Submitted by (ana.araujo@ufrpe.br) on 2016-07-06T15:01:17Z No. of bitstreams: 1 Herbetes de Holanda Cordeiro.pdf: 1261935 bytes, checksum: da7eb431e201178bcb2d605739806e64 (MD5) / Made available in DSpace on 2016-07-06T15:01:17Z (GMT). No. of bitstreams: 1 Herbetes de Holanda Cordeiro.pdf: 1261935 bytes, checksum: da7eb431e201178bcb2d605739806e64 (MD5) 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.

[pt] Apresenta-se uma metodologia geral para a avaliação do risco sísmico em sistemas estruturais de engenharia civil com particularizações para edifícios e, a seguir, executam- se aplicações para exemplificar a proposta e para o desenvolvimento de procedimentos complementares aos adotados na prática por métodos determinísticos. Para tal, considera-se a excitação sísmica como um processo aleatório fracamente estacionário, definido por uma função de densidade de espectro de potência da aceleração do movimento do terreno e, no domínio da frequência, determinam-se funções semelhantes para as respostas estruturais. Considera-se, a seguir, o problema de primeira ultrapassagem, de acordo com a solução de Vanmarcke, para determinar a distribuição de probabilidade das respostas estruturais permanecerem abaixo dos níveis numericamente especificados, designados de barreiras. A partir dessas probabilidades, prossegue-se para desenvolver: - uma metodologia para análise de risco sísmico de estruturas prediais, incluindo uma fase preliminar de avaliação da ameaça sísmica para o território nacional; - recursos para avaliação do compromisso probabilístico entre uma função de densidade de espectro de potência da excitação sísmica, para uma região, e um espectro de resposta de projeto proposto para o mesmo local; - o conceito e o procedimento para geração de um espectro de resposta uniformemente provável a ser utilizado para análise do sistema principal e de um espectro de resposta acoplado uniformemente provável para o caso dos sistemas secundários; - uma comparação entre a capacidade a ações horizontais eólicas de estruturas prediais correntes, no Brasil, e o significado dessa resistência para os requisitos de demanda decorrente dos sismos prováveis; - um procedimento para geração de uma função de densidade de espectro de potência objetivo associada a um espectro de resposta de projeto prescrito. A implementação computacional da análise estrutural no domínio da frequência utiliza parcialmente o programa SASSI-2000 e a análise probabilística usa os programas APESS e CA desenvolvidos internamente ao trabalho. / [en] One presents a general methodology to the evaluation of the seismic risk to civil engineering structures, with emphasis to building systems, and in sequence a series of applications is made to exemplify this proposal and to develop complementary procedures to the deterministic structural analysis. On this way, one considers the structural seismic excitation as a weakly stationary random process mainly defined by a ground acceleration power density function and one determines, in the frequency domain, similar structural response quantity functions. One applies, to this response functions, the first passage problem solution according to Vanmarcke and so determining the distribution probability functions of these maximum structural response quantities to remain below specified numerical levels, which are called barriers. From these probability distributions, one proceeds to develop: − a methodology to the structural seismic risk analysis, including a previous phase to define the seismic hazard over the Brazilian territory; − tools to evaluated the probabilistic compromise between a power spectrum density function of the seismic excitation for a region and a design response spectrum proposed to the same area; − the idea of a uniformly probable design response spectrum and the procedures to generate this function to be used in the analyses of the primary system; and to produce a uniformly probable coupled response spectrum for the analyses of secondary systems; − a comparison between the wind horizontal action capacity of regular building structures in Brazil and the capability which would be expected to the seismic hazard; − a procedure to generate a target power spectrum density function for the seismic hazard probabilistically associated to a prescribed design response spectrum for a site. The computational support to the frequency domain structural analysis is taken partially from SASSI-2000 program and the probabilistic paths are made by APESS and CA programs which have been developed inside this work.

Le réchauffement climatique est un problème majeur pour le monde scientifique et les sociétés. La concentration de dioxyde de carbone a augmenté de 45% depuis la période préindustrielle (Harris, 2010), conséquence des activités humaines déséquilibrant le cycle du carbone mondial. Cela se traduit par un réchauffement de la planète avec des impacts dramatiques sur la terre et encore plus pour les populations fragiles.Parmi les solutions d'atténuation, une meilleure utilisation du sol est proposée. En effet, les sols ont la plus grande capacité d'échange de carbone avec l'atmosphère et renferment un stock important de carbone. Une augmentation minime du stock de carbone du sol, les échanges de carbone entre l'atmosphère et le sol plus favorables à la séquestration du carbone dans le sol compenseraient les émissions de carbone provenant de la combustion des combustibles fossiles. Cependant, la dynamique du carbone dans le sol souffre encore de connaissances insuffisantes. Il subsiste alors une grande incertitude quant à la réponse du carbone du sol aux changements climatiques et aux changements d'affectation des terres.Plusieurs modèles mécanistiques ont été développés pour mieux comprendre la dynamique du carbone du sol. Cependant, ces modèles mécanistes ont encore une vue incomplète des processus physiques affectant la matière organique (MO) du sol. Il faudra beaucoup de temps pour obtenir un modèle complet et à jour de la dynamique des sols.Dans ma thèse, nous avons proposé un modèle statistique bayésien visant à décrire la dynamique verticale du carbone du sol. Cela se fait grâce à la modélisation du carbone organique du sol et aussi des données radiocarbone, car elles illustrent le temps de séjour de la MO et donc la dynamique du carbone du sol. Cette approche statistique visait à mieux représenter les incertitudes sur la dynamique du carbone du sol et quantifier les effets des facteurs climatiques et environnementaux sur le carbone des sols superficiels et profonds.Cette méta-analyse a été réalisée sur une base de données de 344 profils, collectés à partir de 87 articles scientifiques et archéologiques et paléoclimatologiques, sous différentes conditions climatiques et environnementales.Un modèle non linéaire hiérarchique avec effets aléatoires a été proposé pour modéliser la dynamique verticale du radiocarbone en fonction de la profondeur. Les techniques de sélection bayésiennes, récemment publiées, ont été appliquées aux couches latentes de notre modèle, elles-mêmes liées par une relation linéaire aux facteurs climatiques et environnementaux. Le Bayesian Group Lasso, le Bayesian Sparse Group Selection(BSGS) et le Bayesian Effect Fusion(BEF) ont été testés pour identifier les principaux prédicteurs explicatifs catégoriels et le Stochastic Search Variable Selection pour identifier les prédicteurs explicatifs numériques influents. Une comparaison de ces techniques bayésiennes a été effectuée sur la base des critères de sélection du modèle bayésien pour spécifier quel modèle a le meilleur pouvoir prédictif En plus de la sélection de prédicteurs catégoriels, le BSGS permet de formuler une probabilité d'inclusion a posteriori pour chaque niveau dans les prédicteurs catégoriels comme type de sol et type d'écosystème. En outre, le BEF a permis de fusionner les types de sol et les types d’écosystèmes qui, selon le BEF, sont supposés avoir les mêmes effets sur nos réponses d’intérêts que la réponse du radiocarbone du sol arable.L'application de ces techniques a permis de prédire, en moyenne et au niveau mondial, la dynamique verticale du radiocarbone dans le cas d'une augmentation de température et de changement d’usage des sols. Par exemple, nous avons étudié l'impact de la déforestation des forêts tropicales et leur remplacement par des terres cultivées sur la dynamique du carbone du sol. La même analyse statistique a également été effectuée pour mieux comprendre la dynamique verticale de la teneur en carbone du sol. / Global warming is a major issue for both the scientific world and societies. The concentration of carbon dioxide has increased by 45% since the pre-industrial era (Harris, 2010) as a consequence of human activities, unbalancing the global carbon cycle. This results in global warming with dramatic impacts on the Earth, particularly for fragile populations.Amongst mitigation solutions, a better use of soil is proposed. Soils have the largest capacity of carbon exchanges with the atmosphere and contain a large stock of carbon. A tiny increase in this soil carbon stock and in carbon exchanges between atmosphere and soil would be more favorable to soil carbon sequestration and would compensate for carbon emissios from burning fossil fuel. However, soil carbon dynamics still suffers from insufficient knowledge. There remains therefore a huge uncertainty about the soil carbon response to climate and land-use changes.While several mechanistic models have been developed to better understand the dynamics of soil carbon, they provide an incomplete view of the physical processes affecting soil organic matter (OM). It will be long before a complete and updated soil dynamics model becomes available.In my thesis, I propose a Bayesian statistical model aiming at describing the vertical dynamics of soil carbon. This is done thanks to the modeling of both soil organic carbon and of radiocarbon data as they illustrate the residence time of organic matter and thus the soil carbon dynamics. The purpose of this statistical approach was to better represent the uncertainties on soil carbon dynamics and to quantify the effects of climatic and environmental factors on both surface and deep soil carbon.This meta-analysis was performed on a database of 344 profiles, collected from 87 soil science papers and the literature in archeology and paleoclimatology, under different climate conditions (temperature, precipitation, etc.) and environments (soil type and type of ecosystem).A hierarchical non-linear model with random effects was proposed to model the vertical dynamics of radiocarbon as a function of depth. Bayesian selection techniques, recently published, were applied to the latent layers of the model, which in turn are linked by a linear relationship to the climatic and environmental factors. The Bayesian Group Lasso with Spike and Slab Prior (BGL-SS), the Bayesian Sparse Group Selection (BSGS) and the Bayesian Effect Fusion model-based clustering (BEF) were tested to identify the significant categorical explanatory predictors (soil type, ecosystem type) and the Stochastic Search Variable Selection method to identify the influential numerical explanatory predictors. A comparison of these Bayesian techniques was made based on the Bayesian model selection criteria (the DIC (Deviance Information Criterion), the Posterior Predictive Check, etc.) to specify which model has the best predictive and adjustment power of the database profiles. In addition to selecting categorical predictors, the BSGS allows the formulation of an a posteriori inclusion probability for each level within the categorical predictors such as soil type and ecosystem type (9 soil types and 6 ecosystem types were considered in our study). Furthermore, the BEF made it possible to merge the types of soil as well as the types of ecosystem, which according to the BEF, are considered to have the same effects on the responses of interest here, such as the response of the topsoil radiocarbon.The application of these techniques allowed us to predict, on average and on a global level, the vertical dynamics of the radiocarbon in the case of a temperature increase of 1, 1.5 and 2 °C, and in the case of a change in vegetation cover. For example, we studied the impact of deforesting tropical forests and replacing them by cultivated land on soil carbon dynamics. The same statistical analysis was also done to better understand the vertical dynamics of soil carbon content.

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