systems

International Nuclear Information System (INIS)

Zinn-Justin, J.

1969-01-01

We construct the Pade approximants of the S-matrix, starting from the perturbation series, in the case of two body pion and kaon systems. We have three parameters. The seven lowest lying two body resonances (ρ, K * (890), φ, K * (1420), f 0 , f', A 2 ) are obtained within a few per cent of their actual masses. The Regge trajectories are rising, the intercepts of the ρ and f 0 agree well with the experimental values. In the appendices we give some properties and applications of the Pade approximants. (author) [fr

Analytic approximation to the largest eigenvalue distribution of a white Wishart matrix

CSIR Research Space (South Africa)

Vlok, JD

2012-08-14

Full Text Available offers largely simplified computation and provides statistics such as the mean value and region of support of the largest eigenvalue distribution. Numeric results from the literature are compared with the approximation and Monte Carlo simulation results...

Role of Reactive Mn Complexes in a Litter Decomposition Model System

Science.gov (United States)

Nico, P. S.; Keiluweit, M.; Bougoure, J.; Kleber, M.; Summering, J. A.; Maynard, J. J.; Johnson, M.; Pett-Ridge, J.

2012-12-01

The search for controls on litter decomposition rates and pathways has yet to return definitive characteristics that are both statistically robust and can be understood as part of a mechanistic or numerical model. Herein we focus on Mn, an element present in all litter that is likely an active chemical agent of decomposition. Berg and co-workers (2010) found a strong correlation between Mn concentration in litter and the magnitude of litter degradation in boreal forests, suggesting that litter decomposition proceeds more efficiently in the presence of Mn. Although there is much circumstantial evidence for the potential role of Mn in lignin decomposition, few reports exist on mechanistic details of this process. For the current work, we are guided by the hypothesis that the dependence of decomposition on Mn is due to Mn (III)-oxalate complexes act as a 'pretreatment' for structurally intact ligno-carbohydrate complexes (LCC) in fresh plant cell walls (e.g. in litter, root and wood). Manganese (III)-ligand complexes such as Mn (III)-oxalate are known to be potent oxidizers of many different organic and inorganic compounds. In the litter system, the unique property of these complexes may be that they are much smaller than exo-enzymes and therefore more easily able to penetrate LCC complexes in plant cell walls. By acting as 'diffusible oxidizers' and reacting with the organic matrix of the cell wall, these compounds can increase the porosity of fresh litter thereby facilitating access of more specific lignin- and cellulose decomposing enzymes. This possibility was investigated by reacting cell walls of single Zinnia elegans tracheary elements with Mn (III)-oxalate complexes in a continuous flow reactor. The uniformity of these individual plant cells allowed us to examine Mn (III)-induced changes in cell wall chemistry and ultrastructure on the micro-scale using fluorescence and electron microscopy as well as IR and X-ray spectromicroscopy. This presentation will

Complete horizontal skin cell resurfacing and delayed vertical cell infiltration into porcine reconstructive tissue matrix compared to bovine collagen matrix and human dermis.

Science.gov (United States)

Mirastschijski, Ursula; Kerzel, Corinna; Schnabel, Reinhild; Strauss, Sarah; Breuing, Karl-Heinz

2013-10-01

Xenogenous dermal matrices are used for hernia repair and breast reconstruction. Full-thickness skin replacement is needed after burn or degloving injuries with exposure of tendons or bones. The authors used a human skin organ culture model to study whether porcine reconstructive tissue matrix (Strattice) is effective as a dermal tissue replacement. Skin cells or split-thickness skin grafts were seeded onto human deepidermized dermis, Strattice, and Matriderm. Cellular resurfacing and matrix infiltration were monitored by live fluorescence imaging, histology, and electron microscopy. Proliferation, apoptosis, cell differentiation, and adhesion were analyzed by immunohistochemistry. Epithelial resurfacing and vertical proliferation were reduced and delayed with both bioartificial matrices compared with deepidermized dermis; however, no differences in apoptosis, cell differentiation, or basement membrane formation were found. Vertical penetration was greatest on Matriderm, whereas no matrix infiltration was found on Strattice in the first 12 days. Uncompromised horizontal resurfacing was greatest with Strattice but was absent with Matriderm. Strattice showed no stimulatory effect on cellular inflammation. Matrix texture and surface properties governed cellular performance on tissues. Although dense dermal compaction delayed vertical cellular ingrowth for Strattice, it allowed uncompromised horizontal resurfacing. Dense dermal compaction may slow matrix decomposition and result in prolonged biomechanical stability of the graft. Reconstructive surgeons should choose the adequate matrix substitute depending on biomechanical requirements at the recipient site. Strattice may be suitable as a dermal replacement at recipient sites with high mechanical load requirements.

Decomposition of Sodium Tetraphenylborate

International Nuclear Information System (INIS)

Barnes, M.J.

1998-01-01

The chemical decomposition of aqueous alkaline solutions of sodium tetraphenylborate (NaTPB) has been investigated. The focus of the investigation is on the determination of additives and/or variables which influence NaTBP decomposition. This document describes work aimed at providing better understanding into the relationship of copper (II), solution temperature, and solution pH to NaTPB stability

Thermal decomposition of γ-irradiated lead nitrate

International Nuclear Information System (INIS)

Nair, S.M.K.; Kumar, T.S.S.

1990-01-01

The thermal decomposition of unirradiated and γ-irradiated lead nitrate was studied by the gas evolution method. The decomposition proceeds through initial gas evolution, a short induction period, an acceleratory stage and a decay stage. The acceleratory and decay stages follow the Avrami-Erofeev equation. Irradiation enhances the decomposition but does not affect the shape of the decomposition curve. (author) 10 refs.; 7 figs.; 2 tabs

Thermal Decomposition Mechanisms of Lignin Model Compounds: From Phenol to Vanillin

Science.gov (United States)

Scheer, Adam Michael

Lignin is a complex, aromatic polymer abundant in cellulosic biomass (trees, switchgrass etc.). Thermochemical breakdown of lignin for liquid fuel production results in undesirable polycyclic aromatic hydrocarbons that lead to tar and soot byproducts. The fundamental chemistry governing these processes is not well understood. We have studied the unimolecular thermal decomposition mechanisms of aromatic lignin model compounds using a miniature SiC tubular reactor. Products are detected and characterized using time-of-flight mass spectrometry with both single photon (118.2 nm; 10.487 eV) and 1 + 1 resonance-enhanced multiphoton ionization (REMPI) as well as matrix isolation infrared spectroscopy. Gas exiting the heated reactor (300 K--1600 K) is subject to a free expansion after a residence time of approximately 100 micros. The expansion into vacuum rapidly cools the gas mixture and allows the detection of radicals and other highly reactive intermediates. By understanding the unimolecular fragmentation patterns of phenol (C6H5OH), anisole (C6H 5OCH3) and benzaldehyde (C6H5CHO), the more complicated thermocracking processes of the catechols (HO-C 6H4-OH), methoxyphenols (HO-C6H4-OCH 3) and hydroxybenzaldehydes (HO-C6H4-CHO) can be interpreted. These studies have resulted in a predictive model that allows the interpretation of vanillin, a complex phenolic ether containing methoxy, hydroxy and aldehyde functional groups. This model will serve as a guide for the pyrolyses of larger systems including lignin monomers such as coniferyl alcohol. The pyrolysis mechanisms of the dimethoxybenzenes (H3C-C 6H4-OCH3) and syringol, a hydroxydimethoxybenzene have also been studied. These results will aid in the understanding of the thermal fragmentation of sinapyl alcohol, the most complex lignin monomer. In addition to the model compound work, pyrolyisis of biomass has been studied via the pulsed laser ablation of poplar wood. With the REMPI scheme, aromatic lignin decomposition

Freeman-Durden Decomposition with Oriented Dihedral Scattering

Directory of Open Access Journals (Sweden)

Yan Jian

2014-10-01

Full Text Available In this paper, when the azimuth direction of polarimetric Synthetic Aperature Radars (SAR differs from the planting direction of crops, the double bounce of the incident electromagnetic waves from the terrain surface to the growing crops is investigated and compared with the normal double bounce. Oriented dihedral scattering model is developed to explain the investigated double bounce and is introduced into the Freeman-Durden decomposition. The decomposition algorithm corresponding to the improved decomposition is then proposed. The airborne polarimetric SAR data for agricultural land covering two flight tracks are chosen to validate the algorithm; the decomposition results show that for agricultural vegetated land, the improved Freeman-Durden decomposition has the advantage of increasing the decomposition coherency among the polarimetric SAR data along the different flight tracks.

Generalized Benders’ Decomposition for topology optimization problems

DEFF Research Database (Denmark)

Munoz Queupumil, Eduardo Javier; Stolpe, Mathias

2011-01-01

) problems with discrete design variables to global optimality. We present the theoretical aspects of the method, including a proof of finite convergence and conditions for obtaining global optimal solutions. The method is also linked to, and compared with, an Outer-Approximation approach and a mixed 0......–1 semi definite programming formulation of the considered problem. Several ways to accelerate the method are suggested and an implementation is described. Finally, a set of truss topology optimization problems are numerically solved to global optimality.......This article considers the non-linear mixed 0–1 optimization problems that appear in topology optimization of load carrying structures. The main objective is to present a Generalized Benders’ Decomposition (GBD) method for solving single and multiple load minimum compliance (maximum stiffness...

On the rational approximation of the bidimensional potentials

International Nuclear Information System (INIS)

Niculescu, V.I.R; Catana, D.

1997-01-01

In the present letter we introduced a symmetrical bidimensional potential with Woods-Saxon tail. The potential approximation has permitted to replace in the matrix the evaluation of double integration by a product of two integrals. That implied a complexity reduction in the Hamiltonian eigenvalue and eigenvector evaluation. Also, the harmonic bidimensional basis simplifies significantly the evaluation of electric multipole operators. (authors)

Danburite decomposition by hydrochloric acid

International Nuclear Information System (INIS)

Mamatov, E.D.; Ashurov, N.A.; Mirsaidov, U.

2011-01-01

Present article is devoted to decomposition of danburite of Ak-Arkhar Deposit of Tajikistan by hydrochloric acid. The interaction of boron containing ores of Ak-Arkhar Deposit of Tajikistan with mineral acids, including hydrochloric acid was studied. The optimal conditions of extraction of valuable components from danburite composition were determined. The chemical composition of danburite of Ak-Arkhar Deposit was determined as well. The kinetics of decomposition of calcined danburite by hydrochloric acid was studied. The apparent activation energy of the process of danburite decomposition by hydrochloric acid was calculated.

Pade approximants and the calculation of effective interactions

International Nuclear Information System (INIS)

Schucan, T.H.

1975-01-01

It is known that the series expansion of the effective interaction in nuclei diverges in practical applications due to the occurrence of low lying collective states. An approximation scheme which can be used to overcome the difficulties connected with this divergence is reviewed and it is shown that a continued fraction expansion can be used to calculate the eigenstate that has the larger overlap with the model space. An extension of this method is obtained by using Pade approximants (P.A.) which are then applied to the effective interaction, and to related matrices and matrix elements. Mathematical properties of the P.A. are discussed in light of these applications. 7 figures

LMDI decomposition approach: A guide for implementation

International Nuclear Information System (INIS)

Ang, B.W.

2015-01-01

Since it was first used by researchers to analyze industrial electricity consumption in the early 1980s, index decomposition analysis (IDA) has been widely adopted in energy and emission studies. Lately its use as the analytical component of accounting frameworks for tracking economy-wide energy efficiency trends has attracted considerable attention and interest among policy makers. The last comprehensive literature review of IDA was reported in 2000 which is some years back. After giving an update and presenting the key trends in the last 15 years, this study focuses on the implementation issues of the logarithmic mean Divisia index (LMDI) decomposition methods in view of their dominance in IDA in recent years. Eight LMDI models are presented and their origin, decomposition formulae, and strengths and weaknesses are summarized. Guidelines on the choice among these models are provided to assist users in implementation. - Highlights: • Guidelines for implementing LMDI decomposition approach are provided. • Eight LMDI decomposition models are summarized and compared. • The development of the LMDI decomposition approach is presented. • The latest developments of index decomposition analysis are briefly reviewed.

Photogeneration of heptacene in a polymer matrix.

Science.gov (United States)

Mondal, Rajib; Shah, Bipin K; Neckers, Douglas C

2006-08-02

Heptacene (1) was generated by the photodecarbonylation of 7,16-dihydro-7,16-ethanoheptacene-19,20-dione (2) in a polymer matrix using a UV-LED lamp (395 +/- 25 nm). Compound 1 showed a long wavelength absorption band extending from 600 to 825 nm (lambdamax approximately 760 nm) and was found to be stable up to 4 h in the polymer matrix. However, irradiation of a solution of 2 in toluene produced only oxygen adducts.

COMPOSITION OF FOWLPOX VIRUS AND INCLUSION MATRIX.

Science.gov (United States)

RANDALL, C C; GAFFORD, L G; DARLINGTON, R W; HYDE, J

1964-04-01

Randall, Charles C. (University of Mississippi School of Medicine, Jackson), Lanelle G. Gafford, Robert W. Darlington, and James M. Hyde. Composition of fowlpox virus and inclusion matrix. J. Bacteriol. 87:939-944. 1964.-Inclusion bodies of fowlpox virus infection are especially favorable starting material for the isolation of virus and inclusion matrix. Electron micrographs of viral particles and matrix indicated a high degree of purification. Density-gradient centrifugation of virus in cesium chloride and potassium tartrate was unsatisfactory because of inactivation, and clumping or disintegration. Chemical analyses of virus and matrix revealed significant amounts of lipid, protein, and deoxyribonucleic acid, but no ribonucleic acid or carbohydrate. Approximately 47% of the weight of the virus and 83% of the matrix were extractable in chloroform-methanol. The lipid partitions of the petroleum ether extracts were similar, except that the phospholipid content of the matrix was 2.2 times that of the virus. Viral particles were sensitive to diethyl ether and chloroform.

A parabolic velocity-decomposition method for wind turbines

Science.gov (United States)

Mittal, Anshul; Briley, W. Roger; Sreenivas, Kidambi; Taylor, Lafayette K.

2017-02-01

An economical parabolized Navier-Stokes approximation for steady incompressible flow is combined with a compatible wind turbine model to simulate wind turbine flows, both upstream of the turbine and in downstream wake regions. The inviscid parabolizing approximation is based on a Helmholtz decomposition of the secondary velocity vector and physical order-of-magnitude estimates, rather than an axial pressure gradient approximation. The wind turbine is modeled by distributed source-term forces incorporating time-averaged aerodynamic forces generated by a blade-element momentum turbine model. A solution algorithm is given whose dependent variables are streamwise velocity, streamwise vorticity, and pressure, with secondary velocity determined by two-dimensional scalar and vector potentials. In addition to laminar and turbulent boundary-layer test cases, solutions for a streamwise vortex-convection test problem are assessed by mesh refinement and comparison with Navier-Stokes solutions using the same grid. Computed results for a single turbine and a three-turbine array are presented using the NREL offshore 5-MW baseline wind turbine. These are also compared with an unsteady Reynolds-averaged Navier-Stokes solution computed with full rotor resolution. On balance, the agreement in turbine wake predictions for these test cases is very encouraging given the substantial differences in physical modeling fidelity and computer resources required.

Statistical weighted A-summability with application to Korovkin’s type approximation theorem

Directory of Open Access Journals (Sweden)

Syed Abdul Mohiuddine

2016-03-01

Full Text Available Abstract We introduce the notion of statistical weighted A-summability of a sequence and establish its relation with weighted A-statistical convergence. We also define weighted regular matrix and obtain necessary and sufficient conditions for the matrix A to be weighted regular. As an application, we prove the Korovkin type approximation theorem through statistical weighted A-summability and using the BBH operator to construct an illustrative example in support of our result.

FDG decomposition products

International Nuclear Information System (INIS)

Macasek, F.; Buriova, E.

2004-01-01

In this presentation authors present the results of analysis of decomposition products of [ 18 ]fluorodexyglucose. It is concluded that the coupling of liquid chromatography - mass spectrometry with electrospray ionisation is a suitable tool for quantitative analysis of FDG radiopharmaceutical, i.e. assay of basic components (FDG, glucose), impurities (Kryptofix) and decomposition products (gluconic and glucuronic acids etc.); 2-[ 18 F]fluoro-deoxyglucose (FDG) is sufficiently stable and resistant towards autoradiolysis; the content of radiochemical impurities (2-[ 18 F]fluoro-gluconic and 2-[ 18 F]fluoro-glucuronic acids in expired FDG did not exceed 1%

Validity of the broken-pair approximation for N = 50, even-A nuclei

International Nuclear Information System (INIS)

Haq, S.; Gambhir, Y.K.

1977-01-01

The validity of the broken-pair approximation as an approximation to the seniority shell model is investigated. The results of the broken-pair approximation and the seniority shell model, obtained by employing identical input information (single-particle levels and their energies, effective two-body matrix elements, 88 Sr inert core) for N = 50, even-A nuclei are compared. A close agreement obtained between the calculated broken-pair approximation and the seniority shell model energies for 90 Zr, 92 Mo, 94 Ru, and 96 Pd nuclei and large (95--100 %) overlaps between the broken-pair approximation and the senority shell model wave functions for 92 Mo, demonstrates the validity of the broken-pair approximation in this region and in general its usefulness as a good approximation to the seniority shell model

The physical-optics approximation and its application to light backscattering by hexagonal ice crystals

International Nuclear Information System (INIS)

Borovoi, A.; Konoshonkin, A.; Kustova, N.

2014-01-01

The physical-optics approximation in the problem of light scattering by large particles is so defined that it includes the classical physical optics concerning the problem of light penetration through a large aperture in an opaque screen. In the second part of the paper, the problem of light backscattering by quasi-horizontally oriented atmospheric ice crystals is considered where conformity between the physical-optics and geometric-optics approximations is discussed. The differential scattering cross section as well as the polarization elements of the Mueller matrix for quasi-horizontally oriented hexagonal ice plates has been calculated in the physical-optics approximation for the case of vertically pointing lidars. - Highlights: • The physical-optics Mueller matrix is a smoothed geometric-optics counterpart. • Backscatter by partially oriented hexagonal ice plates has been calculated. • Depolarization ratio for partially oriented hexagonal ice plates is negligible

Matrix regularization of 4-manifolds

OpenAIRE

Trzetrzelewski, M.

2012-01-01

We consider products of two 2-manifolds such as S^2 x S^2, embedded in Euclidean space and show that the corresponding 4-volume preserving diffeomorphism algebra can be approximated by a tensor product SU(N)xSU(N) i.e. functions on a manifold are approximated by the Kronecker product of two SU(N) matrices. A regularization of the 4-sphere is also performed by constructing N^2 x N^2 matrix representations of the 4-algebra (and as a byproduct of the 3-algebra which makes the regularization of S...

Management intensity alters decomposition via biological pathways

Science.gov (United States)

Wickings, Kyle; Grandy, A. Stuart; Reed, Sasha; Cleveland, Cory

2011-01-01

Current conceptual models predict that changes in plant litter chemistry during decomposition are primarily regulated by both initial litter chemistry and the stage-or extent-of mass loss. Far less is known about how variations in decomposer community structure (e.g., resulting from different ecosystem management types) could influence litter chemistry during decomposition. Given the recent agricultural intensification occurring globally and the importance of litter chemistry in regulating soil organic matter storage, our objectives were to determine the potential effects of agricultural management on plant litter chemistry and decomposition rates, and to investigate possible links between ecosystem management, litter chemistry and decomposition, and decomposer community composition and activity. We measured decomposition rates, changes in litter chemistry, extracellular enzyme activity, microarthropod communities, and bacterial versus fungal relative abundance in replicated conventional-till, no-till, and old field agricultural sites for both corn and grass litter. After one growing season, litter decomposition under conventional-till was 20% greater than in old field communities. However, decomposition rates in no-till were not significantly different from those in old field or conventional-till sites. After decomposition, grass residue in both conventional- and no-till systems was enriched in total polysaccharides relative to initial litter, while grass litter decomposed in old fields was enriched in nitrogen-bearing compounds and lipids. These differences corresponded with differences in decomposer communities, which also exhibited strong responses to both litter and management type. Overall, our results indicate that agricultural intensification can increase litter decomposition rates, alter decomposer communities, and influence litter chemistry in ways that could have important and long-term effects on soil organic matter dynamics. We suggest that future

The Bloch Approximation in Periodically Perforated Media

International Nuclear Information System (INIS)

Conca, C.; Gomez, D.; Lobo, M.; Perez, E.

2005-01-01

We consider a periodically heterogeneous and perforated medium filling an open domain Ω of R N . Assuming that the size of the periodicity of the structure and of the holes is O(ε),we study the asymptotic behavior, as ε → 0, of the solution of an elliptic boundary value problem with strongly oscillating coefficients posed in Ω ε (Ω ε being Ω minus the holes) with a Neumann condition on the boundary of the holes. We use Bloch wave decomposition to introduce an approximation of the solution in the energy norm which can be computed from the homogenized solution and the first Bloch eigenfunction. We first consider the case where Ωis R N and then localize the problem for abounded domain Ω, considering a homogeneous Dirichlet condition on the boundary of Ω

a Unified Matrix Polynomial Approach to Modal Identification

Science.gov (United States)

Allemang, R. J.; Brown, D. L.

1998-04-01

One important current focus of modal identification is a reformulation of modal parameter estimation algorithms into a single, consistent mathematical formulation with a corresponding set of definitions and unifying concepts. Particularly, a matrix polynomial approach is used to unify the presentation with respect to current algorithms such as the least-squares complex exponential (LSCE), the polyreference time domain (PTD), Ibrahim time domain (ITD), eigensystem realization algorithm (ERA), rational fraction polynomial (RFP), polyreference frequency domain (PFD) and the complex mode indication function (CMIF) methods. Using this unified matrix polynomial approach (UMPA) allows a discussion of the similarities and differences of the commonly used methods. the use of least squares (LS), total least squares (TLS), double least squares (DLS) and singular value decomposition (SVD) methods is discussed in order to take advantage of redundant measurement data. Eigenvalue and SVD transformation methods are utilized to reduce the effective size of the resulting eigenvalue-eigenvector problem as well.

Characterization of the proteins comprising the integral matrix of Strongylocentrotus purpuratus embryonic spicules

Science.gov (United States)

Killian, C. E.; Wilt, F. H.

1996-01-01

In the present study, we enumerate and characterize the proteins that comprise the integral spicule matrix of the Strongylocentrotus purpuratus embryo. Two-dimensional gel electrophoresis of [35S]methionine radiolabeled spicule matrix proteins reveals that there are 12 strongly radiolabeled spicule matrix proteins and approximately three dozen less strongly radiolabeled spicule matrix proteins. The majority of the proteins have acidic isoelectric points; however, there are several spicule matrix proteins that have more alkaline isoelectric points. Western blotting analysis indicates that SM50 is the spicule matrix protein with the most alkaline isoelectric point. In addition, two distinct SM30 proteins are identified in embryonic spicules, and they have apparent molecular masses of approximately 43 and 46 kDa. Comparisons between embryonic spicule matrix proteins and adult spine integral matrix proteins suggest that the embryonic 43-kDa SM30 protein is an embryonic isoform of SM30. An adult 49-kDa spine matrix protein is also identified as a possible adult isoform of SM30. Analysis of the SM30 amino acid sequences indicates that a portion of SM30 proteins is very similar to the carbohydrate recognition domain of C-type lectin proteins.

DOMAIN DECOMPOSITION FOR POROELASTICITY AND ELASTICITY WITH DG JUMPS AND MORTARS

KAUST Repository

GIRAULT, V.

2011-01-01

We couple a time-dependent poroelastic model in a region with an elastic model in adjacent regions. We discretize each model independently on non-matching grids and we realize a domain decomposition on the interface between the regions by introducing DG jumps and mortars. The unknowns are condensed on the interface, so that at each time step, the computation in each subdomain can be performed in parallel. In addition, by extrapolating the displacement, we present an algorithm where the computations of the pressure and displacement are decoupled. We show that the matrix of the interface problem is positive definite and establish error estimates for this scheme. © 2011 World Scientific Publishing Company.

Thermal decomposition of cesium-ethylene-ternary graphite intercalation compounds

International Nuclear Information System (INIS)

Matsumoto, R.; Oishi, Y.; Arii, T.

2010-01-01

In this paper, the thermal decomposition of air-stable Cs-ethylene-ternary graphite intercalation compounds (GICs) is discussed. The air stability of Cs-GICs is improved remarkably after the absorption of ethylene into their interlayer nanospace, because the ethylene molecules oligomerize and block the movement of Cs atoms. In addition, the evaporation of Cs atoms from the Cs-ethylene-ternary GICs is observed above 400 o C under a N 2 atmosphere of 100 Pa by ion attachment mass spectrometry. Although the results indicate that Cs-ethylene-ternary GICs remain stable up to approximately 400 o C, their thermal stability is not very high as compared to that of Cs-GICs.

Decomposition theory of chemical reactions

International Nuclear Information System (INIS)

Rabitz, S.; Rabitz, H.

1977-01-01

The coupled channel formulation is utilized to variationally derive approximate closed-form expressions for reactive transition matrices. In conjunction with this effort it is shown that the effect of differing choices of possible channel coupling arrays becomes important when incomplete channel basis sets are used. Generalized techniques are employed to derive the necessary variational principles. The inherent coupling of the Green's functions in the resulting expression for the transition matrix makes inclusion of continuum states in the basis sets less crucial. The practical viability of this formulation as a computational scheme for chemical systems is discussed

Weakly intrusive low-rank approximation method for nonlinear parameter-dependent equations

KAUST Repository

Giraldi, Loic; Nouy, Anthony

2017-01-01

This paper presents a weakly intrusive strategy for computing a low-rank approximation of the solution of a system of nonlinear parameter-dependent equations. The proposed strategy relies on a Newton-like iterative solver which only requires evaluations of the residual of the parameter-dependent equation and of a preconditioner (such as the differential of the residual) for instances of the parameters independently. The algorithm provides an approximation of the set of solutions associated with a possibly large number of instances of the parameters, with a computational complexity which can be orders of magnitude lower than when using the same Newton-like solver for all instances of the parameters. The reduction of complexity requires efficient strategies for obtaining low-rank approximations of the residual, of the preconditioner, and of the increment at each iteration of the algorithm. For the approximation of the residual and the preconditioner, weakly intrusive variants of the empirical interpolation method are introduced, which require evaluations of entries of the residual and the preconditioner. Then, an approximation of the increment is obtained by using a greedy algorithm for low-rank approximation, and a low-rank approximation of the iterate is finally obtained by using a truncated singular value decomposition. When the preconditioner is the differential of the residual, the proposed algorithm is interpreted as an inexact Newton solver for which a detailed convergence analysis is provided. Numerical examples illustrate the efficiency of the method.

Weakly intrusive low-rank approximation method for nonlinear parameter-dependent equations

KAUST Repository

Giraldi, Loic

2017-06-30

This paper presents a weakly intrusive strategy for computing a low-rank approximation of the solution of a system of nonlinear parameter-dependent equations. The proposed strategy relies on a Newton-like iterative solver which only requires evaluations of the residual of the parameter-dependent equation and of a preconditioner (such as the differential of the residual) for instances of the parameters independently. The algorithm provides an approximation of the set of solutions associated with a possibly large number of instances of the parameters, with a computational complexity which can be orders of magnitude lower than when using the same Newton-like solver for all instances of the parameters. The reduction of complexity requires efficient strategies for obtaining low-rank approximations of the residual, of the preconditioner, and of the increment at each iteration of the algorithm. For the approximation of the residual and the preconditioner, weakly intrusive variants of the empirical interpolation method are introduced, which require evaluations of entries of the residual and the preconditioner. Then, an approximation of the increment is obtained by using a greedy algorithm for low-rank approximation, and a low-rank approximation of the iterate is finally obtained by using a truncated singular value decomposition. When the preconditioner is the differential of the residual, the proposed algorithm is interpreted as an inexact Newton solver for which a detailed convergence analysis is provided. Numerical examples illustrate the efficiency of the method.

Hierarchical matrix techniques for the solution of elliptic equations

KAUST Repository

Chávez, Gustavo

2014-05-04

Hierarchical matrix approximations are a promising tool for approximating low-rank matrices given the compactness of their representation and the economy of the operations between them. Integral and differential operators have been the major applications of this technology, but they can be applied into other areas where low-rank properties exist. Such is the case of the Block Cyclic Reduction algorithm, which is used as a direct solver for the constant-coefficient Poisson quation. We explore the variable-coefficient case, also using Block Cyclic reduction, with the addition of Hierarchical Matrices to represent matrix blocks, hence improving the otherwise O(N2) algorithm, into an efficient O(N) algorithm.

Nonstatic, self-consistent πN t matrix in nuclear matter

International Nuclear Information System (INIS)

Van Orden, J.W.

1984-01-01

In a recent paper, a calculation of the self-consistent πN t matrix in nuclear matter was presented. In this calculation the driving term of the self-consistent equation was chosen to be a static approximation to the free πN t matrix. In the present work, the earlier calculation is extended by using a nonstatic, fully-off-shell free πN t matrix as a starting point. Right-hand pole and cut contributions to the P-wave πN amplitudes are derived using a Low expansion and include effects due to recoil of the interacting πN system as well as the transformation from the πN c.m. frame to the nuclear rest frame. The self-consistent t-matrix equation is rewritten as two integral equations which modify the pole and cut contributions to the t matrix separately. The self-consistent πN t matrix is calculated in nuclear matter and a nonlocal optical potential is constructed from it. The resonant contribution to the optical potential is found to be broadened by 20% to 50% depending on pion momentum and is shifted upward in energy by approximately 10 MeV in comparison to the first-order optical potential. Modifications to the nucleon pole contribution are found to be negligible

Dispersion and betatron function correction in the Advanced Photon Source storage ring using singular value decomposition

International Nuclear Information System (INIS)

Emery, L.

1999-01-01

Magnet errors and off-center orbits through sextuples perturb the dispersion and beta functions in a storage ring (SR), which affects machine performance. In a large ring such as the Advanced Photon Source (APS), the magnet errors are difficult to determine with beam-based methods. Also the non-zero orbit through sextuples result from user requests for steering at light source points. For expediency, a singular value decomposition (SVD) matrix method analogous to orbit correction was adopted to make global corrections to these functions using strengths of several quadrupoles as correcting elements. The direct response matrix is calculated from the model of the perfect lattice. The inverse is calculated by SVD with a selected number of singular vectors. Resulting improvement in the lattice functions and machine performance will be presented

Matrix-dependent multigrid-homogenization for diffusion problems

Energy Technology Data Exchange (ETDEWEB)

Knapek, S. [Institut fuer Informatik tu Muenchen (Germany)

1996-12-31

We present a method to approximately determine the effective diffusion coefficient on the coarse scale level of problems with strongly varying or discontinuous diffusion coefficients. It is based on techniques used also in multigrid, like Dendy`s matrix-dependent prolongations and the construction of coarse grid operators by means of the Galerkin approximation. In numerical experiments, we compare our multigrid-homogenization method with homogenization, renormalization and averaging approaches.

Genten: Software for Generalized Tensor Decompositions v. 1.0.0

Energy Technology Data Exchange (ETDEWEB)

2017-06-22

Tensors, or multidimensional arrays, are a powerful mathematical means of describing multiway data. This software provides computational means for decomposing or approximating a given tensor in terms of smaller tensors of lower dimension, focusing on decomposition of large, sparse tensors. These techniques have applications in many scientific areas, including signal processing, linear algebra, computer vision, numerical analysis, data mining, graph analysis, neuroscience and more. The software is designed to take advantage of parallelism present emerging computer architectures such has multi-core CPUs, many-core accelerators such as the Intel Xeon Phi, and computation-oriented GPUs to enable efficient processing of large tensors.

Photochemical decomposition of catecholamines

International Nuclear Information System (INIS)

Mol, N.J. de; Henegouwen, G.M.J.B. van; Gerritsma, K.W.

1979-01-01

During photochemical decomposition (lambda=254 nm) adrenaline, isoprenaline and noradrenaline in aqueous solution were converted to the corresponding aminochrome for 65, 56 and 35% respectively. In determining this conversion, photochemical instability of the aminochromes was taken into account. Irradiations were performed in such dilute solutions that the neglect of the inner filter effect is permissible. Furthermore, quantum yields for the decomposition of the aminochromes in aqueous solution are given. (Author)

Investigating hydrogel dosimeter decomposition by chemical methods

International Nuclear Information System (INIS)

Jordan, Kevin

2015-01-01

The chemical oxidative decomposition of leucocrystal violet micelle hydrogel dosimeters was investigated using the reaction of ferrous ions with hydrogen peroxide or sodium bicarbonate with hydrogen peroxide. The second reaction is more effective at dye decomposition in gelatin hydrogels. Additional chemical analysis is required to determine the decomposition products

Three-dimensional decomposition models for carbon productivity

International Nuclear Information System (INIS)

Meng, Ming; Niu, Dongxiao

2012-01-01

This paper presents decomposition models for the change in carbon productivity, which is considered a key indicator that reflects the contributions to the control of greenhouse gases. Carbon productivity differential was used to indicate the beginning of decomposition. After integrating the differential equation and designing the Log Mean Divisia Index equations, a three-dimensional absolute decomposition model for carbon productivity was derived. Using this model, the absolute change of carbon productivity was decomposed into a summation of the absolute quantitative influences of each industrial sector, for each influence factor (technological innovation and industrial structure adjustment) in each year. Furthermore, the relative decomposition model was built using a similar process. Finally, these models were applied to demonstrate the decomposition process in China. The decomposition results reveal several important conclusions: (a) technological innovation plays a far more important role than industrial structure adjustment; (b) industry and export trade exhibit great influence; (c) assigning the responsibility for CO 2 emission control to local governments, optimizing the structure of exports, and eliminating backward industrial capacity are highly essential to further increase China's carbon productivity. -- Highlights: ► Using the change of carbon productivity to measure a country's contribution. ► Absolute and relative decomposition models for carbon productivity are built. ► The change is decomposed to the quantitative influence of three-dimension. ► Decomposition results can be used for improving a country's carbon productivity.

Multilevel index decomposition analysis: Approaches and application