85 resultados para Mineração de dados (Computação)


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The experiment was carried out in green house with the objective of evaluating the effect of the bauxite mining residue in the rates of macronutrients in sugarcane and soil. Containers of 10 L were used. They received the following rates of bauxite residue: 0; 28; 56; 84; 112 and 140 t ha(-1). The used culture was the sugarcane (SP92 4221). The incorporation of the bauxite residue in the soil provided an increase in the levels of the soil macronutrients, and only for sulphur levels above 83 t ha(-1), it was possible to provide reductions of this nutrient. For rates of determined macronutrients in the leaf, levels above 70, 5; 125; 101; 56 t ha (-1) diminished the rates of nitrogen, phosphorum, potassium and sulphur, respectively. However, for calcium and magnesium the use of the residue provided the reduction of leaf rates. The level of the bauxite residue which had the largest production of dry mass was 64 t ha(-1).

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A arborização urbana em calçadas é fundamental para manutenção da qualidade de vida, proporcionando conforto aos habitantes das cidades. Contudo, existem problemas causados principalmente pela falta de planejamento na implantação e no manejo da arborização. O objetivo do presente trabalho foi a criação de um banco de dados relacional para auxiliar no cadastro informatizado, na avaliação e no manejo da arborização de vias públicas. Apresenta resultados sobre a valoração de indivíduos cadastrados, cálculo da diversidade entre os bairros, introdução de fotos digitais e relatórios para manejo em interface amigável, podendo servir de instrumento à manutenção da arborização e de vetor de comunicação para educação ambiental.

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O artigo relata parte de estudo desenvolvido junto ao Núcleo de Ensino de Araraquara para caracterizar o professorado que atua em cursos de Magistério (antigo Normal). Por meio de questionários foram obtidas e analisadas informações relativas a sexo, idade, estado civil, experiências anteriores e responsabilidade pelo sustento da família. A análise focaliza relações com o processo educativo, com outros estudos e com aspectos extra-escolares.

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

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As plantas aquáticas têm papel fundamental no equilíbrio dos ecossistemas, porém seu crescimento desequilibrado pode obstruir canais, represas e reservatórios e afetar múltiplos usos da água. em relação a plantas aquáticas submersas, a utilização de medidas de controle torna-se mais complexa, em face da dificuldade em mapear e quantificar volumetricamente as áreas colonizadas. Nessas situações, considera-se que o uso de dados hidroacústicos possibilite o mapeamento e a mensuração dessas áreas, auxiliando na elaboração de propostas de manejo sustentáveis desse tipo de vegetação aquática. Assim, o presente trabalho utilizou dados acústicos e a técnica de krigagem para realizar a inferência espacial do biovolume de plantas aquáticas submersas. Os dados foram obtidos em três levantamentos ecobatimétricos realizados em uma área de estudos localizada no rio Paraná, caracterizada por condições favoráveis para proliferação de vegetação aquática submersa e dificuldade de navegação. Para delimitar as áreas caracterizadas pela presença de plantas aquáticas submersas, utilizou-se uma imagem multiespectral de alta resolução espacial World View-2. O mapeamento do biovolume das plantas aquáticas submersas nas áreas de ocorrência do fenômeno foi realizado a partir da inferência do biovolume por krigagem e do fatiamento dos valores inferidos em intervalos de 15%. A partir do mapa gerado, foi possível identificar os locais de maior concentração de macrófitas submersas, com predominância de valores de biovolume entre 15-30% e 30-45%, confirmando a viabilidade da utilização da krigagem na inferência espacial do biovolume, a partir de medidas ecobatimétricas georreferenciadas e com o suporte de imagem de alta resolução espacial.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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This paper proposes a methodology for automatic extraction of building roof contours from a Digital Elevation Model (DEM), which is generated through the regularization of an available laser point cloud. The methodology is based on two steps. First, in order to detect high objects (buildings, trees etc.), the DEM is segmented through a recursive splitting technique and a Bayesian merging technique. The recursive splitting technique uses the quadtree structure for subdividing the DEM into homogeneous regions. In order to minimize the fragmentation, which is commonly observed in the results of the recursive splitting segmentation, a region merging technique based on the Bayesian framework is applied to the previously segmented data. The high object polygons are extracted by using vectorization and polygonization techniques. Second, the building roof contours are identified among all high objects extracted previously. Taking into account some roof properties and some feature measurements (e. g., area, rectangularity, and angles between principal axes of the roofs), an energy function was developed based on the Markov Random Field (MRF) model. The solution of this function is a polygon set corresponding to building roof contours and is found by using a minimization technique, like the Simulated Annealing (SA) algorithm. Experiments carried out with laser scanning DEM's showed that the methodology works properly, as it delivered roof contours with approximately 90% shape accuracy and no false positive was verified.

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This research presents a methodology for prediction of building shadows cast on urban roads existing on high-resolution aerial imagery. Shadow elements can be used in the modeling of contextual information, whose use has become more and more common in image analysis complex processes. The proposed methodology consists in three sequential steps. First, the building roof contours are manually extracted from an intensity image generated by the transformation of a digital elevation model (DEM) obtained from airborne laser scanning data. In similarly, the roadside contours are extracted, now from the radiometric information of the laser scanning data. Second, the roof contour polygons are projected onto the adjacent roads by using the parallel projection straight lines, whose directions are computed from the solar ephemeris, which depends on the aerial image acquisition time. Finally, parts of shadow polygons that are free from building perspective obstructions are determined, given rise to new shadow polygons. The results obtained in the experimental evaluation of the methodology showed that the method works properly, since it allowed the prediction of shadow in high-resolution imagery with high accuracy and reliability.

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In this paper, a methodology is proposed for the geometric refinement of laser scanning building roof contours using high-resolution aerial images and Markov Random Field (MRF) models. The proposed methodology takes for granted that the 3D description of each building roof reconstructed from the laser scanning data (i.e., a polyhedron) is topologically correct and that it is only necessary to improve its accuracy. Since roof ridges are accurately extracted from laser scanning data, our main objective is to use high-resolution aerial images to improve the accuracy of roof outlines. In order to meet this goal, the available roof contours are first projected onto the image-space. After that, the projected polygons and the straight lines extracted from the image are used to establish an MRF description, which is based on relations ( relative length, proximity, and orientation) between the two sets of straight lines. The energy function associated with the MRF is minimized by using a modified version of the brute force algorithm, resulting in the grouping of straight lines for each roof object. Finally, each grouping of straight lines is topologically reconstructed based on the topology of the corresponding laser scanning polygon projected onto the image-space. The preliminary results showed that the proposed methodology is promising, since most sides of the refined polygons are geometrically better than corresponding projected laser scanning straight lines.

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In this work a method is proposed to allow the indirect orientation of images using photogrammetric control extracted through integration of data derived from Photogrammetry and Light Detection and Ranging (LiDAR) system. The photogrammetric control is obtained by using an inverse photogrammetric model, which allows the projection of image space straight lines onto the object space. This mathematical model is developed based on the intersection between the collinearity-based straight line and a DSM of region, derived from LiDAR data. The mathematical model used in the indirect orientation of the image is known as the model of equivalent t planes. This mathematical model is based on the equivalence between the vector normal to the projection plane in the image space and to the vector normal to the rotated projection plane in the object space. The goal of this work is to verify the quality, efficiency and potential of photogrammetric control straight lines obtained with proposed method applied to the indirect orientation of images. The quality of generated photogrammetric control was statistically available and the results showed that proposed method is promising and it has potential for the indirect orientation of images.