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Cette thèse propose une méthode originale pour la génération automatique d'un code de simulation pour les systèmes à événements discrets. Cette méthode utilise l'information de localisation des produits lors du fonctionnement du système. Ce flux composé par des tuples (product id, location, time) constitue le point d'entrée pour l'algorithme proposé de génération d'un modèle de simulation de type réseau de files d'attente. Ce type d'approche permet, outre un gain important de temps pour la conception initiale du modèle, une maintenance et reconfiguration " on line " du modèle. La thèse est composée de 5 chapitres. Le premier chapitre pose la problématique et fixe le cadre théorique de la thèse. Le second chapitre est une revue de la littérature sur la simulation en général et sur les travaux utilisant la notion de trajectoires à des fins de modélisation. Le troisième chapitre sert à mettre en avant la proposition au coeur de cette thèse. Le quatrième chapitre décrit le générateur développé. Le cinquième et dernier chapitre présente les travaux d'expérimentation et de validation du générateur. / This thesis work proposes a novel method for the automatic generation of simulation code of discrete event systems. This method uses the location information of the products during operation of the system. This flow, of tuples (product id, location, time) is the input of the proposed algorithm that generates a queueing-network simulation model. This type of approach can achieve a significant time gain for the design, maintenance and on-line reconfiguration of the model. The thesis is composed on five chapters. The first chapter poses the problem and fixes the theoretical framework of the thesis. The second chapter is a literature review of the broad sense of simulation and present works using the notion of trajectories for modeling. The third chapter is to highlight the proposal of the heart of this thesis. The fourth chapter describes the generator developed. The fifth and final chapter presents the experiments and the validation of the generator

New reactor designs and the license extensions of the current reactors has created new condition monitoring challenges. A major challenge is the creation of a data-based model for a reactor that has never been built or operated and has no historical data. This is the motivation behind the creation of a hybrid modeling technique based on first principle models that adapts to include operating reactor data as it becomes available. An Adaptive Non-Parametric Model (ANPM) was developed for adaptive monitoring of small to medium size reactors (SMR) but would be applicable to all designs. Ideally, an adaptive model should have the ability to adapt to new operational conditions while maintaining the ability to differentiate faults from nominal conditions. This has been achieved by focusing on two main abilities. The first ability is to adjust the model to adapt from simulated conditions to actual operating conditions, and the second ability is to adapt to expanded operating conditions. In each case the system will not learn new conditions which represent faulted or degraded operations. The ANPM architecture is used to adapt the model's memory matrix from data from a First Principle Model (FPM) to data from actual system operation. This produces a more accurate model with the capability to adjust to system fluctuations. This newly developed adaptive modeling technique was tested with two pilot applications. The first application was a heat exchanger model that was simulated in both a low and high fidelity method in SIMULINK. The ANPM was applied to the heat exchanger and improved the monitoring performance over a first principle model by increasing the model accuracy from an average MSE of 0.1451 to 0.0028 over the range of operation. The second pilot application was a flow loop built at the University of Tennessee and simulated in SIMULINK. An improvement in monitoring system performance was observed with the accuracy of the model improving from an average MSE of 0.302 to an MSE of 0.013 over the adaptation range of operation. This research focused on the theory, development, and testing of the ANPM and the corresponding elements in the surveillance system.

Estamos vivenciando o que pode ser considerado como o sexto evento de extinção global da Biodiversidade. Os anfíbios são os vertebrados mais ameaçados do mundo e ainda o número de espécies ameaçadas pode estar subestimado, pois 22% estão classificadas na categoria Dados Insuficientes (DD). O Brasil possui alta riqueza de anfíbios, porém inúmeras lacunas de conhecimento dificultam a elaboração de listas completas e prejudica a avalição do estado de conservação e o planejamento da conservação dos anfíbios brasileiros. Assim, visando contribuir efetivamente no direcionamento das ações de conservação dos anfíbios brasileiros avaliamos a influência da atitude de especialistas na classificação das espécies, e também identificamos e adaptamos ferramentas para melhor explorar os dados de distribuição disponíveis sobre as espécies DD. Foi proposto um framework de modelagem adaptativa para lidar com a escassez de dados de distribuição destas espécies e incluir a capacidade de dispersão nos modelos de distribuição de espécies. Além disso, para preencher lacunas de conhecimento dos aspectos biológicos e ecológicos das espécies de anfíbios da Mata Atlântica considerados como DD foi realizado busca na literatura e em coleções científicas, bem como a indicação de áreas prioritárias para obter informações adicionais sobre essas espécies. Identificamos que a linha de atuação dos avaliadores influencia na determinação da categoria DD, aumentando ou reduzindo a probabilidade de classificar uma espécie nesta categoria. Com isso, ressalta-se a necessidade de compor equipes multidisciplinares para avaliar o estado de conservação das espécies. O framework aqui proposto tem o potencial de inovar o processo de modelagem com poucos dados disponíveis a partir da inclusão de um dos aspectos mais difíceis de mensurar, a capacidade de dispersão da espécie. O conjunto de informações sobre as espécies DD da Mata Atlântica aumentou consideravelmente com o levantamento de dados e os modelos de distribuição de espécies, e ainda foi possível obter áreas prioritárias para aumentar o conhecimento empírico em mais de 180 municípios. Dentre as categorias de unidades de conservação mais frequentes como áreas prioritárias, destacam-se as Reservas Particulares do Patrimônio Natural nas regiões nordeste e sul, e as Áreas de Preservação permanente na região sudeste. Os resultados deste estudo contribuem efetivamente para o processo de avaliação do estado de conservação dos anfíbios brasileiros, especialmente das espécies DD da Mata Atlântica, de modo que possa ser utilizado no planejamento sistemático da conservação deste grupo. As abordagens utilizadas neste estudo podem servir de modelos para outras espécies ou grupos taxonômicos, reduzindo lacunas e incertezas no processo de avaliação do estado de conservação de espécies. / We are experiencing what could be considered as the sixth global biodiversity extinction event. Amphibians are the most threatened vertebrates in the world, and still the number of endangered species might be underestimated because 22% are classified in the category data deficient (DD). Brazil has a high richness of amphibians, but several knowledge gaps make it difficult to compile complete lists and impair the evaluation of the conservation status and the conservation planning of Brazilian amphibians. Thus, in order to contribute effectively in directing conservation actions for Brazilian anphibians we evaluated the influence of experts attitude on species classification, and also identified and adapted tools to better explore the available data on DD species. It was proposed an adaptive modeling framework to deal with the scarcity of these species distribution data and include dispersion capacity in species distribution modeling. In addition, to fill knowledge gaps of biological and ecological aspects of amphibian species of the Atlantic forest considered as DD literature search and in scientific collections were conducted, as well as the indication of priority areas for gathering additional information about these species. We identified that the line of action of the evaluators influences the determination of the DD category, increasing or reducing the probability of classifying a species in this category. Thereby, it`s emphasized the need to compose multidisciplinary teams to assess species conservation status. The framework proposed here has the potential to innovate the modeling process through the inclusion of one of the most difficult aspects to be measured, the species dispersion capacity. The set of information about DD species of the Atlantic forest has increased considerably with the survey and the species distribution models, and it was still possible to obtain priority areas to increase the empirical knowledge in more than 180 municipalities. Among the categories of protected areas most frequent as priority areas, Private Reserves stands out in the Northeast and South regions and Areas of Permanent Preservation the Southeast. Results of this study contribute effectively to the process conservation status assessment of amphibians, especially DD species from the Atlantic forest, so that it could be used in conservation systematic planning of this group. The approaches used in this study could serve as models for other species or taxonomic groups, reducing gaps and uncertainties in the process of evaluation of species conservation status.

Une Interface Cerveau-Machine (ICM) est un système permettant de transformer l'activité neurale du cerveau en une commande d'effecteurs externes. Cette étude correspond à une étape vers une ICM totalement autonome fonctionnant dans un environnement naturel ce qui est d'une importance cruciale pour les futures applications cliniques d'une ICM. Pour représenter l'environnement naturel, des expériences avec une ICM binaire asynchrone ont été réalisées avec des animaux libres de se mouvoir. En comparaison avec les études précédentes, des expériences sur le long terme ont été réalisées, ce qui est plus conforme aux exigences des applications de la vie réelle. L'objectif principal de cette étude est de différencier le modèle spécifique neuronal lié à l'intention d'action de l'activité de fond du cerveau chez des animaux libres de tous mouvements. Pour atteindre le niveau nécessaire de sélectivité, l'analyse Multi-Voies PLS a été choisie sachant qu'elle fournit simultanément un traitement du signal dans plusieurs domaines, à savoir, temporel, fréquentiel et spatial. Pour améliorer la capacité de l'approche générique Multi-Voies PLS pour le traitement de données à grandes dimensions, l'algorithme « Itérative NPLS » est introduit dans notre travail. En ayant des besoins plus faibles en mémoire, cet algorithme fournit des traitements de grands ensembles de données, permet une résolution élevée, préserve l'exactitude de l'algorithme générique et démontre une meilleure robustesse. Pour la calibration adaptative d'un système ICM, l'algorithme récursif NPLS est proposé. Finalement, l'algorithme pénalisé NPLS est développé pour la sélection efficace d'un sous-ensemble de fonctions, à savoir, un sous-ensemble d'électrodes. Les algorithmes proposés ont été testés sur des ensembles de données artificielles et réelles. Ils ont démontré une performance qui est comparable à celle d'un algorithme générique NPLS. Leur efficacité de calcul est acceptable pour les applications en temps réel. Les algorithmes développés ont été appliqués à la calibration d'un système ICM et ont été utilisés dans des expériences d'ICM avec bouclage en temps réel chez des animaux. Enfin, les méthodes proposées représentent une approche prospective pour de futurs développements de systèmes ICM humains. / Brain Computer Interface (BCI) is a system for translation of brain neural activity into commands for external devices. This study was undertaken as a step toward the fully autonomous (self-paced) BCI functioning in natural environment which is of crucial importance for BCI clinical applications. To model the natural environment binary self-paced BCI experiments were carried out in freely moving animals. In comparison to the previous works, the long-term experimental sessions were carried out, which better comply with the real-life applications requirements. The main goal of the study was to discriminate the specific neuronal pattern related to the animal's control action against background brain activity of freely-moving animal. To achieve the necessary level of selectivity the Multi-Way Analysis was chosen since it provides a simultaneous signal processing in several domains, namely, temporal, frequency and spatial. To improve the capacity of the generic Multy-Way PLS approach for treatment of high-dimensional data, the Iterative NPLS algorithm is introduced in the current study. Having lower memory requirements it provides huge datasets treatment, allows high resolution, preserves the accuracy of the generic algorithm, and demonstrates better robustness. For adaptive calibration of BCI system the Recursive NPLS algorithm is proposed. Finally, the Penalized NPLS algorithm is developed for effective selection of feature subsets, namely, for subset of electrodes. The proposed algorithms were tested on artificial and real datasets. They demonstrated performance which either suppress or is comparable with one of the generic NPLS algorithm. Their computational efficiency is acceptable for the real-time applications. Developed algorithms were applied for calibration of the BCI system and were used in the real-time close-loop binary BCI experiments in animals. The proposed methods represent a prospective approach for further development of a human BCI system.

On s’intéresse ici aux erreurs de modélisation liées à l’usage de modèles de flammelette sous-maille en combustion turbulente non prémélangée. Le but de cette thèse est de développer une stratégie d’estimation d’erreur a posteriori pour déterminer le meilleur modèle parmi une hiérarchie, à un coût numérique similaire à l’utilisation de ces mêmes modèles. Dans un premier temps, une stratégie faisant appel à un estimateur basé sur les résidus pondérés est développée et testée sur un système d’équations d’advection-diffusion-réaction. Dans un deuxième temps, on teste la méthodologie d’estimation d’erreur sur un autre système d’équations, où des effets d’extinction et de réallumage sont ajoutés. Lorsqu’il n’y a pas d’advection, une analyse asymptotique rigoureuse montre l’existence de plusieurs régimes de combustion déjà observés dans les simulations numériques. Nous obtenons une approximation des paramètres de réallumage et d’extinction avec la courbe en «S», un graphe de la température maximale de la flamme en fonction du nombre de Damköhler, composée de trois branches et d’une double courbure. En ajoutant des effets advectifs, on obtient également une courbe en «S» correspondant aux régimes de combustion déjà identifiés. Nous comparons les erreurs de modélisation liées aux approximations asymptotiques dans les deux régimes stables et établissons une nouvelle hiérarchie des modèles en fonction du régime de combustion. Ces erreurs sont comparées aux estimations données par la stratégie d’estimation d’erreur. Si un seul régime stable de combustion existe, l’estimateur d’erreur l’identifie correctement ; si plus d’un régime est possible, on obtient une fac˛on systématique de choisir un régime. Pour les régimes où plus d’un modèle est approprié, la hiérarchie prédite par l’estimateur est correcte. / We are interested here in the modeling errors of subgrid flamelet models in nonpremixed turbulent combustion. The goal of this thesis is to develop an a posteriori error estimation strategy to determine the best model within a hierarchy, with a numerical cost at most that of using the models in the first place. Firstly, we develop and test a dual-weighted residual estimator strategy on a system of advection-diffusion-reaction equations. Secondly, we test that methodology on another system of equations, where quenching and ignition effects are added. In the absence of advection, a rigorous asymptotic analysis shows the existence of many combustion regimes already observed in numerical simulations. We obtain approximations of the quenching and ignition parameters, alongside the S-shaped curve, a plot of the maximal flame temperature as a function of the Damköhler number, consisting of three branches and two bends. When advection effects are added, we still obtain a S-shaped curve corresponding to the known combustion regimes. We compare the modeling errors of the asymptotic approximations in the two stable regimes and establish new model hierarchies for each combustion regime. These errors are compared with the estimations obtained by using the error estimation strategy. When only one stable combustion regime exists, the error estimator correctly identifies that regime; when two or more regimes are possible, it gives a systematic way of choosing one regime. For regimes where more than one model is appropriate, the error estimator’s predicted hierarchy is correct.

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