986 resultados para Métodos computacionais
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Although it has been suggested that retinal vasculature is a diffusion-limited aggregation (DLA) fractal, no study has been dedicated to standardizing its fractal analysis . The aims of this project was to standardize a method to estimate the fractal dimensions of retinal vasculature and to characterize their normal values; to determine if this estimation is dependent on skeletization and on segmentation and calculation methods; to assess the suitability of the DLA model and to determine the usefulness of log-log graphs in characterizing vasculature fractality . To achieve these aims, the information, mass-radius and box counting dimensions of 20 eyes vasculatures were compared when the vessels were manually or computationally segmented; the fractal dimensions of the vasculatures of 60 eyes of healthy volunteers were compared with those of 40 DLA models and the log-log graphs obtained were compared with those of known fractals and those of non-fractals. The main results were: the fractal dimensions of vascular trees were dependent on segmentation methods and dimension calculation methods, but there was no difference between manual segmentation and scale-space, multithreshold and wavelet computational methods; the means of the information and box dimensions for arteriolar trees were 1.29. against 1.34 and 1.35 for the venular trees; the dimension for the DLA models were higher than that for vessels; the log-log graphs were straight, but with varying local slopes, both for vascular trees and for fractals and non-fractals. This results leads to the following conclusions: the estimation of the fractal dimensions for retinal vasculature is dependent on its skeletization and on the segmentation and calculation methods; log-log graphs are not suitable as a fractality test; the means of the information and box counting dimensions for the normal eyes were 1.47 and 1.43, respectively, and the DLA model with optic disc seeding is not sufficient for retinal vascularization modeling
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The frequency selective surfaces, or FSS (Frequency Selective Surfaces), are structures consisting of periodic arrays of conductive elements, called patches, which are usually very thin and they are printed on dielectric layers, or by openings perforated on very thin metallic surfaces, for applications in bands of microwave and millimeter waves. These structures are often used in aircraft, missiles, satellites, radomes, antennae reflector, high gain antennas and microwave ovens, for example. The use of these structures has as main objective filter frequency bands that can be broadcast or rejection, depending on the specificity of the required application. In turn, the modern communication systems such as GSM (Global System for Mobile Communications), RFID (Radio Frequency Identification), Bluetooth, Wi-Fi and WiMAX, whose services are highly demanded by society, have required the development of antennas having, as its main features, and low cost profile, and reduced dimensions and weight. In this context, the microstrip antenna is presented as an excellent choice for communications systems today, because (in addition to meeting the requirements mentioned intrinsically) planar structures are easy to manufacture and integration with other components in microwave circuits. Consequently, the analysis and synthesis of these devices mainly, due to the high possibility of shapes, size and frequency of its elements has been carried out by full-wave models, such as the finite element method, the method of moments and finite difference time domain. However, these methods require an accurate despite great computational effort. In this context, computational intelligence (CI) has been used successfully in the design and optimization of microwave planar structures, as an auxiliary tool and very appropriate, given the complexity of the geometry of the antennas and the FSS considered. The computational intelligence is inspired by natural phenomena such as learning, perception and decision, using techniques such as artificial neural networks, fuzzy logic, fractal geometry and evolutionary computation. This work makes a study of application of computational intelligence using meta-heuristics such as genetic algorithms and swarm intelligence optimization of antennas and frequency selective surfaces. Genetic algorithms are computational search methods based on the theory of natural selection proposed by Darwin and genetics used to solve complex problems, eg, problems where the search space grows with the size of the problem. The particle swarm optimization characteristics including the use of intelligence collectively being applied to optimization problems in many areas of research. The main objective of this work is the use of computational intelligence, the analysis and synthesis of antennas and FSS. We considered the structures of a microstrip planar monopole, ring type, and a cross-dipole FSS. We developed algorithms and optimization results obtained for optimized geometries of antennas and FSS considered. To validate results were designed, constructed and measured several prototypes. The measured results showed excellent agreement with the simulated. Moreover, the results obtained in this study were compared to those simulated using a commercial software has been also observed an excellent agreement. Specifically, the efficiency of techniques used were CI evidenced by simulated and measured, aiming at optimizing the bandwidth of an antenna for wideband operation or UWB (Ultra Wideband), using a genetic algorithm and optimizing the bandwidth, by specifying the length of the air gap between two frequency selective surfaces, using an optimization algorithm particle swarm
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The pumping of fluids in pipelines is the most economic and safe form of transporting fluids. That explains why in Europe there was in 1999 about 30.000 Km [7] of pipelines of several diameters, transporting millíons of cubic meters of crude oil end refined products, belonging to COCAWE (assaciation of companies of petroleum of Europe for health, environment and safety, that joint several petroleum companies). In Brazil they are about 18.000 Km of pipelines transporting millions of cubic meters of liquids and gases. In 1999, nine accidents were registered to COCAWE. Among those accidents one brought a fatal victim. The oil loss was of 171 m3, equivalent to O,2 parts per million of the total of the transported volume. Same considering the facts mentioned the costs involved in ao accident can be high. An accident of great proportions can bríng loss of human lives, severe environmental darnages, loss of drained product, loss . for dismissed profit and damages to the image of the company high recovery cost. In consonance with that and in some cases for legal demands, the companies are, more and more, investing in systems of Leak detection in pipelines based on computer algorithm that operate in real time, seeking wíth that to minimize still more the drained volumes. This decreases the impacts at the environment and the costs. In general way, all the systems based on softWare present some type of false alarm. In general a commitment exists betWeen the sensibílity of the system and the number of false alarms. This work has as objective make a review of thé existent methods and to concentrate in the analysis of a specific system, that is, the system based on hydraulic noise, Pressure Point Analyzis (PPA). We will show which are the most important aspects that must be considered in the implementation of a Leak Detection System (LDS), from the initial phase of the analysis of risks passing by the project bases, design, choice of the necessary field instrumentation to several LDS, implementation and tests. We Will make na analysis of events (noises) originating from the flow system that can be generator of false alarms and we will present a computer algorithm that restricts those noises automatically
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One of the most important goals of bioinformatics is the ability to identify genes in uncharacterized DNA sequences on world wide database. Gene expression on prokaryotes initiates when the RNA-polymerase enzyme interacts with DNA regions called promoters. In these regions are located the main regulatory elements of the transcription process. Despite the improvement of in vitro techniques for molecular biology analysis, characterizing and identifying a great number of promoters on a genome is a complex task. Nevertheless, the main drawback is the absence of a large set of promoters to identify conserved patterns among the species. Hence, a in silico method to predict them on any species is a challenge. Improved promoter prediction methods can be one step towards developing more reliable ab initio gene prediction methods. In this work, we present an empirical comparison of Machine Learning (ML) techniques such as Na¨ýve Bayes, Decision Trees, Support Vector Machines and Neural Networks, Voted Perceptron, PART, k-NN and and ensemble approaches (Bagging and Boosting) to the task of predicting Bacillus subtilis. In order to do so, we first built two data set of promoter and nonpromoter sequences for B. subtilis and a hybrid one. In order to evaluate of ML methods a cross-validation procedure is applied. Good results were obtained with methods of ML like SVM and Naïve Bayes using B. subtilis. However, we have not reached good results on hybrid database
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Pós-graduação em Biofísica Molecular - IBILCE
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Pós-graduação em Agronomia (Energia na Agricultura) - FCA
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Pós-graduação em Educação Matemática - IGCE
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Foi feito um estudo da associação entre a densidade de ocorrência de raios com condições meteorológicas no leste da região Amazônica entre os anos de 2006 a 2008. A região estudada foi limitada por uma grade geográfica entre as latitudes 0º a -10º e longitudes -53º a -43º. Foram desenvolvidos métodos computacionais de processamento estatístico e geração de mapas de ocorrências de raios para diferentes intervalos de tempo. Esses métodos foram aplicados para determinar os pontos de altas ocorrências de raios ao longo de linhas de transmissão de energia elétrica, a fim de oferecer subsídios para a proteção e operação dos sistemas elétricos da região. Foram utilizados dados da rede de detecção de raios do SIPAM para redimensionar a detecção do sistema de alcance intercontinental STARNET, e subsequentemente, foram obtidos mapas de densidade de raios mais uniformes e realistas. Esses mapas foram interpretados em períodos semanais e sazonais, considerando as observações simultâneas de chuva, vento, radiação de onda longa e a presença de sistemas meteorológicos de grande escala. Zona de Convergência Intertropical e Zona de Convergência do Atlântico Sul (ZCIT, ZCAS) definidos pela convergência de ventos e anomalias negativas de Radiação de Ondas Longas ( ROL). Os resultados mostraram boa correspondência entre as áreas de convecção e a intensa ocorrência de raios. Nas regiões de mais alta atividade elétrica atmosférica, foi observada ocorrência de convergência dos ventos e anomalias negativas de ROL, para situações de presença de ZCAS e ZCIT sobre a região. A atividade de raios também coincidiu, com algumas exceções, com áreas de maior precipitação em períodos semanais. Foi observado também que, durante um trimestre seco, os segmentos de linhas de transmissão de Mojú-Tailândia e Jacundá-Marabá apresentaram maior incidência de raios. O pico da densidade de raios chegou a 18 raios/km2/trimestre em alguns locais. Durante o trimestre chuvoso, a densidade geral de raios foi 86% maior e apresentou distribuição espacial mais uniforme quando comparada com um trimestre seco. Este estudo mostrou não somente como as características meteorológicas influenciaram na distribuição e quantidade raios, mas também que a elevada atividade de descargas elétricas na região deve ser uma preocupação importante para os sistemas de distribuição de energia elétrica e outras atividades humanas na Amazônia Oriental.
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There has been a lot of advance in genomics since 1975 when the possibility to determine the nucleotide sequence of a genome was described. In the 90’s the human genome sequencing was started and it was greatly favored by advances in computer technologies. In the last ten years the development of next generation sequencing technologies allowed the sequencing of millions of bases at low cost and in a shorter time compared to the previous technologies. After the conclusion of the human genome project, several initiatives to sequence the genome of domestic animal species were taken, resulting in a large amount of data that is redirecting the goals of genetic studies in domestic animals. The aim of this review was to describe the present situation of the sequencing initiatives on the main domestic animal species of economical interest as well as to list the most important tools available to access the genomic information.
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Se describe someramente el procedimiento de colocación por fondeo de una tubería de polietileno en un emisario submarino. El problema estructural se plantea en grandes movimientos pero con material elástico y deformaciones pequeñas. Se estudian las distintas acciones actuales: peso propio, inundación del tubo, oleaje, corriente marina, tiro de arrastre y modificaciones del esquema estructural. Algunas de las acciones anteriores son de persecución (follower forces) y por lo tanto, generalmente no son conservativas. Por otra parte, se establecen las pertinentes condiciones de contorno, algunas no lineales con carácter unilateral como es la representada por la existencia del fondo marino. Se determinan los esfuerzos y movimientos en las distintas etapas de un proceso de inmersión del emisario, desde su posición inicial de flotación hasta su colocación en el fondo del mar. El modelo presentado se aplica al estudio de unos casos simples de colocación del emisario en el lecho marino.