100 resultados para Sparse matrices


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A new cryptographic hash function Whirlwind is presented. We give the full specification and explain the design rationale. We show how the hash function can be implemented efficiently in software and give first performance numbers. A detailed analysis of the security against state-of-the-art cryptanalysis methods is also provided. In comparison to the algorithms submitted to the SHA-3 competition, Whirlwind takes recent developments in cryptanalysis into account by design. Even though software performance is not outstanding, it compares favourably with the 512-bit versions of SHA-3 candidates such as LANE or the original CubeHash proposal and is about on par with ECHO and MD6.

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This paper presents results of research related to multicriteria decision making under information uncertainty. The Bell-man-Zadeh approach to decision making in a fuzzy environment is utilized for analyzing multicriteria optimization models (< X, M > models) under deterministic information. Its application conforms to the principle of guaranteed result and provides constructive lines in obtaining harmonious solutions on the basis of analyzing associated maxmin problems. This circumstance permits one to generalize the classic approach to considering the uncertainty of quantitative information (based on constructing and analyzing payoff matrices reflecting effects which can be obtained for different combinations of solution alternatives and the so-called states of nature) in monocriteria decision making to multicriteria problems. Considering that the uncertainty of information can produce considerable decision uncertainty regions, the resolving capacity of this generalization does not always permit one to obtain unique solutions. Taking this into account, a proposed general scheme of multicriteria decision making under information uncertainty also includes the construction and analysis of the so-called < X, R > models (which contain fuzzy preference relations as criteria of optimality) as a means for the subsequent contraction of the decision uncertainty regions. The paper results are of a universal character and are illustrated by a simple example. (c) 2007 Elsevier Inc. All rights reserved.

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A geometrical approach of the finite-element analysis applied to electrostatic fields is presented. This approach is particularly well adapted to teaching Finite Elements in Electrical Engineering courses at undergraduate level. The procedure leads to the same system of algebraic equations as that derived by classical approaches, such as variational principle or weighted residuals for nodal elements with plane symmetry. It is shown that the extension of the original procedure to three dimensions is straightforward, provided the domain be meshed in first-order tetrahedral elements. The element matrices are derived by applying Maxwell`s equations in integral form to suitably chosen surfaces in the finite-element mesh.

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The abrasive wear resistance of white cast iron was studied. The iron was solidified using two solidification rates of 1.5 and 15 degrees C/s. Mass loss was evaluated with tests of the type pin on abrasive disc using alumina of different sizes. Two matrices were tested: one predominantly austenitic and the other predominantly martensitic, containing M(3)C carbides. Samples with cooling rate of 15 degrees C/s showed higher hardness and more refined microstructure compared with those solidified at 1.5 degrees C/s. During the test, the movement of successive abrasives gave rise to the strain hardening of the austenite phase, leading to the attainment of similar levels of surface hardness, which explains why the wear rate showed no difference compared to the austenite samples with different solidification rates. For the austenitic matrix the wear rate seems to depend on the hardness of the worn surface and not on the hardness of the material without deformation. The austenitic samples showed cracking and fracture of M(3)C carbides. For the predominantly martensitic matrix, the wear rate was higher at the solidification rate of 1.5 degrees C/s, for grain size of 66 and 93 mu m. Higher abrasive sizes were found to produce greater penetration and strain hardening of austenitic matrices. However, martensitic iron produces more microcutting, increasing the wear rate of the material. The analysis of the worn surface by scanning electron microscopy indicated abrasive wear mechanisms such as: microcutting, microfatigue and microploughing. Yet, for the iron of austenitic matrix, the microploughing mechanism was more severe. (C) 2009 Elsevier B.V. All rights reserved.

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A Fe-22.5%Cr-4.53%Ni-3.0%Mo duplex stainless steel was solution treated at 1,325 A degrees C for 1 h, quenched in water and isothermally treated at 900 A degrees C for 5,000 s. The crystallography of austenite was studied using EBSD technique. Intragranular austenite particles formed from delta ferrite are shown to nucleate on inclusions, and to be subdivided in twin-related sub-particles. Intragranular austenite appears to have planar-only orientation relationships with the ferrite matrix, close to Kurdjumov-Sachs and Nishyiama-Wassermann, but not related to a conjugate direction. Samples treated at 900 A degrees C underwent sparse formation of sigma phase and pronounced growth of elongated austenite particles, very similar to acicular ferrite.

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Properties of hybrid films can be enhanced if their molecular architecture is controlled. In this paper, poly (p-phenylene vinylene) was mixed with stearic acid in order to form stable hybrid Langmuir monolayers. Surface properties of these films were investigated with measurements of surface pressure, and also with polarization modulation infrared reflection-absorption spectroscopy (PM-IRRAS). The films were transferred from the air-water interface to solid supports through the Langmuir-Blodgett technique, and the viability of the film as optical device was investigated with fluorescence spectroscopy. Comparing the fluorescent spectra for the polymer in solution, as a casting film, and as an LB film, the emission bands for LB films were narrower and appeared at lower wavelengths. The interactions between the film components and the design for the LB film may take advantage of the method to immobilize luminescent polymers in mixed ultrathin films adsorbed in solid matrices. (C) 2011 Elsevier B.V. All rights reserved.

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The practicability of estimating directional wave spectra based on a vessel`s 1st order response has been recently addressed by several researchers. Different alternatives regarding statistical inference methods and possible drawbacks that could arise from their application have been extensively discussed, with an apparent preference for estimations based on Bayesian inference algorithms. Most of the results on this matter, however, rely exclusively on numerical simulations or at best on few and sparse full-scale measurements, comprising a questionable basis for validation purposes. This paper discusses several issues that have recently been debated regarding the advantages of Bayesian inference and different alternatives for its implementation. Among those are the definition of the best set of input motions, the number of parameters required for guaranteeing smoothness of the spectrum in frequency and direction and how to determine their optimum values. These subjects are addressed in the light of an extensive experimental campaign performed with a small-scale model of an FPSO platform (VLCC hull), which was conducted in an ocean basin in Brazil. Tests involved long and short crested seas with variable levels of directional spreading and also bimodal conditions. The calibration spectra measured in the tank by means of an array of wave probes configured the paradigm for estimations. Results showed that a wide range of sea conditions could be estimated with good precision, even those with somewhat low peak periods. Some possible drawbacks that have been pointed out in previous works concerning the viability of employing large vessels for such a task are then refuted. Also, it is shown that a second parameter for smoothing the spectrum in frequency may indeed increase the accuracy in some situations, although the criterion usually proposed for estimating the optimum values (ABIC) demands large computational effort and does not seem adequate for practical on-board systems, which require expeditious estimations. (C) 2009 Elsevier Ltd. All rights reserved.

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We present a novel array RLS algorithm with forgetting factor that circumvents the problem of fading regularization, inherent to the standard exponentially-weighted RLS, by allowing for time-varying regularization matrices with generic structure. Simulations in finite precision show the algorithm`s superiority as compared to alternative algorithms in the context of adaptive beamforming.

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The classical approach for acoustic imaging consists of beamforming, and produces the source distribution of interest convolved with the array point spread function. This convolution smears the image of interest, significantly reducing its effective resolution. Deconvolution methods have been proposed to enhance acoustic images and have produced significant improvements. Other proposals involve covariance fitting techniques, which avoid deconvolution altogether. However, in their traditional presentation, these enhanced reconstruction methods have very high computational costs, mostly because they have no means of efficiently transforming back and forth between a hypothetical image and the measured data. In this paper, we propose the Kronecker Array Transform ( KAT), a fast separable transform for array imaging applications. Under the assumption of a separable array, it enables the acceleration of imaging techniques by several orders of magnitude with respect to the fastest previously available methods, and enables the use of state-of-the-art regularized least-squares solvers. Using the KAT, one can reconstruct images with higher resolutions than was previously possible and use more accurate reconstruction techniques, opening new and exciting possibilities for acoustic imaging.

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In Part I [""Fast Transforms for Acoustic Imaging-Part I: Theory,"" IEEE TRANSACTIONS ON IMAGE PROCESSING], we introduced the Kronecker array transform (KAT), a fast transform for imaging with separable arrays. Given a source distribution, the KAT produces the spectral matrix which would be measured by a separable sensor array. In Part II, we establish connections between the KAT, beamforming and 2-D convolutions, and show how these results can be used to accelerate classical and state of the art array imaging algorithms. We also propose using the KAT to accelerate general purpose regularized least-squares solvers. Using this approach, we avoid ill-conditioned deconvolution steps and obtain more accurate reconstructions than previously possible, while maintaining low computational costs. We also show how the KAT performs when imaging near-field source distributions, and illustrate the trade-off between accuracy and computational complexity. Finally, we show that separable designs can deliver accuracy competitive with multi-arm logarithmic spiral geometries, while having the computational advantages of the KAT.

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In this paper, we devise a separation principle for the finite horizon quadratic optimal control problem of continuous-time Markovian jump linear systems driven by a Wiener process and with partial observations. We assume that the output variable and the jump parameters are available to the controller. It is desired to design a dynamic Markovian jump controller such that the closed loop system minimizes the quadratic functional cost of the system over a finite horizon period of time. As in the case with no jumps, we show that an optimal controller can be obtained from two coupled Riccati differential equations, one associated to the optimal control problem when the state variable is available, and the other one associated to the optimal filtering problem. This is a separation principle for the finite horizon quadratic optimal control problem for continuous-time Markovian jump linear systems. For the case in which the matrices are all time-invariant we analyze the asymptotic behavior of the solution of the derived interconnected Riccati differential equations to the solution of the associated set of coupled algebraic Riccati equations as well as the mean square stabilizing property of this limiting solution. When there is only one mode of operation our results coincide with the traditional ones for the LQG control of continuous-time linear systems.

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In this paper we consider the existence of the maximal and mean square stabilizing solutions for a set of generalized coupled algebraic Riccati equations (GCARE for short) associated to the infinite-horizon stochastic optimal control problem of discrete-time Markov jump with multiplicative noise linear systems. The weighting matrices of the state and control for the quadratic part are allowed to be indefinite. We present a sufficient condition, based only on some positive semi-definite and kernel restrictions on some matrices, under which there exists the maximal solution and a necessary and sufficient condition under which there exists the mean square stabilizing solution fir the GCARE. We also present a solution for the discounted and long run average cost problems when the performance criterion is assumed be composed by a linear combination of an indefinite quadratic part and a linear part in the state and control variables. The paper is concluded with a numerical example for pension fund with regime switching.

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In contrast with the abundance of anatomical studies of secretory structures on aerial vegetative organs of Asteraceae species, the information about secretory structures on thickened subterranean organs is sparse. The aim of this study was to investigate the occurrence of secretory structures on thickened and nonthickened subterranean organs of seven Asteraceae species from three tribes: Eupatorieae (Chromolaena squalida and Gyptis lanigera), Vernonieae (Chresta sphaerocephala, Lessingianthus bardanoides, L. glabratus and Orthopappus angustifolius), and Plucheeae (Pterocaulon angustifolium). The specimens were collected in areas of cerrado, from the State of Sao Paulo, Brazil. All species of the tribe Vernonieae studied exhibited endodermic cells, other than the epithelial cells of the canal, with secretory activity in the roots. In C. sphaerocephala roots, two types of endodermic cell were found, but only one had secretory activity. Secretory canals were found in the tuberous and nontuberous roots of all studied species. These data agree with the results from the literature for Asteraceae species. Here, we describe for the first time in Asteraceae the presence of secretory idioblasts in C. sphaerocephala. Secretory trichomes are present in the Orthopappus angustifolius rhizophore. Histochemical tests have shown that all types of secretory structure possess substances containing lipids. (C) 2008 The Linnean Society of London.

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Mixed models have become important in analyzing the results of experiments, particularly those that require more complicated models (e.g., those that involve longitudinal data). This article describes a method for deriving the terms in a mixed model. Our approach extends an earlier method by Brien and Bailey to explicitly identify terms for which autocorrelation and smooth trend arising from longitudinal observations need to be incorporated in the model. At the same time we retain the principle that the model used should include, at least, all the terms that are justified by the randomization. This is done by dividing the factors into sets, called tiers, based on the randomization and determining the crossing and nesting relationships between factors. The method is applied to formulate mixed models for a wide range of examples. We also describe the mixed model analysis of data from a three-phase experiment to investigate the effect of time of refinement on Eucalyptus pulp from four different sources. Cubic smoothing splines are used to describe differences in the trend over time and unstructured covariance matrices between times are found to be necessary.

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Estimation of Taylor`s power law for species abundance data may be performed by linear regression of the log empirical variances on the log means, but this method suffers from a problem of bias for sparse data. We show that the bias may be reduced by using a bias-corrected Pearson estimating function. Furthermore, we investigate a more general regression model allowing for site-specific covariates. This method may be efficiently implemented using a Newton scoring algorithm, with standard errors calculated from the inverse Godambe information matrix. The method is applied to a set of biomass data for benthic macrofauna from two Danish estuaries. (C) 2011 Elsevier B.V. All rights reserved.