71 resultados para dependency of attributes


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OBJETIVO: Analisar o padrão espacial da ocorrência dos casos de hanseníase para identificar áreas com probabilidade de riscos de transmissão da doença. MÉTODOS: Estudo ecológico, tendo como unidade de análise os municípios do Estado de São Paulo georreferenciados em seus centróides. A fonte de dados utilizada foi o banco informatizado dos casos de hanseníase notificados do Centro de Vigilância Epidemiológica do Estado de São Paulo, no período de 1991 a 2002. Utilizou-se de técnicas de geoestatística para a detecção das áreas de probabilidade de risco para hanseníase e quantificação da dependência espacial dos casos. RESULTADOS: Detectou-se o alcance de dependência espacial de 0,55 graus de coordenadas georreferenciadas, correspondendo aproximadamente a 60 km. As principais áreas de probabilidade de risco encontradas foram as regiões nordeste, norte e noroeste do Estado. CONCLUSÕES: A verificação de áreas com probabilidades de riscos de casos de hanseníase, utilizando-se a análise da dependência espacial, pode ser ferramenta útil para avaliar a situação de saúde e planejar alocação de recursos.

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We have studied the phase transition behavior of Pb0.76Ca0.24TiO3 thin films using Raman scattering and dielectric measurement techniques. We also have studied the leakage current conduction mechanism as a function of temperature for these thin films on platinized silicon substrates. A Pb0.76Ca0.24TiO3 thin film was prepared using a soft chemical process, called the polymeric precursor method. The results showed that the dependence of the dielectric constant upon the frequency does not reveal any relaxor behavior. However, a diffuse character-type phase transition was observed upon transformation from a cubic paraelectric phase to a tetragonal ferroelectric phase. The temperature dependency of Raman scattering spectra was investigated through the ferroelectric phase transition. The soft mode showed a marked dependence on temperature and its disappearance at about 598 K. on the other hand, Raman modes persist above the tetragonal to cubic phase transition temperature, although all optical modes should be Raman inactive above the phase transition temperature. The origin of these modes must be interpreted in terms of a local breakdown of cubic symmetry by some kind of disorder. The lack of a well-defined transition temperature suggested a diffuse-type phase transition. This result corroborate the dielectric constant versus temperature data, which showed a broad ferroelectric phase transition in the thin film. The leakage current density of the PCT24 thin film was studied at elevated temperatures, and the data were well fitted by the Schottky emission model. The Schottky barrier height of the PCT24 thin film was estimated to be 1.49 eV. (C) 2003 American Institute of Physics.

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The air temperature is a climatic element of interest for several agricultural related studies. Hence, daily air temperature from two locations in Brazil (Botucatu and Petrolina, with different climate classification), hourly recorded from January 2004 to December 2005, were analysed to verify if 24 h long air temperature variation can be predicted with 6 h interval records. Three data set were selected, with different first time record of air temperature, and analyses performed using geoestatistics to confirm the temporal dependency of records. Then, ordinary krigging was used to model air temperature variation within 1 h interval, and spherical model presented the best approach, with range of 11.6 h for Botucatu and 12.7 for Petrolina. For both locations, the time of air temperature recording was the most importnat factor on accuracy of estimation of air temperature variation. Records at 2, 8, 14 and 20 h and at 4, 10, 16 and 22 h presented the best approaches, but for records at 9, 15 and 21 h, the approach was worst.

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Autonomous robots must be able to learn and maintain models of their environments. In this context, the present work considers techniques for the classification and extraction of features from images in joined with artificial neural networks in order to use them in the system of mapping and localization of the mobile robot of Laboratory of Automation and Evolutive Computer (LACE). To do this, the robot uses a sensorial system composed for ultrasound sensors and a catadioptric vision system formed by a camera and a conical mirror. The mapping system is composed by three modules. Two of them will be presented in this paper: the classifier and the characterizer module. The first module uses a hierarchical neural network to do the classification; the second uses techiniques of extraction of attributes of images and recognition of invariant patterns extracted from the places images set. The neural network of the classifier module is structured in two layers, reason and intuition, and is trained to classify each place explored for the robot amongst four predefine classes. The final result of the exploration is the construction of a topological map of the explored environment. Results gotten through the simulation of the both modules of the mapping system will be presented in this paper. © 2008 IEEE.

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Pós-graduação em Bases Gerais da Cirurgia - FMB

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Pós-graduação em Agronomia (Ciência do Solo) - FCAV

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Pós-graduação em Ciências Sociais - FFC

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Pós-graduação em Educação - IBRC

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)