L'Extraction de connaissances dans les bases de données est un processus qui vise à extraire un ensemble réduit de connaissances à fortes valeurs ajoutées à partir d'un grand volume de données. La fouille de données, l'une des étapes de ce processus, regroupe un certain nombre de taches, telles que : le clustering, la classification, l'extraction de règles d'associations, etc.La problématique d'extraction de règles d'association nécessite l'étape d'extraction de motifs fréquents. Nous distinguons plusieurs catégories de motifs : les motifs classiques, les motifs flous, les motifs graduels, les motifs séquentiels. Ces motifs diffèrent selon le type de données à partir desquelles l'extraction est faite et selon le type de corrélation qu'ils présentent.Les travaux de cette thèse s'inscrivent dans le contexte d'extraction de motifs graduels, flous et clos. En effet, nous définissons de nouveaux systèmes de clôture de la connexion de Galois relatifs, respectivement, aux motifs flous et graduels. Ainsi, nous proposons des algorithmes d'extraction d'un ensemble réduit pour les motifs graduels et les motifs flous.Nous proposons également deux approches d'extraction de motifs graduels flous, ceci en passant par la génération automatique des fonctions d'appartenance des attributs.En se basant sur les motifs flous clos et graduels clos, nous définissons des bases génériques de toutes les règles d'association graduelles et floues. Nous proposons également un système d'inférence complet et valide de toutes les règles à partir de ces bases. / Knowledge discovery in databases is a process aiming at extracting a reduced set of valuable knowledge from a huge amount of data. Data mining, one step of this process, includes a number of tasks, such as clustering, classification, of association rules mining, etc.The problem of mining association rules requires the step of frequent patterns extraction. We distinguish several categories of frequent patterns: classical patterns, fuzzy patterns, gradual patterns, sequential patterns, etc. All these patterns differ on the type of the data from which the extraction is done and the type of the relationship that represent.In this thesis, we particularly contribute with the proposal of fuzzy and gradual patterns extraction method.Indeed, we define new systems of closure of the Galois connection for, respectively, fuzzy and gradual patterns. Thus, we propose algorithms for extracting a reduced set of fuzzy and gradual patterns.We also propose two approaches for automatically defining fuzzy modalities that allow obtaining relevant fuzzy gradual patterns.Based on fuzzy closed and gradual closed patterns, we define generic bases of fuzzy and gradual association rules. We thus propose a complet and valid inference system to derive all redundant fuzzy and gradual association rules.

Dans les habitations collectives, nous observons la répétition en séries de fenêtres, de balcons, de façades, de logements et d'immeubles identiques. Idéologique au XIXème siècle avec la pensée d'un l'homme type pour raison de rendement social, idéaliste avec le projet d'une productivité industrielle, politique des grands ensembles, la série d'une même cellule dans le même immeuble ou d'un même immeuble dans un ensemble est le paradigme de l'habitation collective. Cette répétition n'est pas un thème reconnu de la recherche en architecture comme le type, reproduction d'une même caractéristique dans des objets différents. En posant la question de cette répétition dans le projet et de ses conséquences sur la singularité des œuvres nous ouvrons une voie de la recherche en architecture. Les grands ensembles offrent l'homogénéité de conditions nationales et Toulouse, celle de conditions locales, nécessaires à la généralisation des résultats. A partir des permis de construire et d'enquêtes de terrain, nous avons constitué un état des lieux des 17 grands ensembles toulousains. La méthode d’étude s’appuie sur la réversibilité de l’analyse architecturale et du projet et, en l’absence d’écrits des architectes du corpus sur leur démarche, sur l’homologie entre la répétition et la composition beaux-arts à laquelle ils ont été majoritairement formés. L'analyse opère avec et par le dessin, espace du projet. Dans chacun des 17 grands ensembles, l’étude des configurations des séries aux différentes échelles de répétition permet de connaitre les logiques libres et imposées et d'interpréter le parti de l’architecte. Une lecture transversale des œuvres permet de recenser les conjugaisons des variables formelles et structurelles des séries et leurs ajustements et de constater que la répétition intervient à des moments différents du projet. / In collective habitats, we can observe repetitions in series of windows, balconies, facades, housing and identical buildings. Ideological during the 19th century, with the idea of a stereotype human for social return reasons, idealistic with the project of industrial productivity, housing estate policies, the series of a same cell in the same building or that of a same building in an ensemble, is the paradigm of collective living. This repetition isn't a recognized theme in architectural research as is the type (reproduction of a same characteristic in different objects). By asking the question of this repetition in the project and by its consequences on the singularity of works we open a path to architectural research. The estate policies offer homogeneity in national and in local (Toulouse) conditions which are necessary to the generalization of results. We have constituted an analysis of the current situation from the building permits and in field research of the 17 major Toulousian estates. The study method is based on the reversibility of the architectural analysis and on the project, and considering the absence of written work from the architects in the consensus concerning their approach on the homology between the repetition and the beaux-arts composition with which they have generally been trained. The analysis operates with and through drawing and space of the project. In each of the 17 estates, the study of the configuration of the series on different scales of repetition, allow to be aware of the liberal and imposed logics and to interpret the architects decision. A transversal reading of the works allows an inventory of the variable conjugations whether formal or structural of the series and their adjustments et to establish if the repetition intervenes at different moments of the project.

Proteins and DNA are large, complex molecules that carry out biological functions essential to all life. Their successful operation relies on adopting specific structures, stabilized by intra-molecular interactions between atoms. The spatial and temporal resolution required to study the mechanics of these molecules in full detail can only be obtained using computer simulations of molecular models. In a molecular dynamics simulation, a trajectory of the system is generated, which allows mapping out the states and dynamics of the molecule. However, the time and length scales characteristic of biological events are many orders of magnitude larger than the resolution needed to accurately describe the microscopic processes of the atoms. To overcome this problem, sampling methods have been developed that enhance the occurrence of rare but important events, which improves the statistics of simulation data. This thesis summarizes my work on developing the AWH method, an algorithm that adaptively optimizes sampling toward a target function and simultaneously finds and assigns probabilities to states of the simulated system. I have adapted AWH for use in molecular dynamics simulations. In doing so, I investigated the convergence of the method as a function of its input parameters and improved the robustness of the method. I have also worked on a generally applicable approach for calculating the target function in an automatic and non-arbitrary way. Traditionally, the target is set in an ad hoc way, while now sampling can be improved by 50% or more without extra effort. I have also used AWH to improve sampling in two biologically relevant applications. In one paper, we study the opening of a DNA base pair, which due to the stability of the DNA double helix only very rarely occurs spontaneously. We show that the probability of opening depends on both nearest-neighbor and longer-range sequence effect and furthermore structurally characterize the open states. In the second application the permeability and ammonia selectivity of the membrane protein aquaporin is investigated and we show that these functions are sensitive to specific mutations. / <p>QC 20171117</p>

A pivotal moment in machine learning research was the creation of an important new research area, known as Ensemble Learning. In this work, we argue that ensembles are a very general concept, and though they have been widely used, they can be applied in more situations than they have been to date. Rather than using them only to combine the output of an algorithm, we can apply them to decisions made inside the algorithm itself, during the learning step. We call this approach Inner Ensembles. The motivation to develop Inner Ensembles was the opportunity to produce models with the similar advantages as regular ensembles, accuracy and stability for example, plus additional advantages such as comprehensibility, simplicity, rapid classification and small memory footprint. The main contribution of this work is to demonstrate how broadly this idea can be applied, and highlight its potential impact on all types of algorithms. To support our claim, we first provide a general guideline for applying Inner Ensembles to different algorithms. Then, using this framework, we apply them to two categories of learning methods: supervised and un-supervised. For the former we chose Bayesian network, and for the latter K-Means clustering. Our results show that 1) the overall performance of Inner Ensembles is significantly better than the original methods, and 2) Inner Ensembles provide similar performance improvements as regular ensembles.

Dans cette thèse, nous proposons une méthode pour la visualisation d'ensembles chevauchant et de basé sur les diagrammes d'Euler. Les diagrammes d'Euler sont probablement les plus intuitifs pour représenter de manière schématique les ensembles qui partagent des éléments. Cette métaphore visuelle est ainsi un outil puissant en termes de visualisation d'information. Cependant, la génération automatique de ces diagrammes présente encore de nombreux problèmes difficiles. Premièrement, tous les clustering chevauchants ne peuvent pas être dessinées avec les diagrammes d'Euler classiques. Deuxièmement, la plupart des algorithmes existants permettent uniquement de représenter les diagrammes de dimensions modestes. Troisièmement, les besoins des applications réelles requièrent un processus plus fiable et plus rapide.Dans cette thèse, nous décrivons une version étendue des diagrammes d'Euler. Cette extension permet de modéliser l'ensemble des instances de la classe des clustering chevauchants. Nous proposons ensuite un algorithme automatique de génération de cette extension des diagrammes d'Euler. Enfin, nous présentons une implémentation logicielle et des expérimentations de ce nouvel algorithme. / In this thesis, we propose a method for the visualisation of overlapping sets and of fuzzy graph clusterings based on Euler diagrams.Euler diagrams are probably the most intuitive and most used method to depict sets in which elements can be shared. Such a powerful visualisation metaphor could be an invaluable visualisation tool, but the automatic generation of Euler diagrams still presents many challenging problems. First, not all instances can be drawn using standard Euler diagrams. Second, most existing algorithms focus on diagrams of modest dimensions while real-world applications typically features much larger data. Third, the generation process must be reliable and reasonably fast.In this thesis, we describe an extended version of Euler diagrams that can be produced for every input instance. We then propose an automatic procedure for the generation of such diagrams that specifically target large input instances. Finally, we present a software implementation of this method and we describe some output examples generated on real-world data.

The United House of Prayer was established by Marcelino Manuel da Graça (1881-1960), who is also known as Charles Manuel “Sweet Daddy” Grace, or “Daddy” Grace. He founded and developed the use of the shout bands which are charismatic gospel trombone ensembles within this church. This study explores the importance of shout bands and examines them from multiple perspectives focusing in particular on worship practices. Additionally, it examines rhythmic elements as the most important characteristic of music performed by these unique ensembles, rhythms that reflect the preacher’s personal timing and inflections that the trombones then imitate. The approach used here supports a deeper understanding of the United House of Prayer and of the trombone in church services of this denomination. Indeed, it ultimately establishes the trombone’s role in the United House of Prayer.

In this study, an efficient coupling between Monte Carlo (MC) molecular simulation and Darcy-scale flow in porous media is presented. The cell-centered finite difference method with a non-uniform rectangular mesh were used to discretize the simulation domain and solve the governing equations. To speed up the MC simulations, we implemented a recently developed scheme that quickly generates MC Markov chains out of pre-computed ones, based on the reweighting and reconstruction algorithm. This method astonishingly reduces the required computational time by MC simulations from hours to seconds. In addition, the reweighting and reconstruction scheme, which was originally designed to work with the LJ potential model, is extended to work with a potential model that accounts for the molecular quadrupole moment of fluids with non-spherical molecules such as CO2. The potential model was used to simulate the thermodynamic equilibrium properties for single-phase and two-phase systems using the canonical ensemble and the Gibbs ensemble, respectively. Comparing the simulation results with the experimental data showed that the implemented model has an excellent fit outperforming the standard LJ model. To demonstrate the strength of the proposed coupling in terms of computational time efficiency and numerical accuracy in fluid properties, various numerical experiments covering different compressible single-phase flow scenarios were conducted. The novelty in the introduced scheme is in allowing an efficient coupling of the molecular scale and Darcy scale in reservoir simulators. This leads to an accurate description of the thermodynamic behavior of the simulated reservoir fluids; consequently enhancing the confidence in the flow predictions in porous media.

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Semi-supervised self-learning algorithms have been shown to improve classifier accuracy under a variety of conditions. In this thesis, semi-supervised self-learning using ensembles of random forests and fuzzy c-means clustering similarity was applied to three data sets to show where improvement is possible over random forests alone. Two of the data sets are emulations of large simulations in which the data may be distributed. Additionally, the ratio of majority to minority class examples in the training set was altered to examine the effect of training set bias on performance when applying the semi-supervised algorithm.

Access control policies typically take the form of a set of static rules pertaining to individual entities under control. This can be impractical in real-world scenarios: authorization invariably depends on wider situational context which often tends to be highly dynamic. This leads to increasingly complex rules, which have to change over time to reflect the evolution of the controlled system. Ensemble-based architectures allow dynamic formation of goal-oriented groups in systems with large number of independent autonomous components. Because of the ad-hoc and situation-aware nature of group formation, ensembles offer a novel way of approaching access control. The goal of this work is to design a Scala framework and internal DSL for describing access control related situations via ensembles. In particular, the framework will define ensemble semantics suitable for evaluating the ensembles and establishing access control at runtime.