871 resultados para Sistemas de segurança - Vigilância electrónica - Estudos de caso - Ovar (Portugal)
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The work proposed by Cleverton Hentz (2010) presented an approach to define tests from the formal description of a program s input. Since some programs, such as compilers, may have their inputs formalized through grammars, it is common to use context-free grammars to specify the set of its valid entries. In the original work the author developed a tool that automatically generates tests for compilers. In the present work we identify types of problems in various areas where grammars are used to describe them , for example, to specify software configurations, which are potential situations to use LGen. In addition, we conducted case studies with grammars of different domains and from these studies it was possible to evaluate the behavior and performance of LGen during the generation of sentences, evaluating aspects such as execution time, number of generated sentences and satisfaction of coverage criteria available in LGen
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Web services are computational solutions designed according to the principles of Service Oriented Computing. Web services can be built upon pre-existing services available on the Internet by using composition languages. We propose a method to generate WS-BPEL processes from abstract specifications provided with high-level control-flow information. The proposed method allows the composition designer to concentrate on high-level specifi- cations, in order to increase productivity and generate specifications that are independent of specific web services. We consider service orchestrations, that is compositions where a central process coordinates all the operations of the application. The process of generating compositions is based on a rule rewriting algorithm, which has been extended to support basic control-flow information.We created a prototype of the extended refinement method and performed experiments over simple case studies
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Remote sensing is one technology of extreme importance, allowing capture of data from the Earth's surface that are used with various purposes, including, environmental monitoring, tracking usage of natural resources, geological prospecting and monitoring of disasters. One of the main applications of remote sensing is the generation of thematic maps and subsequent survey of areas from images generated by orbital or sub-orbital sensors. Pattern classification methods are used in the implementation of computational routines to automate this activity. Artificial neural networks present themselves as viable alternatives to traditional statistical classifiers, mainly for applications whose data show high dimensionality as those from hyperspectral sensors. This work main goal is to develop a classiffier based on neural networks radial basis function and Growing Neural Gas, which presents some advantages over using individual neural networks. The main idea is to use Growing Neural Gas's incremental characteristics to determine the radial basis function network's quantity and choice of centers in order to obtain a highly effective classiffier. To demonstrate the performance of the classiffier three studies case are presented along with the results.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Pós-graduação em Ciência da Computação - IBILCE
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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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Pós-graduação em Geografia - IGCE
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Pós-graduação em Engenharia Mecânica - FEB
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Pós-graduação em Ciência da Computação - IBILCE
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Pós-graduação em Direito - FCHS
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Pós-graduação em Ciências Cartográficas - FCT
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Pós-graduação em Design - FAAC
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Pós-graduação em Geociências e Meio Ambiente - IGCE
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)