987 resultados para RM extended algorithm


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By introducing the scattering probability of a subsurface defect (SSD) and statistical distribution functions of SSD radius, refractive index, and position, we derive an extended bidirectional reflectance distribution function (BRDF) from the Jones scattering matrix. This function is applicable to the calculation for comparison with measurement of polarized light-scattering resulting from a SSD. A numerical calculation of the extended BRDF for the case of p-polarized incident light was performed by means of the Monte Carlo method. Our numerical results indicate that the extended BRDF strongly depends on the light incidence angle, the light scattering angle, and the out-of-plane azimuth angle. We observe a 180 degrees symmetry with respect to the azimuth angle. We further investigate the influence of the SSD density, the substrate refractive index, and the statistical distributions of the SSD radius and refractive index on the extended BRDF. For transparent substrates, we also find the dependence of the extended BRDF on the SSD positions. (c) 2006 Optical Society of America.

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The refractive indices of thin films, containing dielectric and voids in an oblique columnar structure, are modeled by extended effective medium in the quasi-static limit. The dielectric function is shown to be strongly dependent on the angle of incidence and on the columnar orientation for p-polarized light. This model is applied to model ZrO2 thin films with oblique columnar structures and the computed results, with the Maxwell Garnett, the Bragg-Pippard, and the Bruggeman formalisms, have been given. (c) 2004 Elsevier B.V. All rights reserved.

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This document aims to describe an update of the implementation of the J48Consolidated class within WEKA platform. The J48Consolidated class implements the CTC algorithm [2][3] which builds a unique decision tree based on a set of samples. The J48Consolidated class extends WEKA’s J48 class which implements the well-known C4.5 algorithm. This implementation was described in the technical report "J48Consolidated: An implementation of CTC algorithm for WEKA". The main, but not only, change in this update is the integration of the notion of coverage in order to determine the number of samples to be generated to build a consolidated tree. We define coverage as the percentage of examples of the training sample present in –or covered by– the set of generated subsamples. So, depending on the type of samples that we use, we will need more or less samples in order to achieve a specific value of coverage.

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The CTC algorithm, Consolidated Tree Construction algorithm, is a machine learning paradigm that was designed to solve a class imbalance problem, a fraud detection problem in the area of car insurance [1] where, besides, an explanation about the classification made was required. The algorithm is based on a decision tree construction algorithm, in this case the well-known C4.5, but it extracts knowledge from data using a set of samples instead of a single one as C4.5 does. In contrast to other methodologies based on several samples to build a classifier, such as bagging, the CTC builds a single tree and as a consequence, it obtains comprehensible classifiers. The main motivation of this implementation is to make public and available an implementation of the CTC algorithm. With this purpose we have implemented the algorithm within the well-known WEKA data mining environment http://www.cs.waikato.ac.nz/ml/weka/). WEKA is an open source project that contains a collection of machine learning algorithms written in Java for data mining tasks. J48 is the implementation of C4.5 algorithm within the WEKA package. We called J48Consolidated to the implementation of CTC algorithm based on the J48 Java class.

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We demonstrate that the surface relief guided-mode resonant gratings with specified central wavelength and FWHM in the visible wavelength range can be designed by analyzing the complex poles of Reflectance and transmission coefficient matrix algorithm (RTCM), a variant of S-matrix propagation algorithm proposed for calculation of multilayer gratings. In addition, FWHM is computed with couple-mode (CM) theory of resonant gratings which is firstly extended by Norton et al. in calculation of waveguide grating. Furthermore, the side band reflections of the filter can be reduced to less than 5% in the visible wavelength with the antireflection (AR) design technique widely used in the thin-film field. (C) 2008 Elsevier B.V. All rights reserved.

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Esta tese propôs uma metodologia para detecção de áreas susceptíveis a deslizamentos de terra a partir de imagens aéreas, culminando no desenvolvimento de uma ferramenta computacional, denominada SASD/T, para testar a metodologia. Para justificar esta pesquisa, um levantamento sobre os desastres naturais da história brasileira relacionada a deslizamentos de terra e as metodologias utilizadas para a detecção e análise de áreas susceptíveis a deslizamentos de terra foi realizado. Estudos preliminares de visualização 3D e conceitos relacionados ao mapeamento 3D foram realizados. Estereoscopia foi implementada para visualizar tridimensionalmente a região selecionada. As altitudes foram encontradas através de paralaxe, a partir dos pontos homólogos encontrados pelo algoritmo SIFT. Os experimentos foram realizados com imagens da cidade de Nova Friburgo. O experimento inicial mostrou que o resultado obtido utilizando SIFT em conjunto com o filtro proposto, foi bastante significativo ao ser comparado com os resultados de Fernandes (2008) e Carmo (2010), devido ao número de pontos homólogos encontrados e da superfície gerada. Para detectar os locais susceptíveis a deslizamentos, informações como altitude, declividade, orientação e curvatura foram extraídas dos pares estéreos e, em conjunto com as variáveis inseridas pelo usuário, forneceram uma análise de quão uma determinada área é susceptível a deslizamentos. A metodologia proposta pode ser estendida para a avaliação e previsão de riscos de deslizamento de terra de qualquer outra região, uma vez que permite a interação com o usuário, de modo que este especifique as características, os itens e as ponderações necessárias à análise em questão.