993 resultados para Processamentos de dados


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O presente trabalho consiste no desenvolvimento de uma interface gráfica para pré e pós-processamentos de dados elétricos e eletromagnéticos em geofísica utilizando-a na transformação da EGSLIB – Electrical Geophysics Software Library, a qual é constituída por um acervo de programas FORTRAN para DOS, em um software integrado e que possua uma eficiente interface gráfica com o usuário. O resultado deste esforço foi a surgimento de um produto que foi denominado EGS 2000 – Electrical Geophysics Suite - 2000 version. Construído em ambiente DELPHI da Borland, através de um processo de desenvolvimento que, além de orientado a objetos, foi centrado em uma arquitetura que permitiu um alto grau de aproveitamento de programas FORTRAN já desenvolvidos e testados. Tal produto, constitui-se em uma poderosa ferramenta de auxílio à modelagem e interpretação de dados geofísicos totalmente executável no sistema operacional MS-Windows. Com isso, alcançou-se uma forma economicamente viável para dar uma destinação prática aos resultados teóricos obtidos nas universidades e institutos de pesquisa. Os exemplos apresentados, mostram-nos que, auxiliadas por computador, modelagens e interpretações de dados geofísicos alcançam um nível de produtividade e versatilidade jamais obtidos pelas ferramentas de outrora, uma vez que diversos modelos podem ser armazenados e recuperados e seus resultados comparados com dados observados sistematicamente colecionados, conferindo ao processo um alto grau de confiabilidade e rapidez.

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Efetua uma análise sobre a Amplitude dos Problemas de Comunicação Intraorganizacional entre a Estrutura de Processamento de Dados e o restante de uma Organização e determina suas possíveis causas, com base no Modelo de Empresa como um Sistema Sócio-Técnico Aberto. Para tal fim: consulta-se não só bibliografia tradicional norte-americana como também brasileira e japonesa; adota-se uma postura tanto quanto eclética e também menos ortodoxa, sem no entanto se ter a pretensão de polemizar.

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Os processamentos de imagens orbitais efetuados através de técnicas de sensoriamento remoto geraram informações qualitativas de natureza textural (morfo-estruturas). Estas permitiram (1) o reconhecimento de áreas com diferentes padrões estruturais tendo diferentes potencialidades para a prospecção de fluorita, (2) a identificação de novos lineamentos estruturais potencialmente favoráveis à mineralização e (3) evidenciaram prolongamentos extensos para as principais estruturas mineralizadas, (4) às quais se associam um grande número de estruturas, antes desconhecidas, com grande potencial prospectivo. O aprimoramento de técnicas de classificação digital sobre produtos de razões de bandas e análise por componentes principais permitiu identificar a alteração hidrotermal associada às estruturas, incorporando novos critérios para a prospecção de fluorita. Buscando-se quantificar os dados de alteração hidrotermal, foi efetuada a análise espectrorradiométrica das rochas do distrito fluorítico. Integrando estas informações com dados TM LANDSAT 5, em nível de reflectância, obteve-se a classificação espectral das imagens orbitais, o que permitiu a identificação de estruturas menores com um detalhe nunca antes obtido. Os processamentos de dados aerogeofísicos forneceram resultados sobre estruturas (magnetometria) e corpos graníticos afetados por alteração hidrotermal (aerogamaespectrometria). Estes produtos foram integrados com dados TM LANDSAT 5 associando o atributo textural da imagem orbital ao comportamento radiométrico das rochas. Diagnosticou-se o lineamento Grão-Pará como o principal prospecto do distrito. E levantaram-se uma série de dados sobre a compartimentação tectônica da região, a zonação de fácies das rochas graníticas (rocha fonte do flúor) e as alterações hidrotermais associadas ao magmatismo granítico. Isto permitiu a compreensão da distribuição regional dos depósitos de fluorita, adicionando-se um novo critério à prospecção de fluorita, a relação espacial entre a mineralização e a rocha fonte de F. Esta última corresponde à fácies granítica da borda do Maciço Pedras Grandes.

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This work aims viewing weather information, by building isosurfaces enabling enjoy the advantages of three-dimensional geometric models, to communicate the meaning of the data used in a clear and efficient way. The evolving technology of data processing makes possible the interpretation of masses of data increasing, through robust algorithms. In meteorology, in particular, we can benefit from this fact, due to the large amount of data required for analysis and statistics. The manipulation of data, by users from other areas, is facilitated by the choice of algorithm and the tools involved in this work. The project was further developed into distinct modules, increasing their flexibility and reusability for future studies

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In the oil prospection research seismic data are usually irregular and sparsely sampled along the spatial coordinates due to obstacles in placement of geophones. Fourier methods provide a way to make the regularization of seismic data which are efficient if the input data is sampled on a regular grid. However, when these methods are applied to a set of irregularly sampled data, the orthogonality among the Fourier components is broken and the energy of a Fourier component may "leak" to other components, a phenomenon called "spectral leakage". The objective of this research is to study the spectral representation of irregularly sampled data method. In particular, it will be presented the basic structure of representation of the NDFT (nonuniform discrete Fourier transform), study their properties and demonstrate its potential in the processing of the seismic signal. In this way we study the FFT (fast Fourier transform) and the NFFT (nonuniform fast Fourier transform) which rapidly calculate the DFT (discrete Fourier transform) and NDFT. We compare the recovery of the signal using the FFT, DFT and NFFT. We approach the interpolation of seismic trace using the ALFT (antileakage Fourier transform) to overcome the problem of spectral leakage caused by uneven sampling. Applications to synthetic and real data showed that ALFT method works well on complex geology seismic data and suffers little with irregular spatial sampling of the data and edge effects, in addition it is robust and stable with noisy data. However, it is not as efficient as the FFT and its reconstruction is not as good in the case of irregular filling with large holes in the acquisition.

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In the oil prospection research seismic data are usually irregular and sparsely sampled along the spatial coordinates due to obstacles in placement of geophones. Fourier methods provide a way to make the regularization of seismic data which are efficient if the input data is sampled on a regular grid. However, when these methods are applied to a set of irregularly sampled data, the orthogonality among the Fourier components is broken and the energy of a Fourier component may "leak" to other components, a phenomenon called "spectral leakage". The objective of this research is to study the spectral representation of irregularly sampled data method. In particular, it will be presented the basic structure of representation of the NDFT (nonuniform discrete Fourier transform), study their properties and demonstrate its potential in the processing of the seismic signal. In this way we study the FFT (fast Fourier transform) and the NFFT (nonuniform fast Fourier transform) which rapidly calculate the DFT (discrete Fourier transform) and NDFT. We compare the recovery of the signal using the FFT, DFT and NFFT. We approach the interpolation of seismic trace using the ALFT (antileakage Fourier transform) to overcome the problem of spectral leakage caused by uneven sampling. Applications to synthetic and real data showed that ALFT method works well on complex geology seismic data and suffers little with irregular spatial sampling of the data and edge effects, in addition it is robust and stable with noisy data. However, it is not as efficient as the FFT and its reconstruction is not as good in the case of irregular filling with large holes in the acquisition.

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In this work, the quantitative analysis of glucose, triglycerides and cholesterol (total and HDL) in both rat and human blood plasma was performed without any kind of pretreatment of samples, by using near infrared spectroscopy (NIR) combined with multivariate methods. For this purpose, different techniques and algorithms used to pre-process data, to select variables and to build multivariate regression models were compared between each other, such as partial least squares regression (PLS), non linear regression by artificial neural networks, interval partial least squares regression (iPLS), genetic algorithm (GA), successive projections algorithm (SPA), amongst others. Related to the determinations of rat blood plasma samples, the variables selection algorithms showed satisfactory results both for the correlation coefficients (R²) and for the values of root mean square error of prediction (RMSEP) for the three analytes, especially for triglycerides and cholesterol-HDL. The RMSEP values for glucose, triglycerides and cholesterol-HDL obtained through the best PLS model were 6.08, 16.07 e 2.03 mg dL-1, respectively. In the other case, for the determinations in human blood plasma, the predictions obtained by the PLS models provided unsatisfactory results with non linear tendency and presence of bias. Then, the ANN regression was applied as an alternative to PLS, considering its ability of modeling data from non linear systems. The root mean square error of monitoring (RMSEM) for glucose, triglycerides and total cholesterol, for the best ANN models, were 13.20, 10.31 e 12.35 mg dL-1, respectively. Statistical tests (F and t) suggest that NIR spectroscopy combined with multivariate regression methods (PLS and ANN) are capable to quantify the analytes (glucose, triglycerides and cholesterol) even when they are present in highly complex biological fluids, such as blood plasma

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Pós-graduação em Matemática em Rede Nacional - IBILCE

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Self-organizing maps (SOM) are artificial neural networks widely used in the data mining field, mainly because they constitute a dimensionality reduction technique given the fixed grid of neurons associated with the network. In order to properly the partition and visualize the SOM network, the various methods available in the literature must be applied in a post-processing stage, that consists of inferring, through its neurons, relevant characteristics of the data set. In general, such processing applied to the network neurons, instead of the entire database, reduces the computational costs due to vector quantization. This work proposes a post-processing of the SOM neurons in the input and output spaces, combining visualization techniques with algorithms based on gravitational forces and the search for the shortest path with the greatest reward. Such methods take into account the connection strength between neighbouring neurons and characteristics of pattern density and distances among neurons, both associated with the position that the neurons occupy in the data space after training the network. Thus, the goal consists of defining more clearly the arrangement of the clusters present in the data. Experiments were carried out so as to evaluate the proposed methods using various artificially generated data sets, as well as real world data sets. The results obtained were compared with those from a number of well-known methods existent in the literature

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This work focuses the geomorphological characterization and spatial data modeling in the shallow continental shelf within the Folha Touros limits (SB-25-CV-II), based on bathymetric data analysis and remote sensing products interpretation. The Rio Grande do Norte state is located in northeastern Brazil and the work area is located at the transition region between the eastern and northern portions of their coast. The bathymetric surveys were conduced between march and may 2009, using a 10 meters long vessel and 0.70 meters draught, equipped with global positioning system and echo sounder (dual beam, 200KHz , 14°). The fieldwork resulted in 44 bathymetric profiles espaced 1.5 km and 30 km average length. The bathymetric data amount were 111,200 points and were navigated 1395.7 km within na area about 1,850 km2. The bathymetric data were corrected for the tide level, vessel draught and were subsequently entered into a geographic information system for further processing. Analysis of remote sensing products was carried out using Landsat 7/ETM + band 1, from november 1999. The image was used for visualization and mapping submerged features. The results showed the presence of geomorphological features within the study area. Were observed, from the analysis of local bathymetry and satellite image, seven types of geomorphological features. The channels, with two longitudinals channels (e. g. San Roque and Cioba channels) and other perpendicular to the coast (e. g. Touros, Pititinga and Barretas). Coastal reef formations (Maracajaú, Rio do Fogo and Cioba). Longitudinal waves, described in the literature as longitudinal dunes. The occurrence of a transverse dune field. Another feature observed was the oceanic reefs, an rock alignment parallel to the coast. Were identified four riscas , from north to south: risca do Liso, Gameleira, Zumbi, Pititinga (the latter being described for the first time). Finally, an oceanic terrace was observed in the deepest area of study. Image interpretation corroborated with the in situ results, enabling visualization and description for all features in the region. The results were analysed in an integrating method (using the diferent methodologies applied in this work) and it was essential to describe all features in the area. This method allowed us to evaluate which methods generated better results to describe certain features. From these results was possible to prove the existence of submerged features in the eastern shallow continental shelf of Rio Grande do Norte. In this way, the conclusions was (1) this study contributed to the provision of new information about the area in question, particularly with regard to data collection in situ depths, (2) the method of data collection and interpretation proves to be effective because, through this, it was possible to visualize and interpret the features present in the study area and (3) the interpretation and discussion of results in an integrated method, using different methodologies, can provide better results

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Pós-graduação em Ciência da Computação - IBILCE