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Modelos probabilísticos aplicados à BiometriaCORDEIRO, Hérbetes de Hollanda 16 December 2005 (has links)
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Previous issue date: 2005-12-16 / The term "Biometria" means, literally, measured of the life. In the world of the security or crime, one on the basis of mentions the methods to it automatized for identification of people its physical characteristics or mannering aspects. In this work, an analysis was proceeded from the main Systems Biométricos de Identificação, in order to integrate them it the too much areas of abrangência of the Biometria, that include since the diagnosis and treatment of illnesses, studies on Botany, Zoology, Epidemiologia and Bioestatística, until the most excellent applications contemporaries, as "Cells Trunk" and "Genoma Project". In another source, it was become fullfilled basically description of some discrete and continuous-chosen Probabilist Models for being the most cited in Biométrica literature and after an exhausting survey of its respective applications. On the other hand, it is also figured as fulcrum of this dissertação, the "Study of the Malaria" and the delineation of the partner-economic models torepresent it in Brazil, where it continues answering for great number of deaths, mainly in the region North. To materialize this last objective, they had been collected in 2004 partner-economic data and of incidence of this illness in the country, in 90 Cities of the regions North, South and Southeast, data these estruturadores of the gotten models. To the end, an analysis of this infection in the cited polar regions of development is made, with presentation of results and suggestions for later works of modeling. / O termo “Biometria” significa, literalmente, medida da vida. No mundo da segurança ou criminalidade, refere-se aos métodos automatizados para identificação de pessoas com base em suas características físicas ou aspectos comportamentais. Neste trabalho, procedeu-se uma análise dos principais Sistemas Biométricos de Identificação, de modo a integrá-los às demais áreas de abrangência da Biometria, que incluem desde o diagnóstico e tratamento de doenças, estudos sobre Botânica, Zoologia, Epidemiologia e Bioestatística, até as mais relevantes aplicações contemporâneas, como “Células Tronco” e “Projeto Genoma”. Em outra vertente, realizou-se a descrição de alguns Modelos Probabilísticos e uma pesquisa de suas aplicações à Biometria. Por outro lado, afigura-se também como fulcro desta dissertação, o “Estudo da Malária” e o delineamento dos modelos sócio-econômicos para representá-la no Brasil, onde continua respondendo por grande número de óbitos, principalmente na região Norte. Para materializar este último objetivo, foram coletados em 2004 dados sócio-econômicos e de incidência desta doença no país, em 90 Municípios das regiões Norte, Sul e Sudeste, dadosesses estruturadores dos modelos obtidos. Ao final, é feita uma análise dessa infecção nos citados pólos de desenvolvimento, com apresentação de resultados e sugestões para ulteriores trabalhos de modelagem.
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Intégration du retour d'expérience pour une stratégie de maintenance dynamique / Integrate experience feedback for dynamic maintenance strategyRozas, Rony 19 December 2014 (has links)
L'optimisation de stratégies de maintenance est un sujet primordial pour un grand nombre d'industriels. Il s'agit d'établir un plan de maintenance qui garantisse des niveaux de sécurité, de sûreté et de fiabilité élevé avec un coût minimum et respectant d'éventuelles contraintes. Le nombre de travaux grandissant sur l'optimisation de paramètres de maintenance et notamment sur la planification d'actions préventives de maintenance souligne l'intérêt de ce problème. Un grand nombre d'études sur la maintenance repose sur une modélisation du processus de dégradation du système étudié. Les Modèles Graphiques Probabilistes (MGP) et particulièrement les MGP Markoviens (MGPM) fournissent un cadre de travail pour la modélisation de processus stochastiques complexes. Le problème de ce type d'approche est que la qualité des résultats est dépendante de celle du modèle. De plus, les paramètres du système considéré peuvent évoluer au cours du temps. Cette évolution est généralement la conséquence d'un changement de fournisseur pour les pièces de remplacement ou d'un changement de paramètres d'exploitation. Cette thèse aborde le problème d'adaptation dynamique d'une stratégie de maintenance face à un système dont les paramètres changent. La méthodologie proposée repose sur des algorithmes de détection de changement dans un flux de données séquentielles et sur une nouvelle méthode d'inférence probabiliste spécifique aux réseaux bayésiens dynamiques. D'autre part, les algorithmes proposés dans cette thèse sont mis en place dans le cadre d'un projet d'étude avec Bombardier Transport. L'étude porte sur la maintenance du système d'accès voyageurs d'une nouvelle automotrice destiné à une exploitation sur le réseau ferré d'Ile-de-France. L'objectif général est de garantir des niveaux de sécurité et de fiabilité importants au cours de l'exploitation du train / The optimization of maintenance strategies is a major issue for many industrial applications. It involves establishing a maintenance plan that ensures security levels, security and high reliability with minimal cost and respecting any constraints. The increasing number of works on optimization of maintenance parameters in particular in scheduling preventive maintenance action underlines the importance of this issue. A large number of studies on maintenance are based on a modeling of the degradation of the system studied. Probabilistic Models Graphics (PGM) and especially Markovian PGM (M-PGM) provide a framework for modeling complex stochastic processes. The issue with this approach is that the quality of the results is dependent on the model. More system parameters considered may change over time. This change is usually the result of a change of supplier for replacement parts or a change in operating parameters. This thesis deals with the issue of dynamic adaptation of a maintenance strategy, with a system whose parameters change. The proposed methodology is based on change detection algorithms in a stream of sequential data and a new method for probabilistic inference specific to the dynamic Bayesian networks. Furthermore, the algorithms proposed in this thesis are implemented in the framework of a research project with Bombardier Transportation. The study focuses on the maintenance of the access system of a new automotive designed to operate on the rail network in Ile-de-France. The overall objective is to ensure a high level of safety and reliability during train operation
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