The complete and exact solution of the scattering of a TE mode frequency domain electromagnetic plane wave by a vertical dike under a conductive overburden has been established. An integral representation composed of one-sided Fourier transforms describes the scattered electric field components in each one of the five media: air, overburden, dike, and the country rocks on both sides of the dike. The determination of the terms of the series that represents the spectral components of the Fourier integrals requires the numerical inversion of a sparse matrix, and the method of successive approaches. The zero-order term of the series representation for the spectral components of the overburden, for given values of the electrical and geometrical parameters of the model, has been computed. This result allowed to determine an approximate value of the variation of the electric field on the top of the overburden in the direction perpendicular to the strike of the dike. The results demonstrate the efficiency of this forward electromagnetic modeling, and are fundamental for the interpretation of VLF and Magnetotelluric data. Estabelecemos a solução exata e completa do espalhamento de uma onda plana eletromagnética no domínio da freqüência e no modo elétrico transverso por um dique vertical soterrado por uma camada condutora. Uma representação integral composta de transformadas unilaterais de Fourier descreve os componentes do campo elétrico espalhado em cada um dos cinco meios: ar, cobertura, dique e as rochas encaixantes de cada lado do dique. A determinação dos termos da série que representa os componentes espectrais das integrais de Fourier requer a inversão numérica de uma matriz esparsa e o método das aproximações sucessivas. Calculamos o termo de ordem zero da série para os componentes espectrais da camada de cobertura, para valores especificados dos parâmetros geométricos e elétricos do modelo. Este resultado permitiu determinar um valor aproximado da variação do campo elétrico no contato entre o ar e a camada de cobertura em uma direção perpendicular ao traço do dique. Os resultados demonstram a eficiência desta modelagem eletromagnética direta, e são fundamentais para a interpretação de levantamentos geofísicos com os métodos VLF e Magnetotelúrico
RESUMO. Este trabalho investiga o padrão da distribuição espacial de partículas de carboneto de silício em uma liga de alumínio (Al/SiC) utilizando análise espacial espectral bidimensional. Esta técnica se baseia na transformada de Fourier da função de autocovariância amostral. A análise espectralé uma ferramenta poderosa para investigar o padrão espacial de pontos, uma vez que não assume características estruturais dos dados antes da análise e utiliza-se apenas da função espectral. As coordenadas dos centros das partículas foram adquiridas através de tecnicas de processamento de imagem. O espectro polar do periodograma e métodos de Monte-Carlo são usados para testar a hipótese de completa aleatoriedade espacial das partículas. Os resultados mostram que as partículas de carboneto de silício apresentam distribuição espacial completamente aleatória na liga de alumínio e que a análise espacial espectral pode ser uma ferramenta alternativa para investigar padrões de configurações pontuais no espaço. Palavras-chave: espectro polar, processos pontuais, propriedade de materiais, distribuição espacial.
A spatial point pattern is a collection of points irregularly located within a bounded area (2D) or space (3D) that have been generated by some form of stochastic mechanism. Examples of point patterns include locations of trees in a forest, of cases of a disease in a region, or of particles in a microscopic section of a composite material. Spatial Point pattern analysis is used mostly to determine the absence (completely spatial randomness) or presence (regularity and clustering) of spatial dependence structure of the locations. Methods based on the space domain are widely used for this purpose, while methods conducted in the frequency domain (spectral analysis) are still unknown to most researchers. Spectral analysis is a powerful tool to investigate spatial point patterns, since it does not assume any structural characteristics of the data (ex. isotropy), and uses only the autocovariance function, and its Fourier transform. There are some methods based on the spectral frameworks for analyzing 2D spatial point patterns. There is no such methods available for the 3D situation and, therefore, the aim of this work is to develop new methods based on spectral framework for the analysis of three-dimensional point patterns. The emphasis is on relating periodogram structure to the type of stochastic process which could have generated a 3D observed pattern. The results show that the methods based on spectral analysis developed in this work are able to identify patterns of three typical three-dimensional point processes, and can be used, concurrently, with analyzes in the space domain for a better characterization of spatial point patterns.
ABSTRACT. The use of Self-Organizing Map (SOM) algorithm for feature extraction and dimensionality reduction applied to underwater object detection with Low Frequency Electromagnetic Waves is presented. Computer simulation is used to generate a direct model for the study region, and a Self Organizing Map Algorithm is used to fit the data and return a similar model, with smaller dimensionality and same characteristics. Results show that virtual sensors are created by the SOM algorithm with consistent predictions, filling the resolution gap of the input data. These results are useful for fastening decision making algorithms by reducing the number of inputs to a group of significant data.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.