Sparse subspace clustering for data with missing entries and high-rank matrix completion.

PubMed

Fan, Jicong; Chow, Tommy W S

2017-09-01

Many methods have recently been proposed for subspace clustering, but they are often unable to handle incomplete data because of missing entries. Using matrix completion methods to recover missing entries is a common way to solve the problem. Conventional matrix completion methods require that the matrix should be of low-rank intrinsically, but most matrices are of high-rank or even full-rank in practice, especially when the number of subspaces is large. In this paper, a new method called Sparse Representation with Missing Entries and Matrix Completion is proposed to solve the problems of incomplete-data subspace clustering and high-rank matrix completion. The proposed algorithm alternately computes the matrix of sparse representation coefficients and recovers the missing entries of a data matrix. The proposed algorithm recovers missing entries through minimizing the representation coefficients, representation errors, and matrix rank. Thorough experimental study and comparative analysis based on synthetic data and natural images were conducted. The presented results demonstrate that the proposed algorithm is more effective in subspace clustering and matrix completion compared with other existing methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

Generation of gas-phase ions from charged clusters: an important ionization step causing suppression of matrix and analyte ions in matrix-assisted laser desorption/ionization mass spectrometry.

PubMed

Lou, Xianwen; van Dongen, Joost L J; Milroy, Lech-Gustav; Meijer, E W

2016-12-30

Ionization in matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) is a very complicated process. It has been reported that quaternary ammonium salts show extremely strong matrix and analyte suppression effects which cannot satisfactorily be explained by charge transfer reactions. Further investigation of the reasons causing these effects can be useful to improve our understanding of the MALDI process. The dried-droplet and modified thin-layer methods were used as sample preparation methods. In the dried-droplet method, analytes were co-crystallized with matrix, whereas in the modified thin-layer method analytes were deposited on the surface of matrix crystals. Model compounds, tetrabutylammonium iodide ([N(Bu) 4 ]I), cesium iodide (CsI), trihexylamine (THA) and polyethylene glycol 600 (PEG 600), were selected as the test analytes given their ability to generate exclusively pre-formed ions, protonated ions and metal ion adducts respectively in MALDI. The strong matrix suppression effect (MSE) observed using the dried-droplet method might disappear using the modified thin-layer method, which suggests that the incorporation of analytes in matrix crystals contributes to the MSE. By depositing analytes on the matrix surface instead of incorporating in the matrix crystals, the competition for evaporation/ionization from charged matrix/analyte clusters could be weakened resulting in reduced MSE. Further supporting evidence for this inference was found by studying the analyte suppression effect using the same two sample deposition methods. By comparing differences between the mass spectra obtained via the two sample preparation methods, we present evidence suggesting that the generation of gas-phase ions from charged matrix/analyte clusters may induce significant suppression of matrix and analyte ions. The results suggest that the generation of gas-phase ions from charged matrix/analyte clusters is an important ionization step in MALDI-MS. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

A robust method of computing finite difference coefficients based on Vandermonde matrix

NASA Astrophysics Data System (ADS)

Zhang, Yijie; Gao, Jinghuai; Peng, Jigen; Han, Weimin

2018-05-01

When the finite difference (FD) method is employed to simulate the wave propagation, high-order FD method is preferred in order to achieve better accuracy. However, if the order of FD scheme is high enough, the coefficient matrix of the formula for calculating finite difference coefficients is close to be singular. In this case, when the FD coefficients are computed by matrix inverse operator of MATLAB, inaccuracy can be produced. In order to overcome this problem, we have suggested an algorithm based on Vandermonde matrix in this paper. After specified mathematical transformation, the coefficient matrix is transformed into a Vandermonde matrix. Then the FD coefficients of high-order FD method can be computed by the algorithm of Vandermonde matrix, which prevents the inverse of the singular matrix. The dispersion analysis and numerical results of a homogeneous elastic model and a geophysical model of oil and gas reservoir demonstrate that the algorithm based on Vandermonde matrix has better accuracy compared with matrix inverse operator of MATLAB.

Comparison of two Galerkin quadrature methods

DOE PAGES

Morel, Jim E.; Warsa, James; Franke, Brian C.; ...

2017-02-21

Here, we compare two methods for generating Galerkin quadratures. In method 1, the standard S N method is used to generate the moment-to-discrete matrix and the discrete-to-moment matrix is generated by inverting the moment-to-discrete matrix. This is a particular form of the original Galerkin quadrature method. In method 2, which we introduce here, the standard S N method is used to generate the discrete-to-moment matrix and the moment-to-discrete matrix is generated by inverting the discrete-to-moment matrix. With an N-point quadrature, method 1 has the advantage that it preserves N eigenvalues and N eigenvectors of the scattering operator in a pointwisemore » sense. With an N-point quadrature, method 2 has the advantage that it generates consistent angular moment equations from the corresponding S N equations while preserving N eigenvalues of the scattering operator. Our computational results indicate that these two methods are quite comparable for the test problem considered.« less

Comparison of two Galerkin quadrature methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Morel, Jim E.; Warsa, James; Franke, Brian C.

Here, we compare two methods for generating Galerkin quadratures. In method 1, the standard S N method is used to generate the moment-to-discrete matrix and the discrete-to-moment matrix is generated by inverting the moment-to-discrete matrix. This is a particular form of the original Galerkin quadrature method. In method 2, which we introduce here, the standard S N method is used to generate the discrete-to-moment matrix and the moment-to-discrete matrix is generated by inverting the discrete-to-moment matrix. With an N-point quadrature, method 1 has the advantage that it preserves N eigenvalues and N eigenvectors of the scattering operator in a pointwisemore » sense. With an N-point quadrature, method 2 has the advantage that it generates consistent angular moment equations from the corresponding S N equations while preserving N eigenvalues of the scattering operator. Our computational results indicate that these two methods are quite comparable for the test problem considered.« less

Method of producing a hybrid matrix fiber composite

DOEpatents

Deteresa, Steven J [Livermore, CA; Lyon, Richard E [Absecon, NJ; Groves, Scott E [Brentwood, CA

2006-03-28

Hybrid matrix fiber composites having enhanced compressive performance as well as enhanced stiffness, toughness and durability suitable for compression-critical applications. The methods for producing the fiber composites using matrix hybridization. The hybrid matrix fiber composites comprised of two chemically or physically bonded matrix materials, whereas the first matrix materials are used to impregnate multi-filament fibers formed into ribbons and the second matrix material is placed around and between the fiber ribbons that are impregnated with the first matrix material and both matrix materials are cured and solidified.

Approximate method of variational Bayesian matrix factorization/completion with sparse prior

NASA Astrophysics Data System (ADS)

Kawasumi, Ryota; Takeda, Koujin

2018-05-01

We derive the analytical expression of a matrix factorization/completion solution by the variational Bayes method, under the assumption that the observed matrix is originally the product of low-rank, dense and sparse matrices with additive noise. We assume the prior of a sparse matrix is a Laplace distribution by taking matrix sparsity into consideration. Then we use several approximations for the derivation of a matrix factorization/completion solution. By our solution, we also numerically evaluate the performance of a sparse matrix reconstruction in matrix factorization, and completion of a missing matrix element in matrix completion.

The fast algorithm of spark in compressive sensing

NASA Astrophysics Data System (ADS)

Xie, Meihua; Yan, Fengxia

2017-01-01

Compressed Sensing (CS) is an advanced theory on signal sampling and reconstruction. In CS theory, the reconstruction condition of signal is an important theory problem, and spark is a good index to study this problem. But the computation of spark is NP hard. In this paper, we study the problem of computing spark. For some special matrixes, for example, the Gaussian random matrix and 0-1 random matrix, we obtain some conclusions. Furthermore, for Gaussian random matrix with fewer rows than columns, we prove that its spark equals to the number of its rows plus one with probability 1. For general matrix, two methods are given to compute its spark. One is the method of directly searching and the other is the method of dual-tree searching. By simulating 24 Gaussian random matrixes and 18 0-1 random matrixes, we tested the computation time of these two methods. Numerical results showed that the dual-tree searching method had higher efficiency than directly searching, especially for those matrixes which has as much as rows and columns.

A sparse matrix-vector multiplication based algorithm for accurate density matrix computations on systems of millions of atoms

NASA Astrophysics Data System (ADS)

Ghale, Purnima; Johnson, Harley T.

2018-06-01

We present an efficient sparse matrix-vector (SpMV) based method to compute the density matrix P from a given Hamiltonian in electronic structure computations. Our method is a hybrid approach based on Chebyshev-Jackson approximation theory and matrix purification methods like the second order spectral projection purification (SP2). Recent methods to compute the density matrix scale as O(N) in the number of floating point operations but are accompanied by large memory and communication overhead, and they are based on iterative use of the sparse matrix-matrix multiplication kernel (SpGEMM), which is known to be computationally irregular. In addition to irregularity in the sparse Hamiltonian H, the nonzero structure of intermediate estimates of P depends on products of H and evolves over the course of computation. On the other hand, an expansion of the density matrix P in terms of Chebyshev polynomials is straightforward and SpMV based; however, the resulting density matrix may not satisfy the required constraints exactly. In this paper, we analyze the strengths and weaknesses of the Chebyshev-Jackson polynomials and the second order spectral projection purification (SP2) method, and propose to combine them so that the accurate density matrix can be computed using the SpMV computational kernel only, and without having to store the density matrix P. Our method accomplishes these objectives by using the Chebyshev polynomial estimate as the initial guess for SP2, which is followed by using sparse matrix-vector multiplications (SpMVs) to replicate the behavior of the SP2 algorithm for purification. We demonstrate the method on a tight-binding model system of an oxide material containing more than 3 million atoms. In addition, we also present the predicted behavior of our method when applied to near-metallic Hamiltonians with a wide energy spectrum.

Optimized Projection Matrix for Compressive Sensing

NASA Astrophysics Data System (ADS)

Xu, Jianping; Pi, Yiming; Cao, Zongjie

2010-12-01

Compressive sensing (CS) is mainly concerned with low-coherence pairs, since the number of samples needed to recover the signal is proportional to the mutual coherence between projection matrix and sparsifying matrix. Until now, papers on CS always assume the projection matrix to be a random matrix. In this paper, aiming at minimizing the mutual coherence, a method is proposed to optimize the projection matrix. This method is based on equiangular tight frame (ETF) design because an ETF has minimum coherence. It is impossible to solve the problem exactly because of the complexity. Therefore, an alternating minimization type method is used to find a feasible solution. The optimally designed projection matrix can further reduce the necessary number of samples for recovery or improve the recovery accuracy. The proposed method demonstrates better performance than conventional optimization methods, which brings benefits to both basis pursuit and orthogonal matching pursuit.

Comparison of matrix effects in HPLC-MS/MS and UPLC-MS/MS analysis of nine basic pharmaceuticals in surface waters.

PubMed

Van De Steene, Jet C; Lambert, Willy E

2008-05-01

When developing an LC-MS/MS-method matrix effects are a major issue. The effect of co-eluting compounds arising from the matrix can result in signal enhancement or suppression. During method development much attention should be paid to diminishing matrix effects as much as possible. The present work evaluates matrix effects from aqueous environmental samples in the simultaneous analysis of a group of 9 specific pharmaceuticals with HPLC-ESI/MS/MS and UPLC-ESI/MS/MS: flubendazole, propiconazole, pipamperone, cinnarizine, ketoconazole, miconazole, rabeprazole, itraconazole and domperidone. When HPLC-MS/MS is used, matrix effects are substantial and can not be compensated for with analogue internal standards. For different surface water samples different matrix effects are found. For accurate quantification the standard addition approach is necessary. Due to the better resolution and more narrow peaks in UPLC, analytes will co-elute less with interferences during ionisation, so matrix effects could be lower, or even eliminated. If matrix effects are eliminated with this technique, the standard addition method for quantification can be omitted and the overall method will be simplified. Results show that matrix effects are almost eliminated if internal standards (structural analogues) are used. Instead of the time-consuming and labour-intensive standard addition method, with UPLC the internal standardization can be used for quantification and the overall method is substantially simplified.

Fast Low-Rank Bayesian Matrix Completion With Hierarchical Gaussian Prior Models

NASA Astrophysics Data System (ADS)

Yang, Linxiao; Fang, Jun; Duan, Huiping; Li, Hongbin; Zeng, Bing

2018-06-01

The problem of low rank matrix completion is considered in this paper. To exploit the underlying low-rank structure of the data matrix, we propose a hierarchical Gaussian prior model, where columns of the low-rank matrix are assumed to follow a Gaussian distribution with zero mean and a common precision matrix, and a Wishart distribution is specified as a hyperprior over the precision matrix. We show that such a hierarchical Gaussian prior has the potential to encourage a low-rank solution. Based on the proposed hierarchical prior model, a variational Bayesian method is developed for matrix completion, where the generalized approximate massage passing (GAMP) technique is embedded into the variational Bayesian inference in order to circumvent cumbersome matrix inverse operations. Simulation results show that our proposed method demonstrates superiority over existing state-of-the-art matrix completion methods.

A Truncated Nuclear Norm Regularization Method Based on Weighted Residual Error for Matrix Completion.

PubMed

Qing Liu; Zhihui Lai; Zongwei Zhou; Fangjun Kuang; Zhong Jin

2016-01-01

Low-rank matrix completion aims to recover a matrix from a small subset of its entries and has received much attention in the field of computer vision. Most existing methods formulate the task as a low-rank matrix approximation problem. A truncated nuclear norm has recently been proposed as a better approximation to the rank of matrix than a nuclear norm. The corresponding optimization method, truncated nuclear norm regularization (TNNR), converges better than the nuclear norm minimization-based methods. However, it is not robust to the number of subtracted singular values and requires a large number of iterations to converge. In this paper, a TNNR method based on weighted residual error (TNNR-WRE) for matrix completion and its extension model (ETNNR-WRE) are proposed. TNNR-WRE assigns different weights to the rows of the residual error matrix in an augmented Lagrange function to accelerate the convergence of the TNNR method. The ETNNR-WRE is much more robust to the number of subtracted singular values than the TNNR-WRE, TNNR alternating direction method of multipliers, and TNNR accelerated proximal gradient with Line search methods. Experimental results using both synthetic and real visual data sets show that the proposed TNNR-WRE and ETNNR-WRE methods perform better than TNNR and Iteratively Reweighted Nuclear Norm (IRNN) methods.

Matrix method for acoustic levitation simulation.

PubMed

Andrade, Marco A B; Perez, Nicolas; Buiochi, Flavio; Adamowski, Julio C

2011-08-01

A matrix method is presented for simulating acoustic levitators. A typical acoustic levitator consists of an ultrasonic transducer and a reflector. The matrix method is used to determine the potential for acoustic radiation force that acts on a small sphere in the standing wave field produced by the levitator. The method is based on the Rayleigh integral and it takes into account the multiple reflections that occur between the transducer and the reflector. The potential for acoustic radiation force obtained by the matrix method is validated by comparing the matrix method results with those obtained by the finite element method when using an axisymmetric model of a single-axis acoustic levitator. After validation, the method is applied in the simulation of a noncontact manipulation system consisting of two 37.9-kHz Langevin-type transducers and a plane reflector. The manipulation system allows control of the horizontal position of a small levitated sphere from -6 mm to 6 mm, which is done by changing the phase difference between the two transducers. The horizontal position of the sphere predicted by the matrix method agrees with the horizontal positions measured experimentally with a charge-coupled device camera. The main advantage of the matrix method is that it allows simulation of non-symmetric acoustic levitators without requiring much computational effort.

Optical matrix-matrix multiplication method demonstrated by the use of a multifocus hololens

NASA Technical Reports Server (NTRS)

Liu, H. K.; Liang, Y.-Z.

1984-01-01

A method of optical matrix-matrix multiplication is presented. The feasibility of the method is also experimentally demonstrated by the use of a dichromated-gelatin multifocus holographic lens (hololens). With the specific values of matrices chosen, the average percentage error between the theoretical and experimental data of the elements of the output matrix of the multiplication of some specific pairs of 3 x 3 matrices is 0.4 percent, which corresponds to an 8-bit accuracy.

HPK1 competes with ADAP for SLP-76 binding and via Rap1 negatively affects T-cell adhesion.

PubMed

Patzak, Irene M; Königsberger, Sebastian; Suzuki, Akira; Mak, Tak W; Kiefer, Friedemann

2010-11-01

The hematopoietic progenitor kinase 1 (HPK1) signals into MAPK and NFκB pathways downstream of immunoreceptors, but enigmatically is a negative regulator of leukocytes. Here, we report a novel role for HPK1 in regulating the activation of the adhesion molecule leukocyte function-associated antigen-1 (LFA-1). Upon TCR stimulation, mediated by binding of adhesion and degranulation promoting adaptor protein (ADAP) to SLP-76, a ternary complex composed of ADAP/55-kDa src kinase associated phosphoprotein (SKAP-55) and RIAM translocates to the membrane and causes membrane recruitment of the active small GTPase Ras-related protein 1 (Rap1). Active Rap1, via its binding to RapL (regulator for cell adhesion and polarization enriched in lymphoid tissues), mediates LFA-1 integrin activation. We show here that HPK1, which also binds SLP-76, compete with ADAP for SLP-76 binding. In addition, HPK1 dampens Rap1 activation, resulting in decreased LFA-1 activity. Analysis of HPK1-deficient T cells revealed increased ADAP recruitment to SLP-76 and elevated Rap1 activation in those cells, leading to increased adhesion to ICAM-1 and cell spreading. Altogether, these results describe a novel function for HPK1 in linking TCR signaling to cell adhesion regulation and provide a mechanistic explanation for the negative regulatory role of HPK1 in T-cell biology.

Seasonal variation of semidiurnal internal tides in the East/Japan Sea

NASA Astrophysics Data System (ADS)

Jeon, Chanhyung; Park, Jae-Hun; Varlamov, Sergey M.; Yoon, Jong-Hwan; Kim, Young Ho; Seo, Seongbong; Park, Young-Gyu; Min, Hong Sik; Lee, Jae Hak; Kim, Cheol-Ho

2014-05-01

The seasonal variation of semidiurnal internal tides in the East/Japan Sea was investigated using 25 month long output from a real-time ocean forecasting system. The z coordinate eddy-resolving high-resolution numerical model, called the RIAM ocean model, incorporates data assimilation that nudges temperature and salinity fields together with volume transport through the Korea Strait to produce realistic oceanic currents and stratification. In addition to atmospheric forcing, it includes tidal forcing of 16 major components along open boundaries. The model generates energetic semidiurnal internal tides around the northern entrance of the Korea Strait. Energy conversion from barotropic to baroclinic (internal) tides varies seasonally with maxima in September (ranging 0.48-0.52 GW) and minima in March (ranging 0.11-0.16 GW). This seasonal variation is induced by the seasonality in stratification near the southwestern East/Japan Sea. The propagation distance of the internal tides is associated with generation intensity and wavelength. From late summer to early winter, the semidiurnal internal tides travel relatively far from the generation region due to stratification changes; its energy dissipates less as a result of longer wavelengths. Our results suggest that spatiotemporal variation of internal-tide-induced mixing due to the seasonality in the generation, propagation, and dissipation of internal tides should be considered for a more realistic simulation of water masses and circulation in models of the East/Japan Sea.

The Bioactivity of Cartilage Extracellular Matrix in Articular Cartilage Regeneration

PubMed Central

Sutherland, Amanda J.; Converse, Gabriel L.; Hopkins, Richard A.; Detamore, Michael S.

2014-01-01

Cartilage matrix is a particularly promising acellular material for cartilage regeneration given the evidence supporting its chondroinductive character. The ‘raw materials’ of cartilage matrix can serve as building blocks and signals for enhanced tissue regeneration. These matrices can be created by chemical or physical methods: physical methods disrupt cellular membranes and nuclei but may not fully remove all cell components and DNA, whereas chemical methods when combined with physical methods are particularly effective in fully decellularizing such materials. Critical endpoints include no detectable residual DNA or immunogenic antigens. It is important to first delineate between the sources of the cartilage matrix, i.e., derived from matrix produced by cells in vitro or from native tissue, and then to further characterize the cartilage matrix based on the processing method, i.e., decellularization or devitalization. With these distinctions, four types of cartilage matrices exist: decellularized native cartilage (DCC), devitalized native cartilage (DVC), decellularized cell derived matrix (DCCM), and devitalized cell derived matrix (DVCM). Delivery of cartilage matrix may be a straightforward approach without the need for additional cells or growth factors. Without additional biological additives, cartilage matrix may be attractive from a regulatory and commercialization standpoint. Source and delivery method are important considerations for clinical translation. Only one currently marketed cartilage matrix medical device is decellularized, although trends in filed patents suggest additional decellularized products may be available in the future. To choose the most relevant source and processing for cartilage matrix, qualifying testing needs to include targeting the desired application, optimizing delivery of the material, identify relevant FDA regulations, assess availability of raw materials, and immunogenic properties of the product. PMID:25044502

Novel image analysis methods for quantification of in situ 3-D tendon cell and matrix strain.

PubMed

Fung, Ashley K; Paredes, J J; Andarawis-Puri, Nelly

2018-01-23

Macroscopic tendon loads modulate the cellular microenvironment leading to biological outcomes such as degeneration or repair. Previous studies have shown that damage accumulation and the phases of tendon healing are marked by significant changes in the extracellular matrix, but it remains unknown how mechanical forces of the extracellular matrix are translated to mechanotransduction pathways that ultimately drive the biological response. Our overarching hypothesis is that the unique relationship between extracellular matrix strain and cell deformation will dictate biological outcomes, prompting the need for quantitative methods to characterize the local strain environment. While 2-D methods have successfully calculated matrix strain and cell deformation, 3-D methods are necessary to capture the increased complexity that can arise due to high levels of anisotropy and out-of-plane motion, particularly in the disorganized, highly cellular, injured state. In this study, we validated the use of digital volume correlation methods to quantify 3-D matrix strain using images of naïve tendon cells, the collagen fiber matrix, and injured tendon cells. Additionally, naïve tendon cell images were used to develop novel methods for 3-D cell deformation and 3-D cell-matrix strain, which is defined as a quantitative measure of the relationship between matrix strain and cell deformation. The results support that these methods can be used to detect strains with high accuracy and can be further extended to an in vivo setting for observing temporal changes in cell and matrix mechanics during degeneration and healing. Copyright © 2017. Published by Elsevier Ltd.

Maximum entropy formalism for the analytic continuation of matrix-valued Green's functions

NASA Astrophysics Data System (ADS)

Kraberger, Gernot J.; Triebl, Robert; Zingl, Manuel; Aichhorn, Markus

2017-10-01

We present a generalization of the maximum entropy method to the analytic continuation of matrix-valued Green's functions. To treat off-diagonal elements correctly based on Bayesian probability theory, the entropy term has to be extended for spectral functions that are possibly negative in some frequency ranges. In that way, all matrix elements of the Green's function matrix can be analytically continued; we introduce a computationally cheap element-wise method for this purpose. However, this method cannot ensure important constraints on the mathematical properties of the resulting spectral functions, namely positive semidefiniteness and Hermiticity. To improve on this, we present a full matrix formalism, where all matrix elements are treated simultaneously. We show the capabilities of these methods using insulating and metallic dynamical mean-field theory (DMFT) Green's functions as test cases. Finally, we apply the methods to realistic material calculations for LaTiO3, where off-diagonal matrix elements in the Green's function appear due to the distorted crystal structure.

Theory and implementation of H-matrix based iterative and direct solvers for Helmholtz and elastodynamic oscillatory kernels

NASA Astrophysics Data System (ADS)

Chaillat, Stéphanie; Desiderio, Luca; Ciarlet, Patrick

2017-12-01

In this work, we study the accuracy and efficiency of hierarchical matrix (H-matrix) based fast methods for solving dense linear systems arising from the discretization of the 3D elastodynamic Green's tensors. It is well known in the literature that standard H-matrix based methods, although very efficient tools for asymptotically smooth kernels, are not optimal for oscillatory kernels. H2-matrix and directional approaches have been proposed to overcome this problem. However the implementation of such methods is much more involved than the standard H-matrix representation. The central questions we address are twofold. (i) What is the frequency-range in which the H-matrix format is an efficient representation for 3D elastodynamic problems? (ii) What can be expected of such an approach to model problems in mechanical engineering? We show that even though the method is not optimal (in the sense that more involved representations can lead to faster algorithms) an efficient solver can be easily developed. The capabilities of the method are illustrated on numerical examples using the Boundary Element Method.

Analytical quality assurance in veterinary drug residue analysis methods: matrix effects determination and monitoring for sulfonamides analysis.

PubMed

Hoff, Rodrigo Barcellos; Rübensam, Gabriel; Jank, Louise; Barreto, Fabiano; Peralba, Maria do Carmo Ruaro; Pizzolato, Tânia Mara; Silvia Díaz-Cruz, M; Barceló, Damià

2015-01-01

In residue analysis of veterinary drugs in foodstuff, matrix effects are one of the most critical points. This work present a discuss considering approaches used to estimate, minimize and monitoring matrix effects in bioanalytical methods. Qualitative and quantitative methods for estimation of matrix effects such as post-column infusion, slopes ratios analysis, calibration curves (mathematical and statistical analysis) and control chart monitoring are discussed using real data. Matrix effects varying in a wide range depending of the analyte and the sample preparation method: pressurized liquid extraction for liver samples show matrix effects from 15.5 to 59.2% while a ultrasound-assisted extraction provide values from 21.7 to 64.3%. The matrix influence was also evaluated: for sulfamethazine analysis, losses of signal were varying from -37 to -96% for fish and eggs, respectively. Advantages and drawbacks are also discussed considering a workflow for matrix effects assessment proposed and applied to real data from sulfonamides residues analysis. Copyright © 2014 Elsevier B.V. All rights reserved.

Fast Minimum Variance Beamforming Based on Legendre Polynomials.

PubMed

Bae, MooHo; Park, Sung Bae; Kwon, Sung Jae

2016-09-01

Currently, minimum variance beamforming (MV) is actively investigated as a method that can improve the performance of an ultrasound beamformer, in terms of the lateral and contrast resolution. However, this method has the disadvantage of excessive computational complexity since the inverse spatial covariance matrix must be calculated. Some noteworthy methods among various attempts to solve this problem include beam space adaptive beamforming methods and the fast MV method based on principal component analysis, which are similar in that the original signal in the element space is transformed to another domain using an orthonormal basis matrix and the dimension of the covariance matrix is reduced by approximating the matrix only with important components of the matrix, hence making the inversion of the matrix very simple. Recently, we proposed a new method with further reduced computational demand that uses Legendre polynomials as the basis matrix for such a transformation. In this paper, we verify the efficacy of the proposed method through Field II simulations as well as in vitro and in vivo experiments. The results show that the approximation error of this method is less than or similar to those of the above-mentioned methods and that the lateral response of point targets and the contrast-to-speckle noise in anechoic cysts are also better than or similar to those methods when the dimensionality of the covariance matrices is reduced to the same dimension.

Convergence analysis of modulus-based matrix splitting iterative methods for implicit complementarity problems.

PubMed

Wang, An; Cao, Yang; Shi, Quan

2018-01-01

In this paper, we demonstrate a complete version of the convergence theory of the modulus-based matrix splitting iteration methods for solving a class of implicit complementarity problems proposed by Hong and Li (Numer. Linear Algebra Appl. 23:629-641, 2016). New convergence conditions are presented when the system matrix is a positive-definite matrix and an [Formula: see text]-matrix, respectively.

Algorithms for Solvents and Spectral Factors of Matrix Polynomials

DTIC Science & Technology

1981-01-01

spectral factors of matrix polynomials LEANG S. SHIEHt, YIH T. TSAYt and NORMAN P. COLEMANt A generalized Newton method , based on the contracted gradient...of a matrix poly- nomial, is derived for solving the right (left) solvents and spectral factors of matrix polynomials. Two methods of selecting initial...estimates for rapid convergence of the newly developed numerical method are proposed. Also, new algorithms for solving complete sets of the right

A sample preparation method for recovering suppressed analyte ions in MALDI TOF MS.

PubMed

Lou, Xianwen; de Waal, Bas F M; Milroy, Lech-Gustav; van Dongen, Joost L J

2015-05-01

In matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI TOF MS), analyte signals can be substantially suppressed by other compounds in the sample. In this technical note, we describe a modified thin-layer sample preparation method that significantly reduces the analyte suppression effect (ASE). In our method, analytes are deposited on top of the surface of matrix preloaded on the MALDI plate. To prevent embedding of analyte into the matrix crystals, the sample solution were prepared without matrix and efforts were taken not to re-dissolve the preloaded matrix. The results with model mixtures of peptides, synthetic polymers and lipids show that detection of analyte ions, which were completely suppressed using the conventional dried-droplet method, could be effectively recovered by using our method. Our findings suggest that the incorporation of analytes in the matrix crystals has an important contributory effect on ASE. By reducing ASE, our method should be useful for the direct MALDI MS analysis of multicomponent mixtures. Copyright © 2015 John Wiley & Sons, Ltd.

Quantitative evaluation of the matrix effect in bioanalytical methods based on LC-MS: A comparison of two approaches.

PubMed

Rudzki, Piotr J; Gniazdowska, Elżbieta; Buś-Kwaśnik, Katarzyna

2018-06-05

Liquid chromatography coupled to mass spectrometry (LC-MS) is a powerful tool for studying pharmacokinetics and toxicokinetics. Reliable bioanalysis requires the characterization of the matrix effect, i.e. influence of the endogenous or exogenous compounds on the analyte signal intensity. We have compared two methods for the quantitation of matrix effect. The CVs(%) of internal standard normalized matrix factors recommended by the European Medicines Agency were evaluated against internal standard normalized relative matrix effects derived from Matuszewski et al. (2003). Both methods use post-extraction spiked samples, but matrix factors require also neat solutions. We have tested both approaches using analytes of diverse chemical structures. The study did not reveal relevant differences in the results obtained with both calculation methods. After normalization with the internal standard, the CV(%) of the matrix factor was on average 0.5% higher than the corresponding relative matrix effect. The method adopted by the European Medicines Agency seems to be slightly more conservative in the analyzed datasets. Nine analytes of different structures enabled a general overview of the problem, still, further studies are encouraged to confirm our observations. Copyright © 2018 Elsevier B.V. All rights reserved.

Direct Iterative Nonlinear Inversion by Multi-frequency T-matrix Completion

NASA Astrophysics Data System (ADS)

Jakobsen, M.; Wu, R. S.

2016-12-01

Researchers in the mathematical physics community have recently proposed a conceptually new method for solving nonlinear inverse scattering problems (like FWI) which is inspired by the theory of nonlocality of physical interactions. The conceptually new method, which may be referred to as the T-matrix completion method, is very interesting since it is not based on linearization at any stage. Also, there are no gradient vectors or (inverse) Hessian matrices to calculate. However, the convergence radius of this promising T-matrix completion method is seriously restricted by it's use of single-frequency scattering data only. In this study, we have developed a modified version of the T-matrix completion method which we believe is more suitable for applications to nonlinear inverse scattering problems in (exploration) seismology, because it makes use of multi-frequency data. Essentially, we have simplified the single-frequency T-matrix completion method of Levinson and Markel and combined it with the standard sequential frequency inversion (multi-scale regularization) method. For each frequency, we first estimate the experimental T-matrix by using the Moore-Penrose pseudo inverse concept. Then this experimental T-matrix is used to initiate an iterative procedure for successive estimation of the scattering potential and the T-matrix using the Lippmann-Schwinger for the nonlinear relation between these two quantities. The main physical requirements in the basic iterative cycle is that the T-matrix should be data-compatible and the scattering potential operator should be dominantly local; although a non-local scattering potential operator is allowed in the intermediate iterations. In our simplified T-matrix completion strategy, we ensure that the T-matrix updates are always data compatible simply by adding a suitable correction term in the real space coordinate representation. The use of singular-value decomposition representations are not required in our formulation since we have developed an efficient domain decomposition method. The results of several numerical experiments for the SEG/EAGE salt model illustrate the importance of using multi-frequency data when performing frequency domain full waveform inversion in strongly scattering media via the new concept of T-matrix completion.

Comparison of experimental methods for estimating matrix diffusion coefficients for contaminant transport modeling

NASA Astrophysics Data System (ADS)

Telfeyan, Katherine; Ware, S. Doug; Reimus, Paul W.; Birdsell, Kay H.

2018-02-01

Diffusion cell and diffusion wafer experiments were conducted to compare methods for estimating effective matrix diffusion coefficients in rock core samples from Pahute Mesa at the Nevada Nuclear Security Site (NNSS). A diffusion wafer method, in which a solute diffuses out of a rock matrix that is pre-saturated with water containing the solute, is presented as a simpler alternative to the traditional through-diffusion (diffusion cell) method. Both methods yielded estimates of effective matrix diffusion coefficients that were within the range of values previously reported for NNSS volcanic rocks. The difference between the estimates of the two methods ranged from 14 to 30%, and there was no systematic high or low bias of one method relative to the other. From a transport modeling perspective, these differences are relatively minor when one considers that other variables (e.g., fracture apertures, fracture spacings) influence matrix diffusion to a greater degree and tend to have greater uncertainty than effective matrix diffusion coefficients. For the same relative random errors in concentration measurements, the diffusion cell method yields effective matrix diffusion coefficient estimates that have less uncertainty than the wafer method. However, the wafer method is easier and less costly to implement and yields estimates more quickly, thus allowing a greater number of samples to be analyzed for the same cost and time. Given the relatively good agreement between the methods, and the lack of any apparent bias between the methods, the diffusion wafer method appears to offer advantages over the diffusion cell method if better statistical representation of a given set of rock samples is desired.

Efficient Algorithms for Estimating the Absorption Spectrum within Linear Response TDDFT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brabec, Jiri; Lin, Lin; Shao, Meiyue

We present two iterative algorithms for approximating the absorption spectrum of molecules within linear response of time-dependent density functional theory (TDDFT) framework. These methods do not attempt to compute eigenvalues or eigenvectors of the linear response matrix. They are designed to approximate the absorption spectrum as a function directly. They take advantage of the special structure of the linear response matrix. Neither method requires the linear response matrix to be constructed explicitly. They only require a procedure that performs the multiplication of the linear response matrix with a vector. These methods can also be easily modified to efficiently estimate themore » density of states (DOS) of the linear response matrix without computing the eigenvalues of this matrix. We show by computational experiments that the methods proposed in this paper can be much more efficient than methods that are based on the exact diagonalization of the linear response matrix. We show that they can also be more efficient than real-time TDDFT simulations. We compare the pros and cons of these methods in terms of their accuracy as well as their computational and storage cost.« less

Comparative test on several forms of background error covariance in 3DVar

NASA Astrophysics Data System (ADS)

Shao, Aimei

2013-04-01

The background error covariance matrix (Hereinafter referred to as B matrix) plays an important role in the three-dimensional variational (3DVar) data assimilation method. However, it is difficult to get B matrix accurately because true atmospheric state is unknown. Therefore, some methods were developed to estimate B matrix (e.g. NMC method, innovation analysis method, recursive filters, and ensemble method such as EnKF). Prior to further development and application of these methods, the function of several B matrixes estimated by these methods in 3Dvar is worth studying and evaluating. For this reason, NCEP reanalysis data and forecast data are used to test the effectiveness of the several B matrixes with VAF (Huang, 1999) method. Here the NCEP analysis is treated as the truth and in this case the forecast error is known. The data from 2006 to 2007 is used as the samples to estimate B matrix and the data in 2008 is used to verify the assimilation effects. The 48h and 24h forecast valid at the same time is used to estimate B matrix with NMC method. B matrix can be represented by a correlation part (a non-diagonal matrix) and a variance part (a diagonal matrix of variances). Gaussian filter function as an approximate approach is used to represent the variation of correlation coefficients with distance in numerous 3DVar systems. On the basis of the assumption, the following several forms of B matrixes are designed and test with VAF in the comparative experiments: (1) error variance and the characteristic lengths are fixed and setted to their mean value averaged over the analysis domain; (2) similar to (1), but the mean characteristic lengths reduce to 50 percent for the height and 60 percent for the temperature of the original; (3) similar to (2), but error variance calculated directly by the historical data is space-dependent; (4) error variance and characteristic lengths are all calculated directly by the historical data; (5) B matrix is estimated directly by the historical data; (6) similar to (5), but a localization process is performed; (7) B matrix is estimated by NMC method but error variance is reduced by 1.7 times in order that the value is close to that calculated from the true forecast error samples; (8) similar to (7), but the localization similar to (6) is performed. Experimental results with the different B matrixes show that for the Gaussian-type B matrix the characteristic lengths calculated from the true error samples don't bring a good analysis results. However, the reduced characteristic lengths (about half of the original one) can lead to a good analysis. If the B matrix estimated directly from the historical data is used in 3DVar, the assimilation effect can not reach to the best. The better assimilation results are generated with the application of reduced characteristic length and localization. Even so, it hasn't obvious advantage compared with Gaussian-type B matrix with the optimal characteristic length. It implies that the Gaussian-type B matrix, widely used for operational 3DVar system, can get a good analysis with the appropriate characteristic lengths. The crucial problem is how to determine the appropriate characteristic lengths. (This work is supported by the National Natural Science Foundation of China (41275102, 40875063), and the Fundamental Research Funds for the Central Universities (lzujbky-2010-9) )

Compatibility of pedigree-based and marker-based relationship matrices for single-step genetic evaluation.

PubMed

Christensen, Ole F

2012-12-03

Single-step methods provide a coherent and conceptually simple approach to incorporate genomic information into genetic evaluations. An issue with single-step methods is compatibility between the marker-based relationship matrix for genotyped animals and the pedigree-based relationship matrix. Therefore, it is necessary to adjust the marker-based relationship matrix to the pedigree-based relationship matrix. Moreover, with data from routine evaluations, this adjustment should in principle be based on both observed marker genotypes and observed phenotypes, but until now this has been overlooked. In this paper, I propose a new method to address this issue by 1) adjusting the pedigree-based relationship matrix to be compatible with the marker-based relationship matrix instead of the reverse and 2) extending the single-step genetic evaluation using a joint likelihood of observed phenotypes and observed marker genotypes. The performance of this method is then evaluated using two simulated datasets. The method derived here is a single-step method in which the marker-based relationship matrix is constructed assuming all allele frequencies equal to 0.5 and the pedigree-based relationship matrix is constructed using the unusual assumption that animals in the base population are related and inbred with a relationship coefficient γ and an inbreeding coefficient γ / 2. Taken together, this γ parameter and a parameter that scales the marker-based relationship matrix can handle the issue of compatibility between marker-based and pedigree-based relationship matrices. The full log-likelihood function used for parameter inference contains two terms. The first term is the REML-log-likelihood for the phenotypes conditional on the observed marker genotypes, whereas the second term is the log-likelihood for the observed marker genotypes. Analyses of the two simulated datasets with this new method showed that 1) the parameters involved in adjusting marker-based and pedigree-based relationship matrices can depend on both observed phenotypes and observed marker genotypes and 2) a strong association between these two parameters exists. Finally, this method performed at least as well as a method based on adjusting the marker-based relationship matrix. Using the full log-likelihood and adjusting the pedigree-based relationship matrix to be compatible with the marker-based relationship matrix provides a new and interesting approach to handle the issue of compatibility between the two matrices in single-step genetic evaluation.

A Novel Sky-Subtraction Method Based on Non-negative Matrix Factorisation with Sparsity for Multi-object Fibre Spectroscopy

NASA Astrophysics Data System (ADS)

Zhang, Bo; Zhang, Long; Ye, Zhongfu

2016-12-01

A novel sky-subtraction method based on non-negative matrix factorisation with sparsity is proposed in this paper. The proposed non-negative matrix factorisation with sparsity method is redesigned for sky-subtraction considering the characteristics of the skylights. It has two constraint terms, one for sparsity and the other for homogeneity. Different from the standard sky-subtraction techniques, such as the B-spline curve fitting methods and the Principal Components Analysis approaches, sky-subtraction based on non-negative matrix factorisation with sparsity method has higher accuracy and flexibility. The non-negative matrix factorisation with sparsity method has research value for the sky-subtraction on multi-object fibre spectroscopic telescope surveys. To demonstrate the effectiveness and superiority of the proposed algorithm, experiments are performed on Large Sky Area Multi-Object Fiber Spectroscopic Telescope data, as the mechanisms of the multi-object fibre spectroscopic telescopes are similar.

Matrix effects in pesticide multi-residue analysis by liquid chromatography-mass spectrometry.

PubMed

Kruve, Anneli; Künnapas, Allan; Herodes, Koit; Leito, Ivo

2008-04-11

Three sample preparation methods: Luke method (AOAC 985.22), QuEChERS (quick, easy, cheap, effective, rugged and safe) and matrix solid-phase dispersion (MSPD) were applied to different fruits and vegetables for analysis of 14 pesticide residues by high-performance liquid chromatography with electrospray ionization-mass spectrometry (HPLC/ESI/MS). Matrix effect, recovery and process efficiency of the sample preparation methods applied to different fruits and vegetables were compared. The Luke method was found to produce least matrix effect. On an average the best recoveries were obtained with the QuEChERS method. MSPD gave unsatisfactory recoveries for some basic pesticide residues. Comparison of matrix effects for different apple varieties showed high variability for some residues. It was demonstrated that the amount of co-extracting compounds that cause ionization suppression of aldicarb depends on the apple variety as well as on the sample preparation method employed.

Comparison of experimental methods for estimating matrix diffusion coefficients for contaminant transport modeling

DOE PAGES

Telfeyan, Katherine Christina; Ware, Stuart Doug; Reimus, Paul William; ...

2018-01-31

Here, diffusion cell and diffusion wafer experiments were conducted to compare methods for estimating effective matrix diffusion coefficients in rock core samples from Pahute Mesa at the Nevada Nuclear Security Site (NNSS). A diffusion wafer method, in which a solute diffuses out of a rock matrix that is pre-saturated with water containing the solute, is presented as a simpler alternative to the traditional through-diffusion (diffusion cell) method. Both methods yielded estimates of effective matrix diffusion coefficients that were within the range of values previously reported for NNSS volcanic rocks. The difference between the estimates of the two methods ranged frommore » 14 to 30%, and there was no systematic high or low bias of one method relative to the other. From a transport modeling perspective, these differences are relatively minor when one considers that other variables (e.g., fracture apertures, fracture spacings) influence matrix diffusion to a greater degree and tend to have greater uncertainty than effective matrix diffusion coefficients. For the same relative random errors in concentration measurements, the diffusion cell method yields effective matrix diffusion coefficient estimates that have less uncertainty than the wafer method. However, the wafer method is easier and less costly to implement and yields estimates more quickly, thus allowing a greater number of samples to be analyzed for the same cost and time. Given the relatively good agreement between the methods, and the lack of any apparent bias between the methods, the diffusion wafer method appears to offer advantages over the diffusion cell method if better statistical representation of a given set of rock samples is desired.« less

Comparison of experimental methods for estimating matrix diffusion coefficients for contaminant transport modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Telfeyan, Katherine Christina; Ware, Stuart Doug; Reimus, Paul William

Here, diffusion cell and diffusion wafer experiments were conducted to compare methods for estimating effective matrix diffusion coefficients in rock core samples from Pahute Mesa at the Nevada Nuclear Security Site (NNSS). A diffusion wafer method, in which a solute diffuses out of a rock matrix that is pre-saturated with water containing the solute, is presented as a simpler alternative to the traditional through-diffusion (diffusion cell) method. Both methods yielded estimates of effective matrix diffusion coefficients that were within the range of values previously reported for NNSS volcanic rocks. The difference between the estimates of the two methods ranged frommore » 14 to 30%, and there was no systematic high or low bias of one method relative to the other. From a transport modeling perspective, these differences are relatively minor when one considers that other variables (e.g., fracture apertures, fracture spacings) influence matrix diffusion to a greater degree and tend to have greater uncertainty than effective matrix diffusion coefficients. For the same relative random errors in concentration measurements, the diffusion cell method yields effective matrix diffusion coefficient estimates that have less uncertainty than the wafer method. However, the wafer method is easier and less costly to implement and yields estimates more quickly, thus allowing a greater number of samples to be analyzed for the same cost and time. Given the relatively good agreement between the methods, and the lack of any apparent bias between the methods, the diffusion wafer method appears to offer advantages over the diffusion cell method if better statistical representation of a given set of rock samples is desired.« less

Automated MALDI matrix deposition method with inkjet printing for imaging mass spectrometry.

PubMed

Baluya, Dodge L; Garrett, Timothy J; Yost, Richard A

2007-09-01

Careful matrix deposition on tissue samples for matrix-assisted laser desorption/ionization (MALDI) is critical for producing reproducible analyte ion signals. Traditional methods for matrix deposition are often considered an art rather than a science, with significant sample-to-sample variability. Here we report an automated method for matrix deposition, employing a desktop inkjet printer (<$200) with 5760 x 1440 dpi resolution and a six-channel piezoelectric head that delivers 3 pL/drop. The inkjet printer tray, designed to hold CDs and DVDs, was modified to hold microscope slides. Empty ink cartridges were filled with MALDI matrix solutions, including DHB in methanol/water (70:30) at concentrations up to 40 mg/mL. Various samples (including rat brain tissue sections and standards of small drug molecules) were prepared using three deposition methods (electrospray, airbrush, inkjet). A linear ion trap equipped with an intermediate-pressure MALDI source was used for analyses. Optical microscopic examination showed that matrix crystals were formed evenly across the sample. There was minimal background signal after storing the matrix in the cartridges over a 6-month period. Overall, the mass spectral images gathered from inkjet-printed tissue specimens were of better quality and more reproducible than from specimens prepared by the electrospray and airbrush methods.

Information matrix estimation procedures for cognitive diagnostic models.

PubMed

Liu, Yanlou; Xin, Tao; Andersson, Björn; Tian, Wei

2018-03-06

Two new methods to estimate the asymptotic covariance matrix for marginal maximum likelihood estimation of cognitive diagnosis models (CDMs), the inverse of the observed information matrix and the sandwich-type estimator, are introduced. Unlike several previous covariance matrix estimators, the new methods take into account both the item and structural parameters. The relationships between the observed information matrix, the empirical cross-product information matrix, the sandwich-type covariance matrix and the two approaches proposed by de la Torre (2009, J. Educ. Behav. Stat., 34, 115) are discussed. Simulation results show that, for a correctly specified CDM and Q-matrix or with a slightly misspecified probability model, the observed information matrix and the sandwich-type covariance matrix exhibit good performance with respect to providing consistent standard errors of item parameter estimates. However, with substantial model misspecification only the sandwich-type covariance matrix exhibits robust performance. © 2018 The British Psychological Society.

Lyophilic matrix method for dissolution and release studies of nanoscale particles.

PubMed

Pessi, Jenni; Svanbäck, Sami; Lassila, Ilkka; Hæggström, Edward; Yliruusi, Jouko

2017-10-25

We introduce a system with a lyophilic matrix to aid dissolution studies of powders and particulate systems. This lyophilic matrix method (LM method) is based on the ability to discriminate between non-dissolved particles and the dissolved species. In the LM method the test substance is embedded in a thin lyophilic core-shell matrix. This permits rapid contact with the dissolution medium while minimizing dispersion of non-dissolved particles without presenting a substantial diffusion barrier. The method produces realistic dissolution and release results for particulate systems, especially those featuring nanoscale particles. By minimizing method-induced effects on the dissolution profile of nanopowders, the LM method overcomes shortcomings associated with current dissolution tests. Copyright © 2017 Elsevier B.V. All rights reserved.

Chosen interval methods for solving linear interval systems with special type of matrix

NASA Astrophysics Data System (ADS)

Szyszka, Barbara

2013-10-01

The paper is devoted to chosen direct interval methods for solving linear interval systems with special type of matrix. This kind of matrix: band matrix with a parameter, from finite difference problem is obtained. Such linear systems occur while solving one dimensional wave equation (Partial Differential Equations of hyperbolic type) by using the central difference interval method of the second order. Interval methods are constructed so as the errors of method are enclosed in obtained results, therefore presented linear interval systems contain elements that determining the errors of difference method. The chosen direct algorithms have been applied for solving linear systems because they have no errors of method. All calculations were performed in floating-point interval arithmetic.

Non-negative matrix factorization in texture feature for classification of dementia with MRI data

NASA Astrophysics Data System (ADS)

Sarwinda, D.; Bustamam, A.; Ardaneswari, G.

2017-07-01

This paper investigates applications of non-negative matrix factorization as feature selection method to select the features from gray level co-occurrence matrix. The proposed approach is used to classify dementia using MRI data. In this study, texture analysis using gray level co-occurrence matrix is done to feature extraction. In the feature extraction process of MRI data, we found seven features from gray level co-occurrence matrix. Non-negative matrix factorization selected three features that influence of all features produced by feature extractions. A Naïve Bayes classifier is adapted to classify dementia, i.e. Alzheimer's disease, Mild Cognitive Impairment (MCI) and normal control. The experimental results show that non-negative factorization as feature selection method able to achieve an accuracy of 96.4% for classification of Alzheimer's and normal control. The proposed method also compared with other features selection methods i.e. Principal Component Analysis (PCA).

Matrix effect and recovery terminology issues in regulated drug bioanalysis.

PubMed

Huang, Yong; Shi, Robert; Gee, Winnie; Bonderud, Richard

2012-02-01

Understanding the meaning of the terms used in the bioanalytical method validation guidance is essential for practitioners to implement best practice. However, terms that have several meanings or that have different interpretations exist within bioanalysis, and this may give rise to differing practices. In this perspective we discuss an important but often confusing term - 'matrix effect (ME)' - in regulated drug bioanalysis. The ME can be interpreted as either the ionization change or the measurement bias of the method caused by the nonanalyte matrix. The ME definition dilemma makes its evaluation challenging. The matrix factor is currently used as a standard method for evaluation of ionization changes caused by the matrix in MS-based methods. Standard additions to pre-extraction samples have been suggested to evaluate the overall effects of a matrix from different sources on the analytical system, because it covers ionization variation and extraction recovery variation. We also provide our personal views on the term 'recovery'.

Automated MALDI Matrix Coating System for Multiple Tissue Samples for Imaging Mass Spectrometry

NASA Astrophysics Data System (ADS)

Mounfield, William P.; Garrett, Timothy J.

2012-03-01

Uniform matrix deposition on tissue samples for matrix-assisted laser desorption/ionization (MALDI) is key for reproducible analyte ion signals. Current methods often result in nonhomogenous matrix deposition, and take time and effort to produce acceptable ion signals. Here we describe a fully-automated method for matrix deposition using an enclosed spray chamber and spray nozzle for matrix solution delivery. A commercial air-atomizing spray nozzle was modified and combined with solenoid controlled valves and a Programmable Logic Controller (PLC) to control and deliver the matrix solution. A spray chamber was employed to contain the nozzle, sample, and atomized matrix solution stream, and to prevent any interference from outside conditions as well as allow complete control of the sample environment. A gravity cup was filled with MALDI matrix solutions, including DHB in chloroform/methanol (50:50) at concentrations up to 60 mg/mL. Various samples (including rat brain tissue sections) were prepared using two deposition methods (spray chamber, inkjet). A linear ion trap equipped with an intermediate-pressure MALDI source was used for analyses. Optical microscopic examination showed a uniform coating of matrix crystals across the sample. Overall, the mass spectral images gathered from tissues coated using the spray chamber system were of better quality and more reproducible than from tissue specimens prepared by the inkjet deposition method.

Automated MALDI matrix coating system for multiple tissue samples for imaging mass spectrometry.

PubMed

Mounfield, William P; Garrett, Timothy J

2012-03-01

Uniform matrix deposition on tissue samples for matrix-assisted laser desorption/ionization (MALDI) is key for reproducible analyte ion signals. Current methods often result in nonhomogenous matrix deposition, and take time and effort to produce acceptable ion signals. Here we describe a fully-automated method for matrix deposition using an enclosed spray chamber and spray nozzle for matrix solution delivery. A commercial air-atomizing spray nozzle was modified and combined with solenoid controlled valves and a Programmable Logic Controller (PLC) to control and deliver the matrix solution. A spray chamber was employed to contain the nozzle, sample, and atomized matrix solution stream, and to prevent any interference from outside conditions as well as allow complete control of the sample environment. A gravity cup was filled with MALDI matrix solutions, including DHB in chloroform/methanol (50:50) at concentrations up to 60 mg/mL. Various samples (including rat brain tissue sections) were prepared using two deposition methods (spray chamber, inkjet). A linear ion trap equipped with an intermediate-pressure MALDI source was used for analyses. Optical microscopic examination showed a uniform coating of matrix crystals across the sample. Overall, the mass spectral images gathered from tissues coated using the spray chamber system were of better quality and more reproducible than from tissue specimens prepared by the inkjet deposition method.

Compensation of matrix effects in gas chromatography-mass spectrometry analysis of pesticides using a combination of matrix matching and multiple isotopically labeled internal standards.

PubMed

Tsuchiyama, Tomoyuki; Katsuhara, Miki; Nakajima, Masahiro

2017-11-17

In the multi-residue analysis of pesticides using GC-MS, the quantitative results are adversely affected by a phenomenon known as the matrix effect. Although the use of matrix-matched standards is considered to be one of the most practical solutions to this problem, complete removal of the matrix effect is difficult in complex food matrices owing to their inconsistency. As a result, residual matrix effects can introduce analytical errors. To compensate for residual matrix effects, we have developed a novel method that employs multiple isotopically labeled internal standards (ILIS). The matrix effects of ILIS and pesticides were evaluated in spiked matrix extracts of various agricultural commodities, and the obtained data were subjected to simple statistical analysis. Based on the similarities between the patterns of variation in the analytical response, a total of 32 isotopically labeled compounds were assigned to 338 pesticides as internal standards. It was found that by utilizing multiple ILIS, residual matrix effects could be effectively compensated. The developed method exhibited superior quantitative performance compared with the common single-internal-standard method. The proposed method is more feasible for regulatory purposes than that using only predetermined correction factors and is considered to be promising for practical applications. Copyright © 2017 Elsevier B.V. All rights reserved.

Pre-form ceramic matrix composite cavity and method of forming and method of forming a ceramic matrix composite component

DOEpatents

Monaghan, Philip Harold; Delvaux, John McConnell; Taxacher, Glenn Curtis

2015-06-09

A pre-form CMC cavity and method of forming pre-form CMC cavity for a ceramic matrix component includes providing a mandrel, applying a base ply to the mandrel, laying-up at least one CMC ply on the base ply, removing the mandrel, and densifying the base ply and the at least one CMC ply. The remaining densified base ply and at least one CMC ply form a ceramic matrix component having a desired geometry and a cavity formed therein. Also provided is a method of forming a CMC component.

MATRIX DISCRIMINANT ANALYSIS WITH APPLICATION TO COLORIMETRIC SENSOR ARRAY DATA

PubMed Central

Suslick, Kenneth S.

2014-01-01

With the rapid development of nano-technology, a “colorimetric sensor array” (CSA) which is referred to as an optical electronic nose has been developed for the identification of toxicants. Unlike traditional sensors which rely on a single chemical interaction, CSA can measure multiple chemical interactions by using chemo-responsive dyes. The color changes of the chemo-responsive dyes are recorded before and after exposure to toxicants and serve as a template for classification. The color changes are digitalized in the form of a matrix with rows representing dye effects and columns representing the spectrum of colors. Thus, matrix-classification methods are highly desirable. In this article, we develop a novel classification method, matrix discriminant analysis (MDA), which is a generalization of linear discriminant analysis (LDA) for the data in matrix form. By incorporating the intrinsic matrix-structure of the data in discriminant analysis, the proposed method can improve CSA’s sensitivity and more importantly, specificity. A penalized MDA method, PMDA, is also introduced to further incorporate sparsity structure in discriminant function. Numerical studies suggest that the proposed MDA and PMDA methods outperform LDA and other competing discriminant methods for matrix predictors. The asymptotic consistency of MDA is also established. R code and data are available online as supplementary material. PMID:26783371

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

PubMed

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

2017-09-21

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

Recognition and defect detection of dot-matrix text via variation-model based learning

NASA Astrophysics Data System (ADS)

Ohyama, Wataru; Suzuki, Koushi; Wakabayashi, Tetsushi

2017-03-01

An algorithm for recognition and defect detection of dot-matrix text printed on products is proposed. Extraction and recognition of dot-matrix text contains several difficulties, which are not involved in standard camera-based OCR, that the appearance of dot-matrix characters is corrupted and broken by illumination, complex texture in the background and other standard characters printed on product packages. We propose a dot-matrix text extraction and recognition method which does not require any user interaction. The method employs detected location of corner points and classification score. The result of evaluation experiment using 250 images shows that recall and precision of extraction are 78.60% and 76.03%, respectively. Recognition accuracy of correctly extracted characters is 94.43%. Detecting printing defect of dot-matrix text is also important in the production scene to avoid illegal productions. We also propose a detection method for printing defect of dot-matrix characters. The method constructs a feature vector of which elements are classification scores of each character class and employs support vector machine to classify four types of printing defect. The detection accuracy of the proposed method is 96.68 %.

Biomimetic Mineralization on a Macroporous Cellulose-Based Matrix for Bone Regeneration

PubMed Central

Petrauskaite, Odeta; Gomes, Pedro de Sousa; Fernandes, Maria Helena; Juodzbalys, Gintaras; Maminskas, Julius

2013-01-01

The aim of this study is to investigate the biomimetic mineralization on a cellulose-based porous matrix with an improved biological profile. The cellulose matrix was precalcified using three methods: (i) cellulose samples were treated with a solution of calcium chloride and diammonium hydrogen phosphate; (ii) the carboxymethylated cellulose matrix was stored in a saturated calcium hydroxide solution; (iii) the cellulose matrix was mixed with a calcium silicate solution in order to introduce silanol groups and to combine them with calcium ions. All the methods resulted in a mineralization of the cellulose surfaces after immersion in a simulated body fluid solution. Over a period of 14 days, the matrix was completely covered with hydroxyapatite crystals. Hydroxyapatite formation depended on functional groups on the matrix surface as well as on the precalcification method. The largest hydroxyapatite crystals were obtained on the carboxymethylated cellulose matrix treated with calcium hydroxide solution. The porous cellulose matrix was not cytotoxic, allowing the adhesion and proliferation of human osteoblastic cells. Comparatively, improved cell adhesion and growth rate were achieved on the mineralized cellulose matrices. PMID:24163816

Enhancing interacting residue prediction with integrated contact matrix prediction in protein-protein interaction.

PubMed

Du, Tianchuan; Liao, Li; Wu, Cathy H

2016-12-01

Identifying the residues in a protein that are involved in protein-protein interaction and identifying the contact matrix for a pair of interacting proteins are two computational tasks at different levels of an in-depth analysis of protein-protein interaction. Various methods for solving these two problems have been reported in the literature. However, the interacting residue prediction and contact matrix prediction were handled by and large independently in those existing methods, though intuitively good prediction of interacting residues will help with predicting the contact matrix. In this work, we developed a novel protein interacting residue prediction system, contact matrix-interaction profile hidden Markov model (CM-ipHMM), with the integration of contact matrix prediction and the ipHMM interaction residue prediction. We propose to leverage what is learned from the contact matrix prediction and utilize the predicted contact matrix as "feedback" to enhance the interaction residue prediction. The CM-ipHMM model showed significant improvement over the previous method that uses the ipHMM for predicting interaction residues only. It indicates that the downstream contact matrix prediction could help the interaction site prediction.

A DEIM Induced CUR Factorization

DTIC Science & Technology

2015-09-18

CUR approximate matrix factorization based on the Discrete Empirical Interpolation Method (DEIM). For a given matrix A, such a factorization provides a...CUR approximations based on leverage scores. 1 Introduction This work presents a new CUR matrix factorization based upon the Discrete Empirical...SUPPLEMENTARY NOTES 14. ABSTRACT We derive a CUR approximate matrix factorization based on the Discrete Empirical Interpolation Method (DEIM). For a given

Phase matrix induced symmetrics for multiple scattering using the matrix operator method

NASA Technical Reports Server (NTRS)

Hitzfelder, S. J.; Kattawar, G. W.

1973-01-01

Entirely rigorous proofs of the symmetries induced by the phase matrix into the reflection and transmission operators used in the matrix operator theory are given. Results are obtained for multiple scattering in both homogeneous and inhomogeneous atmospheres. These results will be useful to researchers using the method since large savings in computer time and storage are obtainable.

Evidence of low molecular weight components in the organic matrix of the reef building coral, Stylophora pistillata.

PubMed

Puverel, S; Houlbrèque, F; Tambutté, E; Zoccola, D; Payan, P; Caminiti, N; Tambutté, S; Allemand, D

2007-08-01

Biominerals contain both inorganic and organic components. Organic components are collectively termed the organic matrix, and this matrix has been reported to play a crucial role in mineralization. Several matrix proteins have been characterized in vertebrates, but only a few in invertebrates, primarily in Molluscs and Echinoderms. Methods classically used to extract organic matrix proteins eliminate potential low molecular weight matrix components, since cut-offs ranging from 3.5 to 10 kDa are used to desalt matrix extracts. Consequently, the presence of such components remains unknown and these are never subjected to further analyses. In the present study, we have used microcolonies from the Scleractinian coral Stylophora pistillata to study newly synthesized matrix components by labelling them with 14C-labelled amino acids. Radioactive matrix components were investigated by a method in which both total organic matrix and fractions of matrix below and above 5 kDa were analyzed. Using this method and SDS-PAGE analyses, we were able to detect the presence of low molecular mass matrix components (<3.5 kDa), but no free amino acids in the skeletal organic matrix. Since more than 98% of the 14C-labelled amino acids were incorporated into low molecular weight molecules, these probably form the bulk of newly synthesized organic matrix components. Our results suggest that these low molecular weight components may be peptides, which can be involved in the regulation of coral skeleton mineralization.

Method of making molten carbonate fuel cell ceramic matrix tape

DOEpatents

Maricle, Donald L.; Putnam, Gary C.; Stewart, Jr., Robert C.

1984-10-23

A method of making a thin, flexible, pliable matrix material for a molten carbonate fuel cell is described. The method comprises admixing particles inert in the molten carbonate environment with an organic polymer binder and ceramic particle. The composition is applied to a mold surface and dried, and the formed compliant matrix material removed.

Modeling State-Space Aeroelastic Systems Using a Simple Matrix Polynomial Approach for the Unsteady Aerodynamics

NASA Technical Reports Server (NTRS)

Pototzky, Anthony S.

2008-01-01

A simple matrix polynomial approach is introduced for approximating unsteady aerodynamics in the s-plane and ultimately, after combining matrix polynomial coefficients with matrices defining the structure, a matrix polynomial of the flutter equations of motion (EOM) is formed. A technique of recasting the matrix-polynomial form of the flutter EOM into a first order form is also presented that can be used to determine the eigenvalues near the origin and everywhere on the complex plane. An aeroservoelastic (ASE) EOM have been generalized to include the gust terms on the right-hand side. The reasons for developing the new matrix polynomial approach are also presented, which are the following: first, the "workhorse" methods such as the NASTRAN flutter analysis lack the capability to consistently find roots near the origin, along the real axis or accurately find roots farther away from the imaginary axis of the complex plane; and, second, the existing s-plane methods, such as the Roger s s-plane approximation method as implemented in ISAC, do not always give suitable fits of some tabular data of the unsteady aerodynamics. A method available in MATLAB is introduced that will accurately fit generalized aerodynamic force (GAF) coefficients in a tabular data form into the coefficients of a matrix polynomial form. The root-locus results from the NASTRAN pknl flutter analysis, the ISAC-Roger's s-plane method and the present matrix polynomial method are presented and compared for accuracy and for the number and locations of roots.

Surrogate matrix and surrogate analyte approaches for definitive quantitation of endogenous biomolecules.

PubMed

Jones, Barry R; Schultz, Gary A; Eckstein, James A; Ackermann, Bradley L

2012-10-01

Quantitation of biomarkers by LC-MS/MS is complicated by the presence of endogenous analytes. This challenge is most commonly overcome by calibration using an authentic standard spiked into a surrogate matrix devoid of the target analyte. A second approach involves use of a stable-isotope-labeled standard as a surrogate analyte to allow calibration in the actual biological matrix. For both methods, parallelism between calibration standards and the target analyte in biological matrix must be demonstrated in order to ensure accurate quantitation. In this communication, the surrogate matrix and surrogate analyte approaches are compared for the analysis of five amino acids in human plasma: alanine, valine, methionine, leucine and isoleucine. In addition, methodology based on standard addition is introduced, which enables a robust examination of parallelism in both surrogate analyte and surrogate matrix methods prior to formal validation. Results from additional assays are presented to introduce the standard-addition methodology and to highlight the strengths and weaknesses of each approach. For the analysis of amino acids in human plasma, comparable precision and accuracy were obtained by the surrogate matrix and surrogate analyte methods. Both assays were well within tolerances prescribed by regulatory guidance for validation of xenobiotic assays. When stable-isotope-labeled standards are readily available, the surrogate analyte approach allows for facile method development. By comparison, the surrogate matrix method requires greater up-front method development; however, this deficit is offset by the long-term advantage of simplified sample analysis.

Systems and methods for deactivating a matrix converter

DOEpatents

Ransom, Ray M.

2013-04-02

Systems and methods are provided for deactivating a matrix conversion module. An electrical system comprises an alternating current (AC) interface, a matrix conversion module coupled to the AC interface, an inductive element coupled between the AC interface and the matrix conversion module, and a control module. The control module is coupled to the matrix conversion module, and in response to a shutdown condition, the control module is configured to operate the matrix conversion module to deactivate the first conversion module when a magnitude of a current through the inductive element is less than a threshold value.

Fission matrix-based Monte Carlo criticality analysis of fuel storage pools

DOE Office of Scientific and Technical Information (OSTI.GOV)

Farlotti, M.; Ecole Polytechnique, Palaiseau, F 91128; Larsen, E. W.

2013-07-01

Standard Monte Carlo transport procedures experience difficulties in solving criticality problems in fuel storage pools. Because of the strong neutron absorption between fuel assemblies, source convergence can be very slow, leading to incorrect estimates of the eigenvalue and the eigenfunction. This study examines an alternative fission matrix-based Monte Carlo transport method that takes advantage of the geometry of a storage pool to overcome this difficulty. The method uses Monte Carlo transport to build (essentially) a fission matrix, which is then used to calculate the criticality and the critical flux. This method was tested using a test code on a simplemore » problem containing 8 assemblies in a square pool. The standard Monte Carlo method gave the expected eigenfunction in 5 cases out of 10, while the fission matrix method gave the expected eigenfunction in all 10 cases. In addition, the fission matrix method provides an estimate of the error in the eigenvalue and the eigenfunction, and it allows the user to control this error by running an adequate number of cycles. Because of these advantages, the fission matrix method yields a higher confidence in the results than standard Monte Carlo. We also discuss potential improvements of the method, including the potential for variance reduction techniques. (authors)« less

Fatigue loading history reconstruction based on the rain-flow technique

NASA Technical Reports Server (NTRS)

Khosrovaneh, A. K.; Dowling, N. E.

1989-01-01

Methods are considered for reducing a non-random fatigue loading history to a concise description and then for reconstructing a time history similar to the original. In particular, three methods of reconstruction based on a rain-flow cycle counting matrix are presented. A rain-flow matrix consists of the numbers of cycles at various peak and valley combinations. Two methods are based on a two dimensional rain-flow matrix, and the third on a three dimensional rain-flow matrix. Histories reconstructed by any of these methods produce a rain-flow matrix identical to that of the original history, and as a result the resulting time history is expected to produce a fatigue life similar to that for the original. The procedures described allow lengthy loading histories to be stored in compact form.

Solving large sparse eigenvalue problems on supercomputers

NASA Technical Reports Server (NTRS)

Philippe, Bernard; Saad, Youcef

1988-01-01

An important problem in scientific computing consists in finding a few eigenvalues and corresponding eigenvectors of a very large and sparse matrix. The most popular methods to solve these problems are based on projection techniques on appropriate subspaces. The main attraction of these methods is that they only require the use of the matrix in the form of matrix by vector multiplications. The implementations on supercomputers of two such methods for symmetric matrices, namely Lanczos' method and Davidson's method are compared. Since one of the most important operations in these two methods is the multiplication of vectors by the sparse matrix, methods of performing this operation efficiently are discussed. The advantages and the disadvantages of each method are compared and implementation aspects are discussed. Numerical experiments on a one processor CRAY 2 and CRAY X-MP are reported. Possible parallel implementations are also discussed.

Method of making silicon carbide-silicon composite having improved oxidation resistance

NASA Technical Reports Server (NTRS)

Wang, Hongyu (Inventor); Luthra, Krishan Lal (Inventor)

2002-01-01

A Silicon carbide-silicon matrix composite having improved oxidation resistance at high temperatures in dry or water-containing environments is provided. A method is given for sealing matrix cracks in situ in melt infiltrated silicon carbide-silicon matrix composites. The composite cracks are sealed by the addition of various additives, such as boron compounds, into the melt infiltrated silicon carbide-silicon matrix.

Silicon carbide-silicon composite having improved oxidation resistance and method of making

NASA Technical Reports Server (NTRS)

Wang, Hongyu (Inventor); Luthra, Krishan Lal (Inventor)

1999-01-01

A Silicon carbide-silicon matrix composite having improved oxidation resistance at high temperatures in dry or water-containing environments is provided. A method is given for sealing matrix cracks in situ in melt infiltrated silicon carbide-silicon matrix composites. The composite cracks are sealed by the addition of various additives, such as boron compounds, into the melt infiltrated silicon carbide-silicon matrix.

A matrix-inversion method for gamma-source mapping from gamma-count data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Adsley, Ian; Burgess, Claire; Bull, Richard K

In a previous paper it was proposed that a simple matrix inversion method could be used to extract source distributions from gamma-count maps, using simple models to calculate the response matrix. The method was tested using numerically generated count maps. In the present work a 100 kBq Co{sup 60} source has been placed on a gridded surface and the count rate measured using a NaI scintillation detector. The resulting map of gamma counts was used as input to the matrix inversion procedure and the source position recovered. A multi-source array was simulated by superposition of several single-source count maps andmore » the source distribution was again recovered using matrix inversion. The measurements were performed for several detector heights. The effects of uncertainties in source-detector distances on the matrix inversion method are also examined. The results from this work give confidence in the application of the method to practical applications, such as the segregation of highly active objects amongst fuel-element debris. (authors)« less

The generalised Sylvester matrix equations over the generalised bisymmetric and skew-symmetric matrices

NASA Astrophysics Data System (ADS)

Dehghan, Mehdi; Hajarian, Masoud

2012-08-01

A matrix P is called a symmetric orthogonal if P = P T = P -1. A matrix X is said to be a generalised bisymmetric with respect to P if X = X T = PXP. It is obvious that any symmetric matrix is also a generalised bisymmetric matrix with respect to I (identity matrix). By extending the idea of the Jacobi and the Gauss-Seidel iterations, this article proposes two new iterative methods, respectively, for computing the generalised bisymmetric (containing symmetric solution as a special case) and skew-symmetric solutions of the generalised Sylvester matrix equation ? (including Sylvester and Lyapunov matrix equations as special cases) which is encountered in many systems and control applications. When the generalised Sylvester matrix equation has a unique generalised bisymmetric (skew-symmetric) solution, the first (second) iterative method converges to the generalised bisymmetric (skew-symmetric) solution of this matrix equation for any initial generalised bisymmetric (skew-symmetric) matrix. Finally, some numerical results are given to illustrate the effect of the theoretical results.

Attitude determination using vector observations: A fast optimal matrix algorithm

NASA Technical Reports Server (NTRS)

Markley, F. Landis

1993-01-01

The attitude matrix minimizing Wahba's loss function is computed directly by a method that is competitive with the fastest known algorithm for finding this optimal estimate. The method also provides an estimate of the attitude error covariance matrix. Analysis of the special case of two vector observations identifies those cases for which the TRIAD or algebraic method minimizes Wahba's loss function.

A Chebyshev matrix method for spatial modes of the Orr-Sommerfeld equation

NASA Technical Reports Server (NTRS)

Danabasoglu, G.; Biringen, S.

1989-01-01

The Chebyshev matrix collocation method is applied to obtain the spatial modes of the Orr-Sommerfeld equation for Poiseuille flow and the Blausius boundary layer. The problem is linearized by the companion matrix technique for semi-infinite domain using a mapping transformation. The method can be easily adapted to problems with different boundary conditions requiring different transformations.

Matrix form of Legendre polynomials for solving linear integro-differential equations of high order

NASA Astrophysics Data System (ADS)

Kammuji, M.; Eshkuvatov, Z. K.; Yunus, Arif A. M.

2017-04-01

This paper presents an effective approximate solution of high order of Fredholm-Volterra integro-differential equations (FVIDEs) with boundary condition. Legendre truncated series is used as a basis functions to estimate the unknown function. Matrix operation of Legendre polynomials is used to transform FVIDEs with boundary conditions into matrix equation of Fredholm-Volterra type. Gauss Legendre quadrature formula and collocation method are applied to transfer the matrix equation into system of linear algebraic equations. The latter equation is solved by Gauss elimination method. The accuracy and validity of this method are discussed by solving two numerical examples and comparisons with wavelet and methods.

Acoustic 3D modeling by the method of integral equations

NASA Astrophysics Data System (ADS)

Malovichko, M.; Khokhlov, N.; Yavich, N.; Zhdanov, M.

2018-02-01

This paper presents a parallel algorithm for frequency-domain acoustic modeling by the method of integral equations (IE). The algorithm is applied to seismic simulation. The IE method reduces the size of the problem but leads to a dense system matrix. A tolerable memory consumption and numerical complexity were achieved by applying an iterative solver, accompanied by an effective matrix-vector multiplication operation, based on the fast Fourier transform (FFT). We demonstrate that, the IE system matrix is better conditioned than that of the finite-difference (FD) method, and discuss its relation to a specially preconditioned FD matrix. We considered several methods of matrix-vector multiplication for the free-space and layered host models. The developed algorithm and computer code were benchmarked against the FD time-domain solution. It was demonstrated that, the method could accurately calculate the seismic field for the models with sharp material boundaries and a point source and receiver located close to the free surface. We used OpenMP to speed up the matrix-vector multiplication, while MPI was used to speed up the solution of the system equations, and also for parallelizing across multiple sources. The practical examples and efficiency tests are presented as well.

Adapting Covariance Propagation to Account for the Presence of Modeled and Unmodeled Maneuvers

NASA Technical Reports Server (NTRS)

Schiff, Conrad

2006-01-01

This paper explores techniques that can be used to adapt the standard linearized propagation of an orbital covariance matrix to the case where there is a maneuver and an associated execution uncertainty. A Monte Carlo technique is used to construct a final orbital covariance matrix for a 'prop-burn-prop' process that takes into account initial state uncertainty and execution uncertainties in the maneuver magnitude. This final orbital covariance matrix is regarded as 'truth' and comparisons are made with three methods using modified linearized covariance propagation. The first method accounts for the maneuver by modeling its nominal effect within the state transition matrix but excludes the execution uncertainty by omitting a process noise matrix from the computation. The second method does not model the maneuver but includes a process noise matrix to account for the uncertainty in its magnitude. The third method, which is essentially a hybrid of the first two, includes the nominal portion of the maneuver via the state transition matrix and uses a process noise matrix to account for the magnitude uncertainty. The first method is unable to produce the final orbit covariance except in the case of zero maneuver uncertainty. The second method yields good accuracy for the final covariance matrix but fails to model the final orbital state accurately. Agreement between the simulated covariance data produced by this method and the Monte Carlo truth data fell within 0.5-2.5 percent over a range of maneuver sizes that span two orders of magnitude (0.1-20 m/s). The third method, which yields a combination of good accuracy in the computation of the final covariance matrix and correct accounting for the presence of the maneuver in the nominal orbit, is the best method for applications involving the computation of times of closest approach and the corresponding probability of collision, PC. However, applications for the two other methods exist and are briefly discussed. Although the process model ("prop-burn-prop") that was studied is very simple - point-mass gravitational effects due to the Earth combined with an impulsive delta-V in the velocity direction for the maneuver - generalizations to more complex scenarios, including high fidelity force models, finite duration maneuvers, and maneuver pointing errors, are straightforward and are discussed in the conclusion.

Convergence of Transition Probability Matrix in CLVMarkov Models

NASA Astrophysics Data System (ADS)

Permana, D.; Pasaribu, U. S.; Indratno, S. W.; Suprayogi, S.

2018-04-01

A transition probability matrix is an arrangement of transition probability from one states to another in a Markov chain model (MCM). One of interesting study on the MCM is its behavior for a long time in the future. The behavior is derived from one property of transition probabilty matrix for n steps. This term is called the convergence of the n-step transition matrix for n move to infinity. Mathematically, the convergence of the transition probability matrix is finding the limit of the transition matrix which is powered by n where n moves to infinity. The convergence form of the transition probability matrix is very interesting as it will bring the matrix to its stationary form. This form is useful for predicting the probability of transitions between states in the future. The method usually used to find the convergence of transition probability matrix is through the process of limiting the distribution. In this paper, the convergence of the transition probability matrix is searched using a simple concept of linear algebra that is by diagonalizing the matrix.This method has a higher level of complexity because it has to perform the process of diagonalization in its matrix. But this way has the advantage of obtaining a common form of power n of the transition probability matrix. This form is useful to see transition matrix before stationary. For example cases are taken from CLV model using MCM called Model of CLV-Markov. There are several models taken by its transition probability matrix to find its convergence form. The result is that the convergence of the matrix of transition probability through diagonalization has similarity with convergence with commonly used distribution of probability limiting method.

Efficient Implementation of the Invariant Imbedding T-Matrix Method and the Separation of Variables Method Applied to Large Nonspherical Inhomogeneous Particles

NASA Technical Reports Server (NTRS)

Bi, Lei; Yang, Ping; Kattawar, George W.; Mishchenko, Michael I.

2012-01-01

Three terms, ''Waterman's T-matrix method'', ''extended boundary condition method (EBCM)'', and ''null field method'', have been interchangeable in the literature to indicate a method based on surface integral equations to calculate the T-matrix. Unlike the previous method, the invariant imbedding method (IIM) calculates the T-matrix by the use of a volume integral equation. In addition, the standard separation of variables method (SOV) can be applied to compute the T-matrix of a sphere centered at the origin of the coordinate system and having a maximal radius such that the sphere remains inscribed within a nonspherical particle. This study explores the feasibility of a numerical combination of the IIM and the SOV, hereafter referred to as the IIMþSOV method, for computing the single-scattering properties of nonspherical dielectric particles, which are, in general, inhomogeneous. The IIMþSOV method is shown to be capable of solving light-scattering problems for large nonspherical particles where the standard EBCM fails to converge. The IIMþSOV method is flexible and applicable to inhomogeneous particles and aggregated nonspherical particles (overlapped circumscribed spheres) representing a challenge to the standard superposition T-matrix method. The IIMþSOV computational program, developed in this study, is validated against EBCM simulated spheroid and cylinder cases with excellent numerical agreement (up to four decimal places). In addition, solutions for cylinders with large aspect ratios, inhomogeneous particles, and two-particle systems are compared with results from discrete dipole approximation (DDA) computations, and comparisons with the improved geometric-optics method (IGOM) are found to be quite encouraging.

Structured Matrix Completion with Applications to Genomic Data Integration.

PubMed

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.

MRL and SuperFine+MRL: new supertree methods

PubMed Central

2012-01-01

Background Supertree methods combine trees on subsets of the full taxon set together to produce a tree on the entire set of taxa. Of the many supertree methods, the most popular is MRP (Matrix Representation with Parsimony), a method that operates by first encoding the input set of source trees by a large matrix (the "MRP matrix") over {0,1, ?}, and then running maximum parsimony heuristics on the MRP matrix. Experimental studies evaluating MRP in comparison to other supertree methods have established that for large datasets, MRP generally produces trees of equal or greater accuracy than other methods, and can run on larger datasets. A recent development in supertree methods is SuperFine+MRP, a method that combines MRP with a divide-and-conquer approach, and produces more accurate trees in less time than MRP. In this paper we consider a new approach for supertree estimation, called MRL (Matrix Representation with Likelihood). MRL begins with the same MRP matrix, but then analyzes the MRP matrix using heuristics (such as RAxML) for 2-state Maximum Likelihood. Results We compared MRP and SuperFine+MRP with MRL and SuperFine+MRL on simulated and biological datasets. We examined the MRP and MRL scores of each method on a wide range of datasets, as well as the resulting topological accuracy of the trees. Our experimental results show that MRL, coupled with a very good ML heuristic such as RAxML, produced more accurate trees than MRP, and MRL scores were more strongly correlated with topological accuracy than MRP scores. Conclusions SuperFine+MRP, when based upon a good MP heuristic, such as TNT, produces among the best scores for both MRP and MRL, and is generally faster and more topologically accurate than other supertree methods we tested. PMID:22280525

Application of the R-matrix method to photoionization of molecules.

PubMed

Tashiro, Motomichi

2010-04-07

The R-matrix method has been used for theoretical calculation of electron collision with atoms and molecules for long years. The method was also formulated to treat photoionization process, however, its application has been mostly limited to photoionization of atoms. In this work, we implement the R-matrix method to treat molecular photoionization problem based on the UK R-matrix codes. This method can be used for diatomic as well as polyatomic molecules, with multiconfigurational description for electronic states of both target neutral molecule and product molecular ion. Test calculations were performed for valence electron photoionization of nitrogen (N(2)) as well as nitric oxide (NO) molecules. Calculated photoionization cross sections and asymmetry parameters agree reasonably well with the available experimental results, suggesting usefulness of the method for molecular photoionization.

Method of multivariate spectral analysis

DOEpatents

Keenan, Michael R.; Kotula, Paul G.

2004-01-06

A method of determining the properties of a sample from measured spectral data collected from the sample by performing a multivariate spectral analysis. The method can include: generating a two-dimensional matrix A containing measured spectral data; providing a weighted spectral data matrix D by performing a weighting operation on matrix A; factoring D into the product of two matrices, C and S.sup.T, by performing a constrained alternating least-squares analysis of D=CS.sup.T, where C is a concentration intensity matrix and S is a spectral shapes matrix; unweighting C and S by applying the inverse of the weighting used previously; and determining the properties of the sample by inspecting C and S. This method can be used to analyze X-ray spectral data generated by operating a Scanning Electron Microscope (SEM) with an attached Energy Dispersive Spectrometer (EDS).

Method of waste stabilization with dewatered chemically bonded phosphate ceramics

DOEpatents

Wagh, Arun; Maloney, Martin D.

2010-06-29

A method of stabilizing a waste in a chemically bonded phosphate ceramic (CBPC). The method consists of preparing a slurry including the waste, water, an oxide binder, and a phosphate binder. The slurry is then allowed to cure to a solid, hydrated CBPC matrix. Next, bound water within the solid, hydrated CBPC matrix is removed. Typically, the bound water is removed by applying heat to the cured CBPC matrix. Preferably, the quantity of heat applied to the cured CBPC matrix is sufficient to drive off water bound within the hydrated CBPC matrix, but not to volatalize other non-water components of the matrix, such as metals and radioactive components. Typically, a temperature range of between 100.degree. C.-200.degree. C. will be sufficient. In another embodiment of the invention wherein the waste and water have been mixed prior to the preparation of the slurry, a select amount of water may be evaporated from the waste and water mixture prior to preparation of the slurry. Another aspect of the invention is a direct anyhydrous CBPC fabrication method wherein water is removed from the slurry by heating and mixing the slurry while allowing the slurry to cure. Additional aspects of the invention are ceramic matrix waste forms prepared by the methods disclosed above.

Drawing a different picture with pencil lead as matrix-assisted laser desorption/ionization matrix for fullerene derivatives.

PubMed

Nye, Leanne C; Hungerbühler, Hartmut; Drewello, Thomas

2018-02-01

Inspired by reports on the use of pencil lead as a matrix-assisted laser desorption/ionization matrix, paving the way towards matrix-free matrix-assisted laser desorption/ionization, the present investigation evaluates its usage with organic fullerene derivatives. Currently, this class of compounds is best analysed using the electron transfer matrix trans-2-[3-(4-tert-butylphenyl)-2-methyl-2-propenylidene] malononitrile (DCTB), which was employed as the standard here. The suitability of pencil lead was additionally compared to direct (i.e. no matrix) laser desorption/ionization-mass spectrometry. The use of (DCTB) was identified as the by far gentler method, producing spectra with abundant molecular ion signals and much reduced fragmentation. Analytically, pencil lead was found to be ineffective as a matrix, however, appears to be an extremely easy and inexpensive method for producing sodium and potassium adducts.

Solution of matrix equations using sparse techniques

NASA Technical Reports Server (NTRS)

Baddourah, Majdi

1994-01-01

The solution of large systems of matrix equations is key to the solution of a large number of scientific and engineering problems. This talk describes the sparse matrix solver developed at Langley which can routinely solve in excess of 263,000 equations in 40 seconds on one Cray C-90 processor. It appears that for large scale structural analysis applications, sparse matrix methods have a significant performance advantage over other methods.

Background recovery via motion-based robust principal component analysis with matrix factorization

NASA Astrophysics Data System (ADS)

Pan, Peng; Wang, Yongli; Zhou, Mingyuan; Sun, Zhipeng; He, Guoping

2018-03-01

Background recovery is a key technique in video analysis, but it still suffers from many challenges, such as camouflage, lighting changes, and diverse types of image noise. Robust principal component analysis (RPCA), which aims to recover a low-rank matrix and a sparse matrix, is a general framework for background recovery. The nuclear norm is widely used as a convex surrogate for the rank function in RPCA, which requires computing the singular value decomposition (SVD), a task that is increasingly costly as matrix sizes and ranks increase. However, matrix factorization greatly reduces the dimension of the matrix for which the SVD must be computed. Motion information has been shown to improve low-rank matrix recovery in RPCA, but this method still finds it difficult to handle original video data sets because of its batch-mode formulation and implementation. Hence, in this paper, we propose a motion-assisted RPCA model with matrix factorization (FM-RPCA) for background recovery. Moreover, an efficient linear alternating direction method of multipliers with a matrix factorization (FL-ADM) algorithm is designed for solving the proposed FM-RPCA model. Experimental results illustrate that the method provides stable results and is more efficient than the current state-of-the-art algorithms.

The performance evaluation model of mining project founded on the weight optimization entropy value method

NASA Astrophysics Data System (ADS)

Mao, Chao; Chen, Shou

2017-01-01

According to the traditional entropy value method still have low evaluation accuracy when evaluating the performance of mining projects, a performance evaluation model of mineral project founded on improved entropy is proposed. First establish a new weight assignment model founded on compatible matrix analysis of analytic hierarchy process (AHP) and entropy value method, when the compatibility matrix analysis to achieve consistency requirements, if it has differences between subjective weights and objective weights, moderately adjust both proportions, then on this basis, the fuzzy evaluation matrix for performance evaluation. The simulation experiments show that, compared with traditional entropy and compatible matrix analysis method, the proposed performance evaluation model of mining project based on improved entropy value method has higher accuracy assessment.

Tensor-GMRES method for large sparse systems of nonlinear equations

NASA Technical Reports Server (NTRS)

Feng, Dan; Pulliam, Thomas H.

1994-01-01

This paper introduces a tensor-Krylov method, the tensor-GMRES method, for large sparse systems of nonlinear equations. This method is a coupling of tensor model formation and solution techniques for nonlinear equations with Krylov subspace projection techniques for unsymmetric systems of linear equations. Traditional tensor methods for nonlinear equations are based on a quadratic model of the nonlinear function, a standard linear model augmented by a simple second order term. These methods are shown to be significantly more efficient than standard methods both on nonsingular problems and on problems where the Jacobian matrix at the solution is singular. A major disadvantage of the traditional tensor methods is that the solution of the tensor model requires the factorization of the Jacobian matrix, which may not be suitable for problems where the Jacobian matrix is large and has a 'bad' sparsity structure for an efficient factorization. We overcome this difficulty by forming and solving the tensor model using an extension of a Newton-GMRES scheme. Like traditional tensor methods, we show that the new tensor method has significant computational advantages over the analogous Newton counterpart. Consistent with Krylov subspace based methods, the new tensor method does not depend on the factorization of the Jacobian matrix. As a matter of fact, the Jacobian matrix is never needed explicitly.

A three dimensional point cloud registration method based on rotation matrix eigenvalue

NASA Astrophysics Data System (ADS)

Wang, Chao; Zhou, Xiang; Fei, Zixuan; Gao, Xiaofei; Jin, Rui

2017-09-01

We usually need to measure an object at multiple angles in the traditional optical three-dimensional measurement method, due to the reasons for the block, and then use point cloud registration methods to obtain a complete threedimensional shape of the object. The point cloud registration based on a turntable is essential to calculate the coordinate transformation matrix between the camera coordinate system and the turntable coordinate system. We usually calculate the transformation matrix by fitting the rotation center and the rotation axis normal of the turntable in the traditional method, which is limited by measuring the field of view. The range of exact feature points used for fitting the rotation center and the rotation axis normal is approximately distributed within an arc less than 120 degrees, resulting in a low fit accuracy. In this paper, we proposes a better method, based on the invariant eigenvalue principle of rotation matrix in the turntable coordinate system and the coordinate transformation matrix of the corresponding coordinate points. First of all, we control the rotation angle of the calibration plate with the turntable to calibrate the coordinate transformation matrix of the corresponding coordinate points by using the least squares method. And then we use the feature decomposition to calculate the coordinate transformation matrix of the camera coordinate system and the turntable coordinate system. Compared with the traditional previous method, it has a higher accuracy, better robustness and it is not affected by the camera field of view. In this method, the coincidence error of the corresponding points on the calibration plate after registration is less than 0.1mm.

Sparse Matrix for ECG Identification with Two-Lead Features.

PubMed

Tseng, Kuo-Kun; Luo, Jiao; Hegarty, Robert; Wang, Wenmin; Haiting, Dong

2015-01-01

Electrocardiograph (ECG) human identification has the potential to improve biometric security. However, improvements in ECG identification and feature extraction are required. Previous work has focused on single lead ECG signals. Our work proposes a new algorithm for human identification by mapping two-lead ECG signals onto a two-dimensional matrix then employing a sparse matrix method to process the matrix. And that is the first application of sparse matrix techniques for ECG identification. Moreover, the results of our experiments demonstrate the benefits of our approach over existing methods.

Efficient l1 -norm-based low-rank matrix approximations for large-scale problems using alternating rectified gradient method.

PubMed

Kim, Eunwoo; Lee, Minsik; Choi, Chong-Ho; Kwak, Nojun; Oh, Songhwai

2015-02-01

Low-rank matrix approximation plays an important role in the area of computer vision and image processing. Most of the conventional low-rank matrix approximation methods are based on the l2 -norm (Frobenius norm) with principal component analysis (PCA) being the most popular among them. However, this can give a poor approximation for data contaminated by outliers (including missing data), because the l2 -norm exaggerates the negative effect of outliers. Recently, to overcome this problem, various methods based on the l1 -norm, such as robust PCA methods, have been proposed for low-rank matrix approximation. Despite the robustness of the methods, they require heavy computational effort and substantial memory for high-dimensional data, which is impractical for real-world problems. In this paper, we propose two efficient low-rank factorization methods based on the l1 -norm that find proper projection and coefficient matrices using the alternating rectified gradient method. The proposed methods are applied to a number of low-rank matrix approximation problems to demonstrate their efficiency and robustness. The experimental results show that our proposals are efficient in both execution time and reconstruction performance unlike other state-of-the-art methods.

Finding a Hadamard matrix by simulated annealing of spin vectors

NASA Astrophysics Data System (ADS)

Bayu Suksmono, Andriyan

2017-05-01

Reformulation of a combinatorial problem into optimization of a statistical-mechanics system enables finding a better solution using heuristics derived from a physical process, such as by the simulated annealing (SA). In this paper, we present a Hadamard matrix (H-matrix) searching method based on the SA on an Ising model. By equivalence, an H-matrix can be converted into a seminormalized Hadamard (SH) matrix, whose first column is unit vector and the rest ones are vectors with equal number of -1 and +1 called SH-vectors. We define SH spin vectors as representation of the SH vectors, which play a similar role as the spins on Ising model. The topology of the lattice is generalized into a graph, whose edges represent orthogonality relationship among the SH spin vectors. Starting from a randomly generated quasi H-matrix Q, which is a matrix similar to the SH-matrix without imposing orthogonality, we perform the SA. The transitions of Q are conducted by random exchange of {+, -} spin-pair within the SH-spin vectors that follow the Metropolis update rule. Upon transition toward zeroth energy, the Q-matrix is evolved following a Markov chain toward an orthogonal matrix, at which the H-matrix is said to be found. We demonstrate the capability of the proposed method to find some low-order H-matrices, including the ones that cannot trivially be constructed by the Sylvester method.

Mueller matrix imaging study to detect the dental demineralization

NASA Astrophysics Data System (ADS)

Chen, Qingguang; Shen, Huanbo; Wang, Binqiang

2018-01-01

Mueller matrix is an optical parameter invasively to reveal the structure information of anisotropic material. Dental tissue has the ordered structure including dental enamel prism and dentinal tubule. The ordered structure of teeth surface will be destroyed by demineralization. The structure information has the possibility to reflect the dental demineralization. In the paper, the experiment setup was built to obtain the Mueller matrix images based on the dual- wave plate rotation method. Two linear polarizer and two quarter-wave plate were rotated by electric control revolving stage respectively to capture 16 images at different group of polarization states. Therefore, Mueller matrix image can be calculated from the 16 images. On this basis, depolarization index, the diattenuation index and retardance index of the Mueller matrix were analyzed by Lu-Chipman polarization decomposition method. Mueller matrix images of artificial demineralized enamels at different stages were analyzed and the results show the possibility to detect the dental demineralization using Mueller matrix imaging method.

Flexible multiply towpreg and method of production therefor

NASA Technical Reports Server (NTRS)

Muzzy, John D. (Inventor); Varughese, Babu (Inventor)

1992-01-01

This invention relates to an improved flexible towpreg and a method of production therefor. The improved flexible towpreg comprises a plurality of towpreg plies which comprise reinforcing filaments and matrix forming material; the reinforcing filaments being substantially wetout by the matrix forming material such that the towpreg plies are substantially void-free composite articles, and the towpreg plies having an average thickness less than about 100 microns. The method of production for the improved flexible towpreg comprises the steps of spreading the reinforcing filaments to expose individually substantially all of the reinforcing filaments; coating the reinforcing filaments with the matrix forming material in a manner causing interfacial adhesion of the matrix forming material to the reinforcing filaments; forming the towpreg plies by heating the matrix forming material contacting the reinforcing filaments until the matrix forming material liquefies and coats the reinforcing filaments; and cooling the towpreg plies in a manner such that substantial cohesion between neighboring towpreg plies is prevented until the matrix forming material solidifies.

Method for preparing porous metal hydride compacts

DOEpatents

Ron, M.; Gruen, D.M.; Mendelsohn, M.H.; Sheft, I.

1980-01-21

A method for preparing porous metallic-matrix hydride compacts which can be repeatedly hydrided and dehydrided without disintegration. A mixture of a finely divided metal hydride and a finely divided matrix metal is contacted with a poison which prevents the metal hydride from dehydriding at room temperature and atmospheric pressure. The mixture of matrix metal and poisoned metal hydride is then compacted under pressure at room temperature to form porous metallic-matrix hydride compacts.

Method for preparing porous metal hydride compacts

DOEpatents

Ron, Moshe; Gruen, Dieter M.; Mendelsohn, Marshall H.; Sheft, Irving

1981-01-01

A method for preparing porous metallic-matrix hydride compacts which can be repeatedly hydrided and dehydrided without disintegration. A mixture of a finely divided metal hydride and a finely divided matrix metal is contacted with a poison which prevents the metal hydride from dehydriding at room temperature and atmospheric pressure. The mixture of matrix metal and poisoned metal hydride is then compacted under pressure at room temperature to form porous metallic-matrix hydride compacts.

Massively parallel sparse matrix function calculations with NTPoly

NASA Astrophysics Data System (ADS)

Dawson, William; Nakajima, Takahito

2018-04-01

We present NTPoly, a massively parallel library for computing the functions of sparse, symmetric matrices. The theory of matrix functions is a well developed framework with a wide range of applications including differential equations, graph theory, and electronic structure calculations. One particularly important application area is diagonalization free methods in quantum chemistry. When the input and output of the matrix function are sparse, methods based on polynomial expansions can be used to compute matrix functions in linear time. We present a library based on these methods that can compute a variety of matrix functions. Distributed memory parallelization is based on a communication avoiding sparse matrix multiplication algorithm. OpenMP task parallellization is utilized to implement hybrid parallelization. We describe NTPoly's interface and show how it can be integrated with programs written in many different programming languages. We demonstrate the merits of NTPoly by performing large scale calculations on the K computer.

Noniterative MAP reconstruction using sparse matrix representations.

PubMed

Cao, Guangzhi; Bouman, Charles A; Webb, Kevin J

2009-09-01

We present a method for noniterative maximum a posteriori (MAP) tomographic reconstruction which is based on the use of sparse matrix representations. Our approach is to precompute and store the inverse matrix required for MAP reconstruction. This approach has generally not been used in the past because the inverse matrix is typically large and fully populated (i.e., not sparse). In order to overcome this problem, we introduce two new ideas. The first idea is a novel theory for the lossy source coding of matrix transformations which we refer to as matrix source coding. This theory is based on a distortion metric that reflects the distortions produced in the final matrix-vector product, rather than the distortions in the coded matrix itself. The resulting algorithms are shown to require orthonormal transformations of both the measurement data and the matrix rows and columns before quantization and coding. The second idea is a method for efficiently storing and computing the required orthonormal transformations, which we call a sparse-matrix transform (SMT). The SMT is a generalization of the classical FFT in that it uses butterflies to compute an orthonormal transform; but unlike an FFT, the SMT uses the butterflies in an irregular pattern, and is numerically designed to best approximate the desired transforms. We demonstrate the potential of the noniterative MAP reconstruction with examples from optical tomography. The method requires offline computation to encode the inverse transform. However, once these offline computations are completed, the noniterative MAP algorithm is shown to reduce both storage and computation by well over two orders of magnitude, as compared to a linear iterative reconstruction methods.

Method for the removal and recovery of mercury

DOEpatents

Easterly, Clay E.; Vass, Arpad A.; Tyndall, Richard L.

1997-01-01

The present invention is an enhanced method for the removal and recovery of mercury from mercury-contaminated matrices. The method involves contacting a mercury-contaminated matrix with an aqueous dispersant solution derived from specific intra-amoebic isolates to release the mercury from the mercury-contaminated matrix and emulsify the mercury; then, contacting the matrix with an amalgamating metal from a metal source to amalgamate the mercury to the amalgamating metal; removing the metallic source from the mercury-contaminated matrix; and heating the metallic source to vaporize the mercury in a closed system to capture the mercury vapors.

Method for the removal and recovery of mercury

DOEpatents

Easterly, C.E.; Vass, A.A.; Tyndall, R.L.

1997-01-28

The present invention is an enhanced method for the removal and recovery of mercury from mercury-contaminated matrices. The method involves contacting a mercury-contaminated matrix with an aqueous dispersant solution derived from specific intra-amoebic isolates to release the mercury from the mercury-contaminated matrix and emulsify the mercury; then, contacting the matrix with an amalgamating metal from a metal source to amalgamate the mercury to the amalgamating metal; removing the metallic source from the mercury-contaminated matrix; and heating the metallic source to vaporize the mercury in a closed system to capture the mercury vapors.

Hybrid matrix fiber composites

DOEpatents

Deteresa, Steven J.; Lyon, Richard E.; Groves, Scott E.

2003-07-15

Hybrid matrix fiber composites having enhanced compressive performance as well as enhanced stiffness, toughness and durability suitable for compression-critical applications. The methods for producing the fiber composites using matrix hybridization. The hybrid matrix fiber composites include two chemically or physically bonded matrix materials, whereas the first matrix materials are used to impregnate multi-filament fibers formed into ribbons and the second matrix material is placed around and between the fiber ribbons that are impregnated with the first matrix material and both matrix materials are cured and solidified.

Electrical condition monitoring method for polymers

DOEpatents

Watkins, Jr., Kenneth S.; Morris, Shelby J [Hampton, VA; Masakowski, Daniel D [Worcester, MA; Wong, Ching Ping [Duluth, GA; Luo, Shijian [Boise, ID

2008-08-19

An electrical condition monitoring method utilizes measurement of electrical resistivity of an age sensor made of a conductive matrix or composite disposed in a polymeric structure such as an electrical cable. The conductive matrix comprises a base polymer and conductive filler. The method includes communicating the resistivity to a measuring instrument and correlating resistivity of the conductive matrix of the polymeric structure with resistivity of an accelerated-aged conductive composite.

A pedagogical derivation of the matrix element method in particle physics data analysis

NASA Astrophysics Data System (ADS)

Sumowidagdo, Suharyo

2018-03-01

The matrix element method provides a direct connection between the underlying theory of particle physics processes and detector-level physical observables. I am presenting a pedagogically-oriented derivation of the matrix element method, drawing from elementary concepts in probability theory, statistics, and the process of experimental measurements. The level of treatment should be suitable for beginning research student in phenomenology and experimental high energy physics.

Method of bonding diamonds in a matrix and articles thus produced

DOEpatents

Taylor, G.W.

1981-01-27

By fluorinating diamond grit, the grit may be readily bonded into a fluorocarbon resin matrix. The matrix is formed by simple hot pressing techniques. Diamond grinding wheels may advantageously be manufactured using such a matrix. Teflon fluorocarbon resins are particularly well suited for using in forming the matrix.

Multi-Shot Sensitivity-Encoded Diffusion Data Recovery Using Structured Low-Rank Matrix Completion (MUSSELS)

PubMed Central

Mani, Merry; Jacob, Mathews; Kelley, Douglas; Magnotta, Vincent

2017-01-01

Purpose To introduce a novel method for the recovery of multi-shot diffusion weighted (MS-DW) images from echo-planar imaging (EPI) acquisitions. Methods Current EPI-based MS-DW reconstruction methods rely on the explicit estimation of the motion-induced phase maps to recover artifact-free images. In the new formulation, the k-space data of the artifact-free DWI is recovered using a structured low-rank matrix completion scheme, which does not require explicit estimation of the phase maps. The structured matrix is obtained as the lifting of the multi-shot data. The smooth phase-modulations between shots manifest as null-space vectors of this matrix, which implies that the structured matrix is low-rank. The missing entries of the structured matrix are filled in using a nuclear-norm minimization algorithm subject to the data-consistency. The formulation enables the natural introduction of smoothness regularization, thus enabling implicit motion-compensated recovery of the MS-DW data. Results Our experiments on in-vivo data show effective removal of artifacts arising from inter-shot motion using the proposed method. The method is shown to achieve better reconstruction than the conventional phase-based methods. Conclusion We demonstrate the utility of the proposed method to effectively recover artifact-free images from Cartesian fully/under-sampled and partial Fourier acquired data without the use of explicit phase estimates. PMID:27550212

Combining kernel matrix optimization and regularization to improve particle size distribution retrieval

NASA Astrophysics Data System (ADS)

Ma, Qian; Xia, Houping; Xu, Qiang; Zhao, Lei

2018-05-01

A new method combining Tikhonov regularization and kernel matrix optimization by multi-wavelength incidence is proposed for retrieving particle size distribution (PSD) in an independent model with improved accuracy and stability. In comparison to individual regularization or multi-wavelength least squares, the proposed method exhibited better anti-noise capability, higher accuracy and stability. While standard regularization typically makes use of the unit matrix, it is not universal for different PSDs, particularly for Junge distributions. Thus, a suitable regularization matrix was chosen by numerical simulation, with the second-order differential matrix found to be appropriate for most PSD types.

Model reduction of nonsquare linear MIMO systems using multipoint matrix continued-fraction expansions

NASA Technical Reports Server (NTRS)

Guo, Tong-Yi; Hwang, Chyi; Shieh, Leang-San

1994-01-01

This paper deals with the multipoint Cauer matrix continued-fraction expansion (MCFE) for model reduction of linear multi-input multi-output (MIMO) systems with various numbers of inputs and outputs. A salient feature of the proposed MCFE approach to model reduction of MIMO systems with square transfer matrices is its equivalence to the matrix Pade approximation approach. The Cauer second form of the ordinary MCFE for a square transfer function matrix is generalized in this paper to a multipoint and nonsquare-matrix version. An interesting connection of the multipoint Cauer MCFE method to the multipoint matrix Pade approximation method is established. Also, algorithms for obtaining the reduced-degree matrix-fraction descriptions and reduced-dimensional state-space models from a transfer function matrix via the multipoint Cauer MCFE algorithm are presented. Practical advantages of using the multipoint Cauer MCFE are discussed and a numerical example is provided to illustrate the algorithms.

Matrix suppression as a guideline for reliable quantification of peptides by matrix-assisted laser desorption ionization.

PubMed

Ahn, Sung Hee; Bae, Yong Jin; Moon, Jeong Hee; Kim, Myung Soo

2013-09-17

We propose to divide matrix suppression in matrix-assisted laser desorption ionization into two parts, normal and anomalous. In quantification of peptides, the normal effect can be accounted for by constructing the calibration curve in the form of peptide-to-matrix ion abundance ratio versus concentration. The anomalous effect forbids reliable quantification and is noticeable when matrix suppression is larger than 70%. With this 70% rule, matrix suppression becomes a guideline for reliable quantification, rather than a nuisance. A peptide in a complex mixture can be quantified even in the presence of large amounts of contaminants, as long as matrix suppression is below 70%. The theoretical basis for the quantification method using a peptide as an internal standard is presented together with its weaknesses. A systematic method to improve quantification of high concentration analytes has also been developed.

Rapid construction of pinhole SPECT system matrices by distance-weighted Gaussian interpolation method combined with geometric parameter estimations

NASA Astrophysics Data System (ADS)

Lee, Ming-Wei; Chen, Yi-Chun

2014-02-01

In pinhole SPECT applied to small-animal studies, it is essential to have an accurate imaging system matrix, called H matrix, for high-spatial-resolution image reconstructions. Generally, an H matrix can be obtained by various methods, such as measurements, simulations or some combinations of both methods. In this study, a distance-weighted Gaussian interpolation method combined with geometric parameter estimations (DW-GIMGPE) is proposed. It utilizes a simplified grid-scan experiment on selected voxels and parameterizes the measured point response functions (PRFs) into 2D Gaussians. The PRFs of missing voxels are interpolated by the relations between the Gaussian coefficients and the geometric parameters of the imaging system with distance-weighting factors. The weighting factors are related to the projected centroids of voxels on the detector plane. A full H matrix is constructed by combining the measured and interpolated PRFs of all voxels. The PRFs estimated by DW-GIMGPE showed similar profiles as the measured PRFs. OSEM reconstructed images of a hot-rod phantom and normal rat myocardium demonstrated the effectiveness of the proposed method. The detectability of a SKE/BKE task on a synthetic spherical test object verified that the constructed H matrix provided comparable detectability to that of the H matrix acquired by a full 3D grid-scan experiment. The reduction in the acquisition time of a full 1.0-mm grid H matrix was about 15.2 and 62.2 times with the simplified grid pattern on 2.0-mm and 4.0-mm grid, respectively. A finer-grid H matrix down to 0.5-mm spacing interpolated by the proposed method would shorten the acquisition time by 8 times, additionally.

Super-resolution Doppler beam sharpening method using fast iterative adaptive approach-based spectral estimation

NASA Astrophysics Data System (ADS)

Mao, Deqing; Zhang, Yin; Zhang, Yongchao; Huang, Yulin; Yang, Jianyu

2018-01-01

Doppler beam sharpening (DBS) is a critical technology for airborne radar ground mapping in forward-squint region. In conventional DBS technology, the narrow-band Doppler filter groups formed by fast Fourier transform (FFT) method suffer from low spectral resolution and high side lobe levels. The iterative adaptive approach (IAA), based on the weighted least squares (WLS), is applied to the DBS imaging applications, forming narrower Doppler filter groups than the FFT with lower side lobe levels. Regrettably, the IAA is iterative, and requires matrix multiplication and inverse operation when forming the covariance matrix, its inverse and traversing the WLS estimate for each sampling point, resulting in a notably high computational complexity for cubic time. We propose a fast IAA (FIAA)-based super-resolution DBS imaging method, taking advantage of the rich matrix structures of the classical narrow-band filtering. First, we formulate the covariance matrix via the FFT instead of the conventional matrix multiplication operation, based on the typical Fourier structure of the steering matrix. Then, by exploiting the Gohberg-Semencul representation, the inverse of the Toeplitz covariance matrix is computed by the celebrated Levinson-Durbin (LD) and Toeplitz-vector algorithm. Finally, the FFT and fast Toeplitz-vector algorithm are further used to traverse the WLS estimates based on the data-dependent trigonometric polynomials. The method uses the Hermitian feature of the echo autocorrelation matrix R to achieve its fast solution and uses the Toeplitz structure of R to realize its fast inversion. The proposed method enjoys a lower computational complexity without performance loss compared with the conventional IAA-based super-resolution DBS imaging method. The results based on simulations and measured data verify the imaging performance and the operational efficiency.

Simple and practical approach for computing the ray Hessian matrix in geometrical optics.

PubMed

Lin, Psang Dain

2018-02-01

A method is proposed for simplifying the computation of the ray Hessian matrix in geometrical optics by replacing the angular variables in the system variable vector with their equivalent cosine and sine functions. The variable vector of a boundary surface is similarly defined in such a way as to exclude any angular variables. It is shown that the proposed formulations reduce the computation time of the Hessian matrix by around 10 times compared to the previous method reported by the current group in Advanced Geometrical Optics (2016). Notably, the method proposed in this study involves only polynomial differentiation, i.e., trigonometric function calls are not required. As a consequence, the computation complexity is significantly reduced. Five illustrative examples are given. The first three examples show that the proposed method is applicable to the determination of the Hessian matrix for any pose matrix, irrespective of the order in which the rotation and translation motions are specified. The last two examples demonstrate the use of the proposed Hessian matrix in determining the axial and lateral chromatic aberrations of a typical optical system.

Implementation of hierarchical clustering using k-mer sparse matrix to analyze MERS-CoV genetic relationship

NASA Astrophysics Data System (ADS)

Bustamam, A.; Ulul, E. D.; Hura, H. F. A.; Siswantining, T.

2017-07-01

Hierarchical clustering is one of effective methods in creating a phylogenetic tree based on the distance matrix between DNA (deoxyribonucleic acid) sequences. One of the well-known methods to calculate the distance matrix is k-mer method. Generally, k-mer is more efficient than some distance matrix calculation techniques. The steps of k-mer method are started from creating k-mer sparse matrix, and followed by creating k-mer singular value vectors. The last step is computing the distance amongst vectors. In this paper, we analyze the sequences of MERS-CoV (Middle East Respiratory Syndrome - Coronavirus) DNA by implementing hierarchical clustering using k-mer sparse matrix in order to perform the phylogenetic analysis. Our results show that the ancestor of our MERS-CoV is coming from Egypt. Moreover, we found that the MERS-CoV infection that occurs in one country may not necessarily come from the same country of origin. This suggests that the process of MERS-CoV mutation might not only be influenced by geographical factor.

Analysis of Nonlinear Dynamics by Square Matrix Method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yu, Li Hua

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. Andmore » 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.« less

Improving stochastic estimates with inference methods: calculating matrix diagonals.

PubMed

Selig, Marco; Oppermann, Niels; Ensslin, Torsten A

2012-02-01

Estimating the diagonal entries of a matrix, that is not directly accessible but only available as a linear operator in the form of a computer routine, is a common necessity in many computational applications, especially in image reconstruction and statistical inference. Here, methods of statistical inference are used to improve the accuracy or the computational costs of matrix probing methods to estimate matrix diagonals. In particular, the generalized Wiener filter methodology, as developed within information field theory, is shown to significantly improve estimates based on only a few sampling probes, in cases in which some form of continuity of the solution can be assumed. The strength, length scale, and precise functional form of the exploited autocorrelation function of the matrix diagonal is determined from the probes themselves. The developed algorithm is successfully applied to mock and real world problems. These performance tests show that, in situations where a matrix diagonal has to be calculated from only a small number of computationally expensive probes, a speedup by a factor of 2 to 10 is possible with the proposed method. © 2012 American Physical Society

Parallel scalability of Hartree-Fock calculations

NASA Astrophysics Data System (ADS)

Chow, Edmond; Liu, Xing; Smelyanskiy, Mikhail; Hammond, Jeff R.

2015-03-01

Quantum chemistry is increasingly performed using large cluster computers consisting of multiple interconnected nodes. For a fixed molecular problem, the efficiency of a calculation usually decreases as more nodes are used, due to the cost of communication between the nodes. This paper empirically investigates the parallel scalability of Hartree-Fock calculations. The construction of the Fock matrix and the density matrix calculation are analyzed separately. For the former, we use a parallelization of Fock matrix construction based on a static partitioning of work followed by a work stealing phase. For the latter, we use density matrix purification from the linear scaling methods literature, but without using sparsity. When using large numbers of nodes for moderately sized problems, density matrix computations are network-bandwidth bound, making purification methods potentially faster than eigendecomposition methods.

Optical character recognition with feature extraction and associative memory matrix

NASA Astrophysics Data System (ADS)

Sasaki, Osami; Shibahara, Akihito; Suzuki, Takamasa

1998-06-01

A method is proposed in which handwritten characters are recognized using feature extraction and an associative memory matrix. In feature extraction, simple processes such as shifting and superimposing patterns are executed. A memory matrix is generated with singular value decomposition and by modifying small singular values. The method is optically implemented with two liquid crystal displays. Experimental results for the recognition of 25 handwritten alphabet characters clearly shows the effectiveness of the method.

Method to measure soil matrix infiltration in forest soil

NASA Astrophysics Data System (ADS)

Zhang, Jing; Lei, Tingwu; Qu, Liqin; Chen, Ping; Gao, Xiaofeng; Chen, Chao; Yuan, Lili; Zhang, Manliang; Su, Guangxu

2017-09-01

Infiltration of water into forest soil commonly involves infiltration through the matrix body and preferential passages. Determining the matrix infiltration process is important in partitioning water infiltrating into the soil through the soil body and macropores to evaluate the effects of soil and water conservation practices on hillslope hydrology and watershed sedimentation. A new method that employs a double-ring infiltrometer was applied in this study to determine the matrix infiltration process in forest soil. Field experiments were conducted in a forest field on the Loess Plateau at Tianshui Soil and Water Conservation Experimental Station. Nylon cloth was placed on the soil surface in the inner ring and between the inner and outer rings of infiltrometers. A thin layer of fine sands were placed onto the nylon cloth to shelter the macropores and ensure that water infiltrates the soil through the matrix only. Brilliant Blue tracers were applied to examine the exclusion of preferential flow occurrences in the measured soil body. The infiltration process was measured, computed, and recorded through procedures similar to those of conventional methods. Horizontal and vertical soil profiles were excavated to check the success of the experiment and ensure that preferential flow did not occur in the measured soil column and that infiltration was only through the soil matrix. The infiltration processes of the replicates of five plots were roughly the same, thereby indicating the feasibility of the methodology to measure soil matrix infiltration. The measured infiltration curves effectively explained the transient process of soil matrix infiltration. Philip and Kostiakov models fitted the measured data well, and all the coefficients of determination were greater than 0.9. The wetted soil bodies through excavations did not present evidence of preferential flow. Therefore, the proposed method can determine the infiltration process through the forest soil matrix. This method can also be applied to explore matrix infiltration in other land-use types.

An investigation of the decontamination of Siqveland matrix bands.

PubMed

Whitworth, C L; Davies, K; Palmer, N O A; Martin, M V

2007-02-24

This study investigated blood contamination of artificially and clinically contaminated Siqveland matrix bands and retainers. A modified version of the recognised Kastle-Meyer test for blood was used to compare the efficacy of enzymatic agents, a washer-disinfector and an instrument washer for pre-sterilisation cleaning of Siqveland matrix bands and retainers. Assembled Siqveland matrix bands were contaminated either artificially with horse blood or clinically during dental treatment. Contaminated assembled matrix bands and retainers were subjected to immersion in an enzymatic agent, automated processing in a washer-disinfector or instrument washer, or a combination of pre-soaking and automatic cleaning. Residual blood contamination from each band and retainer was measured and compared to the volume of blood recovered from an unprocessed control group of contaminated assembled matrix bands or retainers. Residual blood was recovered from every clinically contaminated assembled Siqveland matrix band and retainer. The volume of blood recovered from assembled Siqveland matrix bands ranged from 0.13-7.1 microl and from retainers, following removal of the matrix band, from 0.001-1.523 microl. The most effective method of pre-sterilisation cleaning for artificially contaminated assembled matrix bands was processing in the washer-disinfector. Conversely, the most effective method for cleaning clinically contaminated assembled matrix bands and retainers was pre-soaking in an enzymatic agent followed by a heavy-duty cycle in an instrument washer. It is not possible to clean assembled Siqveland matrix bands using any method currently available to dental practitioners. Matrix bands should be discarded after use on one patient. Once the band is removed, all detectable blood can be removed from the retainer by pre-soaking in an enzymatic detergent followed by processing in an instrument washer.

Utilizing a Robotic Sprayer for High Lateral and Mass Resolution MALDI FT-ICR MSI of Microbial Cultures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anderton, Christopher R.; Chu, Rosalie K.; Tolic, Nikola

The ability to visualize biochemical interactions between microbial communities using MALDI MSI has provided tremendous insights into a variety of biological fields. Matrix application using a sieve proved to be incredibly useful, but it had many limitations that include uneven matrix coverage and limitation in the types of matrices one could employ in their studies. Recently, there has been a concerted effort to improve matrix application for studying agar plated microbial cultures, many of which utilized automated matrix sprayers. Here, we describe the usefulness of using a robotic sprayer for matrix application. The robotic sprayer has two-dimensional control over wheremore » matrix is applied and a heated capillary that allows for rapid drying of the applied matrix. This method provided a significant increase in MALDI sensitivity over the sieve method, as demonstrated by FT-ICR MS analysis, facilitating the ability to gain higher lateral resolution MS images of Bacillus Subtilis than previously reported. This method also allowed for the use of different matrices to be applied to the culture surfaces.« less

Integrable Floquet dynamics, generalized exclusion processes and "fused" matrix ansatz

NASA Astrophysics Data System (ADS)

Vanicat, Matthieu

2018-04-01

We present a general method for constructing integrable stochastic processes, with two-step discrete time Floquet dynamics, from the transfer matrix formalism. The models can be interpreted as a discrete time parallel update. The method can be applied for both periodic and open boundary conditions. We also show how the stationary distribution can be built as a matrix product state. As an illustration we construct parallel discrete time dynamics associated with the R-matrix of the SSEP and of the ASEP, and provide the associated stationary distributions in a matrix product form. We use this general framework to introduce new integrable generalized exclusion processes, where a fixed number of particles is allowed on each lattice site in opposition to the (single particle) exclusion process models. They are constructed using the fusion procedure of R-matrices (and K-matrices for open boundary conditions) for the SSEP and ASEP. We develop a new method, that we named "fused" matrix ansatz, to build explicitly the stationary distribution in a matrix product form. We use this algebraic structure to compute physical observables such as the correlation functions and the mean particle current.

Densified waste form and method for forming

DOEpatents

Garino, Terry J.; Nenoff, Tina M.; Sava Gallis, Dorina Florentina

2015-08-25

Materials and methods of making densified waste forms for temperature sensitive waste material, such as nuclear waste, formed with low temperature processing using metallic powder that forms the matrix that encapsulates the temperature sensitive waste material. The densified waste form includes a temperature sensitive waste material in a physically densified matrix, the matrix is a compacted metallic powder. The method for forming the densified waste form includes mixing a metallic powder and a temperature sensitive waste material to form a waste form precursor. The waste form precursor is compacted with sufficient pressure to densify the waste precursor and encapsulate the temperature sensitive waste material in a physically densified matrix.

A generalization of random matrix theory and its application to statistical physics.

PubMed

Wang, Duan; Zhang, Xin; Horvatic, Davor; Podobnik, Boris; Eugene Stanley, H

2017-02-01

To study the statistical structure of crosscorrelations in empirical data, we generalize random matrix theory and propose a new method of cross-correlation analysis, known as autoregressive random matrix theory (ARRMT). ARRMT takes into account the influence of auto-correlations in the study of cross-correlations in multiple time series. We first analytically and numerically determine how auto-correlations affect the eigenvalue distribution of the correlation matrix. Then we introduce ARRMT with a detailed procedure of how to implement the method. Finally, we illustrate the method using two examples taken from inflation rates for air pressure data for 95 US cities.

Data-Driven Learning of Q-Matrix

PubMed Central

Liu, Jingchen; Xu, Gongjun; Ying, Zhiliang

2013-01-01

The recent surge of interests in cognitive assessment has led to developments of novel statistical models for diagnostic classification. Central to many such models is the well-known Q-matrix, which specifies the item–attribute relationships. This article proposes a data-driven approach to identification of the Q-matrix and estimation of related model parameters. A key ingredient is a flexible T-matrix that relates the Q-matrix to response patterns. The flexibility of the T-matrix allows the construction of a natural criterion function as well as a computationally amenable algorithm. Simulations results are presented to demonstrate usefulness and applicability of the proposed method. Extension to handling of the Q-matrix with partial information is presented. The proposed method also provides a platform on which important statistical issues, such as hypothesis testing and model selection, may be formally addressed. PMID:23926363

Condition number estimation of preconditioned matrices.

PubMed

Kushida, Noriyuki

2015-01-01

The present paper introduces a condition number estimation method for preconditioned matrices. The newly developed method provides reasonable results, while the conventional method which is based on the Lanczos connection gives meaningless results. The Lanczos connection based method provides the condition numbers of coefficient matrices of systems of linear equations with information obtained through the preconditioned conjugate gradient method. Estimating the condition number of preconditioned matrices is sometimes important when describing the effectiveness of new preconditionerers or selecting adequate preconditioners. Operating a preconditioner on a coefficient matrix is the simplest method of estimation. However, this is not possible for large-scale computing, especially if computation is performed on distributed memory parallel computers. This is because, the preconditioned matrices become dense, even if the original matrices are sparse. Although the Lanczos connection method can be used to calculate the condition number of preconditioned matrices, it is not considered to be applicable to large-scale problems because of its weakness with respect to numerical errors. Therefore, we have developed a robust and parallelizable method based on Hager's method. The feasibility studies are curried out for the diagonal scaling preconditioner and the SSOR preconditioner with a diagonal matrix, a tri-daigonal matrix and Pei's matrix. As a result, the Lanczos connection method contains around 10% error in the results even with a simple problem. On the other hand, the new method contains negligible errors. In addition, the newly developed method returns reasonable solutions when the Lanczos connection method fails with Pei's matrix, and matrices generated with the finite element method.

Refractive index inversion based on Mueller matrix method

NASA Astrophysics Data System (ADS)

Fan, Huaxi; Wu, Wenyuan; Huang, Yanhua; Li, Zhaozhao

2016-03-01

Based on Stokes vector and Jones vector, the correlation between Mueller matrix elements and refractive index was studied with the result simplified, and through Mueller matrix way, the expression of refractive index inversion was deduced. The Mueller matrix elements, under different incident angle, are simulated through the expression of specular reflection so as to analyze the influence of the angle of incidence and refractive index on it, which is verified through the measure of the Mueller matrix elements of polished metal surface. Research shows that, under the condition of specular reflection, the result of Mueller matrix inversion is consistent with the experiment and can be used as an index of refraction of inversion method, and it provides a new way for target detection and recognition technology.

Hybrid transfer-matrix FDTD method for layered periodic structures.

PubMed

Deinega, Alexei; Belousov, Sergei; Valuev, Ilya

2009-03-15

A hybrid transfer-matrix finite-difference time-domain (FDTD) method is proposed for modeling the optical properties of finite-width planar periodic structures. This method can also be applied for calculation of the photonic bands in infinite photonic crystals. We describe the procedure of evaluating the transfer-matrix elements by a special numerical FDTD simulation. The accuracy of the new method is tested by comparing computed transmission spectra of a 32-layered photonic crystal composed of spherical or ellipsoidal scatterers with the results of direct FDTD and layer-multiple-scattering calculations.

Galaxy two-point covariance matrix estimation for next generation surveys

NASA Astrophysics Data System (ADS)

Howlett, Cullan; Percival, Will J.

2017-12-01

We perform a detailed analysis of the covariance matrix of the spherically averaged galaxy power spectrum and present a new, practical method for estimating this within an arbitrary survey without the need for running mock galaxy simulations that cover the full survey volume. The method uses theoretical arguments to modify the covariance matrix measured from a set of small-volume cubic galaxy simulations, which are computationally cheap to produce compared to larger simulations and match the measured small-scale galaxy clustering more accurately than is possible using theoretical modelling. We include prescriptions to analytically account for the window function of the survey, which convolves the measured covariance matrix in a non-trivial way. We also present a new method to include the effects of super-sample covariance and modes outside the small simulation volume which requires no additional simulations and still allows us to scale the covariance matrix. As validation, we compare the covariance matrix estimated using our new method to that from a brute-force calculation using 500 simulations originally created for analysis of the Sloan Digital Sky Survey Main Galaxy Sample. We find excellent agreement on all scales of interest for large-scale structure analysis, including those dominated by the effects of the survey window, and on scales where theoretical models of the clustering normally break down, but the new method produces a covariance matrix with significantly better signal-to-noise ratio. Although only formally correct in real space, we also discuss how our method can be extended to incorporate the effects of redshift space distortions.

Polarimetric signatures of a canopy of dielectric cylinders based on first and second order vector radiative transfer theory

NASA Technical Reports Server (NTRS)

Tsang, Leung; Chan, Chi Hou; Kong, Jin AU; Joseph, James

1992-01-01

Complete polarimetric signatures of a canopy of dielectric cylinders overlying a homogeneous half space are studied with the first and second order solutions of the vector radiative transfer theory. The vector radiative transfer equations contain a general nondiagonal extinction matrix and a phase matrix. The energy conservation issue is addressed by calculating the elements of the extinction matrix and the elements of the phase matrix in a manner that is consistent with energy conservation. Two methods are used. In the first method, the surface fields and the internal fields of the dielectric cylinder are calculated by using the fields of an infinite cylinder. The phase matrix is calculated and the extinction matrix is calculated by summing the absorption and scattering to ensure energy conservation. In the second method, the method of moments is used to calculate the elements of the extinction and phase matrices. The Mueller matrix based on the first order and second order multiple scattering solutions of the vector radiative transfer equation are calculated. Results from the two methods are compared. The vector radiative transfer equations, combined with the solution based on method of moments, obey both energy conservation and reciprocity. The polarimetric signatures, copolarized and depolarized return, degree of polarization, and phase differences are studied as a function of the orientation, sizes, and dielectric properties of the cylinders. It is shown that second order scattering is generally important for vegetation canopy at C band and can be important at L band for some cases.

Novel Calibration Algorithm for a Three-Axis Strapdown Magnetometer

PubMed Central

Liu, Yan Xia; Li, Xi Sheng; Zhang, Xiao Juan; Feng, Yi Bo

2014-01-01

A complete error calibration model with 12 independent parameters is established by analyzing the three-axis magnetometer error mechanism. The said model conforms to an ellipsoid restriction, the parameters of the ellipsoid equation are estimated, and the ellipsoid coefficient matrix is derived. However, the calibration matrix cannot be determined completely, as there are fewer ellipsoid parameters than calibration model parameters. Mathematically, the calibration matrix derived from the ellipsoid coefficient matrix by a different matrix decomposition method is not unique, and there exists an unknown rotation matrix R between them. This paper puts forward a constant intersection angle method (angles between the geomagnetic field and gravitational field are fixed) to estimate R. The Tikhonov method is adopted to solve the problem that rounding errors or other errors may seriously affect the calculation results of R when the condition number of the matrix is very large. The geomagnetic field vector and heading error are further corrected by R. The constant intersection angle method is convenient and practical, as it is free from any additional calibration procedure or coordinate transformation. In addition, the simulation experiment indicates that the heading error declines from ±1° calibrated by classical ellipsoid fitting to ±0.2° calibrated by a constant intersection angle method, and the signal-to-noise ratio is 50 dB. The actual experiment exhibits that the heading error is further corrected from ±0.8° calibrated by the classical ellipsoid fitting to ±0.3° calibrated by a constant intersection angle method. PMID:24831110

Designing Feature and Data Parallel Stochastic Coordinate Descent Method forMatrix and Tensor Factorization

DTIC Science & Technology

2016-05-11

AFRL-AFOSR-JP-TR-2016-0046 Designing Feature and Data Parallel Stochastic Coordinate Descent Method for Matrix and Tensor Factorization U Kang Korea...maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or   any other aspect...Designing Feature and Data Parallel Stochastic Coordinate Descent Method for Matrix and Tensor Factorization 5a.  CONTRACT NUMBER 5b.  GRANT NUMBER FA2386

Analytical Solutions for the Resonance Response of Goupillaud-type Elastic Media Using Z-transform Methods

DTIC Science & Technology

2012-02-01

using z-transform methods. The determinant of the resulting global system matrix in the z-space |Am| is a palindromic polynomial with real...resulting global system matrix in the z-space |Am| is a palindromic polynomial with real coefficients. The zeros of the palindromic polynomial are distinct...Goupillaud-type multilayered media. In addition, the present treatment uses a global matrix method that is attributed to Knopoff [16], rather than the

Near-Infrared Collisional Radiative Model for Xe Plasma Electrostatic Thrusters: The Role of Metastable Atoms

DTIC Science & Technology

2009-08-01

the measurements of Jung et al [3], ’BSR’ to the Breit- Pauli B-Spline ft-matrix method, and ’RDW to the relativistic distorted wave method. low...excitation cross sections using both relativistic distorted wave and semi-relativistic Breit- Pauli B-Spline R-matrix methods is presented. The model...population and line intensity enhancement. 15. SUBJECT TERMS Metastable xenon Electrostatic thruster Relativistic Breit- Pauli b-spline matrix

Method of joining metallic and composite components

NASA Technical Reports Server (NTRS)

Semmes, Edmund B. (Inventor)

2010-01-01

A method is provided for joining a metallic member to a structure made of a composite matrix material. One or more surfaces of a portion of the metallic member that is to be joined to the composite matrix structure is provided with a plurality of outwardly projecting studs. The surface including the studs is brought into engagement with a portion of an uncured composite matrix material so that fibers of the composite matrix material intertwine with the studs, and the metallic member and composite structure form an assembly. The assembly is then companion cured so as to join the metallic member to the composite matrix material structure.

Agar/gelatin bilayer gel matrix fabricated by simple thermo-responsive sol-gel transition method.

PubMed

Wang, Yifeng; Dong, Meng; Guo, Mengmeng; Wang, Xia; Zhou, Jing; Lei, Jian; Guo, Chuanhang; Qin, Chaoran

2017-08-01

We present a simple and environmentally-friendly method to generate an agar/gelatin bilayer gel matrix for further biomedical applications. In this method, the thermally responsive sol-gel transitions of agar and gelatin combined with the different transition temperatures are exquisitely employed to fabricate the agar/gelatin bilayer gel matrix and achieve separate loading for various materials (e.g., drugs, fluorescent materials, and nanoparticles). Importantly, the resulting bilayer gel matrix provides two different biopolymer environments (a polysaccharide environment vs a protein environment) with a well-defined border, which allows the loaded materials in different layers to retain their original properties (e.g., magnetism and fluorescence) and reduce mutual interference. In addition, the loaded materials in the bilayer gel matrix exhibit an interesting release behavior under the control of thermal stimuli. Consequently, the resulting agar/gelatin bilayer gel matrix is a promising candidate for biomedical applications in drug delivery, controlled release, fluorescence labeling, and bio-imaging. Copyright © 2017 Elsevier B.V. All rights reserved.

Method for estimating power outages and restoration during natural and man-made events

DOEpatents

Omitaomu, Olufemi A.; Fernandez, Steven J.

2016-01-05

A method of modeling electric supply and demand with a data processor in combination with a recordable medium, and for estimating spatial distribution of electric power outages and affected populations. A geographic area is divided into cells to form a matrix. Within the matrix, supply cells are identified as containing electric substations and demand cells are identified as including electricity customers. Demand cells of the matrix are associated with the supply cells as a function of the capacity of each of the supply cells and the proximity and/or electricity demand of each of the demand cells. The method includes estimating a power outage by applying disaster event prediction information to the matrix, and estimating power restoration using the supply and demand cell information of the matrix and standardized and historical restoration information.

Uniformity Masks Design Method Based on the Shadow Matrix for Coating Materials with Different Condensation Characteristics

PubMed Central

2013-01-01

An intuitionistic method is proposed to design shadow masks to achieve thickness profile control for evaporation coating processes. The proposed method is based on the concept of the shadow matrix, which is a matrix that contains coefficients that build quantitive relations between shape parameters of masks and shadow quantities of substrate directly. By using the shadow matrix, shape parameters of shadow masks could be derived simply by solving a matrix equation. Verification experiments were performed on a special case where coating materials have different condensation characteristics. By using the designed mask pair with complementary shapes, thickness uniformities of better than 98% are demonstrated for MgF2 (m = 1) and LaF3 (m = 0.5) simultaneously on a 280 mm diameter spherical substrate with the radius curvature of 200 mm. PMID:24227996

Unifying time evolution and optimization with matrix product states

NASA Astrophysics Data System (ADS)

Haegeman, Jutho; Lubich, Christian; Oseledets, Ivan; Vandereycken, Bart; Verstraete, Frank

2016-10-01

We show that the time-dependent variational principle provides a unifying framework for time-evolution methods and optimization methods in the context of matrix product states. In particular, we introduce a new integration scheme for studying time evolution, which can cope with arbitrary Hamiltonians, including those with long-range interactions. Rather than a Suzuki-Trotter splitting of the Hamiltonian, which is the idea behind the adaptive time-dependent density matrix renormalization group method or time-evolving block decimation, our method is based on splitting the projector onto the matrix product state tangent space as it appears in the Dirac-Frenkel time-dependent variational principle. We discuss how the resulting algorithm resembles the density matrix renormalization group (DMRG) algorithm for finding ground states so closely that it can be implemented by changing just a few lines of code and it inherits the same stability and efficiency. In particular, our method is compatible with any Hamiltonian for which ground-state DMRG can be implemented efficiently. In fact, DMRG is obtained as a special case of our scheme for imaginary time evolution with infinite time step.

Improved full analytical polygon-based method using Fourier analysis of the three-dimensional affine transformation.

PubMed

Pan, Yijie; Wang, Yongtian; Liu, Juan; Li, Xin; Jia, Jia

2014-03-01

Previous research [Appl. Opt.52, A290 (2013)] has revealed that Fourier analysis of three-dimensional affine transformation theory can be used to improve the computation speed of the traditional polygon-based method. In this paper, we continue our research and propose an improved full analytical polygon-based method developed upon this theory. Vertex vectors of primitive and arbitrary triangles and the pseudo-inverse matrix were used to obtain an affine transformation matrix representing the spatial relationship between the two triangles. With this relationship and the primitive spectrum, we analytically obtained the spectrum of the arbitrary triangle. This algorithm discards low-level angular dependent computations. In order to add diffusive reflection to each arbitrary surface, we also propose a whole matrix computation approach that takes advantage of the affine transformation matrix and uses matrix multiplication to calculate shifting parameters of similar sub-polygons. The proposed method improves hologram computation speed for the conventional full analytical approach. Optical experimental results are demonstrated which prove that the proposed method can effectively reconstruct three-dimensional scenes.

Conversion of a Rhotrix to a "Coupled Matrix"

ERIC Educational Resources Information Center

Sani, B.

2008-01-01

In this note, a method of converting a rhotrix to a special form of matrix termed a "coupled matrix" is proposed. The special matrix can be used to solve various problems involving n x n and (n - 1) x (n - 1) matrices simultaneously.

Multi-color incomplete Cholesky conjugate gradient methods for vector computers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Poole, E.L.

1986-01-01

This research is concerned with the solution on vector computers of linear systems of equations. Ax = b, where A is a large, sparse symmetric positive definite matrix with non-zero elements lying only along a few diagonals of the matrix. The system is solved using the incomplete Cholesky conjugate gradient method (ICCG). Multi-color orderings are used of the unknowns in the linear system to obtain p-color matrices for which a no-fill block ICCG method is implemented on the CYBER 205 with O(N/p) length vector operations in both the decomposition of A and, more importantly, in the forward and back solvesmore » necessary at each iteration of the method. (N is the number of unknowns and p is a small constant). A p-colored matrix is a matrix that can be partitioned into a p x p block matrix where the diagonal blocks are diagonal matrices. The matrix is stored by diagonals and matrix multiplication by diagonals is used to carry out the decomposition of A and the forward and back solves. Additionally, if the vectors across adjacent blocks line up, then some of the overhead associated with vector startups can be eliminated in the matrix vector multiplication necessary at each conjugate gradient iteration. Necessary and sufficient conditions are given to determine which multi-color orderings of the unknowns correspond to p-color matrices, and a process is indicated for choosing multi-color orderings.« less

Determining the Number of Components from the Matrix of Partial Correlations

ERIC Educational Resources Information Center

Velicer, Wayne F.

1976-01-01

A method is presented for determining the number of components to retain in a principal components or image components analysis which utilizes a matrix of partial correlations. Advantages and uses of the method are discussed and a comparison of the proposed method with existing methods is presented. (JKS)

New algorithms to compute the nearness symmetric solution of the matrix equation.

PubMed

Peng, Zhen-Yun; Fang, Yang-Zhi; Xiao, Xian-Wei; Du, Dan-Dan

2016-01-01

In this paper we consider the nearness symmetric solution of the matrix equation AXB = C to a given matrix [Formula: see text] in the sense of the Frobenius norm. By discussing equivalent form of the considered problem, we derive some necessary and sufficient conditions for the matrix [Formula: see text] is a solution of the considered problem. Based on the idea of the alternating variable minimization with multiplier method, we propose two iterative methods to compute the solution of the considered problem, and analyze the global convergence results of the proposed algorithms. Numerical results illustrate the proposed methods are more effective than the existing two methods proposed in Peng et al. (Appl Math Comput 160:763-777, 2005) and Peng (Int J Comput Math 87: 1820-1830, 2010).

Modeling cometary photopolarimetric characteristics with Sh-matrix method

NASA Astrophysics Data System (ADS)

Kolokolova, L.; Petrov, D.

2017-12-01

Cometary dust is dominated by particles of complex shape and structure, which are often considered as fractal aggregates. Rigorous modeling of light scattering by such particles, even using parallelized codes and NASA supercomputer resources, is very computer time and memory consuming. We are presenting a new approach to modeling cometary dust that is based on the Sh-matrix technique (e.g., Petrov et al., JQSRT, 112, 2012). This method is based on the T-matrix technique (e.g., Mishchenko et al., JQSRT, 55, 1996) and was developed after it had been found that the shape-dependent factors could be separated from the size- and refractive-index-dependent factors and presented as a shape matrix, or Sh-matrix. Size and refractive index dependences are incorporated through analytical operations on the Sh-matrix to produce the elements of T-matrix. Sh-matrix method keeps all advantages of the T-matrix method, including analytical averaging over particle orientation. Moreover, the surface integrals describing the Sh-matrix elements themselves can be solvable analytically for particles of any shape. This makes Sh-matrix approach an effective technique to simulate light scattering by particles of complex shape and surface structure. In this paper, we present cometary dust as an ensemble of Gaussian random particles. The shape of these particles is described by a log-normal distribution of their radius length and direction (Muinonen, EMP, 72, 1996). Changing one of the parameters of this distribution, the correlation angle, from 0 to 90 deg., we can model a variety of particles from spheres to particles of a random complex shape. We survey the angular and spectral dependencies of intensity and polarization resulted from light scattering by such particles, studying how they depend on the particle shape, size, and composition (including porous particles to simulate aggregates) to find the best fit to the cometary observations.

Method Modification Study for the Thermo Scientific SureTect™ Listeria Species Assay-Matrix Extension.

PubMed

Cloke, Jonathan; Evans, Katharine; Crabtree, David; Hughes, Annette; Simpson, Helen; Holopainen, Jani; Wickstrand, Nina; Kauppinen, Mikko; Leon-Velarde, Carlos; Larson, Nathan; Dave, Keron; Chen, Yi; Ryser, Elliot; Carter, Mark

2016-01-01

The Thermo Scientific™ SureTect™ Listeria species assay is a new real-time PCR assay for the detection of all species of Listeria in food and environmental samples. The assay was originally certified as Performance Tested Methods(SM) (PTM) 071304 in 2013. This report details the method modification study undertaken to extend the performance claims of the assay for matrixes of raw ground turkey, raw ground pork, bagged lettuce, raw pork sausages, pasteurized 2% fat milk, raw cod, pasteurized brie cheese, and ice cream. The method modification study was conducted using the AOAC Research Institute (RI) PTM program to validate the SureTect PCR assay in comparison to the reference method detailed in ISO 11290-1:1996 including amendment 1:2004. All matrixes were tested by Thermo Fisher Scientific (Basingstoke, United Kingdom). In addition, three matrixes (raw cod, bagged lettuce, and pasteurized brie cheese) were analyzed independently as part of the AOAC RI-controlled independent laboratory study by the University of Guelph, Canada. Using probability of detection statistical analysis, there was no significant difference in the performance between the SureTect assay and the International Organization for Standardization reference method for any of the matrixes analyzed in this study.

A numerical method of detecting singularity

NASA Technical Reports Server (NTRS)

Laporte, M.; Vignes, J.

1978-01-01

A numerical method is reported which determines a value C for the degree of conditioning of a matrix. This value is C = 0 for a singular matrix and has progressively larger values for matrices which are increasingly well-conditioned. This value is C sub = C max sub max (C defined by the precision of the computer) when the matrix is perfectly well conditioned.

Regularized matrix regression

PubMed Central

Zhou, Hua; Li, Lexin

2014-01-01

Summary Modern technologies are producing a wealth of data with complex structures. For instance, in two-dimensional digital imaging, flow cytometry and electroencephalography, matrix-type covariates frequently arise when measurements are obtained for each combination of two underlying variables. To address scientific questions arising from those data, new regression methods that take matrices as covariates are needed, and sparsity or other forms of regularization are crucial owing to the ultrahigh dimensionality and complex structure of the matrix data. The popular lasso and related regularization methods hinge on the sparsity of the true signal in terms of the number of its non-zero coefficients. However, for the matrix data, the true signal is often of, or can be well approximated by, a low rank structure. As such, the sparsity is frequently in the form of low rank of the matrix parameters, which may seriously violate the assumption of the classical lasso. We propose a class of regularized matrix regression methods based on spectral regularization. A highly efficient and scalable estimation algorithm is developed, and a degrees-of-freedom formula is derived to facilitate model selection along the regularization path. Superior performance of the method proposed is demonstrated on both synthetic and real examples. PMID:24648830

Experimental Detection and Visualization of the Extracellular Matrix in Macrocolony Biofilms.

PubMed

Serra, Diego O; Hengge, Regine

2017-01-01

By adopting elaborate three-dimensional morphologies that vary according to their extracellular matrix composition, macrocolony biofilms offer a unique opportunity to interrogate about the roles of specific matrix components in shaping biofilm architecture. Here, we describe two methods optimized for Escherichia coli that profit from morphology and the high level of structural organization of macrocolonies to gain insight into the production and assembly of amyloid curli and cellulose-the two major biofilm matrix elements of E. coli-in biofilms. The first method, the macrocolony morphology assay, is based on the ability of curli and cellulose-either alone or in combination-to generate specific morphological and Congo Red-staining patterns in E. coli macrocolonies, which can then be used as a direct visual readout for the production of these matrix components. The second method involves thin sectioning of macrocolonies, which along with in situ staining of amyloid curli and cellulose and microscopic imaging allows gaining fine details of the spatial arrangement of both matrix elements inside macrocolonies. Beyond their current use with E. coli and related curli and cellulose-producing Enterobacteriaceae, both the methods offer the potential to be adapted to other bacterial species.

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

PubMed

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.

Matrix vapor deposition/recrystallization and dedicated spray preparation for high-resolution scanning microprobe matrix-assisted laser desorption/ionization imaging mass spectrometry (SMALDI-MS) of tissue and single cells.

PubMed

Bouschen, Werner; Schulz, Oliver; Eikel, Daniel; Spengler, Bernhard

2010-02-01

Matrix preparation techniques such as air spraying or vapor deposition were investigated with respect to lateral migration, integration of analyte into matrix crystals and achievable lateral resolution for the purpose of high-resolution biological imaging. The accessible mass range was found to be beyond 5000 u with sufficient analytical sensitivity. Gas-assisted spraying methods (using oxygen-free gases) provide a good compromise between crystal integration of analyte and analyte migration within the sample. Controlling preparational parameters with this method, however, is difficult. Separation of the preparation procedure into two steps, instead, leads to an improved control of migration and incorporation. The first step is a dry vapor deposition of matrix onto the investigated sample. In a second step, incorporation of analyte into the matrix crystal is enhanced by a controlled recrystallization of matrix in a saturated water atmosphere. With this latter method an effective analytical resolution of 2 microm in the x and y direction was achieved for scanning microprobe matrix-assisted laser desorption/ionization imaging mass spectrometry (SMALDI-MS). Cultured A-498 cells of human renal carcinoma were successfully investigated by high-resolution MALDI imaging using the new preparation techniques. Copyright 2010 John Wiley & Sons, Ltd.

Method of making carbon fiber-carbon matrix reinforced ceramic composites

NASA Technical Reports Server (NTRS)

Williams, Brian (Inventor); Benander, Robert (Inventor)

2007-01-01

A method of making a carbon fiber-carbon matrix reinforced ceramic composite wherein the result is a carbon fiber-carbon matrix reinforcement is embedded within a ceramic matrix. The ceramic matrix does not penetrate into the carbon fiber-carbon matrix reinforcement to any significant degree. The carbide matrix is a formed in situ solid carbide of at least one metal having a melting point above about 1850 degrees centigrade. At least when the composite is intended to operate between approximately 1500 and 2000 degrees centigrade for extended periods of time the solid carbide with the embedded reinforcement is formed first by reaction infiltration. Molten silicon is then diffused into the carbide. The molten silicon diffuses preferentially into the carbide matrix but not to any significant degree into the carbon-carbon reinforcement. Where the composite is intended to operate between approximately 2000 and 2700 degrees centigrade for extended periods of time such diffusion of molten silicon into the carbide is optional and generally preferred, but not essential.

Fast iterative image reconstruction using sparse matrix factorization with GPU acceleration

NASA Astrophysics Data System (ADS)

Zhou, Jian; Qi, Jinyi

2011-03-01

Statistically based iterative approaches for image reconstruction have gained much attention in medical imaging. An accurate system matrix that defines the mapping from the image space to the data space is the key to high-resolution image reconstruction. However, an accurate system matrix is often associated with high computational cost and huge storage requirement. Here we present a method to address this problem by using sparse matrix factorization and parallel computing on a graphic processing unit (GPU).We factor the accurate system matrix into three sparse matrices: a sinogram blurring matrix, a geometric projection matrix, and an image blurring matrix. The sinogram blurring matrix models the detector response. The geometric projection matrix is based on a simple line integral model. The image blurring matrix is to compensate for the line-of-response (LOR) degradation due to the simplified geometric projection matrix. The geometric projection matrix is precomputed, while the sinogram and image blurring matrices are estimated by minimizing the difference between the factored system matrix and the original system matrix. The resulting factored system matrix has much less number of nonzero elements than the original system matrix and thus substantially reduces the storage and computation cost. The smaller size also allows an efficient implement of the forward and back projectors on GPUs, which have limited amount of memory. Our simulation studies show that the proposed method can dramatically reduce the computation cost of high-resolution iterative image reconstruction. The proposed technique is applicable to image reconstruction for different imaging modalities, including x-ray CT, PET, and SPECT.

Densified waste form and method for forming

DOE Office of Scientific and Technical Information (OSTI.GOV)

Garino, Terry J.; Nenoff, Tina M.; Sava Gallis, Dorina Florentina

Materials and methods of making densified waste forms for temperature sensitive waste material, such as nuclear waste, formed with low temperature processing using metallic powder that forms the matrix that encapsulates the temperature sensitive waste material. The densified waste form includes a temperature sensitive waste material in a physically densified matrix, the matrix is a compacted metallic powder. The method for forming the densified waste form includes mixing a metallic powder and a temperature sensitive waste material to form a waste form precursor. The waste form precursor is compacted with sufficient pressure to densify the waste precursor and encapsulate themore » temperature sensitive waste material in a physically densified matrix.« less

Covariance Matrix Estimation for Massive MIMO

NASA Astrophysics Data System (ADS)

Upadhya, Karthik; Vorobyov, Sergiy A.

2018-04-01

We propose a novel pilot structure for covariance matrix estimation in massive multiple-input multiple-output (MIMO) systems in which each user transmits two pilot sequences, with the second pilot sequence multiplied by a random phase-shift. The covariance matrix of a particular user is obtained by computing the sample cross-correlation of the channel estimates obtained from the two pilot sequences. This approach relaxes the requirement that all the users transmit their uplink pilots over the same set of symbols. We derive expressions for the achievable rate and the mean-squared error of the covariance matrix estimate when the proposed method is used with staggered pilots. The performance of the proposed method is compared with existing methods through simulations.

Improving estimates of the number of `fake' leptons and other mis-reconstructed objects in hadron collider events: BoB's your UNCLE

NASA Astrophysics Data System (ADS)

Gillam, Thomas P. S.; Lester, Christopher G.

2014-11-01

We consider current and alternative approaches to setting limits on new physics signals having backgrounds from misidentified objects; for example jets misidentified as leptons, b-jets or photons. Many ATLAS and CMS analyses have used a heuristic "matrix method" for estimating the background contribution from such sources. We demonstrate that the matrix method suffers from statistical shortcomings that can adversely affect its ability to set robust limits. A rigorous alternative method is discussed, and is seen to produce fake rate estimates and limits with better qualities, but is found to be too costly to use. Having investigated the nature of the approximations used to derive the matrix method, we propose a third strategy that is seen to marry the speed of the matrix method to the performance and physicality of the more rigorous approach.

A direct method for unfolding the resolution function from measurements of neutron induced reactions

NASA Astrophysics Data System (ADS)

Žugec, P.; Colonna, N.; Sabate-Gilarte, M.; Vlachoudis, V.; Massimi, C.; Lerendegui-Marco, J.; Stamatopoulos, A.; Bacak, M.; Warren, S. G.; n TOF Collaboration

2017-12-01

The paper explores the numerical stability and the computational efficiency of a direct method for unfolding the resolution function from the measurements of the neutron induced reactions. A detailed resolution function formalism is laid out, followed by an overview of challenges present in a practical implementation of the method. A special matrix storage scheme is developed in order to facilitate both the memory management of the resolution function matrix, and to increase the computational efficiency of the matrix multiplication and decomposition procedures. Due to its admirable computational properties, a Cholesky decomposition is at the heart of the unfolding procedure. With the smallest but necessary modification of the matrix to be decomposed, the method is successfully applied to system of 105 × 105. However, the amplification of the uncertainties during the direct inversion procedures limits the applicability of the method to high-precision measurements of neutron induced reactions.

Linear scaling computation of the Fock matrix. II. Rigorous bounds on exchange integrals and incremental Fock build

NASA Astrophysics Data System (ADS)

Schwegler, Eric; Challacombe, Matt; Head-Gordon, Martin

1997-06-01

A new linear scaling method for computation of the Cartesian Gaussian-based Hartree-Fock exchange matrix is described, which employs a method numerically equivalent to standard direct SCF, and which does not enforce locality of the density matrix. With a previously described method for computing the Coulomb matrix [J. Chem. Phys. 106, 5526 (1997)], linear scaling incremental Fock builds are demonstrated for the first time. Microhartree accuracy and linear scaling are achieved for restricted Hartree-Fock calculations on sequences of water clusters and polyglycine α-helices with the 3-21G and 6-31G basis sets. Eightfold speedups are found relative to our previous method. For systems with a small ionization potential, such as graphitic sheets, the method naturally reverts to the expected quadratic behavior. Also, benchmark 3-21G calculations attaining microhartree accuracy are reported for the P53 tetramerization monomer involving 698 atoms and 3836 basis functions.

Metal matrix composite fabrication processes for high performance aerospace structures

NASA Astrophysics Data System (ADS)

Ponzi, C.

A survey is conducted of extant methods of metal matrix composite (MMC) production in order to serve as a basis for prospective MMC users' selection of a matrix/reinforcement combination, cost-effective primary fabrication methods, and secondary fabrication techniques for the achievement of desired performance levels. Attention is given to the illustrative cases of structural fittings, control-surface connecting rods, hypersonic aircraft air inlet ramps, helicopter swash plates, and turbine rotor disks. Methods for technical and cost analysis modeling useful in process optimization are noted.

Implementation of biological tissue Mueller matrix for polarization-sensitive optical coherence tomography based on LabVIEW

NASA Astrophysics Data System (ADS)

Lin, Yongping; Zhang, Xiyang; He, Youwu; Cai, Jianyong; Li, Hui

2018-02-01

The Jones matrix and the Mueller matrix are main tools to study polarization devices. The Mueller matrix can also be used for biological tissue research to get complete tissue properties, while the commercial optical coherence tomography system does not give relevant analysis function. Based on the LabVIEW, a near real time display method of Mueller matrix image of biological tissue is developed and it gives the corresponding phase retardant image simultaneously. A quarter-wave plate was placed at 45 in the sample arm. Experimental results of the two orthogonal channels show that the phase retardance based on incident light vector fixed mode and the Mueller matrix based on incident light vector dynamic mode can provide an effective analysis method of the existing system.

Recognition of Risk Information - Adaptation of J. Bertin's Orderable Matrix for social communication

NASA Astrophysics Data System (ADS)

Ishida, Keiichi

2018-05-01

This paper aims to show capability of the Orderable Matrix of Jacques Bertin which is a visualization method of data analyze and/or a method to recognize data. That matrix can show the data by replacing numbers to visual element. As an example, using a set of data regarding natural hazard rankings for certain metropolitan cities in the world, this paper describes how the Orderable Matrix handles the data set and show characteristic factors of this data to understand it. Not only to see a kind of risk ranking of cities, the Orderable Matrix shows how differently danger concerned cities ones and others are. Furthermore, we will see that the visualized data by Orderable Matrix allows us to see the characteristics of the data set comprehensively and instantaneously.

Study on the Algorithm of Judgment Matrix in Analytic Hierarchy Process

NASA Astrophysics Data System (ADS)

Lu, Zhiyong; Qin, Futong; Jin, Yican

2017-10-01

A new algorithm is proposed for the non-consistent judgment matrix in AHP. A primary judgment matrix is generated firstly through pre-ordering the targeted factor set, and a compared matrix is built through the top integral function. Then a relative error matrix is created by comparing the compared matrix with the primary judgment matrix which is regulated under the control of the relative error matrix and the dissimilar degree of the matrix step by step. Lastly, the targeted judgment matrix is generated to satisfy the requirement of consistence and the least dissimilar degree. The feasibility and validity of the proposed method are verified by simulation results.

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

NASA Astrophysics Data System (ADS)

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.

Assessment of a hybrid finite element-transfer matrix model for flat structures with homogeneous acoustic treatments.

PubMed

Alimonti, Luca; Atalla, Noureddine; Berry, Alain; Sgard, Franck

2014-05-01

Modeling complex vibroacoustic systems including poroelastic materials using finite element based methods can be unfeasible for practical applications. For this reason, analytical approaches such as the transfer matrix method are often preferred to obtain a quick estimation of the vibroacoustic parameters. However, the strong assumptions inherent within the transfer matrix method lead to a lack of accuracy in the description of the geometry of the system. As a result, the transfer matrix method is inherently limited to the high frequency range. Nowadays, hybrid substructuring procedures have become quite popular. Indeed, different modeling techniques are typically sought to describe complex vibroacoustic systems over the widest possible frequency range. As a result, the flexibility and accuracy of the finite element method and the efficiency of the transfer matrix method could be coupled in a hybrid technique to obtain a reduction of the computational burden. In this work, a hybrid methodology is proposed. The performances of the method in predicting the vibroacoutic indicators of flat structures with attached homogeneous acoustic treatments are assessed. The results prove that, under certain conditions, the hybrid model allows for a reduction of the computational effort while preserving enough accuracy with respect to the full finite element solution.

Detection of Protein Complexes Based on Penalized Matrix Decomposition in a Sparse Protein⁻Protein Interaction Network.

PubMed

Cao, Buwen; Deng, Shuguang; Qin, Hua; Ding, Pingjian; Chen, Shaopeng; Li, Guanghui

2018-06-15

High-throughput technology has generated large-scale protein interaction data, which is crucial in our understanding of biological organisms. Many complex identification algorithms have been developed to determine protein complexes. However, these methods are only suitable for dense protein interaction networks, because their capabilities decrease rapidly when applied to sparse protein⁻protein interaction (PPI) networks. In this study, based on penalized matrix decomposition ( PMD ), a novel method of penalized matrix decomposition for the identification of protein complexes (i.e., PMD pc ) was developed to detect protein complexes in the human protein interaction network. This method mainly consists of three steps. First, the adjacent matrix of the protein interaction network is normalized. Second, the normalized matrix is decomposed into three factor matrices. The PMD pc method can detect protein complexes in sparse PPI networks by imposing appropriate constraints on factor matrices. Finally, the results of our method are compared with those of other methods in human PPI network. Experimental results show that our method can not only outperform classical algorithms, such as CFinder, ClusterONE, RRW, HC-PIN, and PCE-FR, but can also achieve an ideal overall performance in terms of a composite score consisting of F-measure, accuracy (ACC), and the maximum matching ratio (MMR).

Distorted Born iterative T-matrix method for inversion of CSEM data in anisotropic media

NASA Astrophysics Data System (ADS)

Jakobsen, Morten; Tveit, Svenn

2018-05-01

We present a direct iterative solutions to the nonlinear controlled-source electromagnetic (CSEM) inversion problem in the frequency domain, which is based on a volume integral equation formulation of the forward modelling problem in anisotropic conductive media. Our vectorial nonlinear inverse scattering approach effectively replaces an ill-posed nonlinear inverse problem with a series of linear ill-posed inverse problems, for which there already exist efficient (regularized) solution methods. The solution update the dyadic Green's function's from the source to the scattering-volume and from the scattering-volume to the receivers, after each iteration. The T-matrix approach of multiple scattering theory is used for efficient updating of all dyadic Green's functions after each linearized inversion step. This means that we have developed a T-matrix variant of the Distorted Born Iterative (DBI) method, which is often used in the acoustic and electromagnetic (medical) imaging communities as an alternative to contrast-source inversion. The main advantage of using the T-matrix approach in this context, is that it eliminates the need to perform a full forward simulation at each iteration of the DBI method, which is known to be consistent with the Gauss-Newton method. The T-matrix allows for a natural domain decomposition, since in the sense that a large model can be decomposed into an arbitrary number of domains that can be treated independently and in parallel. The T-matrix we use for efficient model updating is also independent of the source-receiver configuration, which could be an advantage when performing fast-repeat modelling and time-lapse inversion. The T-matrix is also compatible with the use of modern renormalization methods that can potentially help us to reduce the sensitivity of the CSEM inversion results on the starting model. To illustrate the performance and potential of our T-matrix variant of the DBI method for CSEM inversion, we performed a numerical experiments based on synthetic CSEM data associated with 2D VTI and 3D orthorombic model inversions. The results of our numerical experiment suggest that the DBIT method for inversion of CSEM data in anisotropic media is both accurate and efficient.

Comparison of Experimental Methods for Estimating Matrix Diffusion Coefficients for Contaminant Transport Modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Telfeyan, Katherine Christina; Ware, Stuart Douglas; Reimus, Paul William

Diffusion cell and diffusion wafer experiments were conducted to compare methods for estimating matrix diffusion coefficients in rock core samples from Pahute Mesa at the Nevada Nuclear Security Site (NNSS). A diffusion wafer method, in which a solute diffuses out of a rock matrix that is pre-saturated with water containing the solute, is presented as a simpler alternative to the traditional through-diffusion (diffusion cell) method. Both methods yielded estimates of matrix diffusion coefficients that were within the range of values previously reported for NNSS volcanic rocks. The difference between the estimates of the two methods ranged from 14 to 30%,more » and there was no systematic high or low bias of one method relative to the other. From a transport modeling perspective, these differences are relatively minor when one considers that other variables (e.g., fracture apertures, fracture spacings) influence matrix diffusion to a greater degree and tend to have greater uncertainty than diffusion coefficients. For the same relative random errors in concentration measurements, the diffusion cell method yields diffusion coefficient estimates that have less uncertainty than the wafer method. However, the wafer method is easier and less costly to implement and yields estimates more quickly, thus allowing a greater number of samples to be analyzed for the same cost and time. Given the relatively good agreement between the methods, and the lack of any apparent bias between the methods, the diffusion wafer method appears to offer advantages over the diffusion cell method if better statistical representation of a given set of rock samples is desired.« less

Condition Number Estimation of Preconditioned Matrices

PubMed Central

Kushida, Noriyuki

2015-01-01

The present paper introduces a condition number estimation method for preconditioned matrices. The newly developed method provides reasonable results, while the conventional method which is based on the Lanczos connection gives meaningless results. The Lanczos connection based method provides the condition numbers of coefficient matrices of systems of linear equations with information obtained through the preconditioned conjugate gradient method. Estimating the condition number of preconditioned matrices is sometimes important when describing the effectiveness of new preconditionerers or selecting adequate preconditioners. Operating a preconditioner on a coefficient matrix is the simplest method of estimation. However, this is not possible for large-scale computing, especially if computation is performed on distributed memory parallel computers. This is because, the preconditioned matrices become dense, even if the original matrices are sparse. Although the Lanczos connection method can be used to calculate the condition number of preconditioned matrices, it is not considered to be applicable to large-scale problems because of its weakness with respect to numerical errors. Therefore, we have developed a robust and parallelizable method based on Hager’s method. The feasibility studies are curried out for the diagonal scaling preconditioner and the SSOR preconditioner with a diagonal matrix, a tri-daigonal matrix and Pei’s matrix. As a result, the Lanczos connection method contains around 10% error in the results even with a simple problem. On the other hand, the new method contains negligible errors. In addition, the newly developed method returns reasonable solutions when the Lanczos connection method fails with Pei’s matrix, and matrices generated with the finite element method. PMID:25816331

SAR Polarimetry

NASA Technical Reports Server (NTRS)

vanZyl, Jakob J.

2012-01-01

Radar Scattering includes: Surface Characteristics, Geometric Properties, Dielectric Properties, Rough Surface Scattering, Geometrical Optics and Small Perturbation Method Solutions, Integral Equation Method, Magellan Image of Pancake Domes on Venus, Dickinson Impact Crater on Venus (Magellan), Lakes on Titan (Cassini Radar, Longitudinal Dunes on Titan (Cassini Radar), Rough Surface Scattering: Effect of Dielectric Constant, Vegetation Scattering, Effect of Soil Moisture. Polarimetric Radar includes: Principles of Polarimetry: Field Descriptions, Wave Polarizations: Geometrical Representations, Definition of Ellipse Orientation Angles, Scatter as Polarization Transformer, Scattering Matrix, Coordinate Systems, Scattering Matrix, Covariance Matrix, Pauli Basis and Coherency Matrix, Polarization Synthesis, Polarimeter Implementation.

Pre-form ceramic matrix composite cavity and a ceramic matrix composite component

DOE Office of Scientific and Technical Information (OSTI.GOV)

Monaghan, Philip Harold; Delvaux, John McConnell; Taxacher, Glenn Curtis

A pre-form CMC cavity and method of forming pre-form CMC cavity for a ceramic matrix component includes providing a mandrel, applying a base ply to the mandrel, laying-up at least one CMC ply on the base ply, removing the mandrel, and densifying the base ply and the at least one CMC ply. The remaining densified base ply and at least one CMC ply form a ceramic matrix component having a desired geometry and a cavity formed therein. Also provided is a method of forming a CMC component.

The Augmented Lagrange Multipliers Method for Matrix Completion from Corrupted Samplings with Application to Mixed Gaussian-Impulse Noise Removal

PubMed Central

Meng, Fan; Yang, Xiaomei; Zhou, Chenghu

2014-01-01

This paper studies the problem of the restoration of images corrupted by mixed Gaussian-impulse noise. In recent years, low-rank matrix reconstruction has become a research hotspot in many scientific and engineering domains such as machine learning, image processing, computer vision and bioinformatics, which mainly involves the problem of matrix completion and robust principal component analysis, namely recovering a low-rank matrix from an incomplete but accurate sampling subset of its entries and from an observed data matrix with an unknown fraction of its entries being arbitrarily corrupted, respectively. Inspired by these ideas, we consider the problem of recovering a low-rank matrix from an incomplete sampling subset of its entries with an unknown fraction of the samplings contaminated by arbitrary errors, which is defined as the problem of matrix completion from corrupted samplings and modeled as a convex optimization problem that minimizes a combination of the nuclear norm and the -norm in this paper. Meanwhile, we put forward a novel and effective algorithm called augmented Lagrange multipliers to exactly solve the problem. For mixed Gaussian-impulse noise removal, we regard it as the problem of matrix completion from corrupted samplings, and restore the noisy image following an impulse-detecting procedure. Compared with some existing methods for mixed noise removal, the recovery quality performance of our method is dominant if images possess low-rank features such as geometrically regular textures and similar structured contents; especially when the density of impulse noise is relatively high and the variance of Gaussian noise is small, our method can outperform the traditional methods significantly not only in the simultaneous removal of Gaussian noise and impulse noise, and the restoration ability for a low-rank image matrix, but also in the preservation of textures and details in the image. PMID:25248103

Acceleration of intensity-modulated radiotherapy dose calculation by importance sampling of the calculation matrices.

PubMed

Thieke, Christian; Nill, Simeon; Oelfke, Uwe; Bortfeld, Thomas

2002-05-01

In inverse planning for intensity-modulated radiotherapy, the dose calculation is a crucial element limiting both the maximum achievable plan quality and the speed of the optimization process. One way to integrate accurate dose calculation algorithms into inverse planning is to precalculate the dose contribution of each beam element to each voxel for unit fluence. These precalculated values are stored in a big dose calculation matrix. Then the dose calculation during the iterative optimization process consists merely of matrix look-up and multiplication with the actual fluence values. However, because the dose calculation matrix can become very large, this ansatz requires a lot of computer memory and is still very time consuming, making it not practical for clinical routine without further modifications. In this work we present a new method to significantly reduce the number of entries in the dose calculation matrix. The method utilizes the fact that a photon pencil beam has a rapid radial dose falloff, and has very small dose values for the most part. In this low-dose part of the pencil beam, the dose contribution to a voxel is only integrated into the dose calculation matrix with a certain probability. Normalization with the reciprocal of this probability preserves the total energy, even though many matrix elements are omitted. Three probability distributions were tested to find the most accurate one for a given memory size. The sampling method is compared with the use of a fully filled matrix and with the well-known method of just cutting off the pencil beam at a certain lateral distance. A clinical example of a head and neck case is presented. It turns out that a sampled dose calculation matrix with only 1/3 of the entries of the fully filled matrix does not sacrifice the quality of the resulting plans, whereby the cutoff method results in a suboptimal treatment plan.

In-situ formation of nanoparticles within a silicon-based matrix

DOEpatents

Thoma, Steven G [Albuquerque, NM; Wilcoxon, Jess P [Albuquerque, NM; Abrams, Billie L [Albuquerque, NM

2008-06-10

A method for encapsulating nanoparticles with an encapsulating matrix that minimizes aggregation and maintains favorable properties of the nanoparticles. The matrix comprises silicon-based network-forming compounds such as ormosils and polysiloxanes. The nanoparticles are synthesized from precursors directly within the silicon-based matrix.

Detection of Matrix Crack Density of CFRP using an Electrical Potential Change Method with Multiple Probes

NASA Astrophysics Data System (ADS)

Todoroki, Akira; Omagari, Kazuomi

Carbon Fiber Reinforced Plastic (CFRP) laminates are adopted for fuel tank structures of next generation space rockets or automobiles. Matrix cracks may cause fuel leak or trigger fatigue damage. A monitoring system of the matrix crack density is required. The authors have developed an electrical resistance change method for the monitoring of delamination cracks in CFRP laminates. Reinforcement fibers are used as a self-sensing system. In the present study, the electric potential method is adopted for matrix crack density monitoring. Finite element analysis (FEA) was performed to investigate the possibility of monitoring matrix crack density using multiple electrodes mounted on a single surface of a specimen. The FEA reveals the matrix crack density increases electrical resistance for a target segment between electrodes. Experimental confirmation was also performed using cross-ply laminates. Eight electrodes were mounted on a single surface of a specimen using silver paste after polishing of the specimen surface with sandpaper. The two outermost electrodes applied electrical current, and the inner electrodes measured electric voltage changes. The slope of electrical resistance during reloading is revealed to be an appropriate index for the detection of matrix crack density.

A Brief Research Review for Improvement Methods the Wettability between Ceramic Reinforcement Particulate and Aluminium Matrix Composites

NASA Astrophysics Data System (ADS)

Razzaq, Alaa Mohammed; Majid, Dayang Laila Abang Abdul; Ishak, M. R.; B, Uday M.

2017-05-01

The development of new methods for addition fine ceramic powders to Al aluminium alloy melts, which would lead to more uniform distribution and effective incorporation of the reinforcement particles into the aluminium matrix alloy. Recently the materials engineering research has moved to composite materials from monolithic, adapting to the global need for lightweight, low cost, quality, and high performance advanced materials. Among the different methods, stir casting is one of the simplest ways of making aluminium matrix composites. However, it suffers from poor distribution and combination of the reinforcement ceramic particles in the metal matrix. These problems become significantly effect to reduce reinforcement size, more agglomeration and tendency with less wettability for the ceramic particles in the melt process. Many researchers have carried out different studies on the wettability between the metal matrix and dispersion phase, which includes added wettability agents, fluxes, preheating the reinforcement particles, coating the reinforcement particles, and use composting techniques. The enhancement of wettability of ceramic particles by the molten matrix alloy and the reinforcement particles distribution improvement in the solidified matrix is the main objective for many studies that will be discussed in this paper.

Preparation of magnesium metal matrix composites by powder metallurgy process

NASA Astrophysics Data System (ADS)

Satish, J.; Satish, K. G., Dr.

2018-02-01

Magnesium is the lightest metal used as the source for constructional alloys. Today Magnesium based metal matrix composites are widely used in aerospace, structural, oceanic and automobile applications for its light weight, low density(two thirds that of aluminium), good high temperature mechanical properties and good to excellent corrosion resistance. The reason of designing metal matrix composite is to put in the attractive attributes of metals and ceramics to the base metal. In this study magnesium metal matrix hybrid composite are developed by reinforcing pure magnesium with silicon carbide (SiC) and aluminium oxide by method of powder metallurgy. This method is less expensive and very efficient. The Hardness test was performed on the specimens prepared by powder metallurgy method. The results revealed that the micro hardness of composites was increased with the addition of silicon carbide and alumina particles in magnesium metal matrix composites.

Apparatus and system for multivariate spectral analysis

DOEpatents

Keenan, Michael R.; Kotula, Paul G.

2003-06-24

An apparatus and system for determining the properties of a sample from measured spectral data collected from the sample by performing a method of multivariate spectral analysis. The method can include: generating a two-dimensional matrix A containing measured spectral data; providing a weighted spectral data matrix D by performing a weighting operation on matrix A; factoring D into the product of two matrices, C and S.sup.T, by performing a constrained alternating least-squares analysis of D=CS.sup.T, where C is a concentration intensity matrix and S is a spectral shapes matrix; unweighting C and S by applying the inverse of the weighting used previously; and determining the properties of the sample by inspecting C and S. This method can be used by a spectrum analyzer to process X-ray spectral data generated by a spectral analysis system that can include a Scanning Electron Microscope (SEM) with an Energy Dispersive Detector and Pulse Height Analyzer.

Classification and identification of molecules through factor analysis method based on terahertz spectroscopy

NASA Astrophysics Data System (ADS)

Huang, Jianglou; Liu, Jinsong; Wang, Kejia; Yang, Zhengang; Liu, Xiaming

2018-06-01

By means of factor analysis approach, a method of molecule classification is built based on the measured terahertz absorption spectra of the molecules. A data matrix can be obtained by sampling the absorption spectra at different frequency points. The data matrix is then decomposed into the product of two matrices: a weight matrix and a characteristic matrix. By using the K-means clustering to deal with the weight matrix, these molecules can be classified. A group of samples (spirobenzopyran, indole, styrene derivatives and inorganic salts) has been prepared, and measured via a terahertz time-domain spectrometer. These samples are classified with 75% accuracy compared to that directly classified via their molecular formulas.

Fast radiative transfer models for retrieval of cloud properties in the back-scattering region: application to DSCOVR-EPIC sensor

NASA Astrophysics Data System (ADS)

Molina Garcia, Victor; Sasi, Sruthy; Efremenko, Dmitry; Doicu, Adrian; Loyola, Diego

2017-04-01

In this work, the requirements for the retrieval of cloud properties in the back-scattering region are described, and their application to the measurements taken by the Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR) is shown. Various radiative transfer models and their linearizations are implemented, and their advantages and issues are analyzed. As radiative transfer calculations in the back-scattering region are computationally time-consuming, several acceleration techniques are also studied. The radiative transfer models analyzed include the exact Discrete Ordinate method with Matrix Exponential (DOME), the Matrix Operator method with Matrix Exponential (MOME), and the approximate asymptotic and equivalent Lambertian cloud models. To reduce the computational cost of the line-by-line (LBL) calculations, the k-distribution method, the Principal Component Analysis (PCA) and a combination of the k-distribution method plus PCA are used. The linearized radiative transfer models for retrieval of cloud properties include the Linearized Discrete Ordinate method with Matrix Exponential (LDOME), the Linearized Matrix Operator method with Matrix Exponential (LMOME) and the Forward-Adjoint Discrete Ordinate method with Matrix Exponential (FADOME). These models were applied to the EPIC oxygen-A band absorption channel at 764 nm. It is shown that the approximate asymptotic and equivalent Lambertian cloud models give inaccurate results, so an offline processor for the retrieval of cloud properties in the back-scattering region requires the use of exact models such as DOME and MOME, which behave similarly. The combination of the k-distribution method plus PCA presents similar accuracy to the LBL calculations, but it is up to 360 times faster, and the relative errors for the computed radiances are less than 1.5% compared to the results when the exact phase function is used. Finally, the linearized models studied show similar behavior, with relative errors less than 1% for the radiance derivatives, but FADOME is 2 times faster than LDOME and 2.5 times faster than LMOME.

DNA melting profiles from a matrix method.

PubMed

Poland, Douglas

2004-02-05

In this article we give a new method for the calculation of DNA melting profiles. Based on the matrix formulation of the DNA partition function, the method relies for its efficiency on the fact that the required matrices are very sparse, essentially reducing matrix multiplication to vector multiplication and thus making the computer time required to treat a DNA molecule containing N base pairs proportional to N(2). A key ingredient in the method is the result that multiplication by the inverse matrix can also be reduced to vector multiplication. The task of calculating the melting profile for the entire genome is further reduced by treating regions of the molecule between helix-plateaus, thus breaking the molecule up into independent parts that can each be treated individually. The method is easily modified to incorporate changes in the assignment of statistical weights to the different structural features of DNA. We illustrate the method using the genome of Haemophilus influenzae. Copyright 2003 Wiley Periodicals, Inc.

A comparison of matrix methods for calculating eigenvalues in acoustically lined ducts

NASA Technical Reports Server (NTRS)

Watson, W.; Lansing, D. L.

1976-01-01

Three approximate methods - finite differences, weighted residuals, and finite elements - were used to solve the eigenvalue problem which arises in finding the acoustic modes and propagation constants in an absorptively lined two-dimensional duct without airflow. The matrix equations derived for each of these methods were solved for the eigenvalues corresponding to various values of wall impedance. Two matrix orders, 20 x 20 and 40 x 40, were used. The cases considered included values of wall admittance for which exact eigenvalues were known and for which several nearly equal roots were present. Ten of the lower order eigenvalues obtained from the three approximate methods were compared with solutions calculated from the exact characteristic equation in order to make an assessment of the relative accuracy and reliability of the three methods. The best results were given by the finite element method using a cubic polynomial. Excellent accuracy was consistently obtained, even for nearly equal eigenvalues, by using a 20 x 20 order matrix.

Novel Precursor Approached for CMC Derived by Polymer Pyrolysis

DTIC Science & Technology

1994-02-15

to remove signals from probe polymer materials. C. Pyrolysis Methods The conversion of polymeric PMVS to SiC -containing ceramic was studied by... Composite Fabrication Methods Ceramic matrix composites with different matrix compositions were fabricated using the Polymer Impregnation- Pyrolysis (PIP...Pyrolyzed composites were re- infiltrated with the appropriate polymer matrix source under vacuum, and cured in an autoclave under 100 psi overpressure of N2

Creep-rupture of polymer-matrix composites. [graphite-epoxy laminates

NASA Technical Reports Server (NTRS)

Brinson, H. F.; Griffith, W. I.; Morris, D. H.

1980-01-01

An accelerated characterization method for resin matrix composites is reviewed. Methods for determining modulus and strength master curves are given. Creep rupture analytical models are discussed as applied to polymers and polymer matrix composites. Comparisons between creep rupture experiments and analytical models are presented. The time dependent creep rupture process in graphite epoxy laminates is examined as a function of temperature and stress level.

Bioengineered anterior cruciate ligament

NASA Technical Reports Server (NTRS)

Martin, Ivan (Inventor); Altman, Gregory (Inventor); Kaplan, David (Inventor); Vunjak-Novakovic, Gordana (Inventor)

2001-01-01

The present invention provides a method for producing an anterior cruciate ligament ex vivo. The method comprises seeding pluripotent stem cells in a three dimensional matrix, anchoring the seeded matrix by attachment to two anchors, and culturing the cells within the matrix under conditions appropriate for cell growth and regeneration, while subjecting the matrix to one or more mechanical forces via movement of one or both of the attached anchors. Bone marrow stromal cells are preferably used as the pluripotent cells in the method. Suitable matrix materials are materials to which cells can adhere, such as a gel made from collagen type I. Suitable anchor materials are materials to which the matrix can attach, such as Goinopra coral and also demineralized bone. Optimally, the mechanical forces to which the matrix is subjected mimic mechanical stimuli experienced by an anterior cruciate ligament in vivo. This is accomplished by delivering the appropriate combination of tension, compression, torsion, and shear, to the matrix. The bioengineered ligament which is produced by this method is characterized by a cellular orientation and/or matrix crimp pattern in the direction of the applied mechanical forces, and also by the production of collagen type I, collagen type III, and fibronectin proteins along the axis of mechanical load produced by the mechanical forces. Optimally, the ligament produced has fiber bundles which are arranged into a helical organization. The method for producing an anterior cruciate ligament can be adapted to produce a wide range of tissue types ex vivo by adapting the anchor size and attachment sites to reflect the size of the specific type of tissue to be produced, and also adapting the specific combination of forces applied, to mimic the mechanical stimuli experienced in vivo by the specific type of tissue to be produced. The methods of the present invention can be further modified to incorporate other stimuli experienced in vivo by the particular developing tissue, some examples of the stimuli being chemical stimuli, and electro-magnetic stimuli. Some examples of tissue which can be produced include other ligaments in the body (hand, wrist, elbow, knee), tendon, cartilage, bone, muscle, and blood vessels.

Continuous improvement of medical test reliability using reference methods and matrix-corrected target values in proficiency testing schemes: application to glucose assay.

PubMed

Delatour, Vincent; Lalere, Beatrice; Saint-Albin, Karène; Peignaux, Maryline; Hattchouel, Jean-Marc; Dumont, Gilles; De Graeve, Jacques; Vaslin-Reimann, Sophie; Gillery, Philippe

2012-11-20

The reliability of biological tests is a major issue for patient care in terms of public health that involves high economic stakes. Reference methods, as well as regular external quality assessment schemes (EQAS), are needed to monitor the analytical performance of field methods. However, control material commutability is a major concern to assess method accuracy. To overcome material non-commutability, we investigated the possibility of using lyophilized serum samples together with a limited number of frozen serum samples to assign matrix-corrected target values, taking the example of glucose assays. Trueness of the current glucose assays was first measured against a primary reference method by using human frozen sera. Methods using hexokinase and glucose oxidase with spectroreflectometric detection proved very accurate, with bias ranging between -2.2% and +2.3%. Bias of methods using glucose oxidase with spectrophotometric detection was +4.5%. Matrix-related bias of the lyophilized materials was then determined and ranged from +2.5% to -14.4%. Matrix-corrected target values were assigned and used to assess trueness of 22 sub-peer groups. We demonstrated that matrix-corrected target values can be a valuable tool to assess field method accuracy in large scale surveys where commutable materials are not available in sufficient amount with acceptable costs. Copyright © 2012 Elsevier B.V. All rights reserved.

Multi-color incomplete Cholesky conjugate gradient methods for vector computers. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Poole, E. L.

1986-01-01

In this research, we are concerned with the solution on vector computers of linear systems of equations, Ax = b, where A is a larger, sparse symmetric positive definite matrix. We solve the system using an iterative method, the incomplete Cholesky conjugate gradient method (ICCG). We apply a multi-color strategy to obtain p-color matrices for which a block-oriented ICCG method is implemented on the CYBER 205. (A p-colored matrix is a matrix which can be partitioned into a pXp block matrix where the diagonal blocks are diagonal matrices). This algorithm, which is based on a no-fill strategy, achieves O(N/p) length vector operations in both the decomposition of A and in the forward and back solves necessary at each iteration of the method. We discuss the natural ordering of the unknowns as an ordering that minimizes the number of diagonals in the matrix and define multi-color orderings in terms of disjoint sets of the unknowns. We give necessary and sufficient conditions to determine which multi-color orderings of the unknowns correpond to p-color matrices. A performance model is given which is used both to predict execution time for ICCG methods and also to compare an ICCG method to conjugate gradient without preconditioning or another ICCG method. Results are given from runs on the CYBER 205 at NASA's Langley Research Center for four model problems.

General MoM Solutions for Large Arrays

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fasenfest, B; Capolino, F; Wilton, D R

2003-07-22

This paper focuses on a numerical procedure that addresses the difficulties of dealing with large, finite arrays while preserving the generality and robustness of full-wave methods. We present a fast method based on approximating interactions between sufficiently separated array elements via a relatively coarse interpolation of the Green's function on a uniform grid commensurate with the array's periodicity. The interaction between the basis and testing functions is reduced to a three-stage process. The first stage is a projection of standard (e.g., RWG) subdomain bases onto a set of interpolation functions that interpolate the Green's function on the array face. Thismore » projection, which is used in a matrix/vector product for each array cell in an iterative solution process, need only be carried out once for a single cell and results in a low-rank matrix. An intermediate stage matrix/vector product computation involving the uniformly sampled Green's function is of convolutional form in the lateral (transverse) directions so that a 2D FFT may be used. The final stage is a third matrix/vector product computation involving a matrix resulting from projecting testing functions onto the Green's function interpolation functions; the low-rank matrix is either identical to (using Galerkin's method) or similar to that for the bases projection. An effective MoM solution scheme is developed for large arrays using a modification of the AIM (Adaptive Integral Method) method. The method permits the analysis of arrays with arbitrary contours and nonplanar elements. Both fill and solve times within the MoM method are improved with respect to more standard MoM solvers.« less

Optimization of matrix tablets controlled drug release using Elman dynamic neural networks and decision trees.

PubMed

Petrović, Jelena; Ibrić, Svetlana; Betz, Gabriele; Đurić, Zorica

2012-05-30

The main objective of the study was to develop artificial intelligence methods for optimization of drug release from matrix tablets regardless of the matrix type. Static and dynamic artificial neural networks of the same topology were developed to model dissolution profiles of different matrix tablets types (hydrophilic/lipid) using formulation composition, compression force used for tableting and tablets porosity and tensile strength as input data. Potential application of decision trees in discovering knowledge from experimental data was also investigated. Polyethylene oxide polymer and glyceryl palmitostearate were used as matrix forming materials for hydrophilic and lipid matrix tablets, respectively whereas selected model drugs were diclofenac sodium and caffeine. Matrix tablets were prepared by direct compression method and tested for in vitro dissolution profiles. Optimization of static and dynamic neural networks used for modeling of drug release was performed using Monte Carlo simulations or genetic algorithms optimizer. Decision trees were constructed following discretization of data. Calculated difference (f(1)) and similarity (f(2)) factors for predicted and experimentally obtained dissolution profiles of test matrix tablets formulations indicate that Elman dynamic neural networks as well as decision trees are capable of accurate predictions of both hydrophilic and lipid matrix tablets dissolution profiles. Elman neural networks were compared to most frequently used static network, Multi-layered perceptron, and superiority of Elman networks have been demonstrated. Developed methods allow simple, yet very precise way of drug release predictions for both hydrophilic and lipid matrix tablets having controlled drug release. Copyright © 2012 Elsevier B.V. All rights reserved.

Visualization of extracellular matrix components within sectioned Salmonella biofilms on the surface of human gallstones.

PubMed

Marshall, Joanna M; Flechtner, Alan D; La Perle, Krista M; Gunn, John S

2014-01-01

Chronic carriage of Salmonella Typhi is mediated primarily through the formation of bacterial biofilms on the surface of cholesterol gallstones. Biofilms, by definition, involve the formation of a bacterial community encased within a protective macromolecular matrix. Previous work has demonstrated the composition of the biofilm matrix to be complex and highly variable in response to altered environmental conditions. Although known to play an important role in bacterial persistence in a variety of contexts, the Salmonella biofilm matrix remains largely uncharacterized under physiological conditions. Initial attempts to study matrix components and architecture of the biofilm matrix on gallstone surfaces were hindered by the auto-fluorescence of cholesterol. In this work we describe a method for sectioning and direct visualization of extracellular matrix components of the Salmonella biofilm on the surface of human cholesterol gallstones and provide a description of the major matrix components observed therein. Confocal micrographs revealed robust biofilm formation, characterized by abundant but highly heterogeneous expression of polysaccharides such as LPS, Vi and O-antigen capsule. CsgA was not observed in the biofilm matrix and flagellar expression was tightly restricted to the biofilm-cholesterol interface. Images also revealed the presence of preexisting Enterobacteriaceae encased within the structure of the gallstone. These results demonstrate the use and feasibility of this method while highlighting the importance of studying the native architecture of the gallstone biofilm. A better understanding of the contribution of individual matrix components to the overall biofilm structure will facilitate the development of more effective and specific methods to disrupt these bacterial communities.

Discriminative Transfer Subspace Learning via Low-Rank and Sparse Representation.

PubMed

Xu, Yong; Fang, Xiaozhao; Wu, Jian; Li, Xuelong; Zhang, David

2016-02-01

In this paper, we address the problem of unsupervised domain transfer learning in which no labels are available in the target domain. We use a transformation matrix to transfer both the source and target data to a common subspace, where each target sample can be represented by a combination of source samples such that the samples from different domains can be well interlaced. In this way, the discrepancy of the source and target domains is reduced. By imposing joint low-rank and sparse constraints on the reconstruction coefficient matrix, the global and local structures of data can be preserved. To enlarge the margins between different classes as much as possible and provide more freedom to diminish the discrepancy, a flexible linear classifier (projection) is obtained by learning a non-negative label relaxation matrix that allows the strict binary label matrix to relax into a slack variable matrix. Our method can avoid a potentially negative transfer by using a sparse matrix to model the noise and, thus, is more robust to different types of noise. We formulate our problem as a constrained low-rankness and sparsity minimization problem and solve it by the inexact augmented Lagrange multiplier method. Extensive experiments on various visual domain adaptation tasks show the superiority of the proposed method over the state-of-the art methods. The MATLAB code of our method will be publicly available at http://www.yongxu.org/lunwen.html.

Population clustering based on copy number variations detected from next generation sequencing data.

PubMed

Duan, Junbo; Zhang, Ji-Gang; Wan, Mingxi; Deng, Hong-Wen; Wang, Yu-Ping

2014-08-01

Copy number variations (CNVs) can be used as significant bio-markers and next generation sequencing (NGS) provides a high resolution detection of these CNVs. But how to extract features from CNVs and further apply them to genomic studies such as population clustering have become a big challenge. In this paper, we propose a novel method for population clustering based on CNVs from NGS. First, CNVs are extracted from each sample to form a feature matrix. Then, this feature matrix is decomposed into the source matrix and weight matrix with non-negative matrix factorization (NMF). The source matrix consists of common CNVs that are shared by all the samples from the same group, and the weight matrix indicates the corresponding level of CNVs from each sample. Therefore, using NMF of CNVs one can differentiate samples from different ethnic groups, i.e. population clustering. To validate the approach, we applied it to the analysis of both simulation data and two real data set from the 1000 Genomes Project. The results on simulation data demonstrate that the proposed method can recover the true common CNVs with high quality. The results on the first real data analysis show that the proposed method can cluster two family trio with different ancestries into two ethnic groups and the results on the second real data analysis show that the proposed method can be applied to the whole-genome with large sample size consisting of multiple groups. Both results demonstrate the potential of the proposed method for population clustering.

An Efficient Local Correlation Matrix Decomposition Approach for the Localization Implementation of Ensemble-Based Assimilation Methods

NASA Astrophysics Data System (ADS)

Zhang, Hongqin; Tian, Xiangjun

2018-04-01

Ensemble-based data assimilation methods often use the so-called localization scheme to improve the representation of the ensemble background error covariance (Be). Extensive research has been undertaken to reduce the computational cost of these methods by using the localized ensemble samples to localize Be by means of a direct decomposition of the local correlation matrix C. However, the computational costs of the direct decomposition of the local correlation matrix C are still extremely high due to its high dimension. In this paper, we propose an efficient local correlation matrix decomposition approach based on the concept of alternating directions. This approach is intended to avoid direct decomposition of the correlation matrix. Instead, we first decompose the correlation matrix into 1-D correlation matrices in the three coordinate directions, then construct their empirical orthogonal function decomposition at low resolution. This procedure is followed by the 1-D spline interpolation process to transform the above decompositions to the high-resolution grid. Finally, an efficient correlation matrix decomposition is achieved by computing the very similar Kronecker product. We conducted a series of comparison experiments to illustrate the validity and accuracy of the proposed local correlation matrix decomposition approach. The effectiveness of the proposed correlation matrix decomposition approach and its efficient localization implementation of the nonlinear least-squares four-dimensional variational assimilation are further demonstrated by several groups of numerical experiments based on the Advanced Research Weather Research and Forecasting model.

Use of the maximum entropy method to retrieve the vertical atmospheric ozone profile and predict atmospheric ozone content

NASA Technical Reports Server (NTRS)

Turner, B. Curtis

1992-01-01

A method is developed for prediction of ozone levels in planetary atmospheres. This method is formulated in terms of error covariance matrices, and is associated with both direct measurements, a priori first guess profiles, and a weighting function matrix. This is described by the following linearized equation: y = A(matrix) x X + eta, where A is the weighting matrix and eta is noise. The problems to this approach are: (1) the A matrix is near singularity; (2) the number of unknowns in the profile exceeds the number of data points, therefore, the solution may not be unique; and (3) even if a unique solution exists, eta may cause the solution to be ill conditioned.

Crystallization of bFGF-DNA Aptamer Complexes Using a Sparse Matrix Designed for Protein-Nucleic Acid Complexes

NASA Technical Reports Server (NTRS)

Cannone, Jaime J.; Barnes, Cindy L.; Achari, Aniruddha; Kundrot, Craig E.; Whitaker, Ann F. (Technical Monitor)

2001-01-01

The Sparse Matrix approach for obtaining lead crystallization conditions has proven to be very fruitful for the crystallization of proteins and nucleic acids. Here we report a Sparse Matrix developed specifically for the crystallization of protein-DNA complexes. This method is rapid and economical, typically requiring 2.5 mg of complex to test 48 conditions. The method was originally developed to crystallize basic fibroblast growth factor (bFGF) complexed with DNA sequences identified through in vitro selection, or SELEX, methods. Two DNA aptamers that bind with approximately nanomolar affinity and inhibit the angiogenic properties of bFGF were selected for co-crystallization. The Sparse Matrix produced lead crystallization conditions for both bFGF-DNA complexes.

Carbonate fuel cell matrix

DOEpatents

Farooque, Mohammad; Yuh, Chao-Yi

1996-01-01

A carbonate fuel cell matrix comprising support particles and crack attenuator particles which are made platelet in shape to increase the resistance of the matrix to through cracking. Also disclosed is a matrix having porous crack attenuator particles and a matrix whose crack attenuator particles have a thermal coefficient of expansion which is significantly different from that of the support particles, and a method of making platelet-shaped crack attenuator particles.

A novel method for morphological pleomorphism and heterogeneity quantitative measurement: Named cell feature level co-occurrence matrix.

PubMed

Saito, Akira; Numata, Yasushi; Hamada, Takuya; Horisawa, Tomoyoshi; Cosatto, Eric; Graf, Hans-Peter; Kuroda, Masahiko; Yamamoto, Yoichiro

2016-01-01

Recent developments in molecular pathology and genetic/epigenetic analysis of cancer tissue have resulted in a marked increase in objective and measurable data. In comparison, the traditional morphological analysis approach to pathology diagnosis, which can connect these molecular data and clinical diagnosis, is still mostly subjective. Even though the advent and popularization of digital pathology has provided a boost to computer-aided diagnosis, some important pathological concepts still remain largely non-quantitative and their associated data measurements depend on the pathologist's sense and experience. Such features include pleomorphism and heterogeneity. In this paper, we propose a method for the objective measurement of pleomorphism and heterogeneity, using the cell-level co-occurrence matrix. Our method is based on the widely used Gray-level co-occurrence matrix (GLCM), where relations between neighboring pixel intensity levels are captured into a co-occurrence matrix, followed by the application of analysis functions such as Haralick features. In the pathological tissue image, through image processing techniques, each nucleus can be measured and each nucleus has its own measureable features like nucleus size, roundness, contour length, intra-nucleus texture data (GLCM is one of the methods). In GLCM each nucleus in the tissue image corresponds to one pixel. In this approach the most important point is how to define the neighborhood of each nucleus. We define three types of neighborhoods of a nucleus, then create the co-occurrence matrix and apply Haralick feature functions. In each image pleomorphism and heterogeneity are then determined quantitatively. For our method, one pixel corresponds to one nucleus feature, and we therefore named our method Cell Feature Level Co-occurrence Matrix (CFLCM). We tested this method for several nucleus features. CFLCM is showed as a useful quantitative method for pleomorphism and heterogeneity on histopathological image analysis.

A new fast direct solver for the boundary element method

NASA Astrophysics Data System (ADS)

Huang, S.; Liu, Y. J.

2017-09-01

A new fast direct linear equation solver for the boundary element method (BEM) is presented in this paper. The idea of the new fast direct solver stems from the concept of the hierarchical off-diagonal low-rank matrix. The hierarchical off-diagonal low-rank matrix can be decomposed into the multiplication of several diagonal block matrices. The inverse of the hierarchical off-diagonal low-rank matrix can be calculated efficiently with the Sherman-Morrison-Woodbury formula. In this paper, a more general and efficient approach to approximate the coefficient matrix of the BEM with the hierarchical off-diagonal low-rank matrix is proposed. Compared to the current fast direct solver based on the hierarchical off-diagonal low-rank matrix, the proposed method is suitable for solving general 3-D boundary element models. Several numerical examples of 3-D potential problems with the total number of unknowns up to above 200,000 are presented. The results show that the new fast direct solver can be applied to solve large 3-D BEM models accurately and with better efficiency compared with the conventional BEM.

Detection of LSB+/-1 steganography based on co-occurrence matrix and bit plane clipping

NASA Astrophysics Data System (ADS)

Abolghasemi, Mojtaba; Aghaeinia, Hassan; Faez, Karim; Mehrabi, Mohammad Ali

2010-01-01

Spatial LSB+/-1 steganography changes smooth characteristics between adjoining pixels of the raw image. We present a novel steganalysis method for LSB+/-1 steganography based on feature vectors derived from the co-occurrence matrix in the spatial domain. We investigate how LSB+/-1 steganography affects the bit planes of an image and show that it changes more least significant bit (LSB) planes of it. The co-occurrence matrix is derived from an image in which some of its most significant bit planes are clipped. By this preprocessing, in addition to reducing the dimensions of the feature vector, the effects of embedding were also preserved. We compute the co-occurrence matrix in different directions and with different dependency and use the elements of the resulting co-occurrence matrix as features. This method is sensitive to the data embedding process. We use a Fisher linear discrimination (FLD) classifier and test our algorithm on different databases and embedding rates. We compare our scheme with the current LSB+/-1 steganalysis methods. It is shown that the proposed scheme outperforms the state-of-the-art methods in detecting the LSB+/-1 steganographic method for grayscale images.

Limited memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) method for the parameter estimation on geographically weighted ordinal logistic regression model (GWOLR)

NASA Astrophysics Data System (ADS)

Saputro, Dewi Retno Sari; Widyaningsih, Purnami

2017-08-01

In general, the parameter estimation of GWOLR model uses maximum likelihood method, but it constructs a system of nonlinear equations, making it difficult to find the solution. Therefore, an approximate solution is needed. There are two popular numerical methods: the methods of Newton and Quasi-Newton (QN). Newton's method requires large-scale time in executing the computation program since it contains Jacobian matrix (derivative). QN method overcomes the drawback of Newton's method by substituting derivative computation into a function of direct computation. The QN method uses Hessian matrix approach which contains Davidon-Fletcher-Powell (DFP) formula. The Broyden-Fletcher-Goldfarb-Shanno (BFGS) method is categorized as the QN method which has the DFP formula attribute of having positive definite Hessian matrix. The BFGS method requires large memory in executing the program so another algorithm to decrease memory usage is needed, namely Low Memory BFGS (LBFGS). The purpose of this research is to compute the efficiency of the LBFGS method in the iterative and recursive computation of Hessian matrix and its inverse for the GWOLR parameter estimation. In reference to the research findings, we found out that the BFGS and LBFGS methods have arithmetic operation schemes, including O(n2) and O(nm).

Evaluation of the matrix exponential for use in ground-water-flow and solute-transport simulations; theoretical framework

USGS Publications Warehouse

Umari, A.M.; Gorelick, S.M.

1986-01-01

It is possible to obtain analytic solutions to the groundwater flow and solute transport equations if space variables are discretized but time is left continuous. From these solutions, hydraulic head and concentration fields for any future time can be obtained without ' marching ' through intermediate time steps. This analytical approach involves matrix exponentiation and is referred to as the Matrix Exponential Time Advancement (META) method. Two algorithms are presented for the META method, one for symmetric and the other for non-symmetric exponent matrices. A numerical accuracy indicator, referred to as the matrix condition number, was defined and used to determine the maximum number of significant figures that may be lost in the META method computations. The relative computational and storage requirements of the META method with respect to the time marching method increase with the number of nodes in the discretized problem. The potential greater accuracy of the META method and the associated greater reliability through use of the matrix condition number have to be weighed against this increased relative computational and storage requirements of this approach as the number of nodes becomes large. For a particular number of nodes, the META method may be computationally more efficient than the time-marching method, depending on the size of time steps used in the latter. A numerical example illustrates application of the META method to a sample ground-water-flow problem. (Author 's abstract)

Spectral analysis of the UFBG-based acousto—optical modulator in V-I transmission matrix formalism

NASA Astrophysics Data System (ADS)

Wu, Liang-Ying; Pei, Li; Liu, Chao; Wang, Yi-Qun; Weng, Si-Jun; Wang, Jian-Shuai

2014-11-01

In this study, the V-I transmission matrix formalism (V-I method) is proposed to analyze the spectrum characteristics of the uniform fiber Bragg grating (FBG)-based acousto—optic modulators (UFBG-AOM). The simulation results demonstrate that both the amplitude of the acoustically induced strain and the frequency of the acoustic wave (AW) have an effect on the spectrum. Additionally, the wavelength spacing between the primary reflectivity peak and the secondary reflectivity peak is proportional to the acoustic frequency with the ratio 0.1425 nm/MHz. Meanwhile, we compare the amount of calculation. For the FBG whose period is M, the calculation of the V-I method is 4 × (2M-1) in addition/subtraction, 8 × (2M - 1) in multiply/division and 2M in exponent arithmetic, which is almost a quarter of the multi-film method and transfer matrix (TM) method. The detailed analysis indicates that, compared with the conventional multi-film method and transfer matrix (TM) method, the V-I method is faster and less complex.

A method for the detection of the refractive index of irregular shape solid pigments in light absorbing liquid matrix.

PubMed

Niskanen, Ilpo; Räty, Jukka; Peiponen, Kai-Erik

2010-06-15

The immersion liquid method is powerful for the measurement of the refractive index of solid particles in a liquid matrix. However, this method applies best for cases when the liquid matrix is transparent. A problem is usually how to assess the refractive index of a pigment when it is in a colored host liquid. In this article we introduce a method, and show that by combining so-called multifunction spectrophotometer, immersion liquid method and detection of light transmission and reflection we can assess the refractive index of a pigment in a colored liquid, and also the extinction or absorption coefficient of the host liquid.

Reverse matrix converter control method for PMSM drives using DPC

NASA Astrophysics Data System (ADS)

Bak, Yeongsu; Lee, Kyo-Beum

2018-05-01

This paper proposes a control method for a reverse matrix converter (RMC) that drives a three-phase permanent magnet synchronous motor (PMSM). In this proposed method, direct power control (DPC) is used to control the voltage source rectifier of the RMC. The RMC is an indirect matrix converter operating in the boost mode, in which the power-flow directions of the input and output are switched. It has a minimum voltage transfer ratio of 1/0.866 in a linear-modulation region. In this paper, a control method that uses DPC as an additional control method is proposed in order to control the RMC driving a PMSM in the output stage. Simulations and experimental results verify the effectiveness of the proposed control method.

Response of a Rotating Propeller to Aerodynamic Excitation

NASA Technical Reports Server (NTRS)

Arnoldi, Walter E.

1949-01-01

The flexural vibration of a rotating propeller blade with clamped shank is analyzed with the object of presenting, in matrix form, equations for the elastic bending moments in forced vibration resulting from aerodynamic forces applied at a fixed multiple of rotational speed. Matrix equations are also derived which define the critical speeds end mode shapes for any excitation order and the relation between critical speed and blade angle. Reference is given to standard works on the numerical solution of matrix equations of the forms derived. The use of a segmented blade as an approximation to a continuous blade provides a simple means for obtaining the matrix solution from the integral equation of equilibrium, so that, in the numerical application of the method presented, the several matrix arrays of the basic physical characteristics of the propeller blade are of simple form, end their simplicity is preserved until, with the solution in sight, numerical manipulations well-known in matrix algebra yield the desired critical speeds and mode shapes frame which the vibration at any operating condition may be synthesized. A close correspondence between the familiar Stodola method and the matrix method is pointed out, indicating that any features of novelty are characteristic not of the analytical procedure but only of the abbreviation, condensation, and efficient organization of the numerical procedure made possible by the use of classical matrix theory.

Accuracy verification and identification of matrix effects. The College of American Pathologists' Protocol.

PubMed

Eckfeldt, J H; Copeland, K R

1993-04-01

Proficiency testing using stabilized control materials has been used for decades as a means of monitoring and improving performance in the clinical laboratory. Often, the commonly used proficiency testing materials exhibit "matrix effects" that cause them to behave differently from fresh human specimens in certain clinical analytic systems. Because proficiency testing is the primary method in which regulatory agencies have chosen to evaluate clinical laboratory performance, the College of American Pathologists (CAP) has proposed guidelines for investigating the influence of matrix effects on their Survey results. The purpose of this investigation was to determine the feasibility, usefulness, and potential problems associated with this CAP Matrix Effect Analytical Protocol, in which fresh patient specimens and CAP proficiency specimens are analyzed simultaneously by a field method and a definitive, reference, or other comparative method. The optimal outcome would be that both the fresh human and CAP Survey specimens agree closely with the comparative method result. However, this was not always the case. Using several different analytic configurations, we were able to demonstrate matrix and calibration biases for several of the analytes investigated.

Methods for providing ceramic matrix composite components with increased thermal capacity

NASA Technical Reports Server (NTRS)

Steibel, James Dale (Inventor); Utah, David Alan (Inventor)

2001-01-01

A method for enhancing the cooling capability of a turbine component made from a ceramic matrix composite. The method improves the thermal performance of the component by producing a surface having increased cooling capacity, thereby allowing the component to operate at a higher temperature. The method tailors the available surface area on the cooling surface of the composite component by depositing a particulate layer of coarse grained ceramic powders of preselected size onto the surface of the ceramic matrix composite component. The size of the particulate is selectively tailored to match the desired surface finish or surface roughness of the article. The article may be designed to have different surface finishes for different locations, so that the application of different sized powders can provide different cooling capabilities at different locations, if desired. The compositions of the particulates are chemically compatible with the ceramic material comprising the outer surface or portion of the ceramic matrix composite. The particulates are applied using a slurry and incorporated into the article by heating to an elevated temperature without melting the matrix, the particulates or the fiber reinforcement.

Calculation of Collisional Cross Sections for the 2P3/2 - 2P1/2 Transition in Alkali-Noble Gas Systems

DTIC Science & Technology

2010-03-01

matrix elements. From scattering matrix elements for several different effective potential values and using the Method of Partial Waves[7], the...scattering matrix elements. Through the Method of Par- tial Waves[7], the procedure was repeated for several different effective potentials. The...section calculations. It is important to note that lmax may differ for σel and σi→f . This method may only be used if both σi→f and σel have

Test method development for structural characterization of fiber composites at high temperatures

NASA Technical Reports Server (NTRS)

Mandell, J. F.; Grande, D. H.; Edwards, B.

1985-01-01

Test methods used for structural characterization of polymer matrix composites can be applied to glass and ceramic matrix composites only at low temperatures. New test methods are required for tensile, compressive, and shear properties of fiber composites at high temperatures. A tensile test which should be useful to at least 1000 C has been developed and used to characterize the properties of a Nicalon/glass composite up to the matrix limiting temperature of 600 C. Longitudinal and transverse unidirectional composite data are presented and discussed.

Condensed phase conversion and growth of nanorods and other materials instead of from vapor

DOEpatents

Geohegan, David B.; Seals, Roland D.; Puretzky, Alex A.; Fan, Xudong

2010-10-19

Compositions, systems and methods are described for condensed phase conversion and growth of nanorods and other materials. A method includes providing a condensed phase matrix material; and activating the condensed phase matrix material to produce a plurality of nanorods by condensed phase conversion and growth from the condensed phase matrix material instead of from vapor. The compositions are very strong. The compositions and methods provide advantages because they allow (1) formation rates of nanostructures necessary for reasonable production rates, and (2) the near net shaped production of component structures.

Condensed phase conversion and growth of nanorods instead of from vapor

DOEpatents

Geohegan, David B.; Seals, Roland D.; Puretzky, Alex A.; Fan, Xudong

2005-08-02

Compositions, systems and methods are described for condensed phase conversion and growth of nanorods and other materials. A method includes providing a condensed phase matrix material; and activating the condensed phase matrix material to produce a plurality of nanorods by condensed phase conversion and growth from the condensed chase matrix material instead of from vacor. The compositions are very strong. The compositions and methods provide advantages because they allow (1) formation rates of nanostructures necessary for reasonable production rates, and (2) the near net shaped production of component structures.

Resonance Phenomena in Goupillaud-type Media

DTIC Science & Technology

2010-10-01

time-harmonic forcing function at one end, with the other end fixed. Analytical stress solutions are derived from a global system of recursion...relationships using z-transform methods, where the determinant of the resulting global system matrix |Am| in the z-space is a palindromic polynomial with real...media (35). The present treatment uses a global matrix method that is attributed to Knopoff (36), rather than the Thomsen-Haskell transfer matrix

A matrix equation solution by an optimization technique

NASA Technical Reports Server (NTRS)

Johnson, M. J.; Mittra, R.

1972-01-01

The computer solution of matrix equations is often difficult to accomplish due to an ill-conditioned matrix or high noise levels. Two methods of solution are compared for matrices of various degrees of ill-conditioning and for various noise levels in the right hand side vector. One method employs the usual Gaussian elimination. The other solves the equation by an optimization technique and employs a function minimization subroutine.

A real-space stochastic density matrix approach for density functional electronic structure.

PubMed

Beck, Thomas L

2015-12-21

The recent development of real-space grid methods has led to more efficient, accurate, and adaptable approaches for large-scale electrostatics and density functional electronic structure modeling. With the incorporation of multiscale techniques, linear-scaling real-space solvers are possible for density functional problems if localized orbitals are used to represent the Kohn-Sham energy functional. These methods still suffer from high computational and storage overheads, however, due to extensive matrix operations related to the underlying wave function grid representation. In this paper, an alternative stochastic method is outlined that aims to solve directly for the one-electron density matrix in real space. In order to illustrate aspects of the method, model calculations are performed for simple one-dimensional problems that display some features of the more general problem, such as spatial nodes in the density matrix. This orbital-free approach may prove helpful considering a future involving increasingly parallel computing architectures. Its primary advantage is the near-locality of the random walks, allowing for simultaneous updates of the density matrix in different regions of space partitioned across the processors. In addition, it allows for testing and enforcement of the particle number and idempotency constraints through stabilization of a Feynman-Kac functional integral as opposed to the extensive matrix operations in traditional approaches.

EVALUATION OF SPIKING PROCEDURES FOR RECOVERY OF CRYPTOSPORIDIUM IN STREAM WATERS USING USEPA METHOD 1623

EPA Science Inventory

U.S. Environmental Protection Agency Method 1623 is widely used to monitor source waters and drinking water supplies for Cryptosporidium oocysts. Analyzing matrix spikes is an important component of Method 1623. Matrix spikes are used to determine the effect of the environmental...

Matrix Methods for Estimating the Coherence Functions from Estimates of the Cross-Spectral Density Matrix

DOE PAGES

Smallwood, D. O.

1996-01-01

It is shown that the usual method for estimating the coherence functions (ordinary, partial, and multiple) for a general multiple-input! multiple-output problem can be expressed as a modified form of Cholesky decomposition of the cross-spectral density matrix of the input and output records. The results can be equivalently obtained using singular value decomposition (SVD) of the cross-spectral density matrix. Using SVD suggests a new form of fractional coherence. The formulation as a SVD problem also suggests a way to order the inputs when a natural physical order of the inputs is absent.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Secchieri, M.; Benassi, C.A.; Pastore, S.

A method for the quail-quantitative evaluation of pentachlorophenol (PCP) in solid matrixes has been developed. The procedure is based on solid-liquid extraction of solid samples (leather or wood), followed by purification on a cyanopropyl column and determination of the preservative by second derivative UV spectroscopy considering the PCP A peak-through value (304-297 nm). The method allows rapid PCP determination in the concentration range 1-40 micrograms/mL; any matrix interference is avoided by the purification step and recoveries of the preservative were 99.12% (RSD% 0.13) for the leather matrix and 98.03 (RSD% 0.17) for the wood matrix.

The free and forced vibrations of structures using the finite dynamic element method. Ph.D. Thesis, Aug. 1991 Final Report

NASA Technical Reports Server (NTRS)

Fergusson, Neil J.

1992-01-01

In addition to an extensive review of the literature on exact and corrective displacement based methods of vibration analysis, a few theorems are proven concerning the various structural matrices involved in such analyses. In particular, the consistent mass matrix and the quasi-static mass matrix are shown to be equivalent, in the sense that the terms in their respective Taylor expansions are proportional to one another, and that they both lead to the same dynamic stiffness matrix when used with the appropriate stiffness matrix.

Teaching Improvement Model Designed with DEA Method and Management Matrix

ERIC Educational Resources Information Center

Montoneri, Bernard

2014-01-01

This study uses student evaluation of teachers to design a teaching improvement matrix based on teaching efficiency and performance by combining management matrix and data envelopment analysis. This matrix is designed to formulate suggestions to improve teaching. The research sample consists of 42 classes of freshmen following a course of English…

Tracking Time Evolution of Collective Attention Clusters in Twitter: Time Evolving Nonnegative Matrix Factorisation.

PubMed

Saito, Shota; Hirata, Yoshito; Sasahara, Kazutoshi; Suzuki, Hideyuki

2015-01-01

Micro-blogging services, such as Twitter, offer opportunities to analyse user behaviour. Discovering and distinguishing behavioural patterns in micro-blogging services is valuable. However, it is difficult and challenging to distinguish users, and to track the temporal development of collective attention within distinct user groups in Twitter. In this paper, we formulate this problem as tracking matrices decomposed by Nonnegative Matrix Factorisation for time-sequential matrix data, and propose a novel extension of Nonnegative Matrix Factorisation, which we refer to as Time Evolving Nonnegative Matrix Factorisation (TENMF). In our method, we describe users and words posted in some time interval by a matrix, and use several matrices as time-sequential data. Subsequently, we apply Time Evolving Nonnegative Matrix Factorisation to these time-sequential matrices. TENMF can decompose time-sequential matrices, and can track the connection among decomposed matrices, whereas previous NMF decomposes a matrix into two lower dimension matrices arbitrarily, which might lose the time-sequential connection. Our proposed method has an adequately good performance on artificial data. Moreover, we present several results and insights from experiments using real data from Twitter.

Hypothesis testing for band size detection of high-dimensional banded precision matrices.

PubMed

An, Baiguo; Guo, Jianhua; Liu, Yufeng

2014-06-01

Many statistical analysis procedures require a good estimator for a high-dimensional covariance matrix or its inverse, the precision matrix. When the precision matrix is banded, the Cholesky-based method often yields a good estimator of the precision matrix. One important aspect of this method is determination of the band size of the precision matrix. In practice, crossvalidation is commonly used; however, we show that crossvalidation not only is computationally intensive but can be very unstable. In this paper, we propose a new hypothesis testing procedure to determine the band size in high dimensions. Our proposed test statistic is shown to be asymptotically normal under the null hypothesis, and its theoretical power is studied. Numerical examples demonstrate the effectiveness of our testing procedure.

Micromechanical analysis on anisotropy of structured magneto-rheological elastomer

NASA Astrophysics Data System (ADS)

Li, R.; Zhang, Z.; Chen, S. W.; Wang, X. J.

2015-07-01

This paper investigates the equivalent elastic modulus of structured magneto-rheological elastomer (MRE) in the absence of magnetic field. We assume that both matrix and ferromagnetic particles are linear elastic materials, and ferromagnetic particles are embedded in matrix with layer-like structure. The structured composite could be divided into matrix layer and reinforced layer, in which the reinforced layer is composed of matrix and the homogenously distributed ferromagnetic particles in matrix. The equivalent elastic modulus of reinforced layer is analysed by the Mori-Tanaka method. Finite Element Method (FEM) is also carried out to illustrate the relationship between the elastic modulus and the volume fraction of ferromagnetic particles. The results show that the anisotropy of elastic modulus becomes noticeable, as the volume fraction of particles increases.

Parameter retrieval of chiral metamaterials based on the state-space approach.

PubMed

Zarifi, Davoud; Soleimani, Mohammad; Abdolali, Ali

2013-08-01

This paper deals with the introduction of an approach for the electromagnetic characterization of homogeneous chiral layers. The proposed method is based on the state-space approach and properties of a 4×4 state transition matrix. Based on this, first, the forward problem analysis through the state-space method is reviewed and properties of the state transition matrix of a chiral layer are presented and proved as two theorems. The formulation of a proposed electromagnetic characterization method is then presented. In this method, scattering data for a linearly polarized plane wave incident normally on a homogeneous chiral slab are combined with properties of a state transition matrix and provide a powerful characterization method. The main difference with respect to other well-established retrieval procedures based on the use of the scattering parameters relies on the direct computation of the transfer matrix of the slab as opposed to the conventional calculation of the propagation constant and impedance of the modes supported by the medium. The proposed approach allows avoiding nonlinearity of the problem but requires getting enough equations to fulfill the task which was provided by considering some properties of the state transition matrix. To demonstrate the applicability and validity of the method, the constitutive parameters of two well-known dispersive chiral metamaterial structures at microwave frequencies are retrieved. The results show that the proposed method is robust and reliable.

Flexible multiply towpreg

NASA Technical Reports Server (NTRS)

Muzzy, John D. (Inventor); Varughese, Babu (Inventor)

1992-01-01

This invention relates to an improved flexible towpreg and a method of production therefor. The improved flexible towpreg comprises a plurality of towpreg plies which comprise reinforcing filaments and matrix forming material; the reinforcing filaments being substantially wetout by the matrix forming material such that the towpreg plies are substantially void-free composite articles, and the towpreg plies having an average thickness less than about 100 microns. The method of production for the improved flexible towpreg comprises the steps of spreading the reinforcing filaments to expose individually substantially all of the reinforcing filaments; coating the reinforcing filaments with the matrix forming material in a manner causing interfacial adhesion of the matrix forming material to the reinforcing filaments; forming the towpreg plies by heating the matrix forming material contacting the reinforcing filaments until the matrix forming material liquifies and coats the reinforcing filaments; and cooling the towpreg plies in a manner such that substantial cohesion between neighboring towpreg plies is prevented until the matrix forming material solidifies.

On-Line Identification of Simulation Examples for Forgetting Methods to Track Time Varying Parameters Using the Alternative Covariance Matrix in Matlab

NASA Astrophysics Data System (ADS)

Vachálek, Ján

2011-12-01

The paper compares the abilities of forgetting methods to track time varying parameters of two different simulated models with different types of excitation. The observed parameters in the simulations are the integral sum of the Euclidean norm, deviation of the parameter estimates from their true values and a selected band prediction error count. As supplementary information, we observe the eigenvalues of the covariance matrix. In the paper we used a modified method of Regularized Exponential Forgetting with Alternative Covariance Matrix (REFACM) along with Directional Forgetting (DF) and three standard regularized methods.

Rank-Optimized Logistic Matrix Regression toward Improved Matrix Data Classification.

PubMed

Zhang, Jianguang; Jiang, Jianmin

2018-02-01

While existing logistic regression suffers from overfitting and often fails in considering structural information, we propose a novel matrix-based logistic regression to overcome the weakness. In the proposed method, 2D matrices are directly used to learn two groups of parameter vectors along each dimension without vectorization, which allows the proposed method to fully exploit the underlying structural information embedded inside the 2D matrices. Further, we add a joint [Formula: see text]-norm on two parameter matrices, which are organized by aligning each group of parameter vectors in columns. This added co-regularization term has two roles-enhancing the effect of regularization and optimizing the rank during the learning process. With our proposed fast iterative solution, we carried out extensive experiments. The results show that in comparison to both the traditional tensor-based methods and the vector-based regression methods, our proposed solution achieves better performance for matrix data classifications.

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

NASA Astrophysics Data System (ADS)

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.

Evaluation of matrix effect on the determination of rare earth elements and As, Bi, Cd, Pb, Se and In in honey and pollen of native Brazilian bees (Tetragonisca angustula - Jataí) by Q-ICP-MS.

PubMed

de Oliveira, Fernanda Ataide; de Abreu, Adriana Trópia; de Oliveira Nascimento, Nathália; Froes-Silva, Roberta Eliane Santos; Antonini, Yasmine; Nalini, Hermínio Arias; de Lena, Jorge Carvalho

2017-01-01

Bees are considered the main pollinators in natural and agricultural environments. Chemical elements from honey and pollen have been used for monitoring the environment, the health of bees and the quality of their products. Nevertheless, there are not many studies on honey and pollen of native Brazilian bees. The goal of this work was to determine important chemical elements (Sc, Y, La, Ce, Pr, Nd, Sm, Eu, Gd, Dy, Ho, Er, Tm, Lu and Yb) along with As, Bi, Cd, Pb, Se and In, in honey and pollen of native Brazilian bees, assessing analytical interferences from the matrix. A proposed analytical method was developed for these elements by quadrupole ICP-MS. Matrix effect was verified in honey matrix in the quantification of As, Bi and Dy; and in pollen matrix for Bi, Cd, Ce, Gd, La, Pb and Sc. The quality of the method was considered satisfactory taking into consideration the recovery rate of each element in the spiked solutions: honey matrix (91.6-103.9%) and pollen matrix (94.1-115.6%). The quantification limits of the method ranged between 0.00041 and 10.3μgL -1 for honey and 0.00041-0.095μgL -1 for pollen. The results demonstrate that the method is accurate, precise and suitable. Copyright © 2016 Elsevier B.V. All rights reserved.

Automatic face naming by learning discriminative affinity matrices from weakly labeled images.

PubMed

Xiao, Shijie; Xu, Dong; Wu, Jianxin

2015-10-01

Given a collection of images, where each image contains several faces and is associated with a few names in the corresponding caption, the goal of face naming is to infer the correct name for each face. In this paper, we propose two new methods to effectively solve this problem by learning two discriminative affinity matrices from these weakly labeled images. We first propose a new method called regularized low-rank representation by effectively utilizing weakly supervised information to learn a low-rank reconstruction coefficient matrix while exploring multiple subspace structures of the data. Specifically, by introducing a specially designed regularizer to the low-rank representation method, we penalize the corresponding reconstruction coefficients related to the situations where a face is reconstructed by using face images from other subjects or by using itself. With the inferred reconstruction coefficient matrix, a discriminative affinity matrix can be obtained. Moreover, we also develop a new distance metric learning method called ambiguously supervised structural metric learning by using weakly supervised information to seek a discriminative distance metric. Hence, another discriminative affinity matrix can be obtained using the similarity matrix (i.e., the kernel matrix) based on the Mahalanobis distances of the data. Observing that these two affinity matrices contain complementary information, we further combine them to obtain a fused affinity matrix, based on which we develop a new iterative scheme to infer the name of each face. Comprehensive experiments demonstrate the effectiveness of our approach.

Carbonate fuel cell matrix

DOEpatents

Farooque, M.; Yuh, C.Y.

1996-12-03

A carbonate fuel cell matrix is described comprising support particles and crack attenuator particles which are made platelet in shape to increase the resistance of the matrix to through cracking. Also disclosed is a matrix having porous crack attenuator particles and a matrix whose crack attenuator particles have a thermal coefficient of expansion which is significantly different from that of the support particles, and a method of making platelet-shaped crack attenuator particles. 8 figs.

Designing Hyperchaotic Cat Maps With Any Desired Number of Positive Lyapunov Exponents.

PubMed

Hua, Zhongyun; Yi, Shuang; Zhou, Yicong; Li, Chengqing; Wu, Yue

2018-02-01

Generating chaotic maps with expected dynamics of users is a challenging topic. Utilizing the inherent relation between the Lyapunov exponents (LEs) of the Cat map and its associated Cat matrix, this paper proposes a simple but efficient method to construct an -dimensional ( -D) hyperchaotic Cat map (HCM) with any desired number of positive LEs. The method first generates two basic -D Cat matrices iteratively and then constructs the final -D Cat matrix by performing similarity transformation on one basic -D Cat matrix by the other. Given any number of positive LEs, it can generate an -D HCM with desired hyperchaotic complexity. Two illustrative examples of -D HCMs were constructed to show the effectiveness of the proposed method, and to verify the inherent relation between the LEs and Cat matrix. Theoretical analysis proves that the parameter space of the generated HCM is very large. Performance evaluations show that, compared with existing methods, the proposed method can construct -D HCMs with lower computation complexity and their outputs demonstrate strong randomness and complex ergodicity.

Coupled-cluster based R-matrix codes (CCRM): Recent developments

NASA Astrophysics Data System (ADS)

Sur, Chiranjib; Pradhan, Anil K.

2008-05-01

We report the ongoing development of the new coupled-cluster R-matrix codes (CCRM) for treating electron-ion scattering and radiative processes within the framework of the relativistic coupled-cluster method (RCC), interfaced with the standard R-matrix methodology. The RCC method is size consistent and in principle equivalent to an all-order many-body perturbation theory. The RCC method is one of the most accurate many-body theories, and has been applied for several systems. This project should enable the study of electron-interactions with heavy atoms/ions, utilizing not only high speed computing platforms but also improved theoretical description of the relativistic and correlation effects for the target atoms/ions as treated extensively within the RCC method. Here we present a comprehensive outline of the newly developed theoretical method and a schematic representation of the new suite of CCRM codes. We begin with the flowchart and description of various stages involved in this development. We retain the notations and nomenclature of different stages as analogous to the standard R-matrix codes.

Semiblind channel estimation for MIMO-OFDM systems

NASA Astrophysics Data System (ADS)

Chen, Yi-Sheng; Song, Jyu-Han

2012-12-01

This article proposes a semiblind channel estimation method for multiple-input multiple-output orthogonal frequency-division multiplexing systems based on circular precoding. Relying on the precoding scheme at the transmitters, the autocorrelation matrix of the received data induces a structure relating the outer product of the channel frequency response matrix and precoding coefficients. This structure makes it possible to extract information about channel product matrices, which can be used to form a Hermitian matrix whose positive eigenvalues and corresponding eigenvectors yield the channel impulse response matrix. This article also tests the resistance of the precoding design to finite-sample estimation errors, and explores the effects of the precoding scheme on channel equalization by performing pairwise error probability analysis. The proposed method is immune to channel zero locations, and is reasonably robust to channel order overestimation. The proposed method is applicable to the scenarios in which the number of transmitters exceeds that of the receivers. Simulation results demonstrate the performance of the proposed method and compare it with some existing methods.

Matrix completion-based reconstruction for undersampled magnetic resonance fingerprinting data.

PubMed

Doneva, Mariya; Amthor, Thomas; Koken, Peter; Sommer, Karsten; Börnert, Peter

2017-09-01

An iterative reconstruction method for undersampled magnetic resonance fingerprinting data is presented. The method performs the reconstruction entirely in k-space and is related to low rank matrix completion methods. A low dimensional data subspace is estimated from a small number of k-space locations fully sampled in the temporal direction and used to reconstruct the missing k-space samples before MRF dictionary matching. Performing the iterations in k-space eliminates the need for applying a forward and an inverse Fourier transform in each iteration required in previously proposed iterative reconstruction methods for undersampled MRF data. A projection onto the low dimensional data subspace is performed as a matrix multiplication instead of a singular value thresholding typically used in low rank matrix completion, further reducing the computational complexity of the reconstruction. The method is theoretically described and validated in phantom and in-vivo experiments. The quality of the parameter maps can be significantly improved compared to direct matching on undersampled data. Copyright © 2017 Elsevier Inc. All rights reserved.

A novel edge-preserving nonnegative matrix factorization method for spectral unmixing

NASA Astrophysics Data System (ADS)

Bao, Wenxing; Ma, Ruishi

2015-12-01

Spectral unmixing technique is one of the key techniques to identify and classify the material in the hyperspectral image processing. A novel robust spectral unmixing method based on nonnegative matrix factorization(NMF) is presented in this paper. This paper used an edge-preserving function as hypersurface cost function to minimize the nonnegative matrix factorization. To minimize the hypersurface cost function, we constructed the updating functions for signature matrix of end-members and abundance fraction respectively. The two functions are updated alternatively. For evaluation purpose, synthetic data and real data have been used in this paper. Synthetic data is used based on end-members from USGS digital spectral library. AVIRIS Cuprite dataset have been used as real data. The spectral angle distance (SAD) and abundance angle distance(AAD) have been used in this research for assessment the performance of proposed method. The experimental results show that this method can obtain more ideal results and good accuracy for spectral unmixing than present methods.

Parallel Preconditioning for CFD Problems on the CM-5

NASA Technical Reports Server (NTRS)

Simon, Horst D.; Kremenetsky, Mark D.; Richardson, John; Lasinski, T. A. (Technical Monitor)

1994-01-01

Up to today, preconditioning methods on massively parallel systems have faced a major difficulty. The most successful preconditioning methods in terms of accelerating the convergence of the iterative solver such as incomplete LU factorizations are notoriously difficult to implement on parallel machines for two reasons: (1) the actual computation of the preconditioner is not very floating-point intensive, but requires a large amount of unstructured communication, and (2) the application of the preconditioning matrix in the iteration phase (i.e. triangular solves) are difficult to parallelize because of the recursive nature of the computation. Here we present a new approach to preconditioning for very large, sparse, unsymmetric, linear systems, which avoids both difficulties. We explicitly compute an approximate inverse to our original matrix. This new preconditioning matrix can be applied most efficiently for iterative methods on massively parallel machines, since the preconditioning phase involves only a matrix-vector multiplication, with possibly a dense matrix. Furthermore the actual computation of the preconditioning matrix has natural parallelism. For a problem of size n, the preconditioning matrix can be computed by solving n independent small least squares problems. The algorithm and its implementation on the Connection Machine CM-5 are discussed in detail and supported by extensive timings obtained from real problem data.

Data-Driven Sampling Matrix Boolean Optimization for Energy-Efficient Biomedical Signal Acquisition by Compressive Sensing.

PubMed

Wang, Yuhao; Li, Xin; Xu, Kai; Ren, Fengbo; Yu, Hao

2017-04-01

Compressive sensing is widely used in biomedical applications, and the sampling matrix plays a critical role on both quality and power consumption of signal acquisition. It projects a high-dimensional vector of data into a low-dimensional subspace by matrix-vector multiplication. An optimal sampling matrix can ensure accurate data reconstruction and/or high compression ratio. Most existing optimization methods can only produce real-valued embedding matrices that result in large energy consumption during data acquisition. In this paper, we propose an efficient method that finds an optimal Boolean sampling matrix in order to reduce the energy consumption. Compared to random Boolean embedding, our data-driven Boolean sampling matrix can improve the image recovery quality by 9 dB. Moreover, in terms of sampling hardware complexity, it reduces the energy consumption by 4.6× and the silicon area by 1.9× over the data-driven real-valued embedding.

Stress and Damage in Polymer Matrix Composite Materials Due to Material Degradation at High Temperatures

NASA Technical Reports Server (NTRS)

McManus, Hugh L.; Chamis, Christos C.

1996-01-01

This report describes analytical methods for calculating stresses and damage caused by degradation of the matrix constituent in polymer matrix composite materials. Laminate geometry, material properties, and matrix degradation states are specified as functions of position and time. Matrix shrinkage and property changes are modeled as functions of the degradation states. The model is incorporated into an existing composite mechanics computer code. Stresses, strains, and deformations at the laminate, ply, and micro levels are calculated, and from these calculations it is determined if there is failure of any kind. The rationale for the model (based on published experimental work) is presented, its integration into the laminate analysis code is outlined, and example results are given, with comparisons to existing material and structural data. The mechanisms behind the changes in properties and in surface cracking during long-term aging of polyimide matrix composites are clarified. High-temperature-material test methods are also evaluated.

Biological Matrix Effects in Quantitative Tandem Mass Spectrometry-Based Analytical Methods: Advancing Biomonitoring

PubMed Central

Panuwet, Parinya; Hunter, Ronald E.; D’Souza, Priya E.; Chen, Xianyu; Radford, Samantha A.; Cohen, Jordan R.; Marder, M. Elizabeth; Kartavenka, Kostya; Ryan, P. Barry; Barr, Dana Boyd

2015-01-01

The ability to quantify levels of target analytes in biological samples accurately and precisely, in biomonitoring, involves the use of highly sensitive and selective instrumentation such as tandem mass spectrometers and a thorough understanding of highly variable matrix effects. Typically, matrix effects are caused by co-eluting matrix components that alter the ionization of target analytes as well as the chromatographic response of target analytes, leading to reduced or increased sensitivity of the analysis. Thus, before the desired accuracy and precision standards of laboratory data are achieved, these effects must be characterized and controlled. Here we present our review and observations of matrix effects encountered during the validation and implementation of tandem mass spectrometry-based analytical methods. We also provide systematic, comprehensive laboratory strategies needed to control challenges posed by matrix effects in order to ensure delivery of the most accurate data for biomonitoring studies assessing exposure to environmental toxicants. PMID:25562585

General Matrix Inversion Technique for the Calibration of Electric Field Sensor Arrays on Aircraft Platforms

NASA Technical Reports Server (NTRS)

Mach, D. M.; Koshak, W. J.

2007-01-01

A matrix calibration procedure has been developed that uniquely relates the electric fields measured at the aircraft with the external vector electric field and net aircraft charge. The calibration method can be generalized to any reasonable combination of electric field measurements and aircraft. A calibration matrix is determined for each aircraft that represents the individual instrument responses to the external electric field. The aircraft geometry and configuration of field mills (FMs) uniquely define the matrix. The matrix can then be inverted to determine the external electric field and net aircraft charge from the FM outputs. A distinct advantage of the method is that if one or more FMs need to be eliminated or deemphasized [e.g., due to a malfunction), it is a simple matter to reinvert the matrix without the malfunctioning FMs. To demonstrate the calibration technique, data are presented from several aircraft programs (ER-2, DC-8, Altus, and Citation).

Validation of the Applied Biosystems 7500 Fast Instrument for Detection of Listeria Species with the SureTect Listeria Species PCR Assay.

PubMed

Cloke, Jonathan; Arizanova, Julia; Crabtree, David; Simpson, Helen; Evans, Katharine; Vaahtoranta, Laura; Palomäki, Jukka-Pekka; Artimo, Paulus; Huang, Feng; Liikanen, Maria; Koskela, Suvi; Chen, Yi

2016-01-01

The Thermo Scientific™ SureTect™ Listeria species Real-Time PCR Assay was certified during 2013 by the AOAC Research Institute (RI) Performance Tested Methods(SM) program as a rapid method for the detection of Listeria species from a wide range of food matrixes and surface samples. A method modification study was conducted in 2015 to extend the matrix claims of the product to a wider range of food matrixes. This report details the method modification study undertaken to extend the use of this PCR kit to the Applied Biosystems™ 7500 Fast PCR Instrument and Applied Biosystems RapidFinder™ Express 2.0 software allowing use of the assay on a 96-well format PCR cycler in addition to the current workflow, using the 24-well Thermo Scientific PikoReal™ PCR Instrument and Thermo Scientific SureTect software. The method modification study presented in this report was assessed by the AOAC-RI as being a level 2 method modification study, necessitating a method developer study on a representative range of food matrixes covering raw ground turkey, 2% fat pasteurized milk, and bagged lettuce as well as stainless steel surface samples. All testing was conducted in comparison to the reference method detailed in International Organization for Standardization (ISO) 6579:2002. No significant difference by probability of detection statistical analysis was found between the SureTect Listeria species PCR Assay or the ISO reference method methods for any of the three food matrixes and the surface samples analyzed during the study.

Quantification of strontium in human serum by ICP-MS using alternate analyte-free matrix and its application to a pilot bioequivalence study of two strontium ranelate oral formulations in healthy Chinese subjects.

PubMed

Zhang, Dan; Wang, Xiaolin; Liu, Man; Zhang, Lina; Deng, Ming; Liu, Huichen

2015-01-01

A rapid, sensitive and accurate ICP-MS method using alternate analyte-free matrix for calibration standards preparation and a rapid direct dilution procedure for sample preparation was developed and validated for the quantification of exogenous strontium (Sr) from the drug in human serum. Serum was prepared by direct dilution (1:29, v/v) in an acidic solution consisting of nitric acid (0.1%) and germanium (Ge) added as internal standard (IS), to obtain simple and high-throughput preparation procedure with minimized matrix effect, and good repeatability. ICP-MS analysis was performed using collision cell technology (CCT) mode. Alternate matrix method by using distilled water as an alternate analyte-free matrix for the preparation of calibration standards (CS) was used to avoid the influence of endogenous Sr in serum on the quantification. The method was validated in terms of selectivity, carry-over, matrix effects, lower limit of quantification (LLOQ), linearity, precision and accuracy, and stability. Instrumental linearity was verified in the range of 1.00-500ng/mL, corresponding to a concentration range of 0.0300-15.0μg/mL in 50μL sample of serum matrix and alternate matrix. Intra- and inter-day precision as relative standard deviation (RSD) were less than 8.0% and accuracy as relative error (RE) was within ±3.0%. The method allowed a high sample throughput, and was sensitive and accurate enough for a pilot bioequivalence study in healthy male Chinese subjects following single oral administration of two strontium ranelate formulations containing 2g strontium ranelate. Copyright © 2014 Elsevier GmbH. All rights reserved.

A component prediction method for flue gas of natural gas combustion based on nonlinear partial least squares method.

PubMed

Cao, Hui; Yan, Xingyu; Li, Yaojiang; Wang, Yanxia; Zhou, Yan; Yang, Sanchun

2014-01-01

Quantitative analysis for the flue gas of natural gas-fired generator is significant for energy conservation and emission reduction. The traditional partial least squares method may not deal with the nonlinear problems effectively. In the paper, a nonlinear partial least squares method with extended input based on radial basis function neural network (RBFNN) is used for components prediction of flue gas. For the proposed method, the original independent input matrix is the input of RBFNN and the outputs of hidden layer nodes of RBFNN are the extension term of the original independent input matrix. Then, the partial least squares regression is performed on the extended input matrix and the output matrix to establish the components prediction model of flue gas. A near-infrared spectral dataset of flue gas of natural gas combustion is used for estimating the effectiveness of the proposed method compared with PLS. The experiments results show that the root-mean-square errors of prediction values of the proposed method for methane, carbon monoxide, and carbon dioxide are, respectively, reduced by 4.74%, 21.76%, and 5.32% compared to those of PLS. Hence, the proposed method has higher predictive capabilities and better robustness.

Fast mean and variance computation of the diffuse sound transmission through finite-sized thick and layered wall and floor systems

NASA Astrophysics Data System (ADS)

Decraene, Carolina; Dijckmans, Arne; Reynders, Edwin P. B.

2018-05-01

A method is developed for computing the mean and variance of the diffuse field sound transmission loss of finite-sized layered wall and floor systems that consist of solid, fluid and/or poroelastic layers. This is achieved by coupling a transfer matrix model of the wall or floor to statistical energy analysis subsystem models of the adjacent room volumes. The modal behavior of the wall is approximately accounted for by projecting the wall displacement onto a set of sinusoidal lateral basis functions. This hybrid modal transfer matrix-statistical energy analysis method is validated on multiple wall systems: a thin steel plate, a polymethyl methacrylate panel, a thick brick wall, a sandwich panel, a double-leaf wall with poro-elastic material in the cavity, and a double glazing. The predictions are compared with experimental data and with results obtained using alternative prediction methods such as the transfer matrix method with spatial windowing, the hybrid wave based-transfer matrix method, and the hybrid finite element-statistical energy analysis method. These comparisons confirm the prediction accuracy of the proposed method and the computational efficiency against the conventional hybrid finite element-statistical energy analysis method.

An efficient implementation of a high-order filter for a cubed-sphere spectral element model

NASA Astrophysics Data System (ADS)

Kang, Hyun-Gyu; Cheong, Hyeong-Bin

2017-03-01

A parallel-scalable, isotropic, scale-selective spatial filter was developed for the cubed-sphere spectral element model on the sphere. The filter equation is a high-order elliptic (Helmholtz) equation based on the spherical Laplacian operator, which is transformed into cubed-sphere local coordinates. The Laplacian operator is discretized on the computational domain, i.e., on each cell, by the spectral element method with Gauss-Lobatto Lagrange interpolating polynomials (GLLIPs) as the orthogonal basis functions. On the global domain, the discrete filter equation yielded a linear system represented by a highly sparse matrix. The density of this matrix increases quadratically (linearly) with the order of GLLIP (order of the filter), and the linear system is solved in only O (Ng) operations, where Ng is the total number of grid points. The solution, obtained by a row reduction method, demonstrated the typical accuracy and convergence rate of the cubed-sphere spectral element method. To achieve computational efficiency on parallel computers, the linear system was treated by an inverse matrix method (a sparse matrix-vector multiplication). The density of the inverse matrix was lowered to only a few times of the original sparse matrix without degrading the accuracy of the solution. For better computational efficiency, a local-domain high-order filter was introduced: The filter equation is applied to multiple cells, and then the central cell was only used to reconstruct the filtered field. The parallel efficiency of applying the inverse matrix method to the global- and local-domain filter was evaluated by the scalability on a distributed-memory parallel computer. The scale-selective performance of the filter was demonstrated on Earth topography. The usefulness of the filter as a hyper-viscosity for the vorticity equation was also demonstrated.

Graphene-Reinforced Aluminum Matrix Composites: A Review of Synthesis Methods and Properties

NASA Astrophysics Data System (ADS)

Chen, Fei; Gupta, Nikhil; Behera, Rakesh K.; Rohatgi, Pradeep K.

2018-06-01

Graphene-reinforced aluminum (Gr-Al) matrix nanocomposites (NCs) have attracted strong interest from both research and industry in high-performance weight-sensitive applications. Due to the vastly different bonding characteristics of the Al matrix (metallic) and graphene (in-plane covalent + inter-plane van der Waals), the graphene phase has a general tendency to agglomerate and phase separate in the metal matrix, which is detrimental for the mechanical and chemical properties of the composite. Thus, synthesis of Gr-Al NCs is extremely challenging. This review summarizes the different methods available to synthesize Gr-Al NCs and the resulting properties achieved in these NCs. Understanding the effect of processing parameters on the realized properties opens up the possibility of tailoring the synthesis methods to achieve the desired properties for a given application.

Target detection in GPR data using joint low-rank and sparsity constraints

NASA Astrophysics Data System (ADS)

Bouzerdoum, Abdesselam; Tivive, Fok Hing Chi; Abeynayake, Canicious

2016-05-01

In ground penetrating radars, background clutter, which comprises the signals backscattered from the rough, uneven ground surface and the background noise, impairs the visualization of buried objects and subsurface inspections. In this paper, a clutter mitigation method is proposed for target detection. The removal of background clutter is formulated as a constrained optimization problem to obtain a low-rank matrix and a sparse matrix. The low-rank matrix captures the ground surface reflections and the background noise, whereas the sparse matrix contains the target reflections. An optimization method based on split-Bregman algorithm is developed to estimate these two matrices from the input GPR data. Evaluated on real radar data, the proposed method achieves promising results in removing the background clutter and enhancing the target signature.

Identification of Successive ``Unobservable'' Cyber Data Attacks in Power Systems Through Matrix Decomposition

NASA Astrophysics Data System (ADS)

Gao, Pengzhi; Wang, Meng; Chow, Joe H.; Ghiocel, Scott G.; Fardanesh, Bruce; Stefopoulos, George; Razanousky, Michael P.

2016-11-01

This paper presents a new framework of identifying a series of cyber data attacks on power system synchrophasor measurements. We focus on detecting "unobservable" cyber data attacks that cannot be detected by any existing method that purely relies on measurements received at one time instant. Leveraging the approximate low-rank property of phasor measurement unit (PMU) data, we formulate the identification problem of successive unobservable cyber attacks as a matrix decomposition problem of a low-rank matrix plus a transformed column-sparse matrix. We propose a convex-optimization-based method and provide its theoretical guarantee in the data identification. Numerical experiments on actual PMU data from the Central New York power system and synthetic data are conducted to verify the effectiveness of the proposed method.

Analysis of nonderivatized steroids by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry using C70 fullerene as matrix.

PubMed

Montsko, Gergely; Vaczy, Alexandra; Maasz, Gabor; Mernyak, Erzsebet; Frank, Eva; Bay, Csaba; Kadar, Zalan; Ohmacht, Robert; Wolfling, Janos; Mark, Laszlo

2009-10-01

Neutral steroid hormones are currently analyzed by gas or liquid chromatography/mass spectrometry based methods. Most of the steroid compounds, however, lack volatility and do not contain polar groups, which results in inadequate chromatographic behavior and low ionization efficiency. Derivatization of the steroids to form more volatile, thermostable, and charged products solves this difficulty, but the derivatization of compounds with unknown chemical moieties is not an easy task. In this study, a rapid, high-throughput, sensitive matrix-assisted laser desorption/ionization time-of-flight mass spectrometry method is described using C(70) fullerene as a matrix compound. The application of the method is demonstrated for five general sex steroids and for synthetic steroid compounds in both negative and positive ionization modes.

Graphene-Reinforced Aluminum Matrix Composites: A Review of Synthesis Methods and Properties

NASA Astrophysics Data System (ADS)

Chen, Fei; Gupta, Nikhil; Behera, Rakesh K.; Rohatgi, Pradeep K.

2018-03-01

Graphene-reinforced aluminum (Gr-Al) matrix nanocomposites (NCs) have attracted strong interest from both research and industry in high-performance weight-sensitive applications. Due to the vastly different bonding characteristics of the Al matrix (metallic) and graphene (in-plane covalent + inter-plane van der Waals), the graphene phase has a general tendency to agglomerate and phase separate in the metal matrix, which is detrimental for the mechanical and chemical properties of the composite. Thus, synthesis of Gr-Al NCs is extremely challenging. This review summarizes the different methods available to synthesize Gr-Al NCs and the resulting properties achieved in these NCs. Understanding the effect of processing parameters on the realized properties opens up the possibility of tailoring the synthesis methods to achieve the desired properties for a given application.

Atmospheric pressure matrix-assisted laser desorption ionization as a plume diagnostic tool in laser evaporation methods

NASA Astrophysics Data System (ADS)

Callahan, John H.; Galicia, Marsha C.; Vertes, Akos

2002-09-01

Laser evaporation techniques, including matrix-assisted pulsed laser evaporation (MAPLE), are attracting increasing attention due to their ability to deposit thin layers of undegraded synthetic and biopolymers. Laser evaporation methods can be implemented in reflection geometry with the laser and the substrate positioned on the same side of the target. In some applications (e.g. direct write, DW), however, transmission geometry is used, i.e. the thin target is placed between the laser and the substrate. In this case, the laser pulse perforates the target and transfers some target material to the substrate. In order to optimize evaporation processes it is important to know the composition of the target plume and the material deposited from the plume. We used a recently introduced analytical method, atmospheric pressure matrix-assisted laser desorption ionization (AP-MALDI) to characterize the ionic components of the plume both in reflection and in transmission geometry. This technique can also be used to directly probe materials deposited on surfaces (such as glass slides) by laser evaporation methods. The test compound (small peptides, e.g. Angiotensin I, ATI or Substance P) was mixed with a MALDI matrix (α-cyano-4-hydroxycinnamic acid (CHCA), sinapinic acid (SA) or 2,5-dihydroxybenzoic acid (DHB)) and applied to the stainless steel (reflection geometry) or transparent conducting (transmission geometry) target holder. In addition to the classical dried droplet method, we also used electrospray target deposition to gain better control of crystallite size, thickness and homogeneity. The target was mounted in front of the inlet orifice of an ion trap mass spectrometer (IT-MS) that sampled the ionic components of the plume generated by a nitrogen laser. We studied the effect of several parameters, such as, the orifice to target distance, illumination geometry, extracting voltage distribution and sample preparation on the generated ions. Various analyte-matrix and matrix-matrix cluster ions were observed with relatively low abundance of the matrix ions.

A hybrid method for transient wave propagation in a multilayered solid

NASA Astrophysics Data System (ADS)

Tian, Jiayong; Xie, Zhoumin

2009-08-01

We present a hybrid method for the evaluation of transient elastic-wave propagation in a multilayered solid, integrating reverberation matrix method with the theory of generalized rays. Adopting reverberation matrix formulation, Laplace-Fourier domain solutions of elastic waves in the multilayered solid are expanded into the sum of a series of generalized-ray group integrals. Each generalized-ray group integral containing Kth power of reverberation matrix R represents the set of K-times reflections and refractions of source waves arriving at receivers in the multilayered solid, which was computed by fast inverse Laplace transform (FILT) and fast Fourier transform (FFT) algorithms. However, the calculation burden and low precision of FILT-FFT algorithm limit the application of reverberation matrix method. In this paper, we expand each of generalized-ray group integrals into the sum of a series of generalized-ray integrals, each of which is accurately evaluated by Cagniard-De Hoop method in the theory of generalized ray. The numerical examples demonstrate that the proposed method makes it possible to calculate the early-time transient response in the complex multilayered-solid configuration efficiently.

System matrix computation vs storage on GPU: A comparative study in cone beam CT.

PubMed

Matenine, Dmitri; Côté, Geoffroi; Mascolo-Fortin, Julia; Goussard, Yves; Després, Philippe

2018-02-01

Iterative reconstruction algorithms in computed tomography (CT) require a fast method for computing the intersection distances between the trajectories of photons and the object, also called ray tracing or system matrix computation. This work focused on the thin-ray model is aimed at comparing different system matrix handling strategies using graphical processing units (GPUs). In this work, the system matrix is modeled by thin rays intersecting a regular grid of box-shaped voxels, known to be an accurate representation of the forward projection operator in CT. However, an uncompressed system matrix exceeds the random access memory (RAM) capacities of typical computers by one order of magnitude or more. Considering the RAM limitations of GPU hardware, several system matrix handling methods were compared: full storage of a compressed system matrix, on-the-fly computation of its coefficients, and partial storage of the system matrix with partial on-the-fly computation. These methods were tested on geometries mimicking a cone beam CT (CBCT) acquisition of a human head. Execution times of three routines of interest were compared: forward projection, backprojection, and ordered-subsets convex (OSC) iteration. A fully stored system matrix yielded the shortest backprojection and OSC iteration times, with a 1.52× acceleration for OSC when compared to the on-the-fly approach. Nevertheless, the maximum problem size was bound by the available GPU RAM and geometrical symmetries. On-the-fly coefficient computation did not require symmetries and was shown to be the fastest for forward projection. It also offered reasonable execution times of about 176.4 ms per view per OSC iteration for a detector of 512 × 448 pixels and a volume of 384 3 voxels, using commodity GPU hardware. Partial system matrix storage has shown a performance similar to the on-the-fly approach, while still relying on symmetries. Partial system matrix storage was shown to yield the lowest relative performance. On-the-fly ray tracing was shown to be the most flexible method, yielding reasonable execution times. A fully stored system matrix allowed for the lowest backprojection and OSC iteration times and may be of interest for certain performance-oriented applications. © 2017 American Association of Physicists in Medicine.

Improved Dot Diffusion For Image Halftoning

DTIC Science & Technology

1999-01-01

The dot diffusion method for digital halftoning has the advantage of parallelism unlike the error diffusion method. The method was recently improved...by optimization of the so-called class matrix so that the resulting halftones are comparable to the error diffused halftones . In this paper we will...first review the dot diffusion method. Previously, 82 class matrices were used for dot diffusion method. A problem with this size of class matrix is

Matrix interference evaluation employing GC and LC coupled to triple quadrupole tandem mass spectrometry.

PubMed

Uclés, S; Lozano, A; Sosa, A; Parrilla Vázquez, P; Valverde, A; Fernández-Alba, A R

2017-11-01

Gas and liquid chromatography coupled to triple quadrupole tandem mass spectrometry are currently the most powerful tools employed for the routine analysis of pesticide residues in food control laboratories. However, whatever the multiresidue extraction method, there will be a residual matrix effect making it difficult to identify/quantify some specific compounds in certain cases. Two main effects stand out: (i) co-elution with isobaric matrix interferents, which can be a major drawback for unequivocal identification, and therefore false negative detections, and (ii) signal suppression/enhancement, commonly called the "matrix effect", which may cause serious problems including inaccurate quantitation, low analyte detectability and increased method uncertainty. The aim of this analytical study is to provide a framework for evaluating the maximum expected errors associated with the matrix effects. The worst-case study contrived to give an estimation of the extreme errors caused by matrix effects when extraction/determination protocols are applied in routine multiresidue analysis. Twenty-five different blank matrices extracted with the four most common extraction methods used in routine analysis (citrate QuEChERS with/without PSA clean-up, ethyl acetate and the Dutch mini-Luke "NL" methods) were evaluated by both GC-QqQ-MS/MS and LC-QqQ-MS/MS. The results showed that the presence of matrix compounds with isobaric transitions to target pesticides was higher in GC than under LC in the experimental conditions tested. In a second study, the number of "potential" false negatives was evaluated. For that, ten matrices with higher percentages of natural interfering components were checked. Additionally, the results showed that for more than 90% of the cases, pesticide quantification was not affected by matrix-matched standard calibration when an interferent was kept constant along the calibration curve. The error in quantification depended on the concentration level. In a third study, the "matrix effect" was evaluated for each commodity/extraction method. Results showed 44% of cases with suppression/enhancement for LC and 93% of cases with enhancement for GC. Copyright © 2017 Elsevier B.V. All rights reserved.

A fast collocation method for a variable-coefficient nonlocal diffusion model

NASA Astrophysics Data System (ADS)

Wang, Che; Wang, Hong

2017-02-01

We develop a fast collocation scheme for a variable-coefficient nonlocal diffusion model, for which a numerical discretization would yield a dense stiffness matrix. The development of the fast method is achieved by carefully handling the variable coefficients appearing inside the singular integral operator and exploiting the structure of the dense stiffness matrix. The resulting fast method reduces the computational work from O (N3) required by a commonly used direct solver to O (Nlog ⁡ N) per iteration and the memory requirement from O (N2) to O (N). Furthermore, the fast method reduces the computational work of assembling the stiffness matrix from O (N2) to O (N). Numerical results are presented to show the utility of the fast method.

Method of tissue repair using a composite material

DOEpatents

Hutchens, Stacy A.; Woodward, Jonathan; Evans, Barbara R.; O'Neill, Hugh M.

2016-03-01

A composite biocompatible hydrogel material includes a porous polymer matrix, the polymer matrix including a plurality of pores and providing a Young's modulus of at least 10 GPa. A calcium comprising salt is disposed in at least some of the pores. The porous polymer matrix can comprise cellulose, including bacterial cellulose. The composite can be used as a bone graft material. A method of tissue repair within the body of animals includes the steps of providing a composite biocompatible hydrogel material including a porous polymer matrix, the polymer matrix including a plurality of pores and providing a Young's modulus of at least 10 GPa, and inserting the hydrogel material into cartilage or bone tissue of an animal, wherein the hydrogel material supports cell colonization in vitro for autologous cell seeding.

Method of tissue repair using a composite material

DOEpatents

Hutchens, Stacy A; Woodward, Jonathan; Evans, Barbara R; O'Neill, Hugh M

2014-03-18

A composite biocompatible hydrogel material includes a porous polymer matrix, the polymer matrix including a plurality of pores and providing a Young's modulus of at least 10 GPa. A calcium comprising salt is disposed in at least some of the pores. The porous polymer matrix can comprise cellulose, including bacterial cellulose. The composite can be used as a bone graft material. A method of tissue repair within the body of animals includes the steps of providing a composite biocompatible hydrogel material including a porous polymer matrix, the polymer matrix including a plurality of pores and providing a Young's modulus of at least 10 GPa, and inserting the hydrogel material into cartilage or bone tissue of an animal, wherein the hydrogel material supports cell colonization in vitro for autologous cell seeding.

The covariance matrix for the solution vector of an equality-constrained least-squares problem

NASA Technical Reports Server (NTRS)

Lawson, C. L.

1976-01-01

Methods are given for computing the covariance matrix for the solution vector of an equality-constrained least squares problem. The methods are matched to the solution algorithms given in the book, 'Solving Least Squares Problems.'

Up-and-coming IMCs. [Intermetallic-Matrix Composites

NASA Technical Reports Server (NTRS)

Bowman, Randy; Noebe, Ronald

1989-01-01

While the good oxidation and environmental resistance, high melting points, and comparatively low densities of such ordered intermetallics as Ti3Al, NiAl, FeAl, and NbAl3 render them good candidates for advanced aerospace structures, their poor toughness at low temperatures and low strength at elevated temperatures have prompted the development of fiber-reinforced intermetallic-matrix composites (IMCs) with more balanced characteristics. Fabrication methods for continuous-fiber IMCs under development include the P/M 'powder cloth' method, the foil/fiber method, and thermal spraying. The ultimate success of IMCs depends on fibers truly compatible with the matrix materials.

Mesh-matrix analysis method for electromagnetic launchers

NASA Technical Reports Server (NTRS)

Elliott, David G.

1989-01-01

The mesh-matrix method is a procedure for calculating the current distribution in the conductors of electromagnetic launchers with coil or flat-plate geometry. Once the current distribution is known the launcher performance can be calculated. The method divides the conductors into parallel current paths, or meshes, and finds the current in each mesh by matrix inversion. The author presents procedures for writing equations for the current and voltage relations for a few meshes to serve as a pattern for writing the computer code. An available subroutine package provides routines for field and flux coefficients and equation solution.

Optical factors determined by the T-matrix method in turbidity measurement of absolute coagulation rate constants.

PubMed

Xu, Shenghua; Liu, Jie; Sun, Zhiwei

2006-12-01

Turbidity measurement for the absolute coagulation rate constants of suspensions has been extensively adopted because of its simplicity and easy implementation. A key factor in deriving the rate constant from experimental data is how to theoretically evaluate the so-called optical factor involved in calculating the extinction cross section of doublets formed during aggregation. In a previous paper, we have shown that compared with other theoretical approaches, the T-matrix method provides a robust solution to this problem and is effective in extending the applicability range of the turbidity methodology, as well as increasing measurement accuracy. This paper will provide a more comprehensive discussion of the physical insight for using the T-matrix method in turbidity measurement and associated technical details. In particular, the importance of ensuring the correct value for the refractive indices for colloidal particles and the surrounding medium used in the calculation is addressed, because the indices generally vary with the wavelength of the incident light. The comparison of calculated results with experiments shows that the T-matrix method can correctly calculate optical factors even for large particles, whereas other existing theories cannot. In addition, the data of the optical factor calculated by the T-matrix method for a range of particle radii and incident light wavelengths are listed.

Selection of representative embankments based on rough set - fuzzy clustering method

NASA Astrophysics Data System (ADS)

Bin, Ou; Lin, Zhi-xiang; Fu, Shu-yan; Gao, Sheng-song

2018-02-01

The premise condition of comprehensive evaluation of embankment safety is selection of representative unit embankment, on the basis of dividing the unit levee the influencing factors and classification of the unit embankment are drafted.Based on the rough set-fuzzy clustering, the influence factors of the unit embankment are measured by quantitative and qualitative indexes.Construct to fuzzy similarity matrix of standard embankment then calculate fuzzy equivalent matrix of fuzzy similarity matrix by square method. By setting the threshold of the fuzzy equivalence matrix, the unit embankment is clustered, and the representative unit embankment is selected from the classification of the embankment.

Matrix-Matching as an Improvement Strategy for the Detection of Pesticide Residues.

PubMed

Giacinti, Géraldine; Raynaud, Christine; Capblancq, Sophie; Simon, Valérie

2016-05-01

More than 90% of the pesticides residues in apples are located in the peel. We developed a gas chromatography/ion trap tandem mass spectrometry method for investigating all detectable residues in the peel of 3 apple varieties. Sample preparation is based on the use of the Quick Easy Cheap Effective Rugged and Safe method on the whole fruit, the flesh, and the peel. Pesticide residues were quantified with solvent-matched and matrix-matched standards, by spiking apple sample extracts. Matrix effects dependent on the type of extract (fruit, flesh, or peel) and the apple variety were detected. The best data processing methods involved normalizing matrix effect rates by matrix-matched internal/external calibration. Boscalid, captan, chlorpyrifos, fludioxonil, and pyraclostrobin were the most frequently detected pesticides. However, their concentrations in the whole fruit were below European maximum residue levels. Despite negative matrix effects, the residues in peel were detected at concentrations up to 10 times higher than those in whole fruits. Consequently, other pesticide residues present at concentrations below the limit of quantification in the whole fruit were detected in the peel. © 2016 Institute of Food Technologists®

Fabrication of metal matrix composites by powder metallurgy: A review

NASA Astrophysics Data System (ADS)

Manohar, Guttikonda; Dey, Abhijit; Pandey, K. M.; Maity, S. R.

2018-04-01

Now a day's metal matrix components are used in may industries and it finds the applications in many fields so, to make it as better performable materials. So, the need to increase the mechanical properties of the composites is there. As seen from previous studies major problem faced by the MMC's are wetting, interface bonding between reinforcement and matrix material while they are prepared by conventional methods like stir casting, squeeze casting and other techniques which uses liquid molten metals. So many researchers adopt PM to eliminate these defects and to increase the mechanical properties of the composites. Powder metallurgy is one of the better ways to prepare composites and Nano composites. And the major problem faced by the conventional methods are uniform distribution of the reinforcement particles in the matrix alloy, many researchers tried to homogeneously dispersion of reinforcements in matrix but they find it difficult through conventional methods, among all they find ultrasonic dispersion is efficient. This review article is mainly concentrated on importance of powder metallurgy in homogeneous distribution of reinforcement in matrix by ball milling or mechanical milling and how powder metallurgy improves the mechanical properties of the composites.

Estimating the Inertia Matrix of a Spacecraft

NASA Technical Reports Server (NTRS)

Acikmese, Behcet; Keim, Jason; Shields, Joel

2007-01-01

A paper presents a method of utilizing some flight data, aboard a spacecraft that includes reaction wheels for attitude control, to estimate the inertia matrix of the spacecraft. The required data are digitized samples of (1) the spacecraft attitude in an inertial reference frame as measured, for example, by use of a star tracker and (2) speeds of rotation of the reaction wheels, the moments of inertia of which are deemed to be known. Starting from the classical equations for conservation of angular momentum of a rigid body, the inertia-matrix-estimation problem is formulated as a constrained least-squares minimization problem with explicit bounds on the inertia matrix incorporated as linear matrix inequalities. The explicit bounds reflect physical bounds on the inertia matrix and reduce the volume of data that must be processed to obtain a solution. The resulting minimization problem is a semidefinite optimization problem that can be solved efficiently, with guaranteed convergence to the global optimum, by use of readily available algorithms. In a test case involving a model attitude platform rotating on an air bearing, it is shown that, relative to a prior method, the present method produces better estimates from few data.

Recovering hidden diagonal structures via non-negative matrix factorization with multiple constraints.

PubMed

Yang, Xi; Han, Guoqiang; Cai, Hongmin; Song, Yan

2017-03-31

Revealing data with intrinsically diagonal block structures is particularly useful for analyzing groups of highly correlated variables. Earlier researches based on non-negative matrix factorization (NMF) have been shown to be effective in representing such data by decomposing the observed data into two factors, where one factor is considered to be the feature and the other the expansion loading from a linear algebra perspective. If the data are sampled from multiple independent subspaces, the loading factor would possess a diagonal structure under an ideal matrix decomposition. However, the standard NMF method and its variants have not been reported to exploit this type of data via direct estimation. To address this issue, a non-negative matrix factorization with multiple constraints model is proposed in this paper. The constraints include an sparsity norm on the feature matrix and a total variational norm on each column of the loading matrix. The proposed model is shown to be capable of efficiently recovering diagonal block structures hidden in observed samples. An efficient numerical algorithm using the alternating direction method of multipliers model is proposed for optimizing the new model. Compared with several benchmark models, the proposed method performs robustly and effectively for simulated and real biological data.

Energy Dissipation of Rayleigh Waves due to Absorption Along the Path by the Use of Finite Element Method

DTIC Science & Technology

1979-07-31

3 x 3 t Strain vector a ij,j Space derivative of the stress tensor Fi Force vector per unit volume o Density x CHAPTER III F Total force K Stiffness...matrix 6Vector displacements M Mass matrix B Space operating matrix DO Matrix moduli 2 x 3 DZ Operating matrix in Z direction N Matrix of shape...dissipating medium the deformation of a solid is a function of time, temperature and space . Creep phenomenon is a deformation process in which there is

A frequency domain global parameter estimation method for multiple reference frequency response measurements

NASA Astrophysics Data System (ADS)

Shih, C. Y.; Tsuei, Y. G.; Allemang, R. J.; Brown, D. L.

1988-10-01

A method of using the matrix Auto-Regressive Moving Average (ARMA) model in the Laplace domain for multiple-reference global parameter identification is presented. This method is particularly applicable to the area of modal analysis where high modal density exists. The method is also applicable when multiple reference frequency response functions are used to characterise linear systems. In order to facilitate the mathematical solution, the Forsythe orthogonal polynomial is used to reduce the ill-conditioning of the formulated equations and to decouple the normal matrix into two reduced matrix blocks. A Complex Mode Indicator Function (CMIF) is introduced, which can be used to determine the proper order of the rational polynomials.

On Max-Plus Algebra and Its Application on Image Steganography

PubMed Central

Santoso, Kiswara Agung

2018-01-01

We propose a new steganography method to hide an image into another image using matrix multiplication operations on max-plus algebra. This is especially interesting because the matrix used in encoding or information disguises generally has an inverse, whereas matrix multiplication operations in max-plus algebra do not have an inverse. The advantages of this method are the size of the image that can be hidden into the cover image, larger than the previous method. The proposed method has been tested on many secret images, and the results are satisfactory which have a high level of strength and a high level of security and can be used in various operating systems. PMID:29887761

A-TEEMTM, a new molecular fingerprinting technique: simultaneous absorbance-transmission and fluorescence excitation-emission matrix method

NASA Astrophysics Data System (ADS)

Quatela, Alessia; Gilmore, Adam M.; Steege Gall, Karen E.; Sandros, Marinella; Csatorday, Karoly; Siemiarczuk, Alex; (Ben Yang, Boqian; Camenen, Loïc

2018-04-01

We investigate the new simultaneous absorbance-transmission and fluorescence excitation-emission matrix method for rapid and effective characterization of the varying components from a mixture. The absorbance-transmission and fluorescence excitation-emission matrix method uniquely facilitates correction of fluorescence inner-filter effects to yield quantitative fluorescence spectral information that is largely independent of component concentration. This is significant because it allows one to effectively monitor quantitative component changes using multivariate methods and to generate and evaluate spectral libraries. We present the use of this novel instrument in different fields: i.e. tracking changes in complex mixtures including natural water, wine as well as monitoring stability and aggregation of hormones for biotherapeutics.

On Max-Plus Algebra and Its Application on Image Steganography.

PubMed

Santoso, Kiswara Agung; Fatmawati; Suprajitno, Herry

2018-01-01

We propose a new steganography method to hide an image into another image using matrix multiplication operations on max-plus algebra. This is especially interesting because the matrix used in encoding or information disguises generally has an inverse, whereas matrix multiplication operations in max-plus algebra do not have an inverse. The advantages of this method are the size of the image that can be hidden into the cover image, larger than the previous method. The proposed method has been tested on many secret images, and the results are satisfactory which have a high level of strength and a high level of security and can be used in various operating systems.

On the computation and updating of the modified Cholesky decomposition of a covariance matrix

NASA Technical Reports Server (NTRS)

Vanrooy, D. L.

1976-01-01

Methods for obtaining and updating the modified Cholesky decomposition (MCD) for the particular case of a covariance matrix when one is given only the original data are described. These methods are the standard method of forming the covariance matrix K then solving for the MCD, L and D (where K=LDLT); a method based on Householder reflections; and lastly, a method employing the composite-t algorithm. For many cases in the analysis of remotely sensed data, the composite-t method is the superior method despite the fact that it is the slowest one, since (1) the relative amount of time computing MCD's is often quite small, (2) the stability properties of it are the best of the three, and (3) it affords an efficient and numerically stable procedure for updating the MCD. The properties of these methods are discussed and FORTRAN programs implementing these algorithms are listed.

Sensitivity test of derivative matrix isopotential synchronous fluorimetry and least squares fitting methods.

PubMed

Makkai, Géza; Buzády, Andrea; Erostyák, János

2010-01-01

Determination of concentrations of spectrally overlapping compounds has special difficulties. Several methods are available to calculate the constituents' concentrations in moderately complex mixtures. A method which can provide information about spectrally hidden components in mixtures is very useful. Two methods powerful in resolving spectral components are compared in this paper. The first method tested is the Derivative Matrix Isopotential Synchronous Fluorimetry (DMISF). It is based on derivative analysis of MISF spectra, which are constructed using isopotential trajectories in the Excitation-Emission Matrix (EEM) of background solution. For DMISF method, a mathematical routine fitting the 3D data of EEMs was developed. The other method tested uses classical Least Squares Fitting (LSF) algorithm, wherein Rayleigh- and Raman-scattering bands may lead to complications. Both methods give excellent sensitivity and have advantages against each other. Detection limits of DMISF and LSF have been determined at very different concentration and noise levels.

The analytical transfer matrix method for PT-symmetric complex potential

NASA Astrophysics Data System (ADS)

Naceri, Leila; Hammou, Amine B.

2017-07-01

We have extended the analytical transfer matrix (ATM) method to solve quantum mechanical bound state problems with complex PT-symmetric potentials. Our work focuses on a class of models studied by Bender and Jones, we calculate the energy eigenvalues, discuss the critical values of g and compare the results with those obtained from other methods such as exact numerical computation and WKB approximation method.

Liquid chromatography/electrospray ionization/isotopic dilution mass spectrometry analysis of n-(phosphonomethyl) glycine and mass spectrometry analysis of aminomethyl phosphonic acid in environmental water and vegetation matrixes.

PubMed

Grey, L; Nguyen, B; Yang, P

2001-01-01

A liquid chromatography/electrospray/mass spectrometry (LC/ES/MS) method was developed for the analysis of glyphosate (n-phosphonomethyl glycine) and its metabolite, aminomethyl phosphonic acid (AMPA) using isotope-labelled glyphosate as a method surrogate. Optimized parameters were achieved to derivatize glyphosate and AMPA using 9-fluorenylmethyl chloroformate (FMOC-Cl) in borate buffer prior to a reversed-phase LC analysis. Method spike recovery data obtained using laboratory and real world sample matrixes indicated an excellent correlation between the recovery of the native and isotope-labelled glyphosate. Hence, the first performance-based, isotope dilution MS method with superior precision, accuracy, and data quality was developed for the analysis of glyphosate. There was, however, no observable correlation between the isotope-labelled glyphosate and AMPA. Thus, the use of this procedure for the accurate analysis of AMPA was not supported. Method detection limits established using standard U.S. Environmental Protection Agency protocol were 0.06 and 0.30 microg/L, respectively, for glyphosate and AMPA in water matrixes and 0.11 and 0.53 microg/g, respectively, in vegetation matrixes. Problems, solutions, and the method performance data related to the analysis of chlorine-treated drinking water samples are discussed. Applying this method to other environmental matrixes, e.g., soil, with minimum modifications is possible, assuring accurate, multimedia studies of glyphosate concentration in the environment and the delivery of useful multimedia information for regulatory applications.

Accuracy and speed in computing the Chebyshev collocation derivative

NASA Technical Reports Server (NTRS)

Don, Wai-Sun; Solomonoff, Alex

1991-01-01

We studied several algorithms for computing the Chebyshev spectral derivative and compare their roundoff error. For a large number of collocation points, the elements of the Chebyshev differentiation matrix, if constructed in the usual way, are not computed accurately. A subtle cause is is found to account for the poor accuracy when computing the derivative by the matrix-vector multiplication method. Methods for accurately computing the elements of the matrix are presented, and we find that if the entities of the matrix are computed accurately, the roundoff error of the matrix-vector multiplication is as small as that of the transform-recursion algorithm. Results of CPU time usage are shown for several different algorithms for computing the derivative by the Chebyshev collocation method for a wide variety of two-dimensional grid sizes on both an IBM and a Cray 2 computer. We found that which algorithm is fastest on a particular machine depends not only on the grid size, but also on small details of the computer hardware as well. For most practical grid sizes used in computation, the even-odd decomposition algorithm is found to be faster than the transform-recursion method.

Analytical development of disturbed matrix eigenvalue problem applied to mixed convection stability analysis in Darcy media

NASA Astrophysics Data System (ADS)

Hamed, Haikel Ben; Bennacer, Rachid

2008-08-01

This work consists in evaluating algebraically and numerically the influence of a disturbance on the spectral values of a diagonalizable matrix. Thus, two approaches will be possible; to use the theorem of disturbances of a matrix depending on a parameter, due to Lidskii and primarily based on the structure of Jordan of the no disturbed matrix. The second approach consists in factorizing the matrix system, and then carrying out a numerical calculation of the roots of the disturbances matrix characteristic polynomial. This problem can be a standard model in the equations of the continuous media mechanics. During this work, we chose to use the second approach and in order to illustrate the application, we choose the Rayleigh-Bénard problem in Darcy media, disturbed by a filtering through flow. The matrix form of the problem is calculated starting from a linear stability analysis by a finite elements method. We show that it is possible to break up the general phenomenon into other elementary ones described respectively by a disturbed matrix and a disturbance. A good agreement between the two methods was seen. To cite this article: H.B. Hamed, R. Bennacer, C. R. Mecanique 336 (2008).

Manifold regularized matrix completion for multi-label learning with ADMM.

PubMed

Liu, Bin; Li, Yingming; Xu, Zenglin

2018-05-01

Multi-label learning is a common machine learning problem arising from numerous real-world applications in diverse fields, e.g, natural language processing, bioinformatics, information retrieval and so on. Among various multi-label learning methods, the matrix completion approach has been regarded as a promising approach to transductive multi-label learning. By constructing a joint matrix comprising the feature matrix and the label matrix, the missing labels of test samples are regarded as missing values of the joint matrix. With the low-rank assumption of the constructed joint matrix, the missing labels can be recovered by minimizing its rank. Despite its success, most matrix completion based approaches ignore the smoothness assumption of unlabeled data, i.e., neighboring instances should also share a similar set of labels. Thus they may under exploit the intrinsic structures of data. In addition, the matrix completion problem can be less efficient. To this end, we propose to efficiently solve the multi-label learning problem as an enhanced matrix completion model with manifold regularization, where the graph Laplacian is used to ensure the label smoothness over it. To speed up the convergence of our model, we develop an efficient iterative algorithm, which solves the resulted nuclear norm minimization problem with the alternating direction method of multipliers (ADMM). Experiments on both synthetic and real-world data have shown the promising results of the proposed approach. Copyright © 2018 Elsevier Ltd. All rights reserved.

Visualizing Matrix Multiplication

ERIC Educational Resources Information Center

Daugulis, Peteris; Sondore, Anita

2018-01-01

Efficient visualizations of computational algorithms are important tools for students, educators, and researchers. In this article, we point out an innovative visualization technique for matrix multiplication. This method differs from the standard, formal approach by using block matrices to make computations more visual. We find this method a…

Method and structure for cache aware transposition via rectangular subsections

DOEpatents

Gustavson, Fred Gehrung; Gunnels, John A

2014-02-04

A method and structure for transposing a rectangular matrix A in a computer includes subdividing the rectangular matrix A into one or more square submatrices and executing an in-place transposition for each of the square submatrices A.sub.ij.

Modeling Radioactive Decay Chains with Branching Fraction Uncertainties

DTIC Science & Technology

2013-03-01

moments methods with transmutation matrices. Uncertainty from both half-lives and branching fractions is carried through these calculations by Monte...moment methods, method for sampling from normal distributions for half- life uncertainty, and use of transmutation matrices were leveraged. This...distributions for half-life and branching fraction uncertainties, building decay chains and generating the transmutation matrix (T-matrix

A Synthetic Approach to the Transfer Matrix Method in Classical and Quantum Physics

ERIC Educational Resources Information Center

Pujol, O.; Perez, J. P.

2007-01-01

The aim of this paper is to propose a synthetic approach to the transfer matrix method in classical and quantum physics. This method is an efficient tool to deal with complicated physical systems of practical importance in geometrical light or charged particle optics, classical electronics, mechanics, electromagnetics and quantum physics. Teaching…

A Ranking Analysis/An Interlinking Approach of New Triangular Fuzzy Cognitive Maps and Combined Effective Time Dependent Matrix

NASA Astrophysics Data System (ADS)

Adiga, Shreemathi; Saraswathi, A.; Praveen Prakash, A.

2018-04-01

This paper aims an interlinking approach of new Triangular Fuzzy Cognitive Maps (TrFCM) and Combined Effective Time Dependent (CETD) matrix to find the ranking of the problems of Transgenders. Section one begins with an introduction that briefly describes the scope of Triangular Fuzzy Cognitive Maps (TrFCM) and CETD Matrix. Section two provides the process of causes of problems faced by Transgenders using Fuzzy Triangular Fuzzy Cognitive Maps (TrFCM) method and performs the calculations using the collected data among the Transgender. In Section 3, the reasons for the main causes for the problems of the Transgenders. Section 4 describes the Charles Spearmans coefficients of rank correlation method by interlinking of Triangular Fuzzy Cognitive Maps (TrFCM) Method and CETD Matrix. Section 5 shows the results based on our study.

HIGH DIMENSIONAL COVARIANCE MATRIX ESTIMATION IN APPROXIMATE FACTOR MODELS.

PubMed

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.

A simple non-enzymatic method for the preparation of white spot syndrome virus (WSSV) DNA from the haemolymph of Marsupenaeus japonicus using FTA matrix cards.

PubMed

Sudhakaran, R; Mekata, T; Kono, T; Supamattaya, K; Linh, N T H; Suzuki, Y; Sakai, M; Itami, T

2009-07-01

White spot syndrome virus (WSSV) is an important shrimp pathogen responsible for large economic losses for the shrimp culture industry worldwide. The nucleic acids of the virus must be adequately preserved and transported from the field to the laboratory before molecular diagnostic analysis is performed. Here, we developed a new method to isolate WSSV-DNA using Flinders Technology Associates filter paper (FTA matrix card; Whatman) without centrifugation or hazardous steps involved. FTA technology is a new method allowing the simple collection, shipment and archiving of nucleic acids from haemolymph samples providing DNA protection against nucleases, oxidation, UV damage, microbial and fungal attack. DNA samples prepared from 10-fold dilutions of moribund shrimp haemolymph using FTA matrix cards were analysed using semi-quantitative and quantitative polymerase chain reaction (PCR) and were compared with two commercially available DNA isolation methods, the blood GenomicPrep Mini Spin Kit (GE Healthcare) and the DNAzol (Invitrogen). Sequence analysis was performed for the DNA samples prepared using the various isolation procedures and no differences in the sequence among these methods were identified. Results based on the initial copy number of DNA prepared from the GenomicPrep Mini Spin Kit are a little more sensitive than the DNA prepared from FTA matrix cards, whereas the DNAzol method is not suitable for blood samples. Our data shows the efficiency of retention capacity of WSSV-DNA samples from impregnated FTA matrix cards. Matrix cards were easy to store and ship for long periods of time. They provide ease of handling and are a reliable alternative for sample collection and for molecular detection and characterization of WSSV isolates.

Matrix Methods for Solving Hartree-Fock Equations in Atomic Structure Calculations and Line Broadening

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gomez, Thomas; Nagayama, Taisuke; Fontes, Chris

Atomic structure of N-electron atoms is often determined by solving the Hartree-Fock equations, which are a set of integro-differential equations. The integral part of the Hartree-Fock equations treats electron exchange, but the Hartree-Fock equations are not often treated as an integro-differential equation. The exchange term is often approximated as an inhomogeneous or an effective potential so that the Hartree-Fock equations become a set of ordinary differential equations (which can be solved using the usual shooting methods). Because the Hartree-Fock equations are an iterative-refinement method, the inhomogeneous term relies on the previous guess of the wavefunction. In addition, there are numericalmore » complications associated with solving inhomogeneous differential equations. This work uses matrix methods to solve the Hartree-Fock equations as an integro-differential equation. It is well known that a derivative operator can be expressed as a matrix made of finite-difference coefficients; energy eigenvalues and eigenvectors can be obtained by using linear-algebra packages. The integral (exchange) part of the Hartree-Fock equation can be approximated as a sum and written as a matrix. The Hartree-Fock equations can be solved as a matrix that is the sum of the differential and integral matrices. We compare calculations using this method against experiment and standard atomic structure calculations. This matrix method can also be used to solve for free-electron wavefunctions, thus improving how the atoms and free electrons interact. Here, this technique is important for spectral line broadening in two ways: it improves the atomic structure calculations, and it improves the motion of the plasma electrons that collide with the atom.« less

Matrix Methods for Solving Hartree-Fock Equations in Atomic Structure Calculations and Line Broadening

DOE PAGES

Gomez, Thomas; Nagayama, Taisuke; Fontes, Chris; ...

2018-04-23

Atomic structure of N-electron atoms is often determined by solving the Hartree-Fock equations, which are a set of integro-differential equations. The integral part of the Hartree-Fock equations treats electron exchange, but the Hartree-Fock equations are not often treated as an integro-differential equation. The exchange term is often approximated as an inhomogeneous or an effective potential so that the Hartree-Fock equations become a set of ordinary differential equations (which can be solved using the usual shooting methods). Because the Hartree-Fock equations are an iterative-refinement method, the inhomogeneous term relies on the previous guess of the wavefunction. In addition, there are numericalmore » complications associated with solving inhomogeneous differential equations. This work uses matrix methods to solve the Hartree-Fock equations as an integro-differential equation. It is well known that a derivative operator can be expressed as a matrix made of finite-difference coefficients; energy eigenvalues and eigenvectors can be obtained by using linear-algebra packages. The integral (exchange) part of the Hartree-Fock equation can be approximated as a sum and written as a matrix. The Hartree-Fock equations can be solved as a matrix that is the sum of the differential and integral matrices. We compare calculations using this method against experiment and standard atomic structure calculations. This matrix method can also be used to solve for free-electron wavefunctions, thus improving how the atoms and free electrons interact. Here, this technique is important for spectral line broadening in two ways: it improves the atomic structure calculations, and it improves the motion of the plasma electrons that collide with the atom.« less

The effect of stochiastic technique on estimates of population viability from transition matrix models

USGS Publications Warehouse

Kaye, T.N.; Pyke, David A.

2003-01-01

Population viability analysis is an important tool for conservation biologists, and matrix models that incorporate stochasticity are commonly used for this purpose. However, stochastic simulations may require assumptions about the distribution of matrix parameters, and modelers often select a statistical distribution that seems reasonable without sufficient data to test its fit. We used data from long-term (5a??10 year) studies with 27 populations of five perennial plant species to compare seven methods of incorporating environmental stochasticity. We estimated stochastic population growth rate (a measure of viability) using a matrix-selection method, in which whole observed matrices were selected at random at each time step of the model. In addition, we drew matrix elements (transition probabilities) at random using various statistical distributions: beta, truncated-gamma, truncated-normal, triangular, uniform, or discontinuous/observed. Recruitment rates were held constant at their observed mean values. Two methods of constraining stage-specific survival to a??100% were also compared. Different methods of incorporating stochasticity and constraining matrix column sums interacted in their effects and resulted in different estimates of stochastic growth rate (differing by up to 16%). Modelers should be aware that when constraining stage-specific survival to 100%, different methods may introduce different levels of bias in transition element means, and when this happens, different distributions for generating random transition elements may result in different viability estimates. There was no species effect on the results and the growth rates derived from all methods were highly correlated with one another. We conclude that the absolute value of population viability estimates is sensitive to model assumptions, but the relative ranking of populations (and management treatments) is robust. Furthermore, these results are applicable to a range of perennial plants and possibly other life histories.

Temperature dependent nonlinear metal matrix laminae behavior

NASA Technical Reports Server (NTRS)

Barrett, D. J.; Buesking, K. W.

1986-01-01

An analytical method is described for computing the nonlinear thermal and mechanical response of laminated plates. The material model focuses upon the behavior of metal matrix materials by relating the nonlinear composite response to plasticity effects in the matrix. The foundation of the analysis is the unidirectional material model which is used to compute the instantaneous properties of the lamina based upon the properties of the fibers and matrix. The unidirectional model assumes that the fibers properties are constant with temperature and assumes that the matrix can be modelled as a temperature dependent, bilinear, kinematically hardening material. An incremental approach is used to compute average stresses in the fibers and matrix caused by arbitrary mechanical and thermal loads. The layer model is incorporated in an incremental laminated plate theory to compute the nonlinear response of laminated metal matrix composites of general orientation and stacking sequence. The report includes comparisons of the method with other analytical approaches and compares theoretical calculations with measured experimental material behavior. A section is included which describes the limitations of the material model.

Confocal analysis of the exopolysaccharide matrix of Candida albicans biofilms.

PubMed

Gonçalves, Letícia M; Del Bel Cury, Altair A; de Vasconcellos, Andréa A; Cury, Jaime A; da Silva, Wander J

2015-08-01

Confocal laser-scanning microscopy (CLSM) was carried out to investigate the exopolysaccharide matrix of Candida albicans (C. albicans) biofilms developed on denture material under dietary carbohydrate exposure. Biofilms were developed on poly(methyl methacrylate) discs in culture media without (control) or with supplementation by glucose or sucrose for 72 h. For the CLSM analysis, biofilms were labeled with concanavalin A (ConA) during its development. Afterwards, biofilms were also labeled with SYTO-9. To confirm the results, the matrix was investigated by the phenol-sulfuric method. Data were analyzed by anova, followed by Tukey's test, with the level of significance set at 5%. The use of ConA during biofilm development provided effective labeling of the exopolysaccharide matrix. The exposure to sucrose resulted in biofilms with the highest exopolysaccharide matrix biovolume (P < 0.05). The characterization obtained by CLSM was confirmed by the phenol-sulfuric method. Confocal laser-scanning microscopy was found to be an effective tool for investigating the exopolysaccharide matrix of C. albicans biofilms, and exposure to sucrose resulted in increased matrix production. © 2014 Wiley Publishing Asia Pty Ltd.

Ceramic/metal and A15/metal superconducting composite materials exploiting the superconducting proximity effect and method of making the same

DOEpatents

Holcomb, Matthew J.

1999-01-01

A composite superconducting material made of coated particles of ceramic superconducting material and a metal matrix material. The metal matrix material fills the regions between the coated particles. The coating material is a material that is chemically nonreactive with the ceramic. Preferably, it is silver. The coating serves to chemically insulate the ceramic from the metal matrix material. The metal matrix material is a metal that is susceptible to the superconducting proximity effect. Preferably, it is a NbTi alloy. The metal matrix material is induced to become superconducting by the superconducting proximity effect when the temperature of the material goes below the critical temperature of the ceramic. The material has the improved mechanical properties of the metal matrix material. Preferably, the material consists of approximately 10% NbTi, 90% coated ceramic particles (by volume). Certain aspects of the material and method will depend upon the particular ceramic superconductor employed. An alternative embodiment of the invention utilizes A15 compound superconducting particles in a metal matrix material which is preferably a NbTi alloy.

[Research on partial least squares for determination of impurities in the presence of high concentration of matrix by ICP-AES].

PubMed

Wang, Yan-peng; Gong, Qi; Yu, Sheng-rong; Liu, You-yan

2012-04-01

A method for detecting trace impurities in high concentration matrix by ICP-AES based on partial least squares (PLS) was established. The research showed that PLS could effectively correct the interference caused by high level of matrix concentration error and could withstand higher concentrations of matrix than multicomponent spectral fitting (MSF). When the mass ratios of matrix to impurities were from 1 000 : 1 to 20 000 : 1, the recoveries of standard addition were between 95% and 105% by PLS. For the system in which interference effect has nonlinear correlation with the matrix concentrations, the prediction accuracy of normal PLS method was poor, but it can be improved greatly by using LIN-PPLS, which was based on matrix transformation of sample concentration. The contents of Co, Pb and Ga in stream sediment (GBW07312) were detected by MSF, PLS and LIN-PPLS respectively. The results showed that the prediction accuracy of LIN-PPLS was better than PLS, and the prediction accuracy of PLS was better than MSF.

Evaluating Process Improvement Courses of Action Through Modeling and Simulation

DTIC Science & Technology

2017-09-16

changes to a process is time consuming and has potential to overlook stochastic effects. By modeling a process as a Numerical Design Structure Matrix...13 Methods to Evaluate Process Performance ................................................................15 The Design Structure...Matrix ......................................................................................16 Numerical Design Structure Matrix

Comparison on genomic predictions using three GBLUP methods and two single-step blending methods in the Nordic Holstein population

PubMed Central

2012-01-01

Background A single-step blending approach allows genomic prediction using information of genotyped and non-genotyped animals simultaneously. However, the combined relationship matrix in a single-step method may need to be adjusted because marker-based and pedigree-based relationship matrices may not be on the same scale. The same may apply when a GBLUP model includes both genomic breeding values and residual polygenic effects. The objective of this study was to compare single-step blending methods and GBLUP methods with and without adjustment of the genomic relationship matrix for genomic prediction of 16 traits in the Nordic Holstein population. Methods The data consisted of de-regressed proofs (DRP) for 5 214 genotyped and 9 374 non-genotyped bulls. The bulls were divided into a training and a validation population by birth date, October 1, 2001. Five approaches for genomic prediction were used: 1) a simple GBLUP method, 2) a GBLUP method with a polygenic effect, 3) an adjusted GBLUP method with a polygenic effect, 4) a single-step blending method, and 5) an adjusted single-step blending method. In the adjusted GBLUP and single-step methods, the genomic relationship matrix was adjusted for the difference of scale between the genomic and the pedigree relationship matrices. A set of weights on the pedigree relationship matrix (ranging from 0.05 to 0.40) was used to build the combined relationship matrix in the single-step blending method and the GBLUP method with a polygenetic effect. Results Averaged over the 16 traits, reliabilities of genomic breeding values predicted using the GBLUP method with a polygenic effect (relative weight of 0.20) were 0.3% higher than reliabilities from the simple GBLUP method (without a polygenic effect). The adjusted single-step blending and original single-step blending methods (relative weight of 0.20) had average reliabilities that were 2.1% and 1.8% higher than the simple GBLUP method, respectively. In addition, the GBLUP method with a polygenic effect led to less bias of genomic predictions than the simple GBLUP method, and both single-step blending methods yielded less bias of predictions than all GBLUP methods. Conclusions The single-step blending method is an appealing approach for practical genomic prediction in dairy cattle. Genomic prediction from the single-step blending method can be improved by adjusting the scale of the genomic relationship matrix. PMID:22455934

The supersymmetric method in random matrix theory and applications to QCD

NASA Astrophysics Data System (ADS)

Verbaarschot, Jacobus

2004-12-01

The supersymmetric method is a powerful method for the nonperturbative evaluation of quenched averages in disordered systems. Among others, this method has been applied to the statistical theory of S-matrix fluctuations, the theory of universal conductance fluctuations and the microscopic spectral density of the QCD Dirac operator. We start this series of lectures with a general review of Random Matrix Theory and the statistical theory of spectra. An elementary introduction of the supersymmetric method in Random Matrix Theory is given in the second and third lecture. We will show that a Random Matrix Theory can be rewritten as an integral over a supermanifold. This integral will be worked out in detail for the Gaussian Unitary Ensemble that describes level correlations in systems with broken time-reversal invariance. We especially emphasize the role of symmetries. As a second example of the application of the supersymmetric method we discuss the calculation of the microscopic spectral density of the QCD Dirac operator. This is the eigenvalue density near zero on the scale of the average level spacing which is known to be given by chiral Random Matrix Theory. Also in this case we use symmetry considerations to rewrite the generating function for the resolvent as an integral over a supermanifold. The main topic of the second last lecture is the recent developments on the relation between the supersymmetric partition function and integrable hierarchies (in our case the Toda lattice hierarchy). We will show that this relation is an efficient way to calculate superintegrals. Several examples that were given in previous lectures will be worked out by means of this new method. Finally, we will discuss the quenched QCD Dirac spectrum at nonzero chemical potential. Because of the nonhermiticity of the Dirac operator the usual supersymmetric method has not been successful in this case. However, we will show that the supersymmetric partition function can be evaluated by means of the replica limit of the Toda lattice equation.

A Matrix-Free Algorithm for Multidisciplinary Design Optimization

NASA Astrophysics Data System (ADS)

Lambe, Andrew Borean

Multidisciplinary design optimization (MDO) is an approach to engineering design that exploits the coupling between components or knowledge disciplines in a complex system to improve the final product. In aircraft design, MDO methods can be used to simultaneously design the outer shape of the aircraft and the internal structure, taking into account the complex interaction between the aerodynamic forces and the structural flexibility. Efficient strategies are needed to solve such design optimization problems and guarantee convergence to an optimal design. This work begins with a comprehensive review of MDO problem formulations and solution algorithms. First, a fundamental MDO problem formulation is defined from which other formulations may be obtained through simple transformations. Using these fundamental problem formulations, decomposition methods from the literature are reviewed and classified. All MDO methods are presented in a unified mathematical notation to facilitate greater understanding. In addition, a novel set of diagrams, called extended design structure matrices, are used to simultaneously visualize both data communication and process flow between the many software components of each method. For aerostructural design optimization, modern decomposition-based MDO methods cannot efficiently handle the tight coupling between the aerodynamic and structural states. This fact motivates the exploration of methods that can reduce the computational cost. A particular structure in the direct and adjoint methods for gradient computation motivates the idea of a matrix-free optimization method. A simple matrix-free optimizer is developed based on the augmented Lagrangian algorithm. This new matrix-free optimizer is tested on two structural optimization problems and one aerostructural optimization problem. The results indicate that the matrix-free optimizer is able to efficiently solve structural and multidisciplinary design problems with thousands of variables and constraints. On the aerostructural test problem formulated with thousands of constraints, the matrix-free optimizer is estimated to reduce the total computational time by up to 90% compared to conventional optimizers.

A Matrix-Free Algorithm for Multidisciplinary Design Optimization

NASA Astrophysics Data System (ADS)

Lambe, Andrew Borean

Multidisciplinary design optimization (MDO) is an approach to engineering design that exploits the coupling between components or knowledge disciplines in a complex system to improve the final product. In aircraft design, MDO methods can be used to simultaneously design the outer shape of the aircraft and the internal structure, taking into account the complex interaction between the aerodynamic forces and the structural flexibility. Efficient strategies are needed to solve such design optimization problems and guarantee convergence to an optimal design. This work begins with a comprehensive review of MDO problem formulations and solution algorithms. First, a fundamental MDO problem formulation is defined from which other formulations may be obtained through simple transformations. Using these fundamental problem formulations, decomposition methods from the literature are reviewed and classified. All MDO methods are presented in a unified mathematical notation to facilitate greater understanding. In addition, a novel set of diagrams, called extended design structure matrices, are used to simultaneously visualize both data communication and process flow between the many software components of each method. For aerostructural design optimization, modern decomposition-based MDO methods cannot efficiently handle the tight coupling between the aerodynamic and structural states. This fact motivates the exploration of methods that can reduce the computational cost. A particular structure in the direct and adjoint methods for gradient computation. motivates the idea of a matrix-free optimization method. A simple matrix-free optimizer is developed based on the augmented Lagrangian algorithm. This new matrix-free optimizer is tested on two structural optimization problems and one aerostructural optimization problem. The results indicate that the matrix-free optimizer is able to efficiently solve structural and multidisciplinary design problems with thousands of variables and constraints. On the aerostructural test problem formulated with thousands of constraints, the matrix-free optimizer is estimated to reduce the total computational time by up to 90% compared to conventional optimizers.

RECEPTOR MODELING OF AMBIENT PARTICULATE MATTER DATA USING POSITIVE MATRIX FACTORIZATION REVIEW OF EXISTING METHODS

EPA Science Inventory

Methods for apportioning sources of ambient particulate matter (PM) using the positive matrix factorization (PMF) algorithm are reviewed. Numerous procedural decisions must be made and algorithmic parameters selected when analyzing PM data with PMF. However, few publications docu...

An approximate method for determining of investment risk

NASA Astrophysics Data System (ADS)

Slavkova, Maria; Tzenova, Zlatina

2016-12-01

In this work a method for determining of investment risk during all economic states is considered. It is connected to matrix games with two players. A definition for risk in a matrix game is introduced. Three properties are proven. It is considered an appropriate example.

A Generalized Method of Image Analysis from an Intercorrelation Matrix which May Be Singular.

ERIC Educational Resources Information Center

Yanai, Haruo; Mukherjee, Bishwa Nath

1987-01-01

This generalized image analysis method is applicable to singular and non-singular correlation matrices (CMs). Using the orthogonal projector and a weaker generalized inverse matrix, image and anti-image covariance matrices can be derived from a singular CM. (SLD)

DETERMINING BERYLLIUM IN DRINKING WATER BY GRAPHITE FURNACE ATOMIC ABSORPTION SPECTROSCOPY

EPA Science Inventory

A direct graphite furnace atomic absorption spectroscopy method for the analysis of beryllium in drinking water has been derived from a method for determining beryllium in urine. Ammonium phosphomolybdate and ascorbic acid were employed as matrix modifiers. The matrix modifiers s...

Health monitoring method for composite materials

DOEpatents

Watkins, Jr., Kenneth S.; Morris, Shelby J [Hampton, VA

2011-04-12

An in-situ method for monitoring the health of a composite component utilizes a condition sensor made of electrically conductive particles dispersed in a polymeric matrix. The sensor is bonded or otherwise formed on the matrix surface of the composite material. Age-related shrinkage of the sensor matrix results in a decrease in the resistivity of the condition sensor. Correlation of measured sensor resistivity with data from aged specimens allows indirect determination of mechanical damage and remaining age of the composite component.

Adomian decomposition

NASA Astrophysics Data System (ADS)

Daftardar-Gejji, Varsha; Jafari, Hossein

2005-01-01

Adomian decomposition method has been employed to obtain solutions of a system of fractional differential equations. Convergence of the method has been discussed with some illustrative examples. In particular, for the initial value problem: where A=[aij] is a real square matrix, the solution turns out to be , where E([alpha]1,...,[alpha]n),1 denotes multivariate Mittag-Leffler function defined for matrix arguments and Ai is the matrix having ith row as [ai1...ain], and all other entries are zero. Fractional oscillation and Bagley-Torvik equations are solved as illustrative examples.

Numerical study of a matrix-free trust-region SQP method for equality constrained optimization.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Heinkenschloss, Matthias; Ridzal, Denis; Aguilo, Miguel Antonio

2011-12-01

This is a companion publication to the paper 'A Matrix-Free Trust-Region SQP Algorithm for Equality Constrained Optimization' [11]. In [11], we develop and analyze a trust-region sequential quadratic programming (SQP) method that supports the matrix-free (iterative, in-exact) solution of linear systems. In this report, we document the numerical behavior of the algorithm applied to a variety of equality constrained optimization problems, with constraints given by partial differential equations (PDEs).

Heat exchanger and method of making. [bonding rocket chambers with a porous metal matrix

NASA Technical Reports Server (NTRS)

Fortini, A.; Kazaroff, J. M. (Inventor)

1978-01-01

A heat exchanger of increased effectiveness is disclosed. A porous metal matrix is disposed in a metal chamber or between walls through which a heat-transfer fluid is directed. The porous metal matrix has internal bonds and is bonded to the chamber in order to remove all thermal contact resistance within the composite structure. Utilization of the invention in a rocket chamber is disclosed as a specific use. Also disclosed is a method of constructing the heat exchanger.

Gain Switching for a Detection System to Accommodate a Newly Developed MALDI-Based Quantification Method

NASA Astrophysics Data System (ADS)

Ahn, Sung Hee; Hyeon, Taeghwan; Kim, Myung Soo; Moon, Jeong Hee

2017-09-01

In matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF), matrix-derived ions are routinely deflected away to avoid problems with ion detection. This, however, limits the use of a quantification method that utilizes the analyte-to-matrix ion abundance ratio. In this work, we will show that it is possible to measure this ratio by a minor instrumental modification of a simple form of MALDI-TOF. This involves detector gain switching. [Figure not available: see fulltext.

Transfer matrix method for four-flux radiative transfer.

PubMed

Slovick, Brian; Flom, Zachary; Zipp, Lucas; Krishnamurthy, Srini

2017-07-20

We develop a transfer matrix method for four-flux radiative transfer, which is ideally suited for studying transport through multiple scattering layers. The model predicts the specular and diffuse reflection and transmission of multilayer composite films, including interface reflections, for diffuse or collimated incidence. For spherical particles in the diffusion approximation, we derive closed-form expressions for the matrix coefficients and show remarkable agreement with numerical Monte Carlo simulations for a range of absorption values and film thicknesses, and for an example multilayer slab.

Iterative approach as alternative to S-matrix in modal methods

NASA Astrophysics Data System (ADS)

Semenikhin, Igor; Zanuccoli, Mauro

2014-12-01

The continuously increasing complexity of opto-electronic devices and the rising demands of simulation accuracy lead to the need of solving very large systems of linear equations making iterative methods promising and attractive from the computational point of view with respect to direct methods. In particular, iterative approach potentially enables the reduction of required computational time to solve Maxwell's equations by Eigenmode Expansion algorithms. Regardless of the particular eigenmodes finding method used, the expansion coefficients are computed as a rule by scattering matrix (S-matrix) approach or similar techniques requiring order of M3 operations. In this work we consider alternatives to the S-matrix technique which are based on pure iterative or mixed direct-iterative approaches. The possibility to diminish the impact of M3 -order calculations to overall time and in some cases even to reduce the number of arithmetic operations to M2 by applying iterative techniques are discussed. Numerical results are illustrated to discuss validity and potentiality of the proposed approaches.

Optimal Frequency-Domain System Realization with Weighting

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan; Maghami, Peiman G.

1999-01-01

Several approaches are presented to identify an experimental system model directly from frequency response data. The formulation uses a matrix-fraction description as the model structure. Frequency weighting such as exponential weighting is introduced to solve a weighted least-squares problem to obtain the coefficient matrices for the matrix-fraction description. A multi-variable state-space model can then be formed using the coefficient matrices of the matrix-fraction description. Three different approaches are introduced to fine-tune the model using nonlinear programming methods to minimize the desired cost function. The first method uses an eigenvalue assignment technique to reassign a subset of system poles to improve the identified model. The second method deals with the model in the real Schur or modal form, reassigns a subset of system poles, and adjusts the columns (rows) of the input (output) influence matrix using a nonlinear optimizer. The third method also optimizes a subset of poles, but the input and output influence matrices are refined at every optimization step through least-squares procedures.

Fast time- and frequency-domain finite-element methods for electromagnetic analysis

NASA Astrophysics Data System (ADS)

Lee, Woochan

Fast electromagnetic analysis in time and frequency domain is of critical importance to the design of integrated circuits (IC) and other advanced engineering products and systems. Many IC structures constitute a very large scale problem in modeling and simulation, the size of which also continuously grows with the advancement of the processing technology. This results in numerical problems beyond the reach of existing most powerful computational resources. Different from many other engineering problems, the structure of most ICs is special in the sense that its geometry is of Manhattan type and its dielectrics are layered. Hence, it is important to develop structure-aware algorithms that take advantage of the structure specialties to speed up the computation. In addition, among existing time-domain methods, explicit methods can avoid solving a matrix equation. However, their time step is traditionally restricted by the space step for ensuring the stability of a time-domain simulation. Therefore, making explicit time-domain methods unconditionally stable is important to accelerate the computation. In addition to time-domain methods, frequency-domain methods have suffered from an indefinite system that makes an iterative solution difficult to converge fast. The first contribution of this work is a fast time-domain finite-element algorithm for the analysis and design of very large-scale on-chip circuits. The structure specialty of on-chip circuits such as Manhattan geometry and layered permittivity is preserved in the proposed algorithm. As a result, the large-scale matrix solution encountered in the 3-D circuit analysis is turned into a simple scaling of the solution of a small 1-D matrix, which can be obtained in linear (optimal) complexity with negligible cost. Furthermore, the time step size is not sacrificed, and the total number of time steps to be simulated is also significantly reduced, thus achieving a total cost reduction in CPU time. The second contribution is a new method for making an explicit time-domain finite-element method (TDFEM) unconditionally stable for general electromagnetic analysis. In this method, for a given time step, we find the unstable modes that are the root cause of instability, and deduct them directly from the system matrix resulting from a TDFEM based analysis. As a result, an explicit TDFEM simulation is made stable for an arbitrarily large time step irrespective of the space step. The third contribution is a new method for full-wave applications from low to very high frequencies in a TDFEM based on matrix exponential. In this method, we directly deduct the eigenmodes having large eigenvalues from the system matrix, thus achieving a significantly increased time step in the matrix exponential based TDFEM. The fourth contribution is a new method for transforming the indefinite system matrix of a frequency-domain FEM to a symmetric positive definite one. We deduct non-positive definite component directly from the system matrix resulting from a frequency-domain FEM-based analysis. The resulting new representation of the finite-element operator ensures an iterative solution to converge in a small number of iterations. We then add back the non-positive definite component to synthesize the original solution with negligible cost.

Gradient-based stochastic estimation of the density matrix

NASA Astrophysics Data System (ADS)

Wang, Zhentao; Chern, Gia-Wei; Batista, Cristian D.; Barros, Kipton

2018-03-01

Fast estimation of the single-particle density matrix is key to many applications in quantum chemistry and condensed matter physics. The best numerical methods leverage the fact that the density matrix elements f(H)ij decay rapidly with distance rij between orbitals. This decay is usually exponential. However, for the special case of metals at zero temperature, algebraic decay of the density matrix appears and poses a significant numerical challenge. We introduce a gradient-based probing method to estimate all local density matrix elements at a computational cost that scales linearly with system size. For zero-temperature metals, the stochastic error scales like S-(d+2)/2d, where d is the dimension and S is a prefactor to the computational cost. The convergence becomes exponential if the system is at finite temperature or is insulating.

A Comparative Study of Collagen Matrix Density Effect on Endothelial Sprout Formation Using Experimental and Computational Approaches.

PubMed

Shamloo, Amir; Mohammadaliha, Negar; Heilshorn, Sarah C; Bauer, Amy L

2016-04-01

A thorough understanding of determining factors in angiogenesis is a necessary step to control the development of new blood vessels. Extracellular matrix density is known to have a significant influence on cellular behaviors and consequently can regulate vessel formation. The utilization of experimental platforms in combination with numerical models can be a powerful method to explore the mechanisms of new capillary sprout formation. In this study, using an integrative method, the interplay between the matrix density and angiogenesis was investigated. Owing the fact that the extracellular matrix density is a global parameter that can affect other parameters such as pore size, stiffness, cell-matrix adhesion and cross-linking, deeper understanding of the most important biomechanical or biochemical properties of the ECM causing changes in sprout morphogenesis is crucial. Here, we implemented both computational and experimental methods to analyze the mechanisms responsible for the influence of ECM density on the sprout formation that is difficult to be investigated comprehensively using each of these single methods. For this purpose, we first utilized an innovative approach to quantify the correspondence of the simulated collagen fibril density to the collagen density in the experimental part. Comparing the results of the experimental study and computational model led to some considerable achievements. First, we verified the results of the computational model using the experimental results. Then, we reported parameters such as the ratio of proliferating cells to migrating cells that was difficult to obtain from experimental study. Finally, this integrative system led to gain an understanding of the possible mechanisms responsible for the effect of ECM density on angiogenesis. The results showed that stable and long sprouts were observed at an intermediate collagen matrix density of 1.2 and 1.9 mg/ml due to a balance between the number of migrating and proliferating cells. As a result of weaker connections between the cells and matrix, a lower collagen matrix density (0.7 mg/ml) led to unstable and broken sprouts. However, higher matrix density (2.7 mg/ml) suppressed sprout formation due to the high level of matrix entanglement, which inhibited cell migration. This study also showed that extracellular matrix density can influence sprout branching. Our experimental results support this finding.

The KS Method in Light of Generalized Euler Parameters.

DTIC Science & Technology

1980-01-01

motion for the restricted two-body problem is trans- formed via the Kustaanheimo - Stiefel transformation method (KS) into a dynamical equation in the... Kustaanheimo - Stiefel2 transformation method (KS) in the two-body problem. Many papers have appeared in which specific problems or applications have... TRANSFORMATION MATRIX P. Kustaanheimo and E. Stiefel2 proposed a regularization method by intro- ducing a 4 x 4 transformation matrix and four-component

Nanoparticle-assisted laser desorption/ionization mass spectrometry: Novel sample preparation methods and nanoparticle screening for plant metabolite imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yagnik, Gargey B.

The main goal of the presented research is development of nanoparticle based matrix-assisted laser desorption ionization-mass spectrometry (MALDI-MS). This dissertation includes the application of previously developed data acquisition methods, development of novel sample preparation methods, application and comparison of novel nanoparticle matrices, and comparison of two nanoparticle matrix application methods for MALDI-MS and MALDI-MS imaging.

Development of 10×10 Matrix-anode MCP-PMT

NASA Astrophysics Data System (ADS)

Yang, Jie; Li, Yongbin; Xu, Pengxiao; Zhao, Wenjin

2018-02-01

10×10 matrix-anode is developed by high-temperature co-fired ceramics (HTCC) technology. Based on the new matrix-anode, a new kind of photon counting imaging detector - 10×10 matrix-anode MCP-PMT is developed, and its performance parameters are tested. HTCC technology is suitable for the MCP-PMT's air impermeability and its baking process. Its response uniformity is better than the metal-ceramic or metal-glass sealing anode, and it is also a promising method to realize a higher density matrix-anode.

On the Construction of Involutory Rhotrices

ERIC Educational Resources Information Center

Usaini, S.

2012-01-01

An involutory matrix is a matrix that is its own inverse. Such matrices are of great importance in matrix theory and algebraic cryptography. In this note, we extend this involution to rhotrices and present their properties. We have also provided a method of constructing involutory rhotrices.

Encapsulation of Organic Chemicals within a Starch Matrix.

ERIC Educational Resources Information Center

Wing, R. E.; Shasha, B. S.

1983-01-01

Three experiments demonstrating the feasibility of encapsulating liquids within a starch matrix are described, including encapsulation of linseed oil using the zanthate method and of turpentine and butylate using the calcium adduct procedure. Encapsulated materials, including pesticides, are slowly released from the resulting matrix. Considers…

Stress and Damage in Polymer Matrix Composite Materials Due to Material Degradation at High Temperatures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mcmanus, H.L.; Chamis, C.C.

1996-01-01

This report describes analytical methods for calculating stresses and damage caused by degradation of the matrix constituent in polymer matrix composite materials. Laminate geometry, material properties, and matrix degradation states are specified as functions of position and time. Matrix shrinkage and property changes are modeled as functions of the degradation states. The model is incorporated into an existing composite mechanics computer code. Stresses, strains, and deformations at the laminate, ply, and micro levels are calculated, and from these calculations it is determined if there is failure of any kind. The rationale for the model (based on published experimental work) ismore » presented, its integration into the laminate analysis code is outlined, and example results are given, with comparisons to existing material and structural data. The mechanisms behind the changes in properties and in surface cracking during long-term aging of polyimide matrix composites are clarified. High-temperature-material test methods are also evaluated.« less

General Matrix Inversion for the Calibration of Electric Field Sensor Arrays on Aircraft Platforms

NASA Technical Reports Server (NTRS)

Mach, D. M.; Koshak, W. J.

2006-01-01

We have developed a matrix calibration procedure that uniquely relates the electric fields measured at the aircraft with the external vector electric field and net aircraft charge. Our calibration method is being used with all of our aircraft/electric field sensing combinations and can be generalized to any reasonable combination of electric field measurements and aircraft. We determine a calibration matrix that represents the individual instrument responses to the external electric field. The aircraft geometry and configuration of field mills (FMs) uniquely define the matrix. The matrix can then be inverted to determine the external electric field and net aircraft charge from the FM outputs. A distinct advantage of the method is that if one or more FMs need to be eliminated or de-emphasized (for example, due to a malfunction), it is a simple matter to reinvert the matrix without the malfunctioning FMs. To demonstrate our calibration technique, we present data from several of our aircraft programs (ER-2, DC-8, Altus, Citation).

Application of symbolic/numeric matrix solution techniques to the NASTRAN program

NASA Technical Reports Server (NTRS)

Buturla, E. M.; Burroughs, S. H.

1977-01-01

The matrix solving algorithm of any finite element algorithm is extremely important since solution of the matrix equations requires a large amount of elapse time due to null calculations and excessive input/output operations. An alternate method of solving the matrix equations is presented. A symbolic processing step followed by numeric solution yields the solution very rapidly and is especially useful for nonlinear problems.

Certain topological properties and duals of the domain of a triangle matrix in a sequence space

NASA Astrophysics Data System (ADS)

Altay, Bilâl; Basar, Feyzi

2007-12-01

The matrix domain of the particular limitation methods Cesàro, Riesz, difference, summation and Euler were studied by several authors. In the present paper, certain topological properties and [beta]- and [gamma]-duals of the domain of a triangle matrix in a sequence space have been examined as an application of the characterization of the related matrix classes.

A reformulation of the coupled perturbed self-consistent field equations entirely within a local atomic orbital density matrix-based scheme

NASA Astrophysics Data System (ADS)

Ochsenfeld, Christian; Head-Gordon, Martin

1997-05-01

To exploit the exponential decay found in numerical studies for the density matrix and its derivative with respect to nuclear displacements, we reformulate the coupled perturbed self-consistent field (CPSCF) equations and a quadratically convergent SCF (QCSCF) method for Hartree-Fock and density functional theory within a local density matrix-based scheme. Our D-CPSCF (density matrix-based CPSCF) and D-QCSCF schemes open the way for exploiting sparsity and to achieve asymptotically linear scaling of computational complexity with molecular size ( M), in case of D-CPSCF for all O( M) derivative densities. Furthermore, these methods are even for small molecules strongly competitive to conventional algorithms.

Synthesizing (ZrAl3 + AlN)/Mg-Al composites by a 'matrix exchange' method

NASA Astrophysics Data System (ADS)

Gao, Tong; Li, Zengqiang; Hu, Kaiqi; Han, Mengxia; Liu, Xiangfa

2018-06-01

A method named 'matrix exchange' to synthesize ZrAl3 and AlN reinforced Mg-Al composite was developed in this paper. By inserting Al-10ZrN master alloy into Mg matrix and reheating the cooled ingot to 550 °C, Al and Mg atoms diffuse to the opposite side. As a result, liquid melt occurs once the interface areas reach to proper compositions. Then dissolved Al atoms react with ZrN, leading to the in-situ formation of ZrAl3 and AlN particles, while the Al matrix is finally replaced by Mg. This study provides a new insight for preparing Mg composites.

Selecting appropriate singular values of transmission matrix to improve precision of incident wavefront retrieval

NASA Astrophysics Data System (ADS)

Fang, Longjie; Zhang, Xicheng; Zuo, Haoyi; Pang, Lin; Yang, Zuogang; Du, Jinglei

2018-06-01

A method of selecting appropriate singular values of the transmission matrix to improve the precision of incident wavefront retrieval in focusing light through scattering media is proposed. The optimal singular values selected by this method can reduce the degree of ill-conditionedness of the transmission matrix effectively, which indicates that the incident wavefront retrieved from the optimal set of singular values is more accurate than the incident wavefront retrieved from other sets of singular values. The validity of this method is verified by numerical simulation and actual measurements of the incident wavefront of coherent light through ground glass.

Using Chebyshev polynomials and approximate inverse triangular factorizations for preconditioning the conjugate gradient method

NASA Astrophysics Data System (ADS)

Kaporin, I. E.

2012-02-01

In order to precondition a sparse symmetric positive definite matrix, its approximate inverse is examined, which is represented as the product of two sparse mutually adjoint triangular matrices. In this way, the solution of the corresponding system of linear algebraic equations (SLAE) by applying the preconditioned conjugate gradient method (CGM) is reduced to performing only elementary vector operations and calculating sparse matrix-vector products. A method for constructing the above preconditioner is described and analyzed. The triangular factor has a fixed sparsity pattern and is optimal in the sense that the preconditioned matrix has a minimum K-condition number. The use of polynomial preconditioning based on Chebyshev polynomials makes it possible to considerably reduce the amount of scalar product operations (at the cost of an insignificant increase in the total number of arithmetic operations). The possibility of an efficient massively parallel implementation of the resulting method for solving SLAEs is discussed. For a sequential version of this method, the results obtained by solving 56 test problems from the Florida sparse matrix collection (which are large-scale and ill-conditioned) are presented. These results show that the method is highly reliable and has low computational costs.

Preconditioned conjugate residual methods for the solution of spectral equations

NASA Technical Reports Server (NTRS)

Wong, Y. S.; Zang, T. A.; Hussaini, M. Y.

1986-01-01

Conjugate residual methods for the solution of spectral equations are described. An inexact finite-difference operator is introduced as a preconditioner in the iterative procedures. Application of these techniques is limited to problems for which the symmetric part of the coefficient matrix is positive definite. Although the spectral equation is a very ill-conditioned and full matrix problem, the computational effort of the present iterative methods for solving such a system is comparable to that for the sparse matrix equations obtained from the application of either finite-difference or finite-element methods to the same problems. Numerical experiments are shown for a self-adjoint elliptic partial differential equation with Dirichlet boundary conditions, and comparison with other solution procedures for spectral equations is presented.

Method of thermal strain hysteresis reduction in metal matrix composites

NASA Technical Reports Server (NTRS)

Dries, Gregory A. (Inventor); Tompkins, Stephen S. (Inventor)

1987-01-01

A method is disclosed for treating graphite reinforced metal matrix composites so as to eliminate thermal strain hysteresis and impart dimensional stability through a large thermal cycle. The method is applied to the composite post fabrication and is effective on metal matrix materials using graphite fibers manufactured by both the hot roll bonding and diffusion bonding techniques. The method consists of first heat treating the material in a solution anneal oven followed by a water quench and then subjecting the material to a cryogenic treatment in a cryogenic oven. This heat treatment and cryogenic stress reflief is effective in imparting a dimensional stability and reduced thermal strain hysteresis in the material over a -250.degree. F. to +250.degree. F. thermal cycle.

Computing Fiber/Matrix Interfacial Effects In SiC/RBSN

NASA Technical Reports Server (NTRS)

Goldberg, Robert K.; Hopkins, Dale A.

1996-01-01

Computational study conducted to demonstrate use of boundary-element method in analyzing effects of fiber/matrix interface on elastic and thermal behaviors of representative laminated composite materials. In study, boundary-element method implemented by Boundary Element Solution Technology - Composite Modeling System (BEST-CMS) computer program.

Numerical solutions for Helmholtz equations using Bernoulli polynomials

NASA Astrophysics Data System (ADS)

Bicer, Kubra Erdem; Yalcinbas, Salih

2017-07-01

This paper reports a new numerical method based on Bernoulli polynomials for the solution of Helmholtz equations. The method uses matrix forms of Bernoulli polynomials and their derivatives by means of collocation points. Aim of this paper is to solve Helmholtz equations using this matrix relations.

Adaptive multi-view clustering based on nonnegative matrix factorization and pairwise co-regularization

NASA Astrophysics Data System (ADS)

Zhang, Tianzhen; Wang, Xiumei; Gao, Xinbo

2018-04-01

Nowadays, several datasets are demonstrated by multi-view, which usually include shared and complementary information. Multi-view clustering methods integrate the information of multi-view to obtain better clustering results. Nonnegative matrix factorization has become an essential and popular tool in clustering methods because of its interpretation. However, existing nonnegative matrix factorization based multi-view clustering algorithms do not consider the disagreement between views and neglects the fact that different views will have different contributions to the data distribution. In this paper, we propose a new multi-view clustering method, named adaptive multi-view clustering based on nonnegative matrix factorization and pairwise co-regularization. The proposed algorithm can obtain the parts-based representation of multi-view data by nonnegative matrix factorization. Then, pairwise co-regularization is used to measure the disagreement between views. There is only one parameter to auto learning the weight values according to the contribution of each view to data distribution. Experimental results show that the proposed algorithm outperforms several state-of-the-arts algorithms for multi-view clustering.

Local matrix learning in clustering and applications for manifold visualization.

PubMed

Arnonkijpanich, Banchar; Hasenfuss, Alexander; Hammer, Barbara

2010-05-01

Electronic data sets are increasing rapidly with respect to both, size of the data sets and data resolution, i.e. dimensionality, such that adequate data inspection and data visualization have become central issues of data mining. In this article, we present an extension of classical clustering schemes by local matrix adaptation, which allows a better representation of data by means of clusters with an arbitrary spherical shape. Unlike previous proposals, the method is derived from a global cost function. The focus of this article is to demonstrate the applicability of this matrix clustering scheme to low-dimensional data embedding for data inspection. The proposed method is based on matrix learning for neural gas and manifold charting. This provides an explicit mapping of a given high-dimensional data space to low dimensionality. We demonstrate the usefulness of this method for data inspection and manifold visualization. 2009 Elsevier Ltd. All rights reserved.

A rough set approach for determining weights of decision makers in group decision making.

PubMed

Yang, Qiang; Du, Ping-An; Wang, Yong; Liang, Bin

2017-01-01

This study aims to present a novel approach for determining the weights of decision makers (DMs) based on rough group decision in multiple attribute group decision-making (MAGDM) problems. First, we construct a rough group decision matrix from all DMs' decision matrixes on the basis of rough set theory. After that, we derive a positive ideal solution (PIS) founded on the average matrix of rough group decision, and negative ideal solutions (NISs) founded on the lower and upper limit matrixes of rough group decision. Then, we obtain the weight of each group member and priority order of alternatives by using relative closeness method, which depends on the distances from each individual group member' decision to the PIS and NISs. Through comparisons with existing methods and an on-line business manager selection example, the proposed method show that it can provide more insights into the subjectivity and vagueness of DMs' evaluations and selections.

HIGH DIMENSIONAL COVARIANCE MATRIX ESTIMATION IN APPROXIMATE FACTOR MODELS

PubMed Central

Fan, Jianqing; Liao, Yuan; Mincheva, Martina

2012-01-01

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. PMID:22661790

Google matrix analysis of directed networks

NASA Astrophysics Data System (ADS)

Ermann, Leonardo; Frahm, Klaus M.; Shepelyansky, Dima L.

2015-10-01

In the past decade modern societies have developed enormous communication and social networks. Their classification and information retrieval processing has become a formidable task for the society. Because of the rapid growth of the World Wide Web, and social and communication networks, new mathematical methods have been invented to characterize the properties of these networks in a more detailed and precise way. Various search engines extensively use such methods. It is highly important to develop new tools to classify and rank a massive amount of network information in a way that is adapted to internal network structures and characteristics. This review describes the Google matrix analysis of directed complex networks demonstrating its efficiency using various examples including the World Wide Web, Wikipedia, software architectures, world trade, social and citation networks, brain neural networks, DNA sequences, and Ulam networks. The analytical and numerical matrix methods used in this analysis originate from the fields of Markov chains, quantum chaos, and random matrix theory.

Method of azimuthally stable Mueller-matrix diagnostics of blood plasma polycrystalline films in cancer diagnostics

NASA Astrophysics Data System (ADS)

Ushenko, Yu. A.; Prysyazhnyuk, V. P.; Gavrylyak, M. S.; Gorsky, M. P.; Bachinskiy, V. T.; Vanchuliak, O. Ya.

2015-02-01

A new information optical technique of diagnostics of the structure of polycrystalline films of blood plasma is proposed. The model of Mueller-matrix description of mechanisms of optical anisotropy of such objects as optical activity, birefringence, as well as linear and circular dichroism is suggested. The ensemble of informationally topical azimuthally stable Mueller-matrix invariants is determined. Within the statistical analysis of such parameters distributions the objective criteria of differentiation of films of blood plasma taken from healthy and patients with liver cirrhosis were determined. From the point of view of probative medicine the operational characteristics (sensitivity, specificity and accuracy) of the information-optical method of Mueller-matrix mapping of polycrystalline films of blood plasma were found and its efficiency in diagnostics of liver cirrhosis was demonstrated. Prospects of application of the method in experimental medicine to differentiate postmortem changes of the myocardial tissue was examined.

Matrix Assisted Ionization Vacuum (MAIV), a New Ionization Method for Biological Materials Analysis Using Mass Spectrometry*

PubMed Central

Inutan, Ellen D.; Trimpin, Sarah

2013-01-01

The introduction of electrospray ionization (ESI) and matrix-assisted laser desorption/ionization (MALDI) for the mass spectrometric analysis of peptides and proteins had a dramatic impact on biological science. We now report that a wide variety of compounds, including peptides, proteins, and protein complexes, are transported directly from a solid-state small molecule matrix to gas-phase ions when placed into the vacuum of a mass spectrometer without the use of high voltage, a laser, or added heat. This ionization process produces ions having charge states similar to ESI, making the method applicable for high performance mass spectrometers designed for atmospheric pressure ionization. We demonstrate highly sensitive ionization using intermediate pressure MALDI and modified ESI sources. This matrix and vacuum assisted soft ionization method is suitable for the direct surface analysis of biological materials, including tissue, via mass spectrometry. PMID:23242551

A new estimation of equivalent matrix block sizes in fractured media with two-phase flow applications in dual porosity models

NASA Astrophysics Data System (ADS)

Jerbi, Chahir; Fourno, André; Noetinger, Benoit; Delay, Frederick

2017-05-01

Single and multiphase flows in fractured porous media at the scale of natural reservoirs are often handled by resorting to homogenized models that avoid the heavy computations associated with a complete discretization of both fractures and matrix blocks. For example, the two overlapping continua (fractures and matrix) of a dual porosity system are coupled by way of fluid flux exchanges that deeply condition flow at the large scale. This characteristic is a key to realistic flow simulations, especially for multiphase flow as capillary forces and contrasts of fluid mobility compete in the extraction of a fluid from a capacitive matrix then conveyed through the fractures. The exchange rate between fractures and matrix is conditioned by the so-called mean matrix block size which can be viewed as the size of a single matrix block neighboring a single fracture within a mesh of a dual porosity model. We propose a new evaluation of this matrix block size based on the analysis of discrete fracture networks. The fundaments rely upon establishing at the scale of a fractured block the equivalence between the actual fracture network and a Warren and Root network only made of three regularly spaced fracture families parallel to the facets of the fractured block. The resulting matrix block sizes are then compared via geometrical considerations and two-phase flow simulations to the few other available methods. It is shown that the new method is stable in the sense it provides accurate sizes irrespective of the type of fracture network investigated. The method also results in two-phase flow simulations from dual porosity models very close to that from references calculated in finely discretized networks. Finally, calculations of matrix block sizes by this new technique reveal very rapid, which opens the way to cumbersome applications such as preconditioning a dual porosity approach applied to regional fractured reservoirs.

A sensitive chemiluminescence enzyme immunoassay based on molecularly imprinted polymers solid-phase extraction of parathion.

PubMed

Chen, Ge; Jin, Maojun; Du, Pengfei; Zhang, Chan; Cui, Xueyan; Zhang, Yudan; She, Yongxin; Shao, Hua; Jin, Fen; Wang, Shanshan; Zheng, Lufei; Wang, Jing

2017-08-01

The chemiluminescence enzyme immunoassay (CLEIA) method responds differently to various sample matrices because of the matrix effect. In this work, the CLEIA method was coupled with molecularly imprinted polymers (MIPs) synthesized by precipitation polymerization to study the matrix effect. The sample recoveries ranged from 72.62% to 121.89%, with a relative standard deviation (RSD) of 3.74-18.14%.The ratio of the sample matrix-matched standard curve slope rate to the solvent standard curve slope was 1.21, 1.12, 1.17, and 0.85 for apple, rice, orange and cabbage in samples pretreated with the mixture of PSA and C 18 . However, the ratio of sample (apple, rice, orange, and cabbage) matrix-matched standard-MIPs curve slope rate to the solvent standard curve was 1.05, 0.92, 1.09, and 1.05 in samples pretreated with MIPs, respectively. The results demonstrated that the matrices of the samples greatly interfered with the detection of parathion residues by CLEIA. The MIPs bound specifically to the parathion in the samples and eliminated the matrix interference effect. Therefore, the CLEIA method have successfully applied MIPs in sample pretreatment to eliminate matrix interference effects and provided a new sensitive assay for agro-products. Copyright © 2017 Elsevier Inc. All rights reserved.

Reducing computational costs in large scale 3D EIT by using a sparse Jacobian matrix with block-wise CGLS reconstruction.

PubMed

Yang, C L; Wei, H Y; Adler, A; Soleimani, M

2013-06-01

Electrical impedance tomography (EIT) is a fast and cost-effective technique to provide a tomographic conductivity image of a subject from boundary current-voltage data. This paper proposes a time and memory efficient method for solving a large scale 3D EIT inverse problem using a parallel conjugate gradient (CG) algorithm. The 3D EIT system with a large number of measurement data can produce a large size of Jacobian matrix; this could cause difficulties in computer storage and the inversion process. One of challenges in 3D EIT is to decrease the reconstruction time and memory usage, at the same time retaining the image quality. Firstly, a sparse matrix reduction technique is proposed using thresholding to set very small values of the Jacobian matrix to zero. By adjusting the Jacobian matrix into a sparse format, the element with zeros would be eliminated, which results in a saving of memory requirement. Secondly, a block-wise CG method for parallel reconstruction has been developed. The proposed method has been tested using simulated data as well as experimental test samples. Sparse Jacobian with a block-wise CG enables the large scale EIT problem to be solved efficiently. Image quality measures are presented to quantify the effect of sparse matrix reduction in reconstruction results.

Effective representation of amide III, II, I, and A modes on local vibrational modes: Analysis of ab initio quantum calculation results.

PubMed

Hahn, Seungsoo

2016-10-28

The Hamiltonian matrix for the first excited vibrational states of a protein can be effectively represented by local vibrational modes constituting amide III, II, I, and A modes to simulate various vibrational spectra. Methods for obtaining the Hamiltonian matrix from ab initio quantum calculation results are discussed, where the methods consist of three steps: selection of local vibrational mode coordinates, calculation of a reduced Hessian matrix, and extraction of the Hamiltonian matrix from the Hessian matrix. We introduce several methods for each step. The methods were assessed based on the density functional theory calculation results of 24 oligopeptides with four different peptide lengths and six different secondary structures. The completeness of a Hamiltonian matrix represented in the reduced local mode space is improved by adopting a specific atom group for each amide mode and reducing the effect of ignored local modes. The calculation results are also compared to previous models using C=O stretching vibration and transition dipole couplings. We found that local electric transition dipole moments of the amide modes are mainly bound on the local peptide planes. Their direction and magnitude are well conserved except amide A modes, which show large variation. Contrary to amide I modes, the vibrational coupling constants of amide III, II, and A modes obtained by analysis of a dipeptide are not transferable to oligopeptides with the same secondary conformation because coupling constants are affected by the surrounding atomic environment.

Decomposed direct matrix inversion for fast non-cartesian SENSE reconstructions.

PubMed

Qian, Yongxian; Zhang, Zhenghui; Wang, Yi; Boada, Fernando E

2006-08-01

A new k-space direct matrix inversion (DMI) method is proposed here to accelerate non-Cartesian SENSE reconstructions. In this method a global k-space matrix equation is established on basic MRI principles, and the inverse of the global encoding matrix is found from a set of local matrix equations by taking advantage of the small extension of k-space coil maps. The DMI algorithm's efficiency is achieved by reloading the precalculated global inverse when the coil maps and trajectories remain unchanged, such as in dynamic studies. Phantom and human subject experiments were performed on a 1.5T scanner with a standard four-channel phased-array cardiac coil. Interleaved spiral trajectories were used to collect fully sampled and undersampled 3D raw data. The equivalence of the global k-space matrix equation to its image-space version, was verified via conjugate gradient (CG) iterative algorithms on a 2x undersampled phantom and numerical-model data sets. When applied to the 2x undersampled phantom and human-subject raw data, the decomposed DMI method produced images with small errors (< or = 3.9%) relative to the reference images obtained from the fully-sampled data, at a rate of 2 s per slice (excluding 4 min for precalculating the global inverse at an image size of 256 x 256). The DMI method may be useful for noise evaluations in parallel coil designs, dynamic MRI, and 3D sodium MRI with fixed coils and trajectories. Copyright 2006 Wiley-Liss, Inc.

Vast Volatility Matrix Estimation using High Frequency Data for Portfolio Selection*

PubMed Central

Fan, Jianqing; Li, Yingying; Yu, Ke

2012-01-01

Portfolio allocation with gross-exposure constraint is an effective method to increase the efficiency and stability of portfolios selection among a vast pool of assets, as demonstrated in Fan et al. (2011). The required high-dimensional volatility matrix can be estimated by using high frequency financial data. This enables us to better adapt to the local volatilities and local correlations among vast number of assets and to increase significantly the sample size for estimating the volatility matrix. This paper studies the volatility matrix estimation using high-dimensional high-frequency data from the perspective of portfolio selection. Specifically, we propose the use of “pairwise-refresh time” and “all-refresh time” methods based on the concept of “refresh time” proposed by Barndorff-Nielsen et al. (2008) for estimation of vast covariance matrix and compare their merits in the portfolio selection. We establish the concentration inequalities of the estimates, which guarantee desirable properties of the estimated volatility matrix in vast asset allocation with gross exposure constraints. Extensive numerical studies are made via carefully designed simulations. Comparing with the methods based on low frequency daily data, our methods can capture the most recent trend of the time varying volatility and correlation, hence provide more accurate guidance for the portfolio allocation in the next time period. The advantage of using high-frequency data is significant in our simulation and empirical studies, which consist of 50 simulated assets and 30 constituent stocks of Dow Jones Industrial Average index. PMID:23264708

Bioanalytical method development and validation for the determination of glycine in human cerebrospinal fluid by ion-pair reversed-phase liquid chromatography-tandem mass spectrometry.

PubMed

Jiang, Jian; James, Christopher A; Wong, Philip

2016-09-05

A LC-MS/MS method has been developed and validated for the determination of glycine in human cerebrospinal fluid (CSF). The validated method used artificial cerebrospinal fluid as a surrogate matrix for calibration standards. The calibration curve range for the assay was 100-10,000ng/mL and (13)C2, (15)N-glycine was used as an internal standard (IS). Pre-validation experiments were performed to demonstrate parallelism with surrogate matrix and standard addition methods. The mean endogenous glycine concentration in a pooled human CSF determined on three days by using artificial CSF as a surrogate matrix and the method of standard addition was found to be 748±30.6 and 768±18.1ng/mL, respectively. A percentage difference of -2.6% indicated that artificial CSF could be used as a surrogate calibration matrix for the determination of glycine in human CSF. Quality control (QC) samples, except the lower limit of quantitation (LLOQ) QC and low QC samples, were prepared by spiking glycine into aliquots of pooled human CSF sample. The low QC sample was prepared from a separate pooled human CSF sample containing low endogenous glycine concentrations, while the LLOQ QC sample was prepared in artificial CSF. Standard addition was used extensively to evaluate matrix effects during validation. The validated method was used to determine the endogenous glycine concentrations in human CSF samples. Incurred sample reanalysis demonstrated reproducibility of the method. Copyright © 2016 Elsevier B.V. All rights reserved.

Kinetics and mechanism of release from glyceryl monostearate-based implants: evaluation of release in a gel simulating in vivo implantation.

PubMed

Allababidi, S; Shah, J C

1998-06-01

The overall objective of the study was to design an implantable delivery system based on glyceryl monostearate (GMS) for the site-specific delivery of antibiotics for the prevention of surgical wound infection. To design the implant, a release method had to be developed that simulate the in vivo implantation conditions to be able to predict the release characteristics from the implants when they are actually used in vivo. Also, identifying the release kinetics and mechanism and evaluating the factors that influence the release of drugs from the GMS-based matrix were necessary to allow further design of implants that could yield a desired release rate. The release of cefazolin was monitored from GMS matrixes implanted into agar gel, simulating subcutaneous tissues with respect to viscosity and water content. The gel method resulted in observation of spatial and temporal concentration profiles in the immediate vicinity of the implants, indicating the benefits of local drug delivery; however, there was no significant difference between the cumulative release profiles by the gel method or the vial release method. The release of cefazolin from the GMS-based matrix with the vial method followed Higuchi's square root of time kinetics. The release rate was found to be directly proportional to cefazolin load (A) and the surface area (SA) of the matrix as expressed by the following equation: = 0.24ASA. On the basis of this equation, one can design a variety of GMS matrixes that would result in a desired release rate or release duration. This also indicated that cefazolin release followed the release kinetics of a freely soluble drug from an insoluble matrix and hence it is a diffusion-controlled process. The effect of drug solubility on the release kinetics was determined by comparing the release kinetics of the poorly water soluble ciprofloxacin (0.16 mg/mL) to that of the highly water soluble cefazolin (325 mg/mL). The release duration of ciprofloxacin (80 h) was longer than that of cefazolin (25 h) from identical GMS matrixes. Although ciprofloxacin release was initially controlled by the matrix, agitation accelerated disintegration of the matrix and release due to its poor solubility, and ciprofloxacin release appeared to be a dissolution-controlled process following zero-order release kinetics.

Solid matrix transformation and tracer addition using molten ammonium bifluoride salt as a sample preparation method for laser ablation inductively coupled plasma mass spectrometry.

PubMed

Grate, Jay W; Gonzalez, Jhanis J; O'Hara, Matthew J; Kellogg, Cynthia M; Morrison, Samuel S; Koppenaal, David W; Chan, George C-Y; Mao, Xianglei; Zorba, Vassilia; Russo, Richard E

2017-09-08

Solid sampling and analysis methods, such as laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS), are challenged by matrix effects and calibration difficulties. Matrix-matched standards for external calibration are seldom available and it is difficult to distribute spikes evenly into a solid matrix as internal standards. While isotopic ratios of the same element can be measured to high precision, matrix-dependent effects in the sampling and analysis process frustrate accurate quantification and elemental ratio determinations. Here we introduce a potentially general solid matrix transformation approach entailing chemical reactions in molten ammonium bifluoride (ABF) salt that enables the introduction of spikes as tracers or internal standards. Proof of principle experiments show that the decomposition of uranium ore in sealed PFA fluoropolymer vials at 230 °C yields, after cooling, new solids suitable for direct solid sampling by LA. When spikes are included in the molten salt reaction, subsequent LA-ICP-MS sampling at several spots indicate that the spikes are evenly distributed, and that U-235 tracer dramatically improves reproducibility in U-238 analysis. Precisions improved from 17% relative standard deviation for U-238 signals to 0.1% for the ratio of sample U-238 to spiked U-235, a factor of over two orders of magnitude. These results introduce the concept of solid matrix transformation (SMT) using ABF, and provide proof of principle for a new method of incorporating internal standards into a solid for LA-ICP-MS. This new approach, SMT-LA-ICP-MS, provides opportunities to improve calibration and quantification in solids based analysis. Looking forward, tracer addition to transformed solids opens up LA-based methods to analytical methodologies such as standard addition, isotope dilution, preparation of matrix-matched solid standards, external calibration, and monitoring instrument drift against external calibration standards.

An on-line calibration algorithm for external parameters of visual system based on binocular stereo cameras

NASA Astrophysics Data System (ADS)

Wang, Liqiang; Liu, Zhen; Zhang, Zhonghua

2014-11-01

Stereo vision is the key in the visual measurement, robot vision, and autonomous navigation. Before performing the system of stereo vision, it needs to calibrate the intrinsic parameters for each camera and the external parameters of the system. In engineering, the intrinsic parameters remain unchanged after calibrating cameras, and the positional relationship between the cameras could be changed because of vibration, knocks and pressures in the vicinity of the railway or motor workshops. Especially for large baselines, even minute changes in translation or rotation can affect the epipolar geometry and scene triangulation to such a degree that visual system becomes disabled. A technology including both real-time examination and on-line recalibration for the external parameters of stereo system becomes particularly important. This paper presents an on-line method for checking and recalibrating the positional relationship between stereo cameras. In epipolar geometry, the external parameters of cameras can be obtained by factorization of the fundamental matrix. Thus, it offers a method to calculate the external camera parameters without any special targets. If the intrinsic camera parameters are known, the external parameters of system can be calculated via a number of random matched points. The process is: (i) estimating the fundamental matrix via the feature point correspondences; (ii) computing the essential matrix from the fundamental matrix; (iii) obtaining the external parameters by decomposition of the essential matrix. In the step of computing the fundamental matrix, the traditional methods are sensitive to noise and cannot ensure the estimation accuracy. We consider the feature distribution situation in the actual scene images and introduce a regional weighted normalization algorithm to improve accuracy of the fundamental matrix estimation. In contrast to traditional algorithms, experiments on simulated data prove that the method improves estimation robustness and accuracy of the fundamental matrix. Finally, we take an experiment for computing the relationship of a pair of stereo cameras to demonstrate accurate performance of the algorithm.

Inter-class sparsity based discriminative least square regression.

PubMed

Wen, Jie; Xu, Yong; Li, Zuoyong; Ma, Zhongli; Xu, Yuanrong

2018-06-01

Least square regression is a very popular supervised classification method. However, two main issues greatly limit its performance. The first one is that it only focuses on fitting the input features to the corresponding output labels while ignoring the correlations among samples. The second one is that the used label matrix, i.e., zero-one label matrix is inappropriate for classification. To solve these problems and improve the performance, this paper presents a novel method, i.e., inter-class sparsity based discriminative least square regression (ICS_DLSR), for multi-class classification. Different from other methods, the proposed method pursues that the transformed samples have a common sparsity structure in each class. For this goal, an inter-class sparsity constraint is introduced to the least square regression model such that the margins of samples from the same class can be greatly reduced while those of samples from different classes can be enlarged. In addition, an error term with row-sparsity constraint is introduced to relax the strict zero-one label matrix, which allows the method to be more flexible in learning the discriminative transformation matrix. These factors encourage the method to learn a more compact and discriminative transformation for regression and thus has the potential to perform better than other methods. Extensive experimental results show that the proposed method achieves the best performance in comparison with other methods for multi-class classification. Copyright © 2018 Elsevier Ltd. All rights reserved.

Density matrix renormalization group with efficient dynamical electron correlation through range separation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hedegård, Erik Donovan, E-mail: erik.hedegard@phys.chem.ethz.ch; Knecht, Stefan; Reiher, Markus, E-mail: markus.reiher@phys.chem.ethz.ch

2015-06-14

We present a new hybrid multiconfigurational method based on the concept of range-separation that combines the density matrix renormalization group approach with density functional theory. This new method is designed for the simultaneous description of dynamical and static electron-correlation effects in multiconfigurational electronic structure problems.

More on Chemical Reaction Balancing.

ERIC Educational Resources Information Center

Swinehart, D. F.

1985-01-01

A previous article stated that only the matrix method was powerful enough to balance a particular chemical equation. Shows how this equation can be balanced without using the matrix method. The approach taken involves writing partial mathematical reactions and redox half-reactions, and combining them to yield the final balanced reaction. (JN)

Influence of the intramedullary nail preparation method on nail's mechanical properties and degradation rate.

PubMed

Morawska-Chochół, Anna; Chłopek, Jan; Szaraniec, Barbara; Domalik-Pyzik, Patrycja; Balacha, Ewa; Boguń, Maciej; Kucharski, Rafael

2015-06-01

When it comes to the treatment of long bone fractures, scientists are still investigating new materials for intramedullary nails and different manufacturing methods. Some of the most promising materials used in the field are resorbable polymers and their composites, especially since there is a wide range of potential manufacturing and processing methods. The aim of this work was to select the best manufacturing method and technological parameters to obtain multiphase, and multifunctional, biodegradable intramedullary nails. All composites were based on a poly(l-lactide) matrix. Either magnesium alloy wires or carbon and alginate fibres were introduced in order to reinforce the nails. The polylactide matrix was also modified with tricalcium phosphate and gentamicin sulfate. The composite nails were manufactured using three different methods: forming from solution, injection moulding and hot pressing. The effect of each method of manufacturing on mechanical properties and degradation rate of the nails was evaluated. The study showed that injection moulding provides higher uniformity and homogeneity of the particle-modified polylactide matrix, whereas hot pressing favours applying higher volume fractions of fibres and their better impregnation with the polymer matrix. Thus, it was concluded that the fabrication method should be individually selected dependently on the nail's desired phase composition. Copyright © 2015 Elsevier B.V. All rights reserved.

Deghosting based on the transmission matrix method

NASA Astrophysics Data System (ADS)

Wang, Benfeng; Wu, Ru-Shan; Chen, Xiaohong

2017-12-01

As the developments of seismic exploration and subsequent seismic exploitation advance, marine acquisition systems with towed streamers become an important seismic data acquisition method. But the existing air-water reflective interface can generate surface related multiples, including ghosts, which can affect the accuracy and performance of the following seismic data processing algorithms. Thus, we derive a deghosting method from a new perspective, i.e. using the transmission matrix (T-matrix) method instead of inverse scattering series. The T-matrix-based deghosting algorithm includes all scattering effects and is convergent absolutely. Initially, the effectiveness of the proposed method is demonstrated using synthetic data obtained from a designed layered model, and its noise-resistant property is also illustrated using noisy synthetic data contaminated by random noise. Numerical examples on complicated data from the open SMAART Pluto model and field marine data further demonstrate the validity and flexibility of the proposed method. After deghosting, low frequency components are recovered reasonably and the fake high frequency components are attenuated, and the recovered low frequency components will be useful for the subsequent full waveform inversion. The proposed deghosting method is currently suitable for two-dimensional towed streamer cases with accurate constant depth information and its extension into variable-depth streamers in three-dimensional cases will be studied in the future.

Matrix-free and material-enhanced laser desorption/ionization mass spectrometry for the analysis of low molecular weight compounds.

PubMed

Rainer, Matthias; Qureshi, Muhammad Nasimullah; Bonn, Günther Karl

2011-06-01

The application of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS) for the analysis of low molecular weight (LMW) compounds, such as pharmacologically active constituents or metabolites, is usually hampered by employing conventional MALDI matrices owing to interferences caused by matrix molecules below 700 Da. As a consequence, interpretation of mass spectra remains challenging, although matrix suppression can be achieved under certain conditions. Unlike the conventional MALDI methods which usually suffer from background signals, matrix-free techniques have become more and more popular for the analysis of LMW compounds. In this review we describe recently introduced materials for laser desorption/ionization (LDI) as alternatives to conventionally applied MALDI matrices. In particular, we want to highlight a new method for LDI which is referred to as matrix-free material-enhanced LDI (MELDI). In matrix-free MELDI it could be clearly shown, that besides chemical functionalities, the material's morphology plays a crucial role regarding energy-transfer capabilities. Therefore, it is of great interest to also investigate parameters such as particle size and porosity to study their impact on the LDI process. Especially nanomaterials such as diamond-like carbon, C(60) fullerenes and nanoparticulate silica beads were found to be excellent energy-absorbing materials in matrix-free MELDI.

Extension of modified power method to two-dimensional problems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Peng; Ulsan National Institute of Science and Technology, 50 UNIST-gil, Ulsan 44919; Lee, Hyunsuk

2016-09-01

In this study, the generalized modified power method was extended to two-dimensional problems. A direct application of the method to two-dimensional problems was shown to be unstable when the number of requested eigenmodes is larger than a certain problem dependent number. The root cause of this instability has been identified as the degeneracy of the transfer matrix. In order to resolve this instability, the number of sub-regions for the transfer matrix was increased to be larger than the number of requested eigenmodes; and a new transfer matrix was introduced accordingly which can be calculated by the least square method. Themore » stability of the new method has been successfully demonstrated with a neutron diffusion eigenvalue problem and the 2D C5G7 benchmark problem. - Graphical abstract:.« less

On the Feynman-Hellmann theorem in quantum field theory and the calculation of matrix elements

DOE PAGES

Bouchard, Chris; Chang, Chia Cheng; Kurth, Thorsten; ...

2017-07-12

In this paper, the Feynman-Hellmann theorem can be derived from the long Euclidean-time limit of correlation functions determined with functional derivatives of the partition function. Using this insight, we fully develop an improved method for computing matrix elements of external currents utilizing only two-point correlation functions. Our method applies to matrix elements of any external bilinear current, including nonzero momentum transfer, flavor-changing, and two or more current insertion matrix elements. The ability to identify and control all the systematic uncertainties in the analysis of the correlation functions stems from the unique time dependence of the ground-state matrix elements and the fact that all excited states and contact terms are Euclidean-time dependent. We demonstrate the utility of our method with a calculation of the nucleon axial charge using gradient-flowed domain-wall valence quarks on themore » $$N_f=2+1+1$$ MILC highly improved staggered quark ensemble with lattice spacing and pion mass of approximately 0.15 fm and 310 MeV respectively. We show full control over excited-state systematics with the new method and obtain a value of $$g_A = 1.213(26)$$ with a quark-mass-dependent renormalization coefficient.« less

Prevention of accidental exposure in radiotherapy: the risk matrix approach.

PubMed

Vilaragut, J J; Duménigo, C; Delgado, J M; Morales, J; McDonnell, J D; Ferro, R; Ortiz López, P; Ramírez, M L; Pérez Mulas, A; Papadopulos, S; Gonçalves, M; López Morones, R; Sánchez Cayuela, C; Cascajo Castresana, A; Somoano, F; Álvarez, C; Guillén, A; Rodríguez, M; Pereira, P P; Nader, A

2013-02-01

Knowledge and lessons from past accidental exposures in radiotherapy are very helpful in finding safety provisions to prevent recurrence. Disseminating lessons is necessary but not sufficient. There may be additional latent risks for other accidental exposures, which have not been reported or have not occurred, but are possible and may occur in the future if not identified, analyzed, and prevented by safety provisions. Proactive methods are available for anticipating and quantifying risk from potential event sequences. In this work, proactive methods, successfully used in industry, have been adapted and used in radiotherapy. Risk matrix is a tool that can be used in individual hospitals to classify event sequences in levels of risk. As with any anticipative method, the risk matrix involves a systematic search for potential risks; that is, any situation that can cause an accidental exposure. The method contributes new insights: The application of the risk matrix approach has identified that another group of less catastrophic but still severe single-patient events may have a higher probability, resulting in higher risk. The use of the risk matrix approach for safety assessment in individual hospitals would provide an opportunity for self-evaluation and managing the safety measures that are most suitable to the hospital's own conditions.

Hybrid method (JM-ECS) combining the J-matrix and exterior complex scaling methods for scattering calculations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vanroose, W.; Broeckhove, J.; Arickx, F.

The paper proposes a hybrid method for calculating scattering processes. It combines the J-matrix method with exterior complex scaling and an absorbing boundary condition. The wave function is represented as a finite sum of oscillator eigenstates in the inner region, and it is discretized on a grid in the outer region. The method is validated for a one- and a two-dimensional model with partial wave equations and a calculation of p-shell nuclear scattering with semirealistic interactions.

Affine Projection Algorithm with Improved Data-Selective Method Using the Condition Number

NASA Astrophysics Data System (ADS)

Ban, Sung Jun; Lee, Chang Woo; Kim, Sang Woo

Recently, a data-selective method has been proposed to achieve low misalignment in affine projection algorithm (APA) by keeping the condition number of an input data matrix small. We present an improved method, and a complexity reduction algorithm for the APA with the data-selective method. Experimental results show that the proposed algorithm has lower misalignment and a lower condition number for an input data matrix than both the conventional APA and the APA with the previous data-selective method.

Printing three-dimensional tissue analogues with decellularized extracellular matrix bioink

PubMed Central

Pati, Falguni; Jang, Jinah; Ha, Dong-Heon; Won Kim, Sung; Rhie, Jong-Won; Shim, Jin-Hyung; Kim, Deok-Ho; Cho, Dong-Woo

2014-01-01

The ability to print and pattern all the components that make up a tissue (cells and matrix materials) in three dimensions to generate structures similar to tissues is an exciting prospect of bioprinting. However, the majority of the matrix materials used so far for bioprinting cannot represent the complexity of natural extracellular matrix (ECM) and thus are unable to reconstitute the intrinsic cellular morphologies and functions. Here, we develop a method for the bioprinting of cell-laden constructs with novel decellularized extracellular matrix (dECM) bioink capable of providing an optimized microenvironment conducive to the growth of three-dimensional structured tissue. We show the versatility and flexibility of the developed bioprinting process using tissue-specific dECM bioinks, including adipose, cartilage and heart tissues, capable of providing crucial cues for cells engraftment, survival and long-term function. We achieve high cell viability and functionality of the printed dECM structures using our bioprinting method. PMID:24887553

Stochastic determination of matrix determinants

NASA Astrophysics Data System (ADS)

Dorn, Sebastian; Enßlin, Torsten A.

2015-07-01

Matrix determinants play an important role in data analysis, in particular when Gaussian processes are involved. Due to currently exploding data volumes, linear operations—matrices—acting on the data are often not accessible directly but are only represented indirectly in form of a computer routine. Such a routine implements the transformation a data vector undergoes under matrix multiplication. While efficient probing routines to estimate a matrix's diagonal or trace, based solely on such computationally affordable matrix-vector multiplications, are well known and frequently used in signal inference, there is no stochastic estimate for its determinant. We introduce a probing method for the logarithm of a determinant of a linear operator. Our method rests upon a reformulation of the log-determinant by an integral representation and the transformation of the involved terms into stochastic expressions. This stochastic determinant determination enables large-size applications in Bayesian inference, in particular evidence calculations, model comparison, and posterior determination.

Direct Solve of Electrically Large Integral Equations for Problem Sizes to 1M Unknowns

NASA Technical Reports Server (NTRS)

Shaeffer, John

2008-01-01

Matrix methods for solving integral equations via direct solve LU factorization are presently limited to weeks to months of very expensive supercomputer time for problems sizes of several hundred thousand unknowns. This report presents matrix LU factor solutions for electromagnetic scattering problems for problem sizes to one million unknowns with thousands of right hand sides that run in mere days on PC level hardware. This EM solution is accomplished by utilizing the numerical low rank nature of spatially blocked unknowns using the Adaptive Cross Approximation for compressing the rank deficient blocks of the system Z matrix, the L and U factors, the right hand side forcing function and the final current solution. This compressed matrix solution is applied to a frequency domain EM solution of Maxwell's equations using standard Method of Moments approach. Compressed matrix storage and operations count leads to orders of magnitude reduction in memory and run time.

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

PubMed

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.

Characteristic Analysis on UAV-MIMO Channel Based on Normalized Correlation Matrix

PubMed Central

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

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. PMID:24977185

Constructing service-oriented architecture adoption maturity matrix using Kano model

NASA Astrophysics Data System (ADS)

Hamzah, Mohd Hamdi Irwan; Baharom, Fauziah; Mohd, Haslina

2017-10-01

Commonly, organizations adopted Service-Oriented Architecture (SOA) because it can provide a flexible reconfiguration and can reduce the development time and cost. In order to guide the SOA adoption, previous industry and academia have constructed SOA maturity model. However, there is a limited number of works on how to construct the matrix in the previous SOA maturity model. Therefore, this study is going to provide a method that can be used in order to construct the matrix in the SOA maturity model. This study adapts Kano Model to construct the cross evaluation matrix focused on SOA adoption IT and business benefits. This study found that Kano Model can provide a suitable and appropriate method for constructing the cross evaluation matrix in SOA maturity model. Kano model also can be used to plot, organize and better represent the evaluation dimension for evaluating the SOA adoption.

Printing three-dimensional tissue analogues with decellularized extracellular matrix bioink

NASA Astrophysics Data System (ADS)

Pati, Falguni; Jang, Jinah; Ha, Dong-Heon; Won Kim, Sung; Rhie, Jong-Won; Shim, Jin-Hyung; Kim, Deok-Ho; Cho, Dong-Woo

2014-06-01

The ability to print and pattern all the components that make up a tissue (cells and matrix materials) in three dimensions to generate structures similar to tissues is an exciting prospect of bioprinting. However, the majority of the matrix materials used so far for bioprinting cannot represent the complexity of natural extracellular matrix (ECM) and thus are unable to reconstitute the intrinsic cellular morphologies and functions. Here, we develop a method for the bioprinting of cell-laden constructs with novel decellularized extracellular matrix (dECM) bioink capable of providing an optimized microenvironment conducive to the growth of three-dimensional structured tissue. We show the versatility and flexibility of the developed bioprinting process using tissue-specific dECM bioinks, including adipose, cartilage and heart tissues, capable of providing crucial cues for cells engraftment, survival and long-term function. We achieve high cell viability and functionality of the printed dECM structures using our bioprinting method.

Stochastic determination of matrix determinants.

PubMed

Dorn, Sebastian; Ensslin, Torsten A

2015-07-01

Matrix determinants play an important role in data analysis, in particular when Gaussian processes are involved. Due to currently exploding data volumes, linear operations-matrices-acting on the data are often not accessible directly but are only represented indirectly in form of a computer routine. Such a routine implements the transformation a data vector undergoes under matrix multiplication. While efficient probing routines to estimate a matrix's diagonal or trace, based solely on such computationally affordable matrix-vector multiplications, are well known and frequently used in signal inference, there is no stochastic estimate for its determinant. We introduce a probing method for the logarithm of a determinant of a linear operator. Our method rests upon a reformulation of the log-determinant by an integral representation and the transformation of the involved terms into stochastic expressions. This stochastic determinant determination enables large-size applications in Bayesian inference, in particular evidence calculations, model comparison, and posterior determination.

Multi-energy CT based on a prior rank, intensity and sparsity model (PRISM).

PubMed

Gao, Hao; Yu, Hengyong; Osher, Stanley; Wang, Ge

2011-11-01

We propose a compressive sensing approach for multi-energy computed tomography (CT), namely the prior rank, intensity and sparsity model (PRISM). To further compress the multi-energy image for allowing the reconstruction with fewer CT data and less radiation dose, the PRISM models a multi-energy image as the superposition of a low-rank matrix and a sparse matrix (with row dimension in space and column dimension in energy), where the low-rank matrix corresponds to the stationary background over energy that has a low matrix rank, and the sparse matrix represents the rest of distinct spectral features that are often sparse. Distinct from previous methods, the PRISM utilizes the generalized rank, e.g., the matrix rank of tight-frame transform of a multi-energy image, which offers a way to characterize the multi-level and multi-filtered image coherence across the energy spectrum. Besides, the energy-dependent intensity information can be incorporated into the PRISM in terms of the spectral curves for base materials, with which the restoration of the multi-energy image becomes the reconstruction of the energy-independent material composition matrix. In other words, the PRISM utilizes prior knowledge on the generalized rank and sparsity of a multi-energy image, and intensity/spectral characteristics of base materials. Furthermore, we develop an accurate and fast split Bregman method for the PRISM and demonstrate the superior performance of the PRISM relative to several competing methods in simulations.

Ex Vivo Growth of Bioengineered Ligaments and Other Tissues

NASA Technical Reports Server (NTRS)

Altman, Gregory; Kaplan, David L.; Martin, Ivan; Vunjak-Novakovic, Gordana

2005-01-01

A method of growing bioengineered tissues for use in surgical replacement of damaged anterior cruciate ligaments has been invented. An anterior cruciate ligament is one of two ligaments (the other being the posterior cruciate ligament) that cross in the middle of a knee joint and act to prevent the bones in the knee from sliding forward and backward relative to each other. Anterior cruciate ligaments are frequently torn in sports injuries and traffic accidents, resulting in pain and severe limitations on mobility. By making it possible to grow replacement anterior cruciate ligaments that structurally and functionally resemble natural ones more closely than do totally synthetic replacements, the method could create new opportunities for full or nearly full restoration of functionality in injured knees. The method is also adaptable to the growth of bioengineered replacements for other ligaments (e.g., other knee ligaments as well as those in the hands, wrists, and elbows) and to the production of tissues other than ligaments, including cartilage, bones, muscles, and blood vessels. The method is based on the finding that the histomorphological properties of a bioengineered tissue grown in vitro from pluripotent cells within a matrix are affected by the direct application of mechanical force to the matrix during growth generation. This finding provides important new insights into the relationships among mechanical stress, biochemical and cell-immobilization methods, and cell differentiation, and is applicable to the production of the variety of tissues mentioned above. Moreover, this finding can be generalized to nonmechanical (e.g., chemical and electromagnetic) stimuli that are experienced in vivo by tissues of interest and, hence, the method can be modified to incorporate such stimuli in the ex vivo growth of replacements for the various tissues mentioned above. In this method, a three-dimensional matrix made of a suitable material is seeded with pluripotent stem cells. The patient s bone-marrow stromal cells are preferably used as the pluripotent cells in this method. Suitable matrix materials are materials to which cells can adhere for example, collagen type I. The seeded matrix is attached to anchors at opposite ends and then the cells in the matrix are cultured under conditions appropriate for the growth and regeneration of cells. Suitable anchor materials are materials to which the matrix can attach; examples include demineralized bone and Goinopra coral that has been treated to convert its calcium carbonate to calcium phosphate.

Real-Time Parameter Estimation Method Applied to a MIMO Process and its Comparison with an Offline Identification Method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kaplanoglu, Erkan; Safak, Koray K.; Varol, H. Selcuk

2009-01-12

An experiment based method is proposed for parameter estimation of a class of linear multivariable systems. The method was applied to a pressure-level control process. Experimental time domain input/output data was utilized in a gray-box modeling approach. Prior knowledge of the form of the system transfer function matrix elements is assumed to be known. Continuous-time system transfer function matrix parameters were estimated in real-time by the least-squares method. Simulation results of experimentally determined system transfer function matrix compare very well with the experimental results. For comparison and as an alternative to the proposed real-time estimation method, we also implemented anmore » offline identification method using artificial neural networks and obtained fairly good results. The proposed methods can be implemented conveniently on a desktop PC equipped with a data acquisition board for parameter estimation of moderately complex linear multivariable systems.« less

Quantization of an electromagnetic field in two-dimensional photonic structures based on the scattering matrix formalism ( S-quantization)

NASA Astrophysics Data System (ADS)

Ivanov, K. A.; Nikolaev, V. V.; Gubaydullin, A. R.; Kaliteevski, M. A.

2017-10-01

Based on the scattering matrix formalism, we have developed a method of quantization of an electromagnetic field in two-dimensional photonic nanostructures ( S-quantization in the two-dimensional case). In this method, the fields at the boundaries of the quantization box are expanded into a Fourier series and are related with each other by the scattering matrix of the system, which is the product of matrices describing the propagation of plane waves in empty regions of the quantization box and the scattering matrix of the photonic structure (or an arbitrary inhomogeneity). The quantization condition (similarly to the onedimensional case) is formulated as follows: the eigenvalues of the scattering matrix are equal to unity, which corresponds to the fact that the set of waves that are incident on the structure (components of the expansion into the Fourier series) is equal to the set of waves that travel away from the structure (outgoing waves). The coefficients of the matrix of scattering through the inhomogeneous structure have been calculated using the following procedure: the structure is divided into parallel layers such that the permittivity in each layer varies only along the axis that is perpendicular to the layers. Using the Fourier transform, the Maxwell equations have been written in the form of a matrix that relates the Fourier components of the electric field at the boundaries of neighboring layers. The product of these matrices is the transfer matrix in the basis of the Fourier components of the electric field. Represented in a block form, it is composed by matrices that contain the reflection and transmission coefficients for the Fourier components of the field, which, in turn, constitute the scattering matrix. The developed method considerably simplifies the calculation scheme for the analysis of the behavior of the electromagnetic field in structures with a two-dimensional inhomogeneity. In addition, this method makes it possible to obviate difficulties that arise in the analysis of the Purcell effect because of the divergence of the integral describing the effective volume of the mode in open systems.

Case studies: the impact of nonanalyte components on LC-MS/MS-based bioanalysis: strategies for identifying and overcoming matrix effects.

PubMed

Li, Fumin; Ewles, Matthew; Pelzer, Mary; Brus, Theodore; Ledvina, Aaron; Gray, Nicholas; Koupaei-Abyazani, Mohammad; Blackburn, Michael

2013-10-01

Achieving sufficient selectivity in bioanalysis is critical to ensure accurate quantitation of drugs and metabolites in biological matrices. Matrix effects most classically refer to modification of ionization efficiency of an analyte in the presence of matrix components. However, nonanalyte or matrix components present in samples can adversely impact the performance of a bioanalytical method and are broadly considered as matrix effects. For the current manuscript, we expand the scope to include matrix elements that contribute to isobaric interference and measurement bias. These three categories of matrix effects are illustrated with real examples encountered. The causes, symptoms, and suggested strategies and resolutions for each form of matrix effects are discussed. Each case is presented in the format of situation/action/result to facilitate reading.

Interval-valued intuitionistic fuzzy matrix games based on Archimedean t-conorm and t-norm

NASA Astrophysics Data System (ADS)

Xia, Meimei

2018-04-01

Fuzzy game theory has been applied in many decision-making problems. The matrix game with interval-valued intuitionistic fuzzy numbers (IVIFNs) is investigated based on Archimedean t-conorm and t-norm. The existing matrix games with IVIFNs are all based on Algebraic t-conorm and t-norm, which are special cases of Archimedean t-conorm and t-norm. In this paper, the intuitionistic fuzzy aggregation operators based on Archimedean t-conorm and t-norm are employed to aggregate the payoffs of players. To derive the solution of the matrix game with IVIFNs, several mathematical programming models are developed based on Archimedean t-conorm and t-norm. The proposed models can be transformed into a pair of primal-dual linear programming models, based on which, the solution of the matrix game with IVIFNs is obtained. It is proved that the theorems being valid in the exiting matrix game with IVIFNs are still true when the general aggregation operator is used in the proposed matrix game with IVIFNs. The proposed method is an extension of the existing ones and can provide more choices for players. An example is given to illustrate the validity and the applicability of the proposed method.

A novel image encryption algorithm based on the chaotic system and DNA computing

NASA Astrophysics Data System (ADS)

Chai, Xiuli; Gan, Zhihua; Lu, Yang; Chen, Yiran; Han, Daojun

A novel image encryption algorithm using the chaotic system and deoxyribonucleic acid (DNA) computing is presented. Different from the traditional encryption methods, the permutation and diffusion of our method are manipulated on the 3D DNA matrix. Firstly, a 3D DNA matrix is obtained through bit plane splitting, bit plane recombination, DNA encoding of the plain image. Secondly, 3D DNA level permutation based on position sequence group (3DDNALPBPSG) is introduced, and chaotic sequences generated from the chaotic system are employed to permutate the positions of the elements of the 3D DNA matrix. Thirdly, 3D DNA level diffusion (3DDNALD) is given, the confused 3D DNA matrix is split into sub-blocks, and XOR operation by block is manipulated to the sub-DNA matrix and the key DNA matrix from the chaotic system. At last, by decoding the diffused DNA matrix, we get the cipher image. SHA 256 hash of the plain image is employed to calculate the initial values of the chaotic system to avoid chosen plaintext attack. Experimental results and security analyses show that our scheme is secure against several known attacks, and it can effectively protect the security of the images.

Multiscale Modeling of Ceramic Matrix Composites

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.; Mital, Subodh K.; Pineda, Evan J.; Arnold, Steven M.

2015-01-01

Results of multiscale modeling simulations of the nonlinear response of SiC/SiC ceramic matrix composites are reported, wherein the microstructure of the ceramic matrix is captured. This micro scale architecture, which contains free Si material as well as the SiC ceramic, is responsible for residual stresses that play an important role in the subsequent thermo-mechanical behavior of the SiC/SiC composite. Using the novel Multiscale Generalized Method of Cells recursive micromechanics theory, the microstructure of the matrix, as well as the microstructure of the composite (fiber and matrix) can be captured.

On the Daubechies-based wavelet differentiation matrix

NASA Technical Reports Server (NTRS)

Jameson, Leland

1993-01-01

The differentiation matrix for a Daubechies-based wavelet basis is constructed and superconvergence is proven. That is, it will be proven that under the assumption of periodic boundary conditions that the differentiation matrix is accurate of order 2M, even though the approximation subspace can represent exactly only polynomials up to degree M-1, where M is the number of vanishing moments of the associated wavelet. It is illustrated that Daubechies-based wavelet methods are equivalent to finite difference methods with grid refinement in regions of the domain where small-scale structure is present.

Double ionization in R -matrix theory using a two-electron outer region

NASA Astrophysics Data System (ADS)

Wragg, Jack; Parker, J. S.; van der Hart, H. W.

2015-08-01

We have developed a two-electron outer region for use within R -matrix theory to describe double ionization processes. The capability of this method is demonstrated for single-photon double ionization of He in the photon energy region between 80 and 180 eV. The cross sections are in agreement with established data. The extended R -matrix with time dependence method also provides information on higher-order processes, as demonstrated by the identification of signatures for sequential double ionization processes involving an intermediate He+ state with n =2 .

New method for propagating the square root covariance matrix in triangular form. [using Kalman-Bucy filter

NASA Technical Reports Server (NTRS)

Choe, C. Y.; Tapley, B. D.

1975-01-01

A method proposed by Potter of applying the Kalman-Bucy filter to the problem of estimating the state of a dynamic system is described, in which the square root of the state error covariance matrix is used to process the observations. A new technique which propagates the covariance square root matrix in lower triangular form is given for the discrete observation case. The technique is faster than previously proposed algorithms and is well-adapted for use with the Carlson square root measurement algorithm.

As-received microstructure of a SiC/Ti-15-3 composite

NASA Technical Reports Server (NTRS)

Lerch, Bradley A.; Hull, David R.; Leonhardt, Todd A.

1988-01-01

A silicon carbide fiber reinforced titanium (Ti-15V-3Cr-3Sn-3Al) composite is metallographically examined. Several methods for examining composite materials are investigated and documented. Polishing techniques for this material are described. An interference layering method is developed to reveal the structure of the fiber, the reaction zone, and various phases within the matrix. Microprobe and transmission electron microscope (TEM) analyses are performed on the fiber/matrix interface. A detailed description of the fiber distribution as well as the microstructure of the fiber and matrix are presented.

Method of forming fluorine-bearing diamond layer on substrates, including tool substrates

DOEpatents

Chang, R. P. H.; Grannen, Kevin J.

2002-01-01

A method of forming a fluorine-bearing diamond layer on non-diamond substrates, especially on tool substrates comprising a metal matrix and hard particles, such as tungsten carbide particles, in the metal matrix. The substrate and a fluorine-bearing plasma or other gas are then contacted under temperature and pressure conditions effective to nucleate fluorine-bearing diamond on the substrate. A tool insert substrate is treated prior to the diamond nucleation and growth operation by etching both the metal matrix and the hard particles using suitable etchants.

Thermal Diffusivity and Conductivity in Ceramic Matrix Fiber Composite Materials - Literature Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

R.G. Quinn

A technical literature review was conducted to gain an understanding of the state of the art method, problems, results, and future of thermal diffusivity/conductivity of matrix-fiber composites for high temperature applications. This paper summarizes the results of test method development and theory. Results from testing on various sample types are discussed with concentration on the anisotropic characteristics of matrix-fiber composites, barriers to heat flow, and notable microstructure observations. The conclusion presents some observations from the technical literature, drawbacks of current information and discusses potential needs for future testing.

Comprehensive T-Matrix Reference Database: A 2012 - 2013 Update

NASA Technical Reports Server (NTRS)

Mishchenko, Michael I.; Videen, Gorden; Khlebtsov, Nikolai G.; Wriedt, Thomas

2013-01-01

The T-matrix method is one of the most versatile, efficient, and accurate theoretical techniques widely used for numerically exact computer calculations of electromagnetic scattering by single and composite particles, discrete random media, and particles imbedded in complex environments. This paper presents the fifth update to the comprehensive database of peer-reviewed T-matrix publications initiated by us in 2004 and includes relevant publications that have appeared since 2012. It also lists several earlier publications not incorporated in the original database, including Peter Waterman's reports from the 1960s illustrating the history of the T-matrix approach and demonstrating that John Fikioris and Peter Waterman were the true pioneers of the multi-sphere method otherwise known as the generalized Lorenz - Mie theory.

A comparison of companion matrix methods to find roots of a trigonometric polynomial

NASA Astrophysics Data System (ADS)

Boyd, John P.

2013-08-01

A trigonometric polynomial is a truncated Fourier series of the form fN(t)≡∑j=0Naj cos(jt)+∑j=1N bj sin(jt). It has been previously shown by the author that zeros of such a polynomial can be computed as the eigenvalues of a companion matrix with elements which are complex valued combinations of the Fourier coefficients, the "CCM" method. However, previous work provided no examples, so one goal of this new work is to experimentally test the CCM method. A second goal is introduce a new alternative, the elimination/Chebyshev algorithm, and experimentally compare it with the CCM scheme. The elimination/Chebyshev matrix (ECM) algorithm yields a companion matrix with real-valued elements, albeit at the price of usefulness only for real roots. The new elimination scheme first converts the trigonometric rootfinding problem to a pair of polynomial equations in the variables (c,s) where c≡cos(t) and s≡sin(t). The elimination method next reduces the system to a single univariate polynomial P(c). We show that this same polynomial is the resultant of the system and is also a generator of the Groebner basis with lexicographic ordering for the system. Both methods give very high numerical accuracy for real-valued roots, typically at least 11 decimal places in Matlab/IEEE 754 16 digit floating point arithmetic. The CCM algorithm is typically one or two decimal places more accurate, though these differences disappear if the roots are "Newton-polished" by a single Newton's iteration. The complex-valued matrix is accurate for complex-valued roots, too, though accuracy decreases with the magnitude of the imaginary part of the root. The cost of both methods scales as O(N3) floating point operations. In spite of intimate connections of the elimination/Chebyshev scheme to two well-established technologies for solving systems of equations, resultants and Groebner bases, and the advantages of using only real-valued arithmetic to obtain a companion matrix with real-valued elements, the ECM algorithm is noticeably inferior to the complex-valued companion matrix in simplicity, ease of programming, and accuracy.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Garn, Troy G; Law, Jack D; Greenhalgh, Mitchell R

A composite media including at least one crystalline aluminosilicate material in polyacrylonitrile. A method of forming a composite media is also disclosed. The method comprises dissolving polyacrylonitrile in an organic solvent to form a matrix solution. At least one crystalline aluminosilicate material is combined with the matrix solution to form a composite media solution. The organic solvent present in the composite media solution is diluted. The composite media solution is solidified. In addition, a method of processing a fluid stream is disclosed. The method comprises providing a beads of a composite media comprising at least one crystalline aluminosilicate material dispersedmore » in a polyacrylonitrile matrix. The beads of the composite media are contacted with a fluid stream comprising at least one constituent. The at least one constituent is substantially removed from the fluid stream.« less

Dopant ink composition and method of fabricating a solar cell there from

DOEpatents

Loscutoff, Paul; Wu, Kahn; Molesa, Steven Edward

2017-10-25

Dopant ink compositions and methods of fabricating solar cells there from are described. A dopant ink composition may include a cross-linkable matrix precursor, a bound dopant species, and a solvent. A method of fabricating a solar cell may include delivering a dopant ink composition to a region above a substrate. The dopant ink composition includes a cross-linkable matrix precursor, a bound dopant species, and a solvent. The method also includes baking the dopant ink composition to remove a substantial portion of the solvent of the dopant ink composition, curing the baked dopant ink composition to cross-link a substantial portion of the cross-linkable matrix precursor of the dopant ink composition, and driving dopants from the cured dopant ink composition toward the substrate.

Dopant ink composition and method of fabricating a solar cell there from

DOEpatents

Loscutoff, Paul; Wu, Kahn; Molesa, Steven Edward

2015-03-31

Dopant ink compositions and methods of fabricating solar cells there from are described. A dopant ink composition may include a cross-linkable matrix precursor, a bound dopant species, and a solvent. A method of fabricating a solar cell may include delivering a dopant ink composition to a region above a substrate. The dopant ink composition includes a cross-linkable matrix precursor, a bound dopant species, and a solvent. The method also includes baking the dopant ink composition to remove a substantial portion of the solvent of the dopant ink composition, curing the baked dopant ink composition to cross-link a substantial portion of the cross-linkable matrix precursor of the dopant ink composition, and driving dopants from the cured dopant ink composition toward the substrate.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pratap, Surender; Sarkar, Niladri, E-mail: niladri@pilani.bits-pilani.ac.in

Self-Consistent Quantum Method using Schrodinger-Poisson equations have been used for determining the Channel electron density of Nano-Scale MOSFETs for 6nm and 9nm thick channels. The 6nm thick MOSFET show the peak of the electron density at the middle where as the 9nm thick MOSFET shows the accumulation of the electrons at the oxide/semiconductor interface. The electron density in the channel is obtained from the diagonal elements of the density matrix; [ρ]=[1/(1+exp(β(H − μ)))] A Tridiagonal Hamiltonian Matrix [H] is constructed for the oxide/channel/oxide 1D structure for the dual gate MOSFET. This structure is discretized and Finite-Difference method is used formore » constructing the matrix equation. The comparison of these results which are obtained by Quantum methods are done with Semi-Classical methods.« less

Generalization of the Mulliken-Hush treatment for the calculation of electron transfer matrix elements

NASA Astrophysics Data System (ADS)

Cave, Robert J.; Newton, Marshall D.

1996-01-01

A new method for the calculation of the electronic coupling matrix element for electron transfer processes is introduced and results for several systems are presented. The method can be applied to ground and excited state systems and can be used in cases where several states interact strongly. Within the set of states chosen it is a non-perturbative treatment, and can be implemented using quantities obtained solely in terms of the adiabatic states. Several applications based on quantum chemical calculations are briefly presented. Finally, since quantities for adiabatic states are the only input to the method, it can also be used with purely experimental data to estimate electron transfer matrix elements.

Discoveries far from the lamppost with matrix elements and ranking

DOE Office of Scientific and Technical Information (OSTI.GOV)

Debnath, Dipsikha; Gainer, James S.; Matchev, Konstantin T.

2015-04-01

The prevalence of null results in searches for new physics at the LHC motivates the effort to make these searches as model-independent as possible. We describe procedures for adapting the Matrix Element Method for situations where the signal hypothesis is not known a priori. We also present general and intuitive approaches for performing analyses and presenting results, which involve the flattening of background distributions using likelihood information. The first flattening method involves ranking events by background matrix element, the second involves quantile binning with respect to likelihood (and other) variables, and the third method involves reweighting histograms by the inversemore » of the background distribution.« less

Iris recognition based on robust principal component analysis

NASA Astrophysics Data System (ADS)

Karn, Pradeep; He, Xiao Hai; Yang, Shuai; Wu, Xiao Hong

2014-11-01

Iris images acquired under different conditions often suffer from blur, occlusion due to eyelids and eyelashes, specular reflection, and other artifacts. Existing iris recognition systems do not perform well on these types of images. To overcome these problems, we propose an iris recognition method based on robust principal component analysis. The proposed method decomposes all training images into a low-rank matrix and a sparse error matrix, where the low-rank matrix is used for feature extraction. The sparsity concentration index approach is then applied to validate the recognition result. Experimental results using CASIA V4 and IIT Delhi V1iris image databases showed that the proposed method achieved competitive performances in both recognition accuracy and computational efficiency.

Bandwidth and Detection of Packet Length Covert Channels

DTIC Science & Technology

2011-03-01

Shared Resource Matrix ( SRM ): Develop a matrix of all resources on one side and on the other all the processes. Then, determine which process uses which...system calls. This method is similar to that of the SRM . Covert channels have also been created by modulating packet timing, data and headers of net- work...analysis, noninterference analysis, SRM method, and the covert flow tree method [4]. These methods can be used during the design phase of a system. Less

A stochastic method for computing hadronic matrix elements

DOE PAGES

Alexandrou, Constantia; Constantinou, Martha; Dinter, Simon; ...

2014-01-24

In this study, we present a stochastic method for the calculation of baryon 3-point functions which is an alternative to the typically used sequential method offering more versatility. We analyze the scaling of the error of the stochastically evaluated 3-point function with the lattice volume and find a favorable signal to noise ratio suggesting that the stochastic method can be extended to large volumes providing an efficient approach to compute hadronic matrix elements and form factors.

How to deal with the high condition number of the noise covariance matrix of gravity field functionals synthesised from a satellite-only global gravity field model?

NASA Astrophysics Data System (ADS)

Klees, R.; Slobbe, D. C.; Farahani, H. H.

2018-03-01

The posed question arises for instance in regional gravity field modelling using weighted least-squares techniques if the gravity field functionals are synthesised from the spherical harmonic coefficients of a satellite-only global gravity model (GGM), and are used as one of the noisy datasets. The associated noise covariance matrix, appeared to be extremely ill-conditioned with a singular value spectrum that decayed gradually to zero without any noticeable gap. We analysed three methods to deal with the ill-conditioned noise covariance matrix: Tihonov regularisation of the noise covariance matrix in combination with the standard formula for the weighted least-squares estimator, a formula of the weighted least-squares estimator, which does not involve the inverse noise covariance matrix, and an estimator based on Rao's unified theory of least-squares. Our analysis was based on a numerical experiment involving a set of height anomalies synthesised from the GGM GOCO05s, which is provided with a full noise covariance matrix. We showed that the three estimators perform similar, provided that the two regularisation parameters each method knows were chosen properly. As standard regularisation parameter choice rules do not apply here, we suggested a new parameter choice rule, and demonstrated its performance. Using this rule, we found that the differences between the three least-squares estimates were within noise. For the standard formulation of the weighted least-squares estimator with regularised noise covariance matrix, this required an exceptionally strong regularisation, much larger than one expected from the condition number of the noise covariance matrix. The preferred method is the inversion-free formulation of the weighted least-squares estimator, because of its simplicity with respect to the choice of the two regularisation parameters.

Myocardial matrix-polyethylene glycol hybrid hydrogels for tissue engineering

NASA Astrophysics Data System (ADS)

Grover, Gregory N.; Rao, Nikhil; Christman, Karen L.

2014-01-01

Similar to other protein-based hydrogels, extracellular matrix (ECM) based hydrogels, derived from decellularized tissues, have a narrow range of mechanical properties and are rapidly degraded. These hydrogels contain natural cellular adhesion sites, form nanofibrous networks similar to native ECM, and are biodegradable. In this study, we expand the properties of these types of materials by incorporating poly(ethylene glycol) (PEG) into the ECM network. We use decellularized myocardial matrix as an example of a tissue specific ECM derived hydrogel. Myocardial matrix-PEG hybrids were synthesized by two different methods, cross-linking the proteins with an amine-reactive PEG-star and photo-induced radical polymerization of two different multi-armed PEG-acrylates. We show that both methods allow for conjugation of PEG to the myocardial matrix by gel electrophoresis and infrared spectroscopy. Scanning electron microscopy demonstrated that the hybrid materials still contain a nanofibrous network similar to unmodified myocardial matrix and that the fiber diameter is changed by the method of PEG incorporation and PEG molecular weight. PEG conjugation also decreased the rate of enzymatic degradation in vitro, and increased material stiffness. Hybrids synthesized with amine-reactive PEG had gelation rates of 30 min, similar to the unmodified myocardial matrix, and incorporation of PEG did not prevent cell adhesion and migration through the hydrogels, thus offering the possibility to have an injectable ECM hydrogel that degrades more slowly in vivo. The photo-polymerized radical systems gelled in 4 min upon irradiation, allowing 3D encapsulation and culture of cells, unlike the soft unmodified myocardial matrix. This work demonstrates that PEG incorporation into ECM-based hydrogels can expand material properties, thereby opening up new possibilities for in vitro and in vivo applications.

Reconstituted asbestos matrix for fuel cells

NASA Technical Reports Server (NTRS)

Mcbryar, H.

1975-01-01

Method is described for reprocessing commercially available asbestos matrix stock to yield greater porosity and bubble pressure (due to increased surface tension), improved homogeneity, and greater uniformity.

Systems for column-based separations, methods of forming packed columns, and methods of purifying sample components

DOEpatents

Egorov, Oleg B.; O'Hara, Matthew J.; Grate, Jay W.; Chandler, Darrell P.; Brockman, Fred J.; Bruckner-Lea, Cynthia J.

2000-01-01

The invention encompasses systems for column-based separations, methods of packing and unpacking columns and methods of separating components of samples. In one aspect, the invention includes a method of packing and unpacking a column chamber, comprising: a) packing a matrix material within a column chamber to form a packed column; and b) after the packing, unpacking the matrix material from the column chamber without moving the column chamber. In another aspect, the invention includes a system for column-based separations, comprising: a) a fluid passageway, the fluid passageway comprising a column chamber and a flow path in fluid communication with the column chamber, the flow path being obstructed by a retaining material permeable to a carrier fluid and impermeable to a column matrix material suspended in the carrier fluid, the flow path extending through the column chamber and through the retaining material, the flow path being configured to form a packed column within the column chamber when a suspension of the fluid and the column matrix material is flowed along the flow path; and b) the fluid passageway extending through a valve intermediate the column chamber and the retaining material.

Systems For Column-Based Separations, Methods Of Forming Packed Columns, And Methods Of Purifying Sample Components

DOEpatents

Egorov, Oleg B.; O'Hara, Matthew J.; Grate, Jay W.; Chandler, Darrell P.; Brockman, Fred J.; Bruckner-Lea, Cynthia J.

2006-02-21

The invention encompasses systems for column-based separations, methods of packing and unpacking columns and methods of separating components of samples. In one aspect, the invention includes a method of packing and unpacking a column chamber, comprising: a) packing a matrix material within a column chamber to form a packed column; and b) after the packing, unpacking the matrix material from the column chamber without moving the column chamber. In another aspect, the invention includes a system for column-based separations, comprising: a) a fluid passageway, the fluid passageway comprising a column chamber and a flow path in fluid communication with the column chamber, the flow path being obstructed by a retaining material permeable to a carrier fluid and impermeable to a column matrix material suspended in the carrier fluid, the flow path extending through the column chamber and through the retaining material, the flow path being configured to form a packed column within the column chamber when a suspension of the fluid and the column matrix material is flowed along the flow path; and b) the fluid passageway extending through a valve intermediate the column chamber and the retaining material.

Systems For Column-Based Separations, Methods Of Forming Packed Columns, And Methods Of Purifying Sample Components.

DOEpatents

Egorov, Oleg B.; O'Hara, Matthew J.; Grate, Jay W.; Chandler, Darrell P.; Brockman, Fred J.; Bruckner-Lea, Cynthia J.

2004-08-24

The invention encompasses systems for column-based separations, methods of packing and unpacking columns and methods of separating components of samples. In one aspect, the invention includes a method of packing and unpacking a column chamber, comprising: a) packing a matrix material within a column chamber to form a packed column; and b) after the packing, unpacking the matrix material from the column chamber without moving the column chamber. In another aspect, the invention includes a system for column-based separations, comprising: a) a fluid passageway, the fluid passageway comprising a column chamber and a flow path in fluid communication with the column chamber, the flow path being obstructed by a retaining material permeable to a carrier fluid and impermeable to a column matrix material suspended in the carrier fluid, the flow path extending through the column chamber and through the retaining material, the flow path being configured to form a packed column within the column chamber when a suspension of the fluid and the column matrix material is flowed along the flow path; and b) the fluid passageway extending through a valve intermediate the column chamber and the retaining material.

Aeroelastic analysis of a troposkien-type wind turbine blade

NASA Technical Reports Server (NTRS)

Nitzsche, F.

1981-01-01

The linear aeroelastic equations for one curved blade of a vertical axis wind turbine in state vector form are presented. The method is based on a simple integrating matrix scheme together with the transfer matrix idea. The method is proposed as a convenient way of solving the associated eigenvalue problem for general support conditions.

Solving rational matrix equations in the state space with applications to computer-aided control-system design

NASA Technical Reports Server (NTRS)

Packard, A. K.; Sastry, S. S.

1986-01-01

A method of solving a class of linear matrix equations over various rings is proposed, using results from linear geometric control theory. An algorithm, successfully implemented, is presented, along with non-trivial numerical examples. Applications of the method to the algebraic control system design methodology are discussed.

Generating Multiple Imputations for Matrix Sampling Data Analyzed with Item Response Models.

ERIC Educational Resources Information Center

Thomas, Neal; Gan, Nianci

1997-01-01

Describes and assesses missing data methods currently used to analyze data from matrix sampling designs implemented by the National Assessment of Educational Progress. Several improved methods are developed, and these models are evaluated using an EM algorithm to obtain maximum likelihood estimates followed by multiple imputation of complete data…

Heuristic Implementation of Dynamic Programming for Matrix Permutation Problems in Combinatorial Data Analysis

ERIC Educational Resources Information Center

Brusco, Michael J.; Kohn, Hans-Friedrich; Stahl, Stephanie

2008-01-01

Dynamic programming methods for matrix permutation problems in combinatorial data analysis can produce globally-optimal solutions for matrices up to size 30x30, but are computationally infeasible for larger matrices because of enormous computer memory requirements. Branch-and-bound methods also guarantee globally-optimal solutions, but computation…

Representation learning via Dual-Autoencoder for recommendation.

PubMed

Zhuang, Fuzhen; Zhang, Zhiqiang; Qian, Mingda; Shi, Chuan; Xie, Xing; He, Qing

2017-06-01

Recommendation has provoked vast amount of attention and research in recent decades. Most previous works employ matrix factorization techniques to learn the latent factors of users and items. And many subsequent works consider external information, e.g., social relationships of users and items' attributions, to improve the recommendation performance under the matrix factorization framework. However, matrix factorization methods may not make full use of the limited information from rating or check-in matrices, and achieve unsatisfying results. Recently, deep learning has proven able to learn good representation in natural language processing, image classification, and so on. Along this line, we propose a new representation learning framework called Recommendation via Dual-Autoencoder (ReDa). In this framework, we simultaneously learn the new hidden representations of users and items using autoencoders, and minimize the deviations of training data by the learnt representations of users and items. Based on this framework, we develop a gradient descent method to learn hidden representations. Extensive experiments conducted on several real-world data sets demonstrate the effectiveness of our proposed method compared with state-of-the-art matrix factorization based methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

A computational method for solving stochastic Itô–Volterra integral equations based on stochastic operational matrix for generalized hat basis functions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Heydari, M.H., E-mail: heydari@stu.yazd.ac.ir; The Laboratory of Quantum Information Processing, Yazd University, Yazd; Hooshmandasl, M.R., E-mail: hooshmandasl@yazd.ac.ir

2014-08-01

In this paper, a new computational method based on the generalized hat basis functions is proposed for solving stochastic Itô–Volterra integral equations. In this way, a new stochastic operational matrix for generalized hat functions on the finite interval [0,T] is obtained. By using these basis functions and their stochastic operational matrix, such problems can be transformed into linear lower triangular systems of algebraic equations which can be directly solved by forward substitution. Also, the rate of convergence of the proposed method is considered and it has been shown that it is O(1/(n{sup 2}) ). Further, in order to show themore » accuracy and reliability of the proposed method, the new approach is compared with the block pulse functions method by some examples. The obtained results reveal that the proposed method is more accurate and efficient in comparison with the block pule functions method.« less

Assessment of Matrix Multiplication Learning with a Rule-Based Analytical Model--"A Bayesian Network Representation"

ERIC Educational Resources Information Center

Zhang, Zhidong

2016-01-01

This study explored an alternative assessment procedure to examine learning trajectories of matrix multiplication. It took rule-based analytical and cognitive task analysis methods specifically to break down operation rules for a given matrix multiplication. Based on the analysis results, a hierarchical Bayesian network, an assessment model,…

An Alternative Method for Computing Mean and Covariance Matrix of Some Multivariate Distributions

ERIC Educational Resources Information Center

Radhakrishnan, R.; Choudhury, Askar

2009-01-01

Computing the mean and covariance matrix of some multivariate distributions, in particular, multivariate normal distribution and Wishart distribution are considered in this article. It involves a matrix transformation of the normal random vector into a random vector whose components are independent normal random variables, and then integrating…

Constructing a Covariance Matrix that Yields a Specified Minimizer and a Specified Minimum Discrepancy Function Value.

ERIC Educational Resources Information Center

Cudeck, Robert; Browne, Michael W.

1992-01-01

A method is proposed for constructing a population covariance matrix as the sum of a particular model plus a nonstochastic residual matrix, with the stipulation that the model holds with a prespecified lack of fit. The procedure is considered promising for Monte Carlo studies. (SLD)

Sparse Matrix Software Catalog, Sparse Matrix Symposium 1982, Fairfield Glade, Tennessee, October 24-27, 1982,

DTIC Science & Technology

1982-10-27

are buried within * a much larger, special purpose package. We regret such omissions, but to have reached the practi- tioners in each of the diverse...sparse matrix (form PAQ ) 4. Method of solution: Distribution count sort 5. Programming language: FORTRAN g Precision: Single and double precision 7

Application of the matrix exponential kernel

NASA Technical Reports Server (NTRS)

Rohach, A. F.

1972-01-01

A point matrix kernel for radiation transport, developed by the transmission matrix method, has been used to develop buildup factors and energy spectra through slab layers of different materials for a point isotropic source. Combinations of lead-water slabs were chosen for examples because of the extreme differences in shielding properties of these two materials.

Numerical stability analysis of two-dimensional solute transport along a discrete fracture in a porous rock matrix

NASA Astrophysics Data System (ADS)

Watanabe, Norihiro; Kolditz, Olaf

2015-07-01

This work reports numerical stability conditions in two-dimensional solute transport simulations including discrete fractures surrounded by an impermeable rock matrix. We use an advective-dispersive problem described in Tang et al. (1981) and examine the stability of the Crank-Nicolson Galerkin finite element method (CN-GFEM). The stability conditions are analyzed in terms of the spatial discretization length perpendicular to the fracture, the flow velocity, the diffusion coefficient, the matrix porosity, the fracture aperture, and the fracture longitudinal dispersivity. In addition, we verify applicability of the recently developed finite element method-flux corrected transport (FEM-FCT) method by Kuzmin () to suppress oscillations in the hybrid system, with a comparison to the commonly utilized Streamline Upwinding/Petrov-Galerkin (SUPG) method. Major findings of this study are (1) the mesh von Neumann number (Fo) ≥ 0.373 must be satisfied to avoid undershooting in the matrix, (2) in addition to an upper bound, the Courant number also has a lower bound in the fracture in cases of low dispersivity, and (3) the FEM-FCT method can effectively suppress the oscillations in both the fracture and the matrix. The results imply that, in cases of low dispersivity, prerefinement of a numerical mesh is not sufficient to avoid the instability in the hybrid system if a problem involves evolutionary flow fields and dynamic material parameters. Applying the FEM-FCT method to such problems is recommended if negative concentrations cannot be tolerated and computing time is not a strong issue.

Inelastic response of metal matrix composites under biaxial loading

NASA Technical Reports Server (NTRS)

Lissenden, C. J.; Mirzadeh, F.; Pindera, M.-J.; Herakovich, C. T.

1991-01-01

Theoretical predictions and experimental results were obtained for inelastic response of unidirectional and angle ply composite tubes subjected to axial and torsional loading. The composite material consist of silicon carbide fibers in a titanium alloy matrix. This material is known to be susceptible to fiber matrix interfacial damage. A method to distinguish between matrix yielding and fiber matrix interfacial damage is suggested. Biaxial tests were conducted on the two different layup configurations using an MTS Axial/Torsional load frame with a PC based data acquisition system. The experimentally determined elastic moduli of the SiC/Ti system are compared with those predicted by a micromechanics model. The test results indicate that fiber matrix interfacial damage occurs at relatively low load levels and is a local phenomenon. The micromechanics model used is the method of cells originally proposed by Aboudi. Finite element models using the ABACUS finite element program were used to study end effects and fixture specimen interactions. The results to date have shown good correlation between theory and experiment for response prior to damage initiation.

Estimation of genetic connectedness diagnostics based on prediction errors without the prediction error variance-covariance matrix.

PubMed

Holmes, John B; Dodds, Ken G; Lee, Michael A

2017-03-02

An important issue in genetic evaluation is the comparability of random effects (breeding values), particularly between pairs of animals in different contemporary groups. This is usually referred to as genetic connectedness. While various measures of connectedness have been proposed in the literature, there is general agreement that the most appropriate measure is some function of the prediction error variance-covariance matrix. However, obtaining the prediction error variance-covariance matrix is computationally demanding for large-scale genetic evaluations. Many alternative statistics have been proposed that avoid the computational cost of obtaining the prediction error variance-covariance matrix, such as counts of genetic links between contemporary groups, gene flow matrices, and functions of the variance-covariance matrix of estimated contemporary group fixed effects. In this paper, we show that a correction to the variance-covariance matrix of estimated contemporary group fixed effects will produce the exact prediction error variance-covariance matrix averaged by contemporary group for univariate models in the presence of single or multiple fixed effects and one random effect. We demonstrate the correction for a series of models and show that approximations to the prediction error matrix based solely on the variance-covariance matrix of estimated contemporary group fixed effects are inappropriate in certain circumstances. Our method allows for the calculation of a connectedness measure based on the prediction error variance-covariance matrix by calculating only the variance-covariance matrix of estimated fixed effects. Since the number of fixed effects in genetic evaluation is usually orders of magnitudes smaller than the number of random effect levels, the computational requirements for our method should be reduced.

Robust Principal Component Analysis Regularized by Truncated Nuclear Norm for Identifying Differentially Expressed Genes.

PubMed

Wang, Ya-Xuan; Gao, Ying-Lian; Liu, Jin-Xing; Kong, Xiang-Zhen; Li, Hai-Jun

2017-09-01

Identifying differentially expressed genes from the thousands of genes is a challenging task. Robust principal component analysis (RPCA) is an efficient method in the identification of differentially expressed genes. RPCA method uses nuclear norm to approximate the rank function. However, theoretical studies showed that the nuclear norm minimizes all singular values, so it may not be the best solution to approximate the rank function. The truncated nuclear norm is defined as the sum of some smaller singular values, which may achieve a better approximation of the rank function than nuclear norm. In this paper, a novel method is proposed by replacing nuclear norm of RPCA with the truncated nuclear norm, which is named robust principal component analysis regularized by truncated nuclear norm (TRPCA). The method decomposes the observation matrix of genomic data into a low-rank matrix and a sparse matrix. Because the significant genes can be considered as sparse signals, the differentially expressed genes are viewed as the sparse perturbation signals. Thus, the differentially expressed genes can be identified according to the sparse matrix. The experimental results on The Cancer Genome Atlas data illustrate that the TRPCA method outperforms other state-of-the-art methods in the identification of differentially expressed genes.

A new decentralised controller design method for a class of strongly interconnected systems

NASA Astrophysics Data System (ADS)

Duan, Zhisheng; Jiang, Zhong-Ping; Huang, Lin

2017-02-01

In this paper, two interconnected structures are first discussed, under which some closed-loop subsystems must be unstable to make the whole interconnected system stable, which can be viewed as a kind of strongly interconnected systems. Then, comparisons with small gain theorem are discussed and large gain interconnected characteristics are shown. A new approach for the design of decentralised controllers is presented by determining the Lyapunov function structure previously, which allows the existence of unstable subsystems. By fully utilising the orthogonal space information of input matrix, some new understandings are presented for the construction of Lyapunov matrix. This new method can deal with decentralised state feedback, static output feedback and dynamic output feedback controllers in a unified framework. Furthermore, in order to reduce the design conservativeness and deal with robustness, a new robust decentralised controller design method is given by combining with the parameter-dependent Lyapunov function method. Some basic rules are provided for the choice of initial variables in Lyapunov matrix or new introduced slack matrices. As byproducts, some linear matrix inequality based sufficient conditions are established for centralised static output feedback stabilisation. Effects of unstable subsystems in nonlinear Lur'e systems are further discussed. The corresponding decentralised controller design method is presented for absolute stability. The examples illustrate that the new method is significantly effective.

Simultaneous determination of phenolic compounds in Equisetum palustre L. by ultra high performance liquid chromatography with tandem mass spectrometry combined with matrix solid-phase dispersion extraction.

PubMed

Wei, Zuofu; Pan, Youzhi; Li, Lu; Huang, Yuyang; Qi, Xiaolin; Luo, Meng; Zu, Yuangang; Fu, Yujie

2014-11-01

A method based on matrix solid-phase dispersion extraction followed by ultra high performance liquid chromatography with tandem mass spectrometry is presented for the extraction and determination of phenolic compounds in Equisetum palustre. This method combines the high efficiency of matrix solid-phase dispersion extraction and the rapidity, sensitivity, and accuracy of ultra high performance liquid chromatography with tandem mass spectrometry. The influential parameters of the matrix solid-phase dispersion extraction were investigated and optimized. The optimized conditions were as follows: silica gel was selected as dispersing sorbent, the ratio of silica gel to sample was selected to be 2:1 (400/200 mg), and 8 mL of 80% methanol was used as elution solvent. Furthermore, a fast and sensitive ultra high performance liquid chromatography with tandem mass spectrometry method was developed for the determination of nine phenolic compounds in E. palustre. This method was carried out within <6 min, and exhibited satisfactory linearity, precision, and recovery. Compared with ultrasound-assisted extraction, the proposed matrix solid-phase dispersion procedure possessed higher extraction efficiency, and was more convenient and time saving with reduced requirements on sample and solvent amounts. All these results suggest that the developed method represents an excellent alternative for the extraction and determination of active components in plant matrices. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Fast calculation of the `ILC norm' in iterative learning control

NASA Astrophysics Data System (ADS)

Rice, Justin K.; van Wingerden, Jan-Willem

2013-06-01

In this paper, we discuss and demonstrate a method for the exploitation of matrix structure in computations for iterative learning control (ILC). In Barton, Bristow, and Alleyne [International Journal of Control, 83(2), 1-8 (2010)], a special insight into the structure of the lifted convolution matrices involved in ILC is used along with a modified Lanczos method to achieve very fast computational bounds on the learning convergence, by calculating the 'ILC norm' in ? computational complexity. In this paper, we show how their method is equivalent to a special instance of the sequentially semi-separable (SSS) matrix arithmetic, and thus can be extended to many other computations in ILC, and specialised in some cases to even faster methods. Our SSS-based methodology will be demonstrated on two examples: a linear time-varying example resulting in the same ? complexity as in Barton et al., and a linear time-invariant example where our approach reduces the computational complexity to ?, thus decreasing the computation time, for an example, from the literature by a factor of almost 100. This improvement is achieved by transforming the norm computation via a linear matrix inequality into a check of positive definiteness - which allows us to further exploit the almost-Toeplitz properties of the matrix, and additionally provides explicit upper and lower bounds on the norm of the matrix, instead of the indirect Ritz estimate. These methods are now implemented in a MATLAB toolbox, freely available on the Internet.

Workshop report on large-scale matrix diagonalization methods in chemistry theory institute

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bischof, C.H.; Shepard, R.L.; Huss-Lederman, S.

The Large-Scale Matrix Diagonalization Methods in Chemistry theory institute brought together 41 computational chemists and numerical analysts. The goal was to understand the needs of the computational chemistry community in problems that utilize matrix diagonalization techniques. This was accomplished by reviewing the current state of the art and looking toward future directions in matrix diagonalization techniques. This institute occurred about 20 years after a related meeting of similar size. During those 20 years the Davidson method continued to dominate the problem of finding a few extremal eigenvalues for many computational chemistry problems. Work on non-diagonally dominant and non-Hermitian problems asmore » well as parallel computing has also brought new methods to bear. The changes and similarities in problems and methods over the past two decades offered an interesting viewpoint for the success in this area. One important area covered by the talks was overviews of the source and nature of the chemistry problems. The numerical analysts were uniformly grateful for the efforts to convey a better understanding of the problems and issues faced in computational chemistry. An important outcome was an understanding of the wide range of eigenproblems encountered in computational chemistry. The workshop covered problems involving self- consistent-field (SCF), configuration interaction (CI), intramolecular vibrational relaxation (IVR), and scattering problems. In atomic structure calculations using the Hartree-Fock method (SCF), the symmetric matrices can range from order hundreds to thousands. These matrices often include large clusters of eigenvalues which can be as much as 25% of the spectrum. However, if Cl methods are also used, the matrix size can be between 10{sup 4} and 10{sup 9} where only one or a few extremal eigenvalues and eigenvectors are needed. Working with very large matrices has lead to the development of« less

Comparison of Transmission Line Methods for Surface Acoustic Wave Modeling

NASA Technical Reports Server (NTRS)

Wilson, William; Atkinson, Gary

2009-01-01

Surface Acoustic Wave (SAW) technology is low cost, rugged, lightweight, extremely low power and can be used to develop passive wireless sensors. For these reasons, NASA is investigating the use of SAW technology for Integrated Vehicle Health Monitoring (IVHM) of aerospace structures. To facilitate rapid prototyping of passive SAW sensors for aerospace applications, SAW models have been developed. This paper reports on the comparison of three methods of modeling SAWs. The three models are the Impulse Response Method (a first order model), and two second order matrix methods; the conventional matrix approach, and a modified matrix approach that is extended to include internal finger reflections. The second order models are based upon matrices that were originally developed for analyzing microwave circuits using transmission line theory. Results from the models are presented with measured data from devices. Keywords: Surface Acoustic Wave, SAW, transmission line models, Impulse Response Method.

The density-matrix renormalization group: a short introduction.

PubMed

Schollwöck, Ulrich

2011-07-13

The density-matrix renormalization group (DMRG) method has established itself over the last decade as the leading method for the simulation of the statics and dynamics of one-dimensional strongly correlated quantum lattice systems. The DMRG is a method that shares features of a renormalization group procedure (which here generates a flow in the space of reduced density operators) and of a variational method that operates on a highly interesting class of quantum states, so-called matrix product states (MPSs). The DMRG method is presented here entirely in the MPS language. While the DMRG generally fails in larger two-dimensional systems, the MPS picture suggests a straightforward generalization to higher dimensions in the framework of tensor network states. The resulting algorithms, however, suffer from difficulties absent in one dimension, apart from a much more unfavourable efficiency, such that their ultimate success remains far from clear at the moment.

Newmark-Beta-FDTD method for super-resolution analysis of time reversal waves

NASA Astrophysics Data System (ADS)

Shi, Sheng-Bing; Shao, Wei; Ma, Jing; Jin, Congjun; Wang, Xiao-Hua

2017-09-01

In this work, a new unconditionally stable finite-difference time-domain (FDTD) method with the split-field perfectly matched layer (PML) is proposed for the analysis of time reversal (TR) waves. The proposed method is very suitable for multiscale problems involving microstructures. The spatial and temporal derivatives in this method are discretized by the central difference technique and Newmark-Beta algorithm, respectively, and the derivation results in the calculation of a banded-sparse matrix equation. Since the coefficient matrix keeps unchanged during the whole simulation process, the lower-upper (LU) decomposition of the matrix needs to be performed only once at the beginning of the calculation. Moreover, the reverse Cuthill-Mckee (RCM) technique, an effective preprocessing technique in bandwidth compression of sparse matrices, is used to improve computational efficiency. The super-resolution focusing of TR wave propagation in two- and three-dimensional spaces is included to validate the accuracy and efficiency of the proposed method.

Cucheb: A GPU implementation of the filtered Lanczos procedure

NASA Astrophysics Data System (ADS)

Aurentz, Jared L.; Kalantzis, Vassilis; Saad, Yousef

2017-11-01

This paper describes the software package Cucheb, a GPU implementation of the filtered Lanczos procedure for the solution of large sparse symmetric eigenvalue problems. The filtered Lanczos procedure uses a carefully chosen polynomial spectral transformation to accelerate convergence of the Lanczos method when computing eigenvalues within a desired interval. This method has proven particularly effective for eigenvalue problems that arise in electronic structure calculations and density functional theory. We compare our implementation against an equivalent CPU implementation and show that using the GPU can reduce the computation time by more than a factor of 10. Program Summary Program title: Cucheb Program Files doi:http://dx.doi.org/10.17632/rjr9tzchmh.1 Licensing provisions: MIT Programming language: CUDA C/C++ Nature of problem: Electronic structure calculations require the computation of all eigenvalue-eigenvector pairs of a symmetric matrix that lie inside a user-defined real interval. Solution method: To compute all the eigenvalues within a given interval a polynomial spectral transformation is constructed that maps the desired eigenvalues of the original matrix to the exterior of the spectrum of the transformed matrix. The Lanczos method is then used to compute the desired eigenvectors of the transformed matrix, which are then used to recover the desired eigenvalues of the original matrix. The bulk of the operations are executed in parallel using a graphics processing unit (GPU). Runtime: Variable, depending on the number of eigenvalues sought and the size and sparsity of the matrix. Additional comments: Cucheb is compatible with CUDA Toolkit v7.0 or greater.

On the cross-stream spectral method for the Orr-Sommerfeld equation

NASA Technical Reports Server (NTRS)

Zorumski, William E.; Hodge, Steven L.

1993-01-01

Cross-stream models are defined as solutions to the Orr-Sommerfeld equation which are propagating normal to the flow direction. These models are utilized as a basis for a Hilbert space to approximate the spectrum of the Orr-Sommerfeld equation with plane Poiseuille flow. The cross-stream basis leads to a standard eigenvalue problem for the frequencies of Poiseuille flow instability waves. The coefficient matrix in the eigenvalue problem is shown to be the sum of a real matrix and a negative-imaginary diagonal matrix which represents the frequencies of the cross-stream modes. The real coefficient matrix is shown to approach a Toeplitz matrix when the row and column indices are large. The Toeplitz matrix is diagonally dominant, and the diagonal elements vary inversely in magnitude with diagonal position. The Poiseuille flow eigenvalues are shown to lie within Gersgorin disks with radii bounded by the product of the average flow speed and the axial wavenumber. It is shown that the eigenvalues approach the Gersgorin disk centers when the mode index is large, so that the method may be used to compute spectra with an essentially unlimited number of elements. When the mode index is large, the real part of the eigenvalue is the product of the axial wavenumber and the average flow speed, and the imaginary part of the eigen value is identical to the corresponding cross-stream mode frequency. The cross-stream method is numerically well-conditioned in comparison to Chebyshev based methods, providing equivalent accuracy for small mode indices and superior accuracy for large indices.

Orthonormal vector general polynomials derived from the Cartesian gradient of the orthonormal Zernike-based polynomials.

PubMed

Mafusire, Cosmas; Krüger, Tjaart P J

2018-06-01

The concept of orthonormal vector circle polynomials is revisited by deriving a set from the Cartesian gradient of Zernike polynomials in a unit circle using a matrix-based approach. The heart of this model is a closed-form matrix equation of the gradient of Zernike circle polynomials expressed as a linear combination of lower-order Zernike circle polynomials related through a gradient matrix. This is a sparse matrix whose elements are two-dimensional standard basis transverse Euclidean vectors. Using the outer product form of the Cholesky decomposition, the gradient matrix is used to calculate a new matrix, which we used to express the Cartesian gradient of the Zernike circle polynomials as a linear combination of orthonormal vector circle polynomials. Since this new matrix is singular, the orthonormal vector polynomials are recovered by reducing the matrix to its row echelon form using the Gauss-Jordan elimination method. We extend the model to derive orthonormal vector general polynomials, which are orthonormal in a general pupil by performing a similarity transformation on the gradient matrix to give its equivalent in the general pupil. The outer form of the Gram-Schmidt procedure and the Gauss-Jordan elimination method are then applied to the general pupil to generate the orthonormal vector general polynomials from the gradient of the orthonormal Zernike-based polynomials. The performance of the model is demonstrated with a simulated wavefront in a square pupil inscribed in a unit circle.

A Delphi-matrix approach to SEA and its application within the tourism sector in Taiwan

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kuo, N.-W.; Hsiao, T.-Y.; Yu, Y.-H.

Strategic Environmental Assessment (SEA) is a procedural tool and within the framework of SEA, several different types of analytical methods can be used in the assessment. However, the impact matrix used currently in Taiwan has some disadvantages. Hence, a Delphi-matrix approach to SEA is proposed here to improve the performance of Taiwan's SEA. This new approach is based on the impact matrix combination with indicators of sustainability, and then the Delphi method is employed to collect experts' opinions. In addition, the assessment of National Floriculture Park Plan and Taiwan Flora 2008 Program is taken as an example to examine thismore » new method. Although international exhibition is one of the important tourism (economic) activities, SEA is seldom about tourism sector. Finally, the Delphi-matrix approach to SEA for tourism development plan is established containing eight assessment topics and 26 corresponding categories. In summary, three major types of impacts: resources' usages, pollution emissions, and local cultures change are found. Resources' usages, such as water, electricity, and natural gas demand, are calculated on a per capita basis. Various forms of pollution resulting from this plan, such as air, water, soil, waste, and noise, are also identified.« less

Matrix method for two-dimensional waveguide mode solution

NASA Astrophysics Data System (ADS)

Sun, Baoguang; Cai, Congzhong; Venkatesh, Balajee Seshasayee

2018-05-01

In this paper, we show that the transfer matrix theory of multilayer optics can be used to solve the modes of any two-dimensional (2D) waveguide for their effective indices and field distributions. A 2D waveguide, even composed of numerous layers, is essentially a multilayer stack and the transmission through the stack can be analysed using the transfer matrix theory. The result is a transfer matrix with four complex value elements, namely A, B, C and D. The effective index of a guided mode satisfies two conditions: (1) evanescent waves exist simultaneously in the first (cladding) layer and last (substrate) layer, and (2) the complex element D vanishes. For a given mode, the field distribution in the waveguide is the result of a 'folded' plane wave. In each layer, there is only propagation and absorption; at each boundary, only reflection and refraction occur, which can be calculated according to the Fresnel equations. As examples, we show that this method can be used to solve modes supported by the multilayer step-index dielectric waveguide, slot waveguide, gradient-index waveguide and various plasmonic waveguides. The results indicate the transfer matrix method is effective for 2D waveguide mode solution in general.

The multifacet graphically contracted function method. I. Formulation and implementation

NASA Astrophysics Data System (ADS)

Shepard, Ron; Gidofalvi, Gergely; Brozell, Scott R.

2014-08-01

The basic formulation for the multifacet generalization of the graphically contracted function (MFGCF) electronic structure method is presented. The analysis includes the discussion of linear dependency and redundancy of the arc factor parameters, the computation of reduced density matrices, Hamiltonian matrix construction, spin-density matrix construction, the computation of optimization gradients for single-state and state-averaged calculations, graphical wave function analysis, and the efficient computation of configuration state function and Slater determinant expansion coefficients. Timings are given for Hamiltonian matrix element and analytic optimization gradient computations for a range of model problems for full-CI Shavitt graphs, and it is observed that both the energy and the gradient computation scale as O(N2n4) for N electrons and n orbitals. The important arithmetic operations are within dense matrix-matrix product computational kernels, resulting in a computationally efficient procedure. An initial implementation of the method is used to present applications to several challenging chemical systems, including N2 dissociation, cubic H8 dissociation, the symmetric dissociation of H2O, and the insertion of Be into H2. The results are compared to the exact full-CI values and also to those of the previous single-facet GCF expansion form.

The multifacet graphically contracted function method. I. Formulation and implementation.

PubMed

Shepard, Ron; Gidofalvi, Gergely; Brozell, Scott R

2014-08-14

The basic formulation for the multifacet generalization of the graphically contracted function (MFGCF) electronic structure method is presented. The analysis includes the discussion of linear dependency and redundancy of the arc factor parameters, the computation of reduced density matrices, Hamiltonian matrix construction, spin-density matrix construction, the computation of optimization gradients for single-state and state-averaged calculations, graphical wave function analysis, and the efficient computation of configuration state function and Slater determinant expansion coefficients. Timings are given for Hamiltonian matrix element and analytic optimization gradient computations for a range of model problems for full-CI Shavitt graphs, and it is observed that both the energy and the gradient computation scale as O(N(2)n(4)) for N electrons and n orbitals. The important arithmetic operations are within dense matrix-matrix product computational kernels, resulting in a computationally efficient procedure. An initial implementation of the method is used to present applications to several challenging chemical systems, including N2 dissociation, cubic H8 dissociation, the symmetric dissociation of H2O, and the insertion of Be into H2. The results are compared to the exact full-CI values and also to those of the previous single-facet GCF expansion form.

Purity Determination by Capillary Electrophoresis Sodium Hexadecyl Sulfate (CE-SHS): A Novel Application For Therapeutic Protein Characterization.

PubMed

Beckman, Jeff; Song, Yuanli; Gu, Yan; Voronov, Sergey; Chennamsetty, Naresh; Krystek, Stanley; Mussa, Nesredin; Li, Zheng Jian

2018-02-20

Capillary gel electrophoresis using sodium dodecyl sulfate (CE-SDS) is used commercially to provide quantitative purity data for therapeutic protein characterization and release. In CE-SDS, proteins are denatured under reducing or nonreducing conditions in the presence of SDS and electrophoretically separated by molecular weight and hydrodynamic radius through a sieving polymer matrix. Acceptable performance of this method would yield protein peaks that are baseline resolved and symmetrical. Nominal CE-SDS conditions and parameters are not optimal for all therapeutic proteins, specifically for Recombinant Therapeutic Protein-1 (RTP-1), where acceptable resolution and peak symmetry were not achieved. The application of longer alkyl chain detergents in the running buffer matrix substantially improved assay performance. Matrix running buffer containing sodium hexadecyl sulfate (SHS) increased peak resolution and plate count 3- and 8-fold, respectively, compared to a traditional SDS-based running gel matrix. At Bristol-Myers Squibb (BMS), we developed and qualified a viable method for the characterization and release of RTP-1 using an SHS-containing running buffer matrix. This work underscores the potential of detergents other than SDS to enhance the resolution and separation power of CE-based separation methods.

Efficient diagonalization of the sparse matrices produced within the framework of the UK R-matrix molecular codes

NASA Astrophysics Data System (ADS)

Galiatsatos, P. G.; Tennyson, J.

2012-11-01

The most time consuming step within the framework of the UK R-matrix molecular codes is that of the diagonalization of the inner region Hamiltonian matrix (IRHM). Here we present the method that we follow to speed up this step. We use shared memory machines (SMM), distributed memory machines (DMM), the OpenMP directive based parallel language, the MPI function based parallel language, the sparse matrix diagonalizers ARPACK and PARPACK, a variation for real symmetric matrices of the official coordinate sparse matrix format and finally a parallel sparse matrix-vector product (PSMV). The efficient application of the previous techniques rely on two important facts: the sparsity of the matrix is large enough (more than 98%) and in order to get back converged results we need a small only part of the matrix spectrum.

General transfer matrix formalism to calculate DNA-protein-drug binding in gene regulation: application to OR operator of phage lambda.

PubMed

Teif, Vladimir B

2007-01-01

The transfer matrix methodology is proposed as a systematic tool for the statistical-mechanical description of DNA-protein-drug binding involved in gene regulation. We show that a genetic system of several cis-regulatory modules is calculable using this method, considering explicitly the site-overlapping, competitive, cooperative binding of regulatory proteins, their multilayer assembly and DNA looping. In the methodological section, the matrix models are solved for the basic types of short- and long-range interactions between DNA-bound proteins, drugs and nucleosomes. We apply the matrix method to gene regulation at the O(R) operator of phage lambda. The transfer matrix formalism allowed the description of the lambda-switch at a single-nucleotide resolution, taking into account the effects of a range of inter-protein distances. Our calculations confirm previously established roles of the contact CI-Cro-RNAP interactions. Concerning long-range interactions, we show that while the DNA loop between the O(R) and O(L) operators is important at the lysogenic CI concentrations, the interference between the adjacent promoters P(R) and P(RM) becomes more important at small CI concentrations. A large change in the expression pattern may arise in this regime due to anticooperative interactions between DNA-bound RNA polymerases. The applicability of the matrix method to more complex systems is discussed.

General transfer matrix formalism to calculate DNA–protein–drug binding in gene regulation: application to OR operator of phage λ

PubMed Central

Teif, Vladimir B.

2007-01-01

The transfer matrix methodology is proposed as a systematic tool for the statistical–mechanical description of DNA–protein–drug binding involved in gene regulation. We show that a genetic system of several cis-regulatory modules is calculable using this method, considering explicitly the site-overlapping, competitive, cooperative binding of regulatory proteins, their multilayer assembly and DNA looping. In the methodological section, the matrix models are solved for the basic types of short- and long-range interactions between DNA-bound proteins, drugs and nucleosomes. We apply the matrix method to gene regulation at the OR operator of phage λ. The transfer matrix formalism allowed the description of the λ-switch at a single-nucleotide resolution, taking into account the effects of a range of inter-protein distances. Our calculations confirm previously established roles of the contact CI–Cro–RNAP interactions. Concerning long-range interactions, we show that while the DNA loop between the OR and OL operators is important at the lysogenic CI concentrations, the interference between the adjacent promoters PR and PRM becomes more important at small CI concentrations. A large change in the expression pattern may arise in this regime due to anticooperative interactions between DNA-bound RNA polymerases. The applicability of the matrix method to more complex systems is discussed. PMID:17526526

Fabric defect detection based on visual saliency using deep feature and low-rank recovery

NASA Astrophysics Data System (ADS)

Liu, Zhoufeng; Wang, Baorui; Li, Chunlei; Li, Bicao; Dong, Yan

2018-04-01

Fabric defect detection plays an important role in improving the quality of fabric product. In this paper, a novel fabric defect detection method based on visual saliency using deep feature and low-rank recovery was proposed. First, unsupervised training is carried out by the initial network parameters based on MNIST large datasets. The supervised fine-tuning of fabric image library based on Convolutional Neural Networks (CNNs) is implemented, and then more accurate deep neural network model is generated. Second, the fabric images are uniformly divided into the image block with the same size, then we extract their multi-layer deep features using the trained deep network. Thereafter, all the extracted features are concentrated into a feature matrix. Third, low-rank matrix recovery is adopted to divide the feature matrix into the low-rank matrix which indicates the background and the sparse matrix which indicates the salient defect. In the end, the iterative optimal threshold segmentation algorithm is utilized to segment the saliency maps generated by the sparse matrix to locate the fabric defect area. Experimental results demonstrate that the feature extracted by CNN is more suitable for characterizing the fabric texture than the traditional LBP, HOG and other hand-crafted features extraction method, and the proposed method can accurately detect the defect regions of various fabric defects, even for the image with complex texture.

Toward active-matrix lab-on-a-chip: programmable electrofluidic control enabled by arrayed oxide thin film transistors.

PubMed

Noh, Joo Hyon; Noh, Jiyong; Kreit, Eric; Heikenfeld, Jason; Rack, Philip D

2012-01-21

Agile micro- and nano-fluidic control is critical to numerous life science and chemical science synthesis as well as kinetic and thermodynamic studies. To this end, we have demonstrated the use of thin film transistor arrays as an active matrix addressing method to control an electrofluidic array. Because the active matrix method minimizes the number of control lines necessary (m + n lines for the m×n element array), the active matrix addressing method integrated with an electrofluidic platform can be a significant breakthrough for complex electrofluidic arrays (increased size or resolution) with enhanced function, agility and programmability. An amorphous indium gallium zinc oxide (a-IGZO) semiconductor active layer is used because of its high mobility of 1-15 cm(2) V(-1) s(-1), low-temperature processing and transparency for potential spectroscopy and imaging. Several electrofluidic functionalities are demonstrated using a simple 2 × 5 electrode array connected to a 2 × 5 IGZO thin film transistor array with the semiconductor channel width of 50 μm and mobility of 6.3 cm(2) V(-1) s(-1). Additionally, using the TFT device characteristics, active matrix addressing schemes are discussed as the geometry of the electrode array can be tailored to act as a storage capacitor element. Finally, requisite material and device parameters are discussed in context with a VGA scale active matrix addressed electrofluidic platform.

A robust bi-orthogonal/dynamically-orthogonal method using the covariance pseudo-inverse with application to stochastic flow problems

NASA Astrophysics Data System (ADS)

Babaee, Hessam; Choi, Minseok; Sapsis, Themistoklis P.; Karniadakis, George Em

2017-09-01

We develop a new robust methodology for the stochastic Navier-Stokes equations based on the dynamically-orthogonal (DO) and bi-orthogonal (BO) methods [1-3]. Both approaches are variants of a generalized Karhunen-Loève (KL) expansion in which both the stochastic coefficients and the spatial basis evolve according to system dynamics, hence, capturing the low-dimensional structure of the solution. The DO and BO formulations are mathematically equivalent [3], but they exhibit computationally complimentary properties. Specifically, the BO formulation may fail due to crossing of the eigenvalues of the covariance matrix, while both BO and DO become unstable when there is a high condition number of the covariance matrix or zero eigenvalues. To this end, we combine the two methods into a robust hybrid framework and in addition we employ a pseudo-inverse technique to invert the covariance matrix. The robustness of the proposed method stems from addressing the following issues in the DO/BO formulation: (i) eigenvalue crossing: we resolve the issue of eigenvalue crossing in the BO formulation by switching to the DO near eigenvalue crossing using the equivalence theorem and switching back to BO when the distance between eigenvalues is larger than a threshold value; (ii) ill-conditioned covariance matrix: we utilize a pseudo-inverse strategy to invert the covariance matrix; (iii) adaptivity: we utilize an adaptive strategy to add/remove modes to resolve the covariance matrix up to a threshold value. In particular, we introduce a soft-threshold criterion to allow the system to adapt to the newly added/removed mode and therefore avoid repetitive and unnecessary mode addition/removal. When the total variance approaches zero, we show that the DO/BO formulation becomes equivalent to the evolution equation of the Optimally Time-Dependent modes [4]. We demonstrate the capability of the proposed methodology with several numerical examples, namely (i) stochastic Burgers equation: we analyze the performance of the method in the presence of eigenvalue crossing and zero eigenvalues; (ii) stochastic Kovasznay flow: we examine the method in the presence of a singular covariance matrix; and (iii) we examine the adaptivity of the method for an incompressible flow over a cylinder where for large stochastic forcing thirteen DO/BO modes are active.

A new Newton-like method for solving nonlinear equations.

PubMed

Saheya, B; Chen, Guo-Qing; Sui, Yun-Kang; Wu, Cai-Ying

2016-01-01

This paper presents an iterative scheme for solving nonline ar equations. We establish a new rational approximation model with linear numerator and denominator which has generalizes the local linear model. We then employ the new approximation for nonlinear equations and propose an improved Newton's method to solve it. The new method revises the Jacobian matrix by a rank one matrix each iteration and obtains the quadratic convergence property. The numerical performance and comparison show that the proposed method is efficient.

A Measurement of the Top Quark Mass with the D0 Detector at s**(1/2) = 1.96-TeV using the Matrix Element Method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kroeninger, Kevin Alexander; /Bonn U.

2004-04-01

Using a data set of 158 and 169 pb{sup -1} of D0 Run-II data in the electron and muon plus jets channel, respectively, the top quark mass has been measured using the Matrix Element Method. The method and its implementation are described. Its performance is studied in Monte Carlo using ensemble tests and the method is applied to the Moriond 2004 data set.

Quantitative nondestructive evaluation of ceramic matrix composite by the resonance method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Watanabe, T.; Aizawa, T.; Kihara, J.

The resonance method was developed to make quantitative nondestructive evaluation on the mechanical properties without any troublesome procedure. Since the present method is indifferent to the geometry of specimen, both monolithic and ceramic matrix composite materials in process can be evaluated in the nondestructive manner. Al{sub 2}O{sub 3}, Si{sub 3}N{sub 4}, SiC/Si{sub 3}N{sub 4}, and various C/C composite materials are employed to demonstrate the validity and effectiveness of the present method.

Integrated identification and control for nanosatellites reclaiming failed satellite

NASA Astrophysics Data System (ADS)

Han, Nan; Luo, Jianjun; Ma, Weihua; Yuan, Jianping

2018-05-01

Using nanosatellites to reclaim a failed satellite needs nanosatellites to attach to its surface to take over its attitude control function. This is challenging, since parameters including the inertia matrix of the combined spacecraft and the relative attitude information of attached nanosatellites with respect to the given body-fixed frame of the failed satellite are all unknown after the attachment. Besides, if the total control capacity needs to be increased during the reclaiming process by new nanosatellites, real-time parameters updating will be necessary. For these reasons, an integrated identification and control method is proposed in this paper, which enables the real-time parameters identification and attitude takeover control to be conducted concurrently. Identification of the inertia matrix of the combined spacecraft and the relative attitude information of attached nanosatellites are both considered. To guarantee sufficient excitation for the identification of the inertia matrix, a modified identification equation is established by filtering out sample points leading to ill-conditioned identification, and the identification performance of the inertia matrix is improved. Based on the real-time estimated inertia matrix, an attitude takeover controller is designed, the stability of the controller is analysed using Lyapunov method. The commanded control torques are allocated to each nanosatellite while the control saturation constraint being satisfied using the Quadratic Programming (QP) method. Numerical simulations are carried out to demonstrate the feasibility and effectiveness of the proposed integrated identification and control method.

Confocal microscopy imaging of the biofilm matrix.

PubMed

Schlafer, Sebastian; Meyer, Rikke L

2017-07-01

The extracellular matrix is an integral part of microbial biofilms and an important field of research. Confocal laser scanning microscopy is a valuable tool for the study of biofilms, and in particular of the biofilm matrix, as it allows real-time visualization of fully hydrated, living specimens. Confocal microscopes are held by many research groups, and a number of methods for qualitative and quantitative imaging of the matrix have emerged in recent years. This review provides an overview and a critical discussion of techniques used to visualize different matrix compounds, to determine the concentration of solutes and the diffusive properties of the biofilm matrix. Copyright © 2016 Elsevier B.V. All rights reserved.

Method for making a microporous membrane

NASA Technical Reports Server (NTRS)

Gavalas, Lillian Susan (Inventor)

2013-01-01

A method for making a microporous membrane comprises the steps of: providing a plurality of carbon nanotubes having a hollow interior diameter of 20 Angstroms or less; sonicating the plurality of carbon nanotubes utilizing a solution comprising deionized, distilled water and a surfactant that coats at least one of the plurality of carbon nanotubes; collecting the coated carbon nanotubes; forming a matrix that supports the plurality of carbon nanotubes; embedding the coated carbon nanotubes into the matrix; rinsing the coated nanotubes to remove at least a portion of the surfactant; curing the nanotube-matrix assembly; and cutting the nanotube-matrix assembly to a particular thickness so as to open the ends of the embedded nanotubes. The hollow interiors of the plurality of embedded carbon nanotubes comprise the pores of the microporous membrane.

Semiotic indexing of digital resources

DOEpatents

Parker, Charles T; Garrity, George M

2014-12-02

A method of classifying a plurality of documents. The method includes steps of providing a first set of classification terms and a second set of classification terms, the second set of classification terms being different from the first set of classification terms; generating a first frequency array of a number of occurrences of each term from the first set of classification terms in each document; generating a second frequency array of a number of occurrences of each term from the second set of classification terms in each document; generating a first similarity matrix from the first frequency array; generating a second similarity matrix from the second frequency array; determining an entrywise combination of the first similarity matrix and the second similarity matrix; and clustering the plurality of documents based on the result of the entrywise combination.

Knowledge of damage identification about tensegrities via flexibility disassembly

NASA Astrophysics Data System (ADS)

Jiang, Ge; Feng, Xiaodong; Du, Shigui

2017-12-01

Tensegrity structures composing of continuous cables and discrete struts are under tension and compression, respectively. In order to determine the damage extents of tensegrity structures, a new method for tensegrity structural damage identification is presented based on flexibility disassembly. To decompose a tensegrity structural flexibility matrix into the matrix represention of the connectivity between degress-of-freedoms and the diagonal matrix comprising of magnitude informations. Step 1: Calculate perturbation flexibility; Step 2: Compute the flexibility connectivity matrix and perturbation flexibility parameters; Step 3: Calculate the perturbation stiffness parameters. The efficiency of the proposed method is demonstrated by a numeical example comprising of 12 cables and 4 struts with pretensioned. Accurate identification of local damage depends on the availability of good measured data, an accurate and reasonable algorithm.

Sparse nonnegative matrix factorization with ℓ0-constraints

PubMed Central

Peharz, Robert; Pernkopf, Franz

2012-01-01

Although nonnegative matrix factorization (NMF) favors a sparse and part-based representation of nonnegative data, there is no guarantee for this behavior. Several authors proposed NMF methods which enforce sparseness by constraining or penalizing the ℓ1-norm of the factor matrices. On the other hand, little work has been done using a more natural sparseness measure, the ℓ0-pseudo-norm. In this paper, we propose a framework for approximate NMF which constrains the ℓ0-norm of the basis matrix, or the coefficient matrix, respectively. For this purpose, techniques for unconstrained NMF can be easily incorporated, such as multiplicative update rules, or the alternating nonnegative least-squares scheme. In experiments we demonstrate the benefits of our methods, which compare to, or outperform existing approaches. PMID:22505792

Protein structure estimation from NMR data by matrix completion.

PubMed

Li, Zhicheng; Li, Yang; Lei, Qiang; Zhao, Qing

2017-09-01

Knowledge of protein structures is very important to understand their corresponding physical and chemical properties. Nuclear Magnetic Resonance (NMR) spectroscopy is one of the main methods to measure protein structure. In this paper, we propose a two-stage approach to calculate the structure of a protein from a highly incomplete distance matrix, where most data are obtained from NMR. We first randomly "guess" a small part of unobservable distances by utilizing the triangle inequality, which is crucial for the second stage. Then we use matrix completion to calculate the protein structure from the obtained incomplete distance matrix. We apply the accelerated proximal gradient algorithm to solve the corresponding optimization problem. Furthermore, the recovery error of our method is analyzed, and its efficiency is demonstrated by several practical examples.

Implementation of Fiber Substructuring Into Strain Rate Dependent Micromechanics Analysis of Polymer Matrix Composites

NASA Technical Reports Server (NTRS)

Goldberg, Robert K.

2001-01-01

A research program is in progress to develop strain rate dependent deformation and failure models for the analysis of polymer matrix composites subject to impact loads. Previously, strain rate dependent inelastic constitutive equations developed to model the polymer matrix were incorporated into a mechanics of materials based micromechanics method. In the current work, the micromechanics method is revised such that the composite unit cell is divided into a number of slices. Micromechanics equations are then developed for each slice, with laminate theory applied to determine the elastic properties, effective stresses and effective inelastic strains for the unit cell. Verification studies are conducted using two representative polymer matrix composites with a nonlinear, strain rate dependent deformation response. The computed results compare well to experimentally obtained values.

A rough set approach for determining weights of decision makers in group decision making

PubMed Central

Yang, Qiang; Du, Ping-an; Wang, Yong; Liang, Bin

2017-01-01

This study aims to present a novel approach for determining the weights of decision makers (DMs) based on rough group decision in multiple attribute group decision-making (MAGDM) problems. First, we construct a rough group decision matrix from all DMs’ decision matrixes on the basis of rough set theory. After that, we derive a positive ideal solution (PIS) founded on the average matrix of rough group decision, and negative ideal solutions (NISs) founded on the lower and upper limit matrixes of rough group decision. Then, we obtain the weight of each group member and priority order of alternatives by using relative closeness method, which depends on the distances from each individual group member’ decision to the PIS and NISs. Through comparisons with existing methods and an on-line business manager selection example, the proposed method show that it can provide more insights into the subjectivity and vagueness of DMs’ evaluations and selections. PMID:28234974

A coloured oil level indicator detection method based on simple linear iterative clustering

NASA Astrophysics Data System (ADS)

Liu, Tianli; Li, Dongsong; Jiao, Zhiming; Liang, Tao; Zhou, Hao; Yang, Guoqing

2017-12-01

A detection method of coloured oil level indicator is put forward. The method is applied to inspection robot in substation, which realized the automatic inspection and recognition of oil level indicator. Firstly, the detected image of the oil level indicator is collected, and the detected image is clustered and segmented to obtain the label matrix of the image. Secondly, the detection image is processed by colour space transformation, and the feature matrix of the image is obtained. Finally, the label matrix and feature matrix are used to locate and segment the detected image, and the upper edge of the recognized region is obtained. If the upper limb line exceeds the preset oil level threshold, the alarm will alert the station staff. Through the above-mentioned image processing, the inspection robot can independently recognize the oil level of the oil level indicator, and instead of manual inspection. It embodies the automatic and intelligent level of unattended operation.

Mueller coherency matrix method for contrast image in tissue polarimetry

NASA Astrophysics Data System (ADS)

Arce-Diego, J. L.; Fanjul-Vélez, F.; Samperio-García, D.; Pereda-Cubián, D.

2007-07-01

In this work, we propose the use of the Mueller Coherency matrix of biological tissues in order to increase the information from tissue images and so their contrast. This method involves different Mueller Coherency matrix based parameters, like the eigenvalues analysis, the entropy factor calculation, polarization components crosstalks, linear and circular polarization degrees, hermiticity or the Quaternions analysis in case depolarisation properties of tissue are sufficiently low. All these parameters make information appear clearer and so increase image contrast, so pathologies like cancer could be detected in a sooner stage of development. The election will depend on the concrete pathological process under study. This Mueller Coherency matrix method can be applied to a single tissue point, or it can be combined with a tomographic technique, so as to obtain a 3D representation of polarization contrast parameters in pathological tissues. The application of this analysis to concrete diseases can lead to tissue burn depth estimation or cancer early detection.

Lanczos algorithm with matrix product states for dynamical correlation functions

NASA Astrophysics Data System (ADS)

Dargel, P. E.; Wöllert, A.; Honecker, A.; McCulloch, I. P.; Schollwöck, U.; Pruschke, T.

2012-05-01

The density-matrix renormalization group (DMRG) algorithm can be adapted to the calculation of dynamical correlation functions in various ways which all represent compromises between computational efficiency and physical accuracy. In this paper we reconsider the oldest approach based on a suitable Lanczos-generated approximate basis and implement it using matrix product states (MPS) for the representation of the basis states. The direct use of matrix product states combined with an ex post reorthogonalization method allows us to avoid several shortcomings of the original approach, namely the multitargeting and the approximate representation of the Hamiltonian inherent in earlier Lanczos-method implementations in the DMRG framework, and to deal with the ghost problem of Lanczos methods, leading to a much better convergence of the spectral weights and poles. We present results for the dynamic spin structure factor of the spin-1/2 antiferromagnetic Heisenberg chain. A comparison to Bethe ansatz results in the thermodynamic limit reveals that the MPS-based Lanczos approach is much more accurate than earlier approaches at minor additional numerical cost.

Kernel K-Means Sampling for Nyström Approximation.

PubMed

He, Li; Zhang, Hong

2018-05-01

A fundamental problem in Nyström-based kernel matrix approximation is the sampling method by which training set is built. In this paper, we suggest to use kernel -means sampling, which is shown in our works to minimize the upper bound of a matrix approximation error. We first propose a unified kernel matrix approximation framework, which is able to describe most existing Nyström approximations under many popular kernels, including Gaussian kernel and polynomial kernel. We then show that, the matrix approximation error upper bound, in terms of the Frobenius norm, is equal to the -means error of data points in kernel space plus a constant. Thus, the -means centers of data in kernel space, or the kernel -means centers, are the optimal representative points with respect to the Frobenius norm error upper bound. Experimental results, with both Gaussian kernel and polynomial kernel, on real-world data sets and image segmentation tasks show the superiority of the proposed method over the state-of-the-art methods.

An efficient numerical method for the solution of the problem of elasticity for 3D-homogeneous elastic medium with cracks and inclusions

NASA Astrophysics Data System (ADS)

Kanaun, S.; Markov, A.

2017-06-01

An efficient numerical method for solution of static problems of elasticity for an infinite homogeneous medium containing inhomogeneities (cracks and inclusions) is developed. Finite number of heterogeneous inclusions and planar parallel cracks of arbitrary shapes is considered. The problem is reduced to a system of surface integral equations for crack opening vectors and volume integral equations for stress tensors inside the inclusions. For the numerical solution of these equations, a class of Gaussian approximating functions is used. The method based on these functions is mesh free. For such functions, the elements of the matrix of the discretized system are combinations of explicit analytical functions and five standard 1D-integrals that can be tabulated. Thus, the numerical integration is excluded from the construction of the matrix of the discretized problem. For regular node grids, the matrix of the discretized system has Toeplitz's properties, and Fast Fourier Transform technique can be used for calculation matrix-vector products of such matrices.

Electronic method for autofluorography of macromolecules on two-D matrices

DOEpatents

Davidson, Jackson B.; Case, Arthur L.

1983-01-01

A method for detecting, localizing, and quantifying macromolecules contained in a two-dimensional matrix is provided which employs a television-based position sensitive detection system. A molecule-containing matrix may be produced by conventional means to produce spots of light at the molecule locations which are detected by the television system. The matrix, such as a gel matrix, is exposed to an electronic camera system including an image-intensifier and secondary electron conduction camera capable of light integrating times of many minutes. A light image stored in the form of a charge image on the camera tube target is scanned by conventional television techniques, digitized, and stored in a digital memory. Intensity of any point on the image may be determined from the number at the memory address of the point. The entire image may be displayed on a television monitor for inspection and photographing or individual spots may be analyzed through selected readout of the memory locations. Compared to conventional film exposure methods, the exposure time may be reduced 100-1000 times.

A Comparison of Surface Acoustic Wave Modeling Methods

NASA Technical Reports Server (NTRS)

Wilson, W. c.; Atkinson, G. M.

2009-01-01

Surface Acoustic Wave (SAW) technology is low cost, rugged, lightweight, extremely low power and can be used to develop passive wireless sensors. For these reasons, NASA is investigating the use of SAW technology for Integrated Vehicle Health Monitoring (IVHM) of aerospace structures. To facilitate rapid prototyping of passive SAW sensors for aerospace applications, SAW models have been developed. This paper reports on the comparison of three methods of modeling SAWs. The three models are the Impulse Response Method a first order model, and two second order matrix methods; the conventional matrix approach, and a modified matrix approach that is extended to include internal finger reflections. The second order models are based upon matrices that were originally developed for analyzing microwave circuits using transmission line theory. Results from the models are presented with measured data from devices.

Measurement and calibration of differential Mueller matrix of distributed targets

NASA Technical Reports Server (NTRS)

Sarabandi, Kamal; Oh, Yisok; Ulaby, Fawwaz T.

1992-01-01

A rigorous method for calibrating polarimetric backscatter measurements of distributed targets is presented. By characterizing the radar distortions over the entire mainlobe of the antenna, the differential Mueller matrix is derived from the measured scattering matrices with a high degree of accuracy. It is shown that the radar distortions can be determined by measuring the polarimetric response of a metallic sphere over the main lobe of the antenna. Comparison of results obtained with the new algorithm with the results derived from the old calibration method show that the discrepancy between the two methods is less than 1 dB for the backscattering coefficients. The discrepancy is more drastic for the phase-difference statistics, indicating that removal of the radar distortions from the cross products of the scattering matrix elements cannot be accomplished with the traditional calibration methods.

A Transfer Learning Approach for Applying Matrix Factorization to Small ITS Datasets

ERIC Educational Resources Information Center

Voß, Lydia; Schatten, Carlotta; Mazziotti, Claudia; Schmidt-Thieme, Lars

2015-01-01

Machine Learning methods for Performance Prediction in Intelligent Tutoring Systems (ITS) have proven their efficacy; specific methods, e.g. Matrix Factorization (MF), however suffer from the lack of available information about new tasks or new students. In this paper we show how this problem could be solved by applying Transfer Learning (TL),…

RELAP-7 Software Verification and Validation Plan: Requirements Traceability Matrix (RTM) Part 1 – Physics and numerical methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Choi, Yong Joon; Yoo, Jun Soo; Smith, Curtis Lee

2015-09-01

This INL plan comprehensively describes the Requirements Traceability Matrix (RTM) on main physics and numerical method of the RELAP-7. The plan also describes the testing-based software verification and validation (SV&V) process—a set of specially designed software models used to test RELAP-7.

Graph-Theoretic Representations for Proximity Matrices through Strongly-Anti-Robinson or Circular Strongly-Anti-Robinson Matrices.

ERIC Educational Resources Information Center

Hubert, Lawrence; Arabie, Phipps; Meulman, Jacqueline

1998-01-01

Introduces a method for fitting order-constrained matrices that satisfy the strongly anti-Robinson restrictions (SAR). The method permits a representation of the fitted values in a (least-squares) SAR approximating matrix as lengths of paths in a graph. The approach is illustrated with a published proximity matrix. (SLD)

A SIMPLE AND RAPID MATRIX-ASSISTED LASER DESORPTION/IONIZATION TIME OF FLIGHT MASS SPECTROMETRY METHOD TO SCREEN FISH PLASMA SAMPLES FOR ESTROGEN-RESPONSIVE BIOMARKERS

EPA Science Inventory

In this study, we describe and evaluate the performance of a simple and rapid mass spectral method for screening fish plasma for estrogen-responsive biomarkers using matrix assisted laster desorption/ionization time of flight mass spectrometry (MALDI-TOF-MS) couopled with a short...

The Split Coefficient Matrix method for hyperbolic systems of gasdynamic equations

NASA Technical Reports Server (NTRS)

Chakravarthy, S. R.; Anderson, D. A.; Salas, M. D.

1980-01-01

The Split Coefficient Matrix (SCM) finite difference method for solving hyperbolic systems of equations is presented. This new method is based on the mathematical theory of characteristics. The development of the method from characteristic theory is presented. Boundary point calculation procedures consistent with the SCM method used at interior points are explained. The split coefficient matrices that define the method for steady supersonic and unsteady inviscid flows are given for several examples. The SCM method is used to compute several flow fields to demonstrate its accuracy and versatility. The similarities and differences between the SCM method and the lambda-scheme are discussed.

Bayesian Factor Analysis When Only a Sample Covariance Matrix Is Available

ERIC Educational Resources Information Center

Hayashi, Kentaro; Arav, Marina

2006-01-01

In traditional factor analysis, the variance-covariance matrix or the correlation matrix has often been a form of inputting data. In contrast, in Bayesian factor analysis, the entire data set is typically required to compute the posterior estimates, such as Bayes factor loadings and Bayes unique variances. We propose a simple method for computing…

Scale-Free Nonparametric Factor Analysis: A User-Friendly Introduction with Concrete Heuristic Examples.

ERIC Educational Resources Information Center

Mittag, Kathleen Cage

Most researchers using factor analysis extract factors from a matrix of Pearson product-moment correlation coefficients. A method is presented for extracting factors in a non-parametric way, by extracting factors from a matrix of Spearman rho (rank correlation) coefficients. It is possible to factor analyze a matrix of association such that…

Statistical Refinement of the Q-Matrix in Cognitive Diagnosis

ERIC Educational Resources Information Center

Chiu, Chia-Yi

2013-01-01

Most methods for fitting cognitive diagnosis models to educational test data and assigning examinees to proficiency classes require the Q-matrix that associates each item in a test with the cognitive skills (attributes) needed to answer it correctly. In most cases, the Q-matrix is not known but is constructed from the (fallible) judgments of…

Thermal and mechanical behavior of metal matrix and ceramic matrix composites

NASA Technical Reports Server (NTRS)

Kennedy, John M. (Editor); Moeller, Helen H. (Editor); Johnson, W. S. (Editor)

1990-01-01

The present conference discusses local stresses in metal-matrix composites (MMCs) subjected to thermal and mechanical loads, the computational simulation of high-temperature MMCs' cyclic behavior, an analysis of a ceramic-matrix composite (CMC) flexure specimen, and a plasticity analysis of fibrous composite laminates under thermomechanical loads. Also discussed are a comparison of methods for determining the fiber-matrix interface frictional stresses of CMCs, the monotonic and cyclic behavior of an SiC/calcium aluminosilicate CMC, the mechanical and thermal properties of an SiC particle-reinforced Al alloy MMC, the temperature-dependent tensile and shear response of a graphite-reinforced 6061 Al-alloy MMC, the fiber/matrix interface bonding strength of MMCs, and fatigue crack growth in an Al2O3 short fiber-reinforced Al-2Mg matrix MMC.

Adjustment of Pesticide Concentrations for Temporal Changes in Analytical Recovery, 1992-2006

USGS Publications Warehouse

Martin, Jeffrey D.; Stone, Wesley W.; Wydoski, Duane S.; Sandstrom, Mark W.

2009-01-01

Recovery is the proportion of a target analyte that is quantified by an analytical method and is a primary indicator of the analytical bias of a measurement. Recovery is measured by analysis of quality-control (QC) water samples that have known amounts of target analytes added ('spiked' QC samples). For pesticides, recovery is the measured amount of pesticide in the spiked QC sample expressed as percentage of the amount spiked, ideally 100 percent. Temporal changes in recovery have the potential to adversely affect time-trend analysis of pesticide concentrations by introducing trends in environmental concentrations that are caused by trends in performance of the analytical method rather than by trends in pesticide use or other environmental conditions. This report examines temporal changes in the recovery of 44 pesticides and 8 pesticide degradates (hereafter referred to as 'pesticides') that were selected for a national analysis of time trends in pesticide concentrations in streams. Water samples were analyzed for these pesticides from 1992 to 2006 by gas chromatography/mass spectrometry. Recovery was measured by analysis of pesticide-spiked QC water samples. Temporal changes in pesticide recovery were investigated by calculating robust, locally weighted scatterplot smooths (lowess smooths) for the time series of pesticide recoveries in 5,132 laboratory reagent spikes; 1,234 stream-water matrix spikes; and 863 groundwater matrix spikes. A 10-percent smoothing window was selected to show broad, 6- to 12-month time scale changes in recovery for most of the 52 pesticides. Temporal patterns in recovery were similar (in phase) for laboratory reagent spikes and for matrix spikes for most pesticides. In-phase temporal changes among spike types support the hypothesis that temporal change in method performance is the primary cause of temporal change in recovery. Although temporal patterns of recovery were in phase for most pesticides, recovery in matrix spikes was greater than recovery in reagent spikes for nearly every pesticide. Models of recovery based on matrix spikes are deemed more appropriate for adjusting concentrations of pesticides measured in groundwater and stream-water samples than models based on laboratory reagent spikes because (1) matrix spikes are expected to more closely match the matrix of environmental water samples than are reagent spikes and (2) method performance is often matrix dependent, as was shown by higher recovery in matrix spikes for most of the pesticides. Models of recovery, based on lowess smooths of matrix spikes, were developed separately for groundwater and stream-water samples. The models of recovery can be used to adjust concentrations of pesticides measured in groundwater or stream-water samples to 100 percent recovery to compensate for temporal changes in the performance (bias) of the analytical method.

Solution of nonlinear time-dependent PDEs through componentwise approximation of matrix functions

NASA Astrophysics Data System (ADS)

Cibotarica, Alexandru; Lambers, James V.; Palchak, Elisabeth M.

2016-09-01

Exponential propagation iterative (EPI) methods provide an efficient approach to the solution of large stiff systems of ODEs, compared to standard integrators. However, the bulk of the computational effort in these methods is due to products of matrix functions and vectors, which can become very costly at high resolution due to an increase in the number of Krylov projection steps needed to maintain accuracy. In this paper, it is proposed to modify EPI methods by using Krylov subspace spectral (KSS) methods, instead of standard Krylov projection methods, to compute products of matrix functions and vectors. Numerical experiments demonstrate that this modification causes the number of Krylov projection steps to become bounded independently of the grid size, thus dramatically improving efficiency and scalability. As a result, for each test problem featured, as the total number of grid points increases, the growth in computation time is just below linear, while other methods achieved this only on selected test problems or not at all.

Evaluation of the impact of matrix effect on quantification of pesticides in foods by gas chromatography-mass spectrometry using isotope-labeled internal standards.

PubMed

Yarita, Takashi; Aoyagi, Yoshie; Otake, Takamitsu

2015-05-29

The impact of the matrix effect in GC-MS quantification of pesticides in food using the corresponding isotope-labeled internal standards was evaluated. A spike-and-recovery study of nine target pesticides was first conducted using paste samples of corn, green soybean, carrot, and pumpkin. The observed analytical values using isotope-labeled internal standards were more accurate for most target pesticides than that obtained using the external calibration method, but were still biased from the spiked concentrations when a matrix-free calibration solution was used for calibration. The respective calibration curves for each target pesticide were also prepared using matrix-free calibration solutions and matrix-matched calibration solutions with blank soybean extract. The intensity ratio of the peaks of most target pesticides to that of the corresponding isotope-labeled internal standards was influenced by the presence of the matrix in the calibration solution; therefore, the observed slope varied. The ratio was also influenced by the type of injection method (splitless or on-column). These results indicated that matrix-matching of the calibration solution is required for very accurate quantification, even if isotope-labeled internal standards were used for calibration. Copyright © 2015 Elsevier B.V. All rights reserved.

A Deep Stochastic Model for Detecting Community in Complex Networks

NASA Astrophysics Data System (ADS)

Fu, Jingcheng; Wu, Jianliang

2017-01-01

Discovering community structures is an important step to understanding the structure and dynamics of real-world networks in social science, biology and technology. In this paper, we develop a deep stochastic model based on non-negative matrix factorization to identify communities, in which there are two sets of parameters. One is the community membership matrix, of which the elements in a row correspond to the probabilities of the given node belongs to each of the given number of communities in our model, another is the community-community connection matrix, of which the element in the i-th row and j-th column represents the probability of there being an edge between a randomly chosen node from the i-th community and a randomly chosen node from the j-th community. The parameters can be evaluated by an efficient updating rule, and its convergence can be guaranteed. The community-community connection matrix in our model is more precise than the community-community connection matrix in traditional non-negative matrix factorization methods. Furthermore, the method called symmetric nonnegative matrix factorization, is a special case of our model. Finally, based on the experiments on both synthetic and real-world networks data, it can be demonstrated that our algorithm is highly effective in detecting communities.

A Distributed-Memory Package for Dense Hierarchically Semi-Separable Matrix Computations Using Randomization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rouet, François-Henry; Li, Xiaoye S.; Ghysels, Pieter

In this paper, we present a distributed-memory library for computations with dense structured matrices. A matrix is considered structured if its off-diagonal blocks can be approximated by a rank-deficient matrix with low numerical rank. Here, we use Hierarchically Semi-Separable (HSS) representations. Such matrices appear in many applications, for example, finite-element methods, boundary element methods, and so on. Exploiting this structure allows for fast solution of linear systems and/or fast computation of matrix-vector products, which are the two main building blocks of matrix computations. The compression algorithm that we use, that computes the HSS form of an input dense matrix, reliesmore » on randomized sampling with a novel adaptive sampling mechanism. We discuss the parallelization of this algorithm and also present the parallelization of structured matrix-vector product, structured factorization, and solution routines. The efficiency of the approach is demonstrated on large problems from different academic and industrial applications, on up to 8,000 cores. Finally, this work is part of a more global effort, the STRUctured Matrices PACKage (STRUMPACK) software package for computations with sparse and dense structured matrices. Hence, although useful on their own right, the routines also represent a step in the direction of a distributed-memory sparse solver.« less

A Distributed-Memory Package for Dense Hierarchically Semi-Separable Matrix Computations Using Randomization

DOE PAGES

Rouet, François-Henry; Li, Xiaoye S.; Ghysels, Pieter; ...

2016-06-30

In this paper, we present a distributed-memory library for computations with dense structured matrices. A matrix is considered structured if its off-diagonal blocks can be approximated by a rank-deficient matrix with low numerical rank. Here, we use Hierarchically Semi-Separable (HSS) representations. Such matrices appear in many applications, for example, finite-element methods, boundary element methods, and so on. Exploiting this structure allows for fast solution of linear systems and/or fast computation of matrix-vector products, which are the two main building blocks of matrix computations. The compression algorithm that we use, that computes the HSS form of an input dense matrix, reliesmore » on randomized sampling with a novel adaptive sampling mechanism. We discuss the parallelization of this algorithm and also present the parallelization of structured matrix-vector product, structured factorization, and solution routines. The efficiency of the approach is demonstrated on large problems from different academic and industrial applications, on up to 8,000 cores. Finally, this work is part of a more global effort, the STRUctured Matrices PACKage (STRUMPACK) software package for computations with sparse and dense structured matrices. Hence, although useful on their own right, the routines also represent a step in the direction of a distributed-memory sparse solver.« less

Combined micromechanical and fabrication process optimization for metal-matrix composites

NASA Technical Reports Server (NTRS)

Morel, M.; Saravanos, D. A.; Chamis, C. C.

1991-01-01

A method is presented to minimize the residual matrix stresses in metal matrix composites. Fabrication parameters such as temperature and consolidation pressure are optimized concurrently with the characteristics (i.e., modulus, coefficient of thermal expansion, strength, and interphase thickness) of a fiber-matrix interphase. By including the interphase properties in the fabrication process, lower residual stresses are achievable. Results for an ultra-high modulus graphite (P100)/copper composite show a reduction of 21 percent for the maximum matrix microstress when optimizing the fabrication process alone. Concurrent optimization of the fabrication process and interphase properties show a 41 percent decrease in the maximum microstress. Therefore, this optimization method demonstrates the capability of reducing residual microstresses by altering the temperature and consolidation pressure histories and tailoring the interphase properties for an improved composite material. In addition, the results indicate that the consolidation pressures are the most important fabrication parameters, and the coefficient of thermal expansion is the most critical interphase property.

Fault detection of helicopter gearboxes using the multi-valued influence matrix method

NASA Technical Reports Server (NTRS)

Chin, Hsinyung; Danai, Kourosh; Lewicki, David G.

1993-01-01

In this paper we investigate the effectiveness of a pattern classifying fault detection system that is designed to cope with the variability of fault signatures inherent in helicopter gearboxes. For detection, the measurements are monitored on-line and flagged upon the detection of abnormalities, so that they can be attributed to a faulty or normal case. As such, the detection system is composed of two components, a quantization matrix to flag the measurements, and a multi-valued influence matrix (MVIM) that represents the behavior of measurements during normal operation and at fault instances. Both the quantization matrix and influence matrix are tuned during a training session so as to minimize the error in detection. To demonstrate the effectiveness of this detection system, it was applied to vibration measurements collected from a helicopter gearbox during normal operation and at various fault instances. The results indicate that the MVIM method provides excellent results when the full range of faults effects on the measurements are included in the training set.

Concurrent micromechanical tailoring and fabrication process optimization for metal-matrix composites

NASA Technical Reports Server (NTRS)

Morel, M.; Saravanos, D. A.; Chamis, Christos C.

1990-01-01

A method is presented to minimize the residual matrix stresses in metal matrix composites. Fabrication parameters such as temperature and consolidation pressure are optimized concurrently with the characteristics (i.e., modulus, coefficient of thermal expansion, strength, and interphase thickness) of a fiber-matrix interphase. By including the interphase properties in the fabrication process, lower residual stresses are achievable. Results for an ultra-high modulus graphite (P100)/copper composite show a reduction of 21 percent for the maximum matrix microstress when optimizing the fabrication process alone. Concurrent optimization of the fabrication process and interphase properties show a 41 percent decrease in the maximum microstress. Therefore, this optimization method demonstrates the capability of reducing residual microstresses by altering the temperature and consolidation pressure histories and tailoring the interphase properties for an improved composite material. In addition, the results indicate that the consolidation pressures are the most important fabrication parameters, and the coefficient of thermal expansion is the most critical interphase property.

MALDI-MS analysis and theoretical evaluation of olanzapine as a UV laser desorption ionization (LDI) matrix.

PubMed

Musharraf, Syed Ghulam; Ameer, Mariam; Ali, Arslan

2017-01-05

Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) being soft ionization technique, has become a method of choice for high-throughput analysis of proteins and peptides. In this study, we have explored the potential of atypical anti-psychotic drug olanzapine (OLZ) as a matrix for MALDI-MS analysis of peptides aided with the theoretical studies. Seven small peptides were employed as target analytes to check performance of olanzapine and compared with conventional MALDI matrix α-cyano-4-hydroxycinnamic acid (HCCA). All peptides were successfully detected when olanzapine was used as a matrix. Moreover, peptides angiotensin Ι and angiotensin ΙΙ were detected with better S/N ratio and resolution with this method as compared to their analysis by HCCA. Computational studies were performed to determine the thermochemical properties of olanzapine in order to further evaluate its similarity to MALDI matrices which were found in good agreement with the data of existing MALDI matrices. Copyright © 2016. Published by Elsevier B.V.

The effect of process parameters in Aluminum Metal Matrix Composites with Powder Metallurgy

NASA Astrophysics Data System (ADS)

Vani, Vemula Vijaya; Chak, Sanjay Kumar

2018-06-01

Metal Matrix Composites are developed in recent years as an alternative over conventional engineering materials due to their improved properties. Among all, Aluminium Matrix Composites (AMCs) are increasing their demand due to low density, high strength-to-weight ratio, high toughness, corrosion resistance, higher stiffness, improved wear resistance, increased creep resistance, low co-efficient of thermal expansion, improved high temperature properties. Major applications of these materials have been in aerospace, automobile, military. There are different processing techniques for the fabrication of AMCs. Powder metallurgy is a one of the most promising and versatile routes for fabrication of particle reinforced AMCs as compared to other manufacturing methods. This method ensures the good wettability between matrix and reinforcement, homogeneous microstructure of the fabricated MMC, and prevents the formation of any undesirable phases. This article addresses mainly on the effect of process parameters like sintering time, temperature and particle size on the microstructure of aluminum metal matrix composites.

A general parallel sparse-blocked matrix multiply for linear scaling SCF theory

NASA Astrophysics Data System (ADS)

Challacombe, Matt

2000-06-01

A general approach to the parallel sparse-blocked matrix-matrix multiply is developed in the context of linear scaling self-consistent-field (SCF) theory. The data-parallel message passing method uses non-blocking communication to overlap computation and communication. The space filling curve heuristic is used to achieve data locality for sparse matrix elements that decay with “separation”. Load balance is achieved by solving the bin packing problem for blocks with variable size.With this new method as the kernel, parallel performance of the simplified density matrix minimization (SDMM) for solution of the SCF equations is investigated for RHF/6-31G ∗∗ water clusters and RHF/3-21G estane globules. Sustained rates above 5.7 GFLOPS for the SDMM have been achieved for (H 2 O) 200 with 95 Origin 2000 processors. Scalability is found to be limited by load imbalance, which increases with decreasing granularity, due primarily to the inhomogeneous distribution of variable block sizes.

Cladding material, tube including such cladding material and methods of forming the same

DOE Office of Scientific and Technical Information (OSTI.GOV)

Garnier, John E.; Griffith, George W.

A multi-layered cladding material including a ceramic matrix composite and a metallic material, and a tube formed from the cladding material. The metallic material forms an inner liner of the tube and enables hermetic sealing of thereof. The metallic material at ends of the tube may be exposed and have an increased thickness enabling end cap welding. The metallic material may, optionally, be formed to infiltrate voids in the ceramic matrix composite, the ceramic matrix composite encapsulated by the metallic material. The ceramic matrix composite includes a fiber reinforcement and provides increased mechanical strength, stiffness, thermal shock resistance and highmore » temperature load capacity to the metallic material of the inner liner. The tube may be used as a containment vessel for nuclear fuel used in a nuclear power plant or other reactor. Methods for forming the tube comprising the ceramic matrix composite and the metallic material are also disclosed.« less

Proving Program Termination With Matrix Weighted Digraphs

NASA Technical Reports Server (NTRS)

Dutle, Aaron

2015-01-01

Program termination analysis is an important task in logic and computer science. While determining if a program terminates is known to be undecidable in general, there has been a significant amount of attention given to finding sufficient and computationally practical conditions to prove termination. One such method takes a program and builds from it a matrix weighted digraph. These are directed graphs whose edges are labeled by square matrices with entries in {-1,0,1}, equipped with a nonstandard matrix multiplication. Certain properties of this digraph are known to imply the termination of the related program. In particular, termination of the program can be determined from the weights of the circuits in the digraph. In this talk, the motivation for addressing termination and how matrix weighted digraphs arise will be briefly discussed. The remainder of the talk will describe an efficient method for bounding the weights of a finite set of the circuits in a matrix weighted digraph, which allows termination of the related program to be deduced.

A fast object-oriented Matlab implementation of the Reproducing Kernel Particle Method

NASA Astrophysics Data System (ADS)

Barbieri, Ettore; Meo, Michele

2012-05-01

Novel numerical methods, known as Meshless Methods or Meshfree Methods and, in a wider perspective, Partition of Unity Methods, promise to overcome most of disadvantages of the traditional finite element techniques. The absence of a mesh makes meshfree methods very attractive for those problems involving large deformations, moving boundaries and crack propagation. However, meshfree methods still have significant limitations that prevent their acceptance among researchers and engineers, namely the computational costs. This paper presents an in-depth analysis of computational techniques to speed-up the computation of the shape functions in the Reproducing Kernel Particle Method and Moving Least Squares, with particular focus on their bottlenecks, like the neighbour search, the inversion of the moment matrix and the assembly of the stiffness matrix. The paper presents numerous computational solutions aimed at a considerable reduction of the computational times: the use of kd-trees for the neighbour search, sparse indexing of the nodes-points connectivity and, most importantly, the explicit and vectorized inversion of the moment matrix without using loops and numerical routines.

Nanocrystal doped matrixes

DOEpatents

Parce, J. Wallace; Bernatis, Paul; Dubrow, Robert; Freeman, William P.; Gamoras, Joel; Kan, Shihai; Meisel, Andreas; Qian, Baixin; Whiteford, Jeffery A.; Ziebarth, Jonathan

2010-01-12

Matrixes doped with semiconductor nanocrystals are provided. In certain embodiments, the semiconductor nanocrystals have a size and composition such that they absorb or emit light at particular wavelengths. The nanocrystals can comprise ligands that allow for mixing with various matrix materials, including polymers, such that a minimal portion of light is scattered by the matrixes. The matrixes of the present invention can also be utilized in refractive index matching applications. In other embodiments, semiconductor nanocrystals are embedded within matrixes to form a nanocrystal density gradient, thereby creating an effective refractive index gradient. The matrixes of the present invention can also be used as filters and antireflective coatings on optical devices and as down-converting layers. Processes for producing matrixes comprising semiconductor nanocrystals are also provided. Nanostructures having high quantum efficiency, small size, and/or a narrow size distribution are also described, as are methods of producing indium phosphide nanostructures and core-shell nanostructures with Group II-VI shells.

Krylov subspace iterative methods for boundary element method based near-field acoustic holography.

PubMed

Valdivia, Nicolas; Williams, Earl G

2005-02-01

The reconstruction of the acoustic field for general surfaces is obtained from the solution of a matrix system that results from a boundary integral equation discretized using boundary element methods. The solution to the resultant matrix system is obtained using iterative regularization methods that counteract the effect of noise on the measurements. These methods will not require the calculation of the singular value decomposition, which can be expensive when the matrix system is considerably large. Krylov subspace methods are iterative methods that have the phenomena known as "semi-convergence," i.e., the optimal regularization solution is obtained after a few iterations. If the iteration is not stopped, the method converges to a solution that generally is totally corrupted by errors on the measurements. For these methods the number of iterations play the role of the regularization parameter. We will focus our attention to the study of the regularizing properties from the Krylov subspace methods like conjugate gradients, least squares QR and the recently proposed Hybrid method. A discussion and comparison of the available stopping rules will be included. A vibrating plate is considered as an example to validate our results.

Computational Study of Electron-Molecule Collisions Related to Low-Temperature Plasmas.

NASA Astrophysics Data System (ADS)

Huo, Winifred M.

1997-10-01

Computational study of electron-molecule collisions not only complements experimental measurements, but can also be used to investigate processes not readily accessible experimentally. A number of ab initio computational methods are available for this type of calculations. Here we describe a recently developed technique, the finite element Z-matrix method. Analogous to the R-matrix method, it partitions the space into regions and employs real matrix elements. However, unlike the implementation of the R-matrix method commonly used in atomic and molecular physics,(C. J. Gillan, J. Tennyson, and P. G. Burke, Chapter 10 in Computational Methods for Electron-Molecule Collisions), W. M. Huo and F. A. Gianturco, Editors, Plenum, New York (1995), p. 239. the Z-matrix method is fully variational.(D. Brown and J. C. Light, J. Chem. Phys. 101), 3723 (1994). In the present implementation, a mixed basis of finite elements and Gaussians is used to represent the continuum electron, thus offering full flexibility without imposing fixed boundary conditions. Numerical examples include the electron-impact dissociation of N2 via the metastable A^3Σ_u^+ state, a process which may be important in the lower thermosphere, and the dissociation of the CF radical, a process of interest to plasma etching. To understand the dissociation pathways, large scale quantum chemical calculations have been carried out for all target states which dissociate to the lowest five limits in the case of N_2, and to the lowest two limits in the case of CF. For N_2, the structural calculations clearly show the preference for predissociation if the initial state is the ground X^1Σ_g^+ state, but direct dissociation appears to be preferable if the initial state is the A^3Σ_u^+ state. Multi-configuration SCF target functions are used in the collisional calculation,

Evaluation of the confusion matrix method in the validation of an automated system for measuring feeding behaviour of cattle.

PubMed

Ruuska, Salla; Hämäläinen, Wilhelmiina; Kajava, Sari; Mughal, Mikaela; Matilainen, Pekka; Mononen, Jaakko

2018-03-01

The aim of the present study was to evaluate empirically confusion matrices in device validation. We compared the confusion matrix method to linear regression and error indices in the validation of a device measuring feeding behaviour of dairy cattle. In addition, we studied how to extract additional information on classification errors with confusion probabilities. The data consisted of 12 h behaviour measurements from five dairy cows; feeding and other behaviour were detected simultaneously with a device and from video recordings. The resulting 216 000 pairs of classifications were used to construct confusion matrices and calculate performance measures. In addition, hourly durations of each behaviour were calculated and the accuracy of measurements was evaluated with linear regression and error indices. All three validation methods agreed when the behaviour was detected very accurately or inaccurately. Otherwise, in the intermediate cases, the confusion matrix method and error indices produced relatively concordant results, but the linear regression method often disagreed with them. Our study supports the use of confusion matrix analysis in validation since it is robust to any data distribution and type of relationship, it makes a stringent evaluation of validity, and it offers extra information on the type and sources of errors. Copyright © 2018 Elsevier B.V. All rights reserved.

Limited-memory BFGS based least-squares pre-stack Kirchhoff depth migration

NASA Astrophysics Data System (ADS)

Wu, Shaojiang; Wang, Yibo; Zheng, Yikang; Chang, Xu

2015-08-01

Least-squares migration (LSM) is a linearized inversion technique for subsurface reflectivity estimation. Compared to conventional migration algorithms, it can improve spatial resolution significantly with a few iterative calculations. There are three key steps in LSM, (1) calculate data residuals between observed data and demigrated data using the inverted reflectivity model; (2) migrate data residuals to form reflectivity gradient and (3) update reflectivity model using optimization methods. In order to obtain an accurate and high-resolution inversion result, the good estimation of inverse Hessian matrix plays a crucial role. However, due to the large size of Hessian matrix, the inverse matrix calculation is always a tough task. The limited-memory BFGS (L-BFGS) method can evaluate the Hessian matrix indirectly using a limited amount of computer memory which only maintains a history of the past m gradients (often m < 10). We combine the L-BFGS method with least-squares pre-stack Kirchhoff depth migration. Then, we validate the introduced approach by the 2-D Marmousi synthetic data set and a 2-D marine data set. The results show that the introduced method can effectively obtain reflectivity model and has a faster convergence rate with two comparison gradient methods. It might be significant for general complex subsurface imaging.

More efficient parameter estimates for factor analysis of ordinal variables by ridge generalized least squares.

PubMed

Yuan, Ke-Hai; Jiang, Ge; Cheng, Ying

2017-11-01

Data in psychology are often collected using Likert-type scales, and it has been shown that factor analysis of Likert-type data is better performed on the polychoric correlation matrix than on the product-moment covariance matrix, especially when the distributions of the observed variables are skewed. In theory, factor analysis of the polychoric correlation matrix is best conducted using generalized least squares with an asymptotically correct weight matrix (AGLS). However, simulation studies showed that both least squares (LS) and diagonally weighted least squares (DWLS) perform better than AGLS, and thus LS or DWLS is routinely used in practice. In either LS or DWLS, the associations among the polychoric correlation coefficients are completely ignored. To mend such a gap between statistical theory and empirical work, this paper proposes new methods, called ridge GLS, for factor analysis of ordinal data. Monte Carlo results show that, for a wide range of sample sizes, ridge GLS methods yield uniformly more accurate parameter estimates than existing methods (LS, DWLS, AGLS). A real-data example indicates that estimates by ridge GLS are 9-20% more efficient than those by existing methods. Rescaled and adjusted test statistics as well as sandwich-type standard errors following the ridge GLS methods also perform reasonably well. © 2017 The British Psychological Society.

Analysis of the release process of phenylpropanolamine hydrochloride from ethylcellulose matrix granules V. Release properties of ethylcellulose layered matrix granules.

PubMed

Fukui, Atsuko; Fujii, Ryuta; Yonezawa, Yorinobu; Sunada, Hisakazu

2008-04-01

In the pharmaceutical preparation of a controlled release drug, it is very important and necessary to understand the release properties. In previous papers, a combination of the square-root time law and cube-root law equations was confirmed to be a useful equation for qualitative treatment. It was also confirmed that the combination equation could analyze the release properties of layered granules as well as matrix granules. The drug release property from layered granules is different from that of matrix granules. A time lag occurs before release, and the entire release property of layered granules was analyzed using the combination of the square-root time law and cube-root law equations. It is considered that the analysis method is very useful and efficient for both matrix and layered granules. Comparing the granulation methods, it is easier to control the manufacturing process by tumbling granulation (method B) than by tumbling-fluidized bed granulation (method C). Ethylcellulose (EC) layered granulation by a fluidized bed granulator might be convenient for the preparation of controlled release dosage forms as compared with a tumbling granulator, because the layered granules prepared by the fluidized bed granulator can granulate and dry at the same time. The time required for drying by the fluidized bed granulator is shorter than that by the tumbling granulator, so the fluidized bed granulator is convenient for preparation of granules in handling and shorter processing time than the tumbling granulator. It was also suggested that the EC layered granules prepared by the fluidized bed granulator were suitable for a controlled release system as well as the EC matrix granules.

Electroless plating of silver nanoparticles on porous silicon for laser desorption/ionization mass spectrometry

NASA Astrophysics Data System (ADS)

Yan, Hong; Xu, Ning; Huang, Wen-Yi; Han, Huan-Mei; Xiao, Shou-Jun

2009-03-01

An improved DIOS (desorption ionization on porous silicon) method for laser desorption/ionization mass spectrometry (LDI MS) by electroless plating of silver nanoparticles (AgNPs) on porous silicon (PSi) was developed. By addition of 4-aminothiophenol (4-ATP) into the AgNO3 plating solution, the plating speed can be slowed down and simultaneously 4-ATP self-assembled monolayers (SAMs) on AgNPs (4-ATP/AgNPs) were formed. Both AgNPs and 4-ATP/AgNPs coated PSi substrates present much higher stability, sensitivity and reproducibility for LDI MS than the un-treated porous silicon ones. Their shelf life in air was tested for several weeks to a month and their mass spectra still displayed the same high quality and sensitivity as the freshly prepared ones. And more 4-ATP SAMs partly play a role of matrix to increase the ionization efficiency. A small organic molecule of tetrapyridinporphyrin (TPyP), oligomers of polyethylene glycol (PEG 400 and 2300), and a peptide of oxytocin were used as examples to demonstrate the feasibility of the silver-plated PSi as a matrix-free-like method for LDI MS. This approach can obtain limits of detection to femtomoles for TPyP, subpicomoles for oxytocin, and picomoles for PEG 400 and 2300, comparable to the traditional matrix method and much better than the DIOS method. It simplifies the sample preparation as a matrix-free-like method without addition of matrix molecules and homogenizes the sample spread over the spot for better and more even mass signals.

Application of Wave Distribution Function Method to the ERG/PWE Data

NASA Astrophysics Data System (ADS)

Ota, M.; Kasahara, Y.; Matsuda, S.; Kojima, H.; Matsuoka, A.; Hikishima, M.; Kasaba, Y.; Ozaki, M.; Yagitani, S.; Tsuchiya, F.; Kumamoto, A.

2017-12-01

The ERG (Arase) satellite was launched on 20 December 2016 to study acceleration and loss mechanisms of relativistic electrons in the Earth's magnetosphere. The Plasma Wave Experiment (PWE), which is one of the science instruments on board the ERG satellite, measures electric field and magnetic field. The PWE consists of three sub-systems; EFD (Electric Field Detector), OFA/WFC (Onboard Frequency Analyzer and Waveform Capture), and HFA (High Frequency Analyzer).The OFA/WFC measures electromagnetic field spectra and raw waveforms in the frequency range from few Hz to 20 kHz. The OFA produces three kind of data; OFA-SPEC (power spectrum), OFA-MATRIX (spectral matrix), and OFA-COMPLEX (complex spectrum). The OFA-MATRIX measures ensemble averaged complex cross-spectra of two electric field components, and of three magnetic field components. The OFA-COMPLEX measures instantaneous complex spectra of electric and magnetic fields. These data are produced every 8 seconds in the nominal mode, and it can be used for polarization analysis and wave propagation direction finding.In general, spectral matrix composed by cross-spectra of observed signals is used for direction finding, and many algorithms have been proposed. For example, Means method and SVD method can be applied on the assumption that the spectral matrix is consists of a single plane wave, while wave distribution function (WDF) method is applicable even to the data in which multiple numbers of plane waves are simultaneously included. In this presentation, we introduce the results when the WDF method is applied to the ERG/PWE data.

A numerical scheme based on radial basis function finite difference (RBF-FD) technique for solving the high-dimensional nonlinear Schrödinger equations using an explicit time discretization: Runge-Kutta method

NASA Astrophysics Data System (ADS)

Dehghan, Mehdi; Mohammadi, Vahid

2017-08-01

In this research, we investigate the numerical solution of nonlinear Schrödinger equations in two and three dimensions. The numerical meshless method which will be used here is RBF-FD technique. The main advantage of this method is the approximation of the required derivatives based on finite difference technique at each local-support domain as Ωi. At each Ωi, we require to solve a small linear system of algebraic equations with a conditionally positive definite matrix of order 1 (interpolation matrix). This scheme is efficient and its computational cost is same as the moving least squares (MLS) approximation. A challengeable issue is choosing suitable shape parameter for interpolation matrix in this way. In order to overcome this matter, an algorithm which was established by Sarra (2012), will be applied. This algorithm computes the condition number of the local interpolation matrix using the singular value decomposition (SVD) for obtaining the smallest and largest singular values of that matrix. Moreover, an explicit method based on Runge-Kutta formula of fourth-order accuracy will be applied for approximating the time variable. It also decreases the computational costs at each time step since we will not solve a nonlinear system. On the other hand, to compare RBF-FD method with another meshless technique, the moving kriging least squares (MKLS) approximation is considered for the studied model. Our results demonstrate the ability of the present approach for solving the applicable model which is investigated in the current research work.

Hybrid matrix method for stable numerical analysis of the propagation of Dirac electrons in gapless bilayer graphene superlattices

NASA Astrophysics Data System (ADS)

Briones-Torres, J. A.; Pernas-Salomón, R.; Pérez-Álvarez, R.; Rodríguez-Vargas, I.

2016-05-01

Gapless bilayer graphene (GBG), like monolayer graphene, is a material system with unique properties, such as anti-Klein tunneling and intrinsic Fano resonances. These properties rely on the gapless parabolic dispersion relation and the chiral nature of bilayer graphene electrons. In addition, propagating and evanescent electron states coexist inherently in this material, giving rise to these exotic properties. In this sense, bilayer graphene is unique, since in most material systems in which Fano resonance phenomena are manifested an external source that provides extended states is required. However, from a numerical standpoint, the presence of evanescent-divergent states in the eigenfunctions linear superposition representing the Dirac spinors, leads to a numerical degradation (the so called Ωd problem) in the practical applications of the standard Coefficient Transfer Matrix (K) method used to study charge transport properties in Bilayer Graphene based multi-barrier systems. We present here a straightforward procedure based in the hybrid compliance-stiffness matrix method (H) that can overcome this numerical degradation. Our results show that in contrast to standard matrix method, the proposed H method is suitable to study the transmission and transport properties of electrons in GBG superlattice since it remains numerically stable regardless the size of the superlattice and the range of values taken by the input parameters: the energy and angle of the incident electrons, the barrier height and the thickness and number of barriers. We show that the matrix determinant can be used as a test of the numerical accuracy in real calculations.

Multireference configuration interaction theory using cumulant reconstruction with internal contraction of density matrix renormalization group wave function.

PubMed

Saitow, Masaaki; Kurashige, Yuki; Yanai, Takeshi

2013-07-28

We report development of the multireference configuration interaction (MRCI) method that can use active space scalable to much larger size references than has previously been possible. The recent development of the density matrix renormalization group (DMRG) method in multireference quantum chemistry offers the ability to describe static correlation in a large active space. The present MRCI method provides a critical correction to the DMRG reference by including high-level dynamic correlation through the CI treatment. When the DMRG and MRCI theories are combined (DMRG-MRCI), the full internal contraction of the reference in the MRCI ansatz, including contraction of semi-internal states, plays a central role. However, it is thought to involve formidable complexity because of the presence of the five-particle rank reduced-density matrix (RDM) in the Hamiltonian matrix elements. To address this complexity, we express the Hamiltonian matrix using commutators, which allows the five-particle rank RDM to be canceled out without any approximation. Then we introduce an approximation to the four-particle rank RDM by using a cumulant reconstruction from lower-particle rank RDMs. A computer-aided approach is employed to derive the exceedingly complex equations of the MRCI in tensor-contracted form and to implement them into an efficient parallel computer code. This approach extends to the size-consistency-corrected variants of MRCI, such as the MRCI+Q, MR-ACPF, and MR-AQCC methods. We demonstrate the capability of the DMRG-MRCI method in several benchmark applications, including the evaluation of single-triplet gap of free-base porphyrin using 24 active orbitals.