6 resultados para Smart Campus

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo


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In this paper we address the "skull-stripping" problem in 3D MR images. We propose a new method that employs an efficient and unique histogram analysis. A fundamental component of this analysis is an algorithm for partitioning a histogram based on the position of the maximum deviation from a Gaussian fit. In our experiments we use a comprehensive image database, including both synthetic and real MRI. and compare our method with other two well-known methods, namely BSE and BET. For all datasets we achieved superior results. Our method is also highly independent of parameter tuning and very robust across considerable variations of noise ratio.

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The purpose of this article is to present a method which consists in the development of unit cell numerical models for smart composite materials with piezoelectric fibers made of PZT embedded in a non-piezoelectric matrix (epoxy resin). This method evaluates a globally homogeneous medium equivalent to the original composite, using a representative volume element (RVE). The suitable boundary conditions allow the simulation of all modes of the overall deformation arising from any arbitrary combination of mechanical and electrical loading. In the first instance, the unit cell is applied to predict the effective material coefficients of the transversely isotropic piezoelectric composite with circular cross section fibers. The numerical results are compared to other methods reported in the literature and also to results previously published, in order to evaluate the method proposal. In the second step, the method is applied to calculate the equivalent properties for smart composite materials with square cross section fibers. Results of comparison between different combinations of circular and square fiber geometries, observing the influence of the boundary conditions and arrangements are presented.

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In this work, some TDEM (Time Domain Electromagnetic) results at USP (University of Sao Paulo) campus in Sao Paulo city, Brazil, are presented. The data were acquired focusing on two mains objectives: (i) to map geoelectrical stratigraphy of Sao Paulo sedimentary basin, emphasizing on hydrogeological studies about sedimentary and crystalline aquifers, and (ii) to analyze the viability of TDEM data acquisition use in urban environment. The study area is located in Sao Paulo basin border, characterized by Resende and Sao Paulo formations, which are constituted by sand-clays sediments over a granite-gneissic basement. Two equipments were used in order to acquire database: Protem47 (low power), and Protem57-MK2 (high power). Capacitive noise affect obtained data with Protem47 due to the presence of metal pipes buried at IAG/USP (Institute of Astronomy, Geophysics, and Atmospheric Science) test site at USP. On the other hand, capacitive noise did not affect acquired data with Protem57-MK2, and the data present high signal to noise ratio. Surveys helped in determining sedimentary and crystalline aquifers, characterized by a fracture zone with water inside basin basement (conductive zone). Results show good agreement with local geology obtained from lithological boreholes located in the study areas. Moreover, it shows that TDEM method can be used in urban environments with a countless potential in hydrogeological studies, offering great reliability. Studies showed that main TDEM-method limitation at USP was the lack of space for opening the transmitter loop. Results are very promising and open new perspectives for TDEM-method use in urban environments as this area remains unexplored. (C) 2011 Elsevier B.V. All rights reserved.

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Recently, researches have shown that the performance of metaheuristics can be affected by population initialization. Opposition-based Differential Evolution (ODE), Quasi-Oppositional Differential Evolution (QODE), and Uniform-Quasi-Opposition Differential Evolution (UQODE) are three state-of-the-art methods that improve the performance of the Differential Evolution algorithm based on population initialization and different search strategies. In a different approach to achieve similar results, this paper presents a technique to discover promising regions in a continuous search-space of an optimization problem. Using machine-learning techniques, the algorithm named Smart Sampling (SS) finds regions with high possibility of containing a global optimum. Next, a metaheuristic can be initialized inside each region to find that optimum. SS and DE were combined (originating the SSDE algorithm) to evaluate our approach, and experiments were conducted in the same set of benchmark functions used by ODE, QODE and UQODE authors. Results have shown that the total number of function evaluations required by DE to reach the global optimum can be significantly reduced and that the success rate improves if SS is employed first. Such results are also in consonance with results from the literature, stating the importance of an adequate starting population. Moreover, SS presents better efficacy to find initial populations of superior quality when compared to the other three algorithms that employ oppositional learning. Finally and most important, the SS performance in finding promising regions is independent of the employed metaheuristic with which SS is combined, making SS suitable to improve the performance of a large variety of optimization techniques. (C) 2012 Elsevier Inc. All rights reserved.

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O objetivo do presente trabalho foi analisar/quantificar a produtividade científica dos docentes pertencentes à Universidade de Estadual Paulista (UNESP), campus de Marília/SP. Para cada professor, analisamos o número total de artigos na plataforma Lattes, no ISI Web of Science e no SCOPUS. Além disso, verificamos o total de livros publicados, capítulos de livros publicados e orientações em Programas de Pós-Graduação (PPG). A análise dos nove departamentos da Faculdade de Filosofia e Ciências (FFC) mostrou que o Departamento de Ciências Políticas e Econômicas possui uma média elevada (21,42) de artigos na Plataforma Lattes, quando comparado aos outros departamentos. Entretanto, o Departamento de Fonoaudiologia apresentou médias mais altas em artigos indexados pelo ISI (2,61) e SCOPUS (4,39), bem como o índice-h, nessas plataformas. Em relação aos programas de pós-graduação, o Departamento de Administração e Supervisão Escolar foi o que apresentou a maior média de orientações em andamento e/ou concluídas. O desempenho mais baixo, em relação aos artigos publicados pelo ISI e SCOPUS, pelos departamentos na área de Humanas/Humanidades pode estar associado às características do campo da concentração e da cobertura limitada do banco de dados ISI e SCOPUS, indicando que o índice-h é muito sensível ao campo de concentração.

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The purpose of this article is to present a method which consists in the development of unit cell numerical models for smart composite materials with piezoelectric fibers made of PZT embedded in a non-piezoelectric matrix (epoxy resin). This method evaluates a globally homogeneous medium equivalent to the original composite, using a representative volume element (RVE). The suitable boundary conditions allow the simulation of all modes of the overall deformation arising from any arbitrary combination of mechanical and electrical loading. In the first instance, the unit cell is applied to predict the effective material coefficients of the transversely isotropic piezoelectric composite with circular cross section fibers. The numerical results are compared to other methods reported in the literature and also to results previously published, in order to evaluate the method proposal. In the second step, the method is applied to calculate the equivalent properties for smart composite materials with square cross section fibers. Results of comparison between different combinations of circular and square fiber geometries, observing the influence of the boundary conditions and arrangements are presented.