853 resultados para Probabilistic decision process model


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The use of intelligent agents in multi-classifier systems appeared in order to making the centralized decision process of a multi-classifier system into a distributed, flexible and incremental one. Based on this, the NeurAge (Neural Agents) system (Abreu et al 2004) was proposed. This system has a superior performance to some combination-centered methods (Abreu, Canuto, and Santana 2005). The negotiation is important to the multiagent system performance, but most of negotiations are defined informaly. A way to formalize the negotiation process is using an ontology. In the context of classification tasks, the ontology provides an approach to formalize the concepts and rules that manage the relations between these concepts. This work aims at using ontologies to make a formal description of the negotiation methods of a multi-agent system for classification tasks, more specifically the NeurAge system. Through ontologies, we intend to make the NeurAge system more formal and open, allowing that new agents can be part of such system during the negotiation. In this sense, the NeurAge System will be studied on the basis of its functioning and reaching, mainly, the negotiation methods used by the same ones. After that, some negotiation ontologies found in literature will be studied, and then those that were chosen for this work will be adapted to the negotiation methods used in the NeurAge.

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The way to deal with information assets means nowadays the main factor not only for the success but also for keeping the companies in the global world. The number of information security incidents has grown for the last years. The establishment of information security policies that search to keep the security requirements of assets in the desired degrees is the major priority for the companies. This dissertation suggests a unified process for elaboration, maintenance and development of information security policies, the Processo Unificado para Políticas de Segurança da Informação - PUPSI. The elaboration of this proposal started with the construction of a structure of knowledge based on documents and official rules, published in the last two decades, about security policies and information security. It's a model based on the examined documents which defines the needed security policies to be established in the organization, its work flow and identifies the sequence of hierarchy among them. It's also made a model of the entities participating in the process. Being the problem treated by the model so complex, which involves all security policies that the company must have. PUPSI has an interative and developing approach. This approach was obtained from the instantiation of the RUP - Rational Unified Process model. RUP is a platform for software development object oriented, of Rational Software (IBM group). Which uses the best practice known by the market. PUPSI got from RUP a structure of process that offers functionality, diffusion capacity and comprehension, performance and agility for the process adjustment, offering yet capacity of adjustment to technological and structural charges of the market and the company

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We present a generic spatially explicit modeling framework to estimate carbon emissions from deforestation (INPE-EM). The framework incorporates the temporal dynamics related to the deforestation process and accounts for the biophysical and socioeconomic heterogeneity of the region under study. We build an emission model for the Brazilian Amazon combining annual maps of new clearings, four maps of biomass, and a set of alternative parameters based on the recent literature. The most important results are as follows: (a) Using different biomass maps leads to large differences in estimates of emission; for the entire region of the Brazilian Amazon in the last decade, emission estimates of primary forest deforestation range from 0.21 to 0.26 similar to Pg similar to C similar to yr-1. (b) Secondary vegetation growth presents a small impact on emission balance because of the short duration of secondary vegetation. In average, the balance is only 5% smaller than the primary forest deforestation emissions. (c) Deforestation rates decreased significantly in the Brazilian Amazon in recent years, from 27 similar to Mkm2 in 2004 to 7 similar to Mkm2 in 2010. INPE-EM process-based estimates reflect this decrease even though the agricultural frontier is moving to areas of higher biomass. The decrease is slower than a non-process instantaneous model would estimate as it considers residual emissions (slash, wood products, and secondary vegetation). The average balance, considering all biomass, decreases from 0.28 in 2004 to 0.15 similar to Pg similar to C similar to yr-1 in 2009; the non-process model estimates a decrease from 0.33 to 0.10 similar to Pg similar to C similar to yr-1. We conclude that the INPE-EM is a powerful tool for representing deforestation-driven carbon emissions. Biomass estimates are still the largest source of uncertainty in the effective use of this type of model for informing mechanisms such as REDD+. The results also indicate that efforts to reduce emissions should focus not only on controlling primary forest deforestation but also on creating incentives for the restoration of secondary forests.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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A matrix approach is described for assessing the variance of effects in incomplete diallels designs. The method is illustrated by reference to simulated complete and incomplete diallels using different combinations of constraints, average degree of dominance and, for the incomplete diallel, number of hybrids. Our results showed that caution should be taken in working with incomplete diallels under conditions of overdominance because there were changes in the rank of the genotypes when the excluded hybrid had parents with a low frequency of the favorable allele (i.e. the allele which increases expression of a character). The expression described in this paper is a rapid and safe approach to estimate variances and covariances of the effects of contrasts of incomplete diallels. Copyright by the Brazilian Society of Genetics.

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Protein-protein interactions (PPIs) are essential for understanding the function of biological systems and have been characterized using a vast array of experimental techniques. These techniques detect only a small proportion of all PPIs and are labor intensive and time consuming. Therefore, the development of computational methods capable of predicting PPIs accelerates the pace of discovery of new interactions. This paper reports a machine learning-based prediction model, the Universal In Silico Predictor of Protein-Protein Interactions (UNISPPI), which is a decision tree model that can reliably predict PPIs for all species (including proteins from parasite-host associations) using only 20 combinations of amino acids frequencies from interacting and non-interacting proteins as learning features. UNISPPI was able to correctly classify 79.4% and 72.6% of experimentally supported interactions and non-interacting protein pairs, respectively, from an independent test set. Moreover, UNISPPI suggests that the frequencies of the amino acids asparagine, cysteine and isoleucine are important features for distinguishing between interacting and non-interacting protein pairs. We envisage that UNISPPI can be a useful tool for prioritizing interactions for experimental validation. © 2013 Valente et al.

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Pós-graduação em Direito - FCHS

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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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Pós-graduação em Educação - FFC

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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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Uma série de iniciativas para melhoria do processo de software surgiu recentemente visando melhorar a qualidade e a produtividade em organizações de desenvolvimento de software. Alguns modelos e normas têm buscado a implantação de melhorias no processo de desenvolvimento de software, o MPS.BR é um deles. Esse modelo de melhoria de processo é voltado para as micro, pequenas e médias empresas, de forma a atender as suas necessidades de negócio e foi o modelo escolhido para ser explorado nesse trabalho. Várias são as vantagens adquiridas com a implantação de um modelo de melhoria, umas delas é a definição de um processo sistemático de desenvolvimento de software, que auxilie tanto na qualidade e produtividade do processo quanto na qualidade do produto desenvolvido. Com um modelo de processo definido a organização pode contar com diversos benefícios associados à padronização, como, por exemplo, a otimização, a redução de custos com retrabalho, a redução de defeitos nos produtos, dentre outros. Mas não existem modelos prontos que possam ser aplicados diretamente a uma empresa específica de desenvolvimento de software e, por isso, é necessário modelar o processo, customizando-o, com o objetivo final de gerar um modelo que adequadamente represente o processo da organização. Uma das dificuldades para a implantação de modelos como o MPS.BR é a falta de metodologia que mostre como a implantação de melhoria deve ser feita e não apenas o que deve ser feito. Este trabalho propõe uma metodologia para a implementação do modelo MPS.BR baseada no modelo de implantação IDEAL, através de uma ferramenta específica, chamada WebAPSEE. A metodologia foi experimentada no CTIC - Centro de Tecnologia da Informação e Comunicação da UFPA que ao final do trabalho foi avaliado Nível G do MPS.BR.

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Este trabalho apresenta uma solução para o problema de controle admissão de conexão e alocação dinâmica de recursos em redes IEEE 802.16 através da modelagem de um Processo Markoviano de Decisão (PMD) utilizando o conceito de degradação de largura de banda, o qual é baseado nos requisitos diferenciados de largura de banda das classes de serviço do IEEE 802.16. Para o critério de desempenho do PMD é feita a atribuição de diferentes retornos a cada classe de serviço, fazendo assim o tratamento diferenciado de cada fluxo. Nesse sentido, é possível avaliar a política ótima, obtida através de um algoritmo de iteração de valores, considerando aspectos como o nível de degradação médio das classes de serviço, utilização dos recursos e probabilidades de bloqueios de cada classe de serviço em relação à carga do sistema. Resultados obtidos mostram que o método de controle markoviano proposto é capaz de priorizar as classes de serviço consideradas mais relevantes para o sistema.