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DTSTART;TZID=Europe/Paris:20181109T140000
DTEND;TZID=Europe/Paris:20181109T150000
DTSTAMP:20181107T131026Z
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UID:6163-1541772000-1541775600@www.loria.fr
SUMMARY:PhD Defense : Gabin Personeni
DESCRIPTION:Gabin Personeni (Orpailleur) will defend his thesis on Friday\, November 9th at 2pm in room A008. \nHis thesis is entitled « Contribution of domain ontologies for knowledge discovery in biomedical data ». \n \nThe jury will be composed of the following 8 members :\n\nRapporteurs\n-Olivier Dameron\, Maître de Conférences à l’Université de Rennes 1\n-Céline Rouveirol\, Professeur à l’Université Paris 13\nExaminateurs\n-Jérôme Azé\, Professeur à l’Université de Montpellier\n-Anne Boyer\, Professeur à l’Université de Lorraine\n-Adrien Coulet\, Maître de Conférences à l’Université de Lorraine\n-Marie-Dominique\, Chargée de Recherches\, CNRS\nInvités\n-Michel Dumontier\, Distinguished Professor\, Maastricht University\n-Malika Smaïl-Tabbone\,  Maître de Conférences à l’Université de Lorraine\n\n\n\n\nAbstract\n\n\n   The semantic Web proposes standards and tools to formalize and share knowledge on the Web\, in the form of ontologies. Biomedical ontologies and associated data represents a vast collection of complex\, heterogeneous and linked knowledge. The analysis of such knowledge presents great opportunities in healthcare\, for instance in pharmacovigilance. This thesis explores several ways to make use of this biomedical knowledge in the data mining step of a knowledge discovery process. In particular\, we propose three methods in which several ontologies cooperate to improve data mining results.\n A first contribution of this thesis describes a method based on pattern structures\, an extension of formal concept analysis\, to extract associations between adverse drug events from patient data. In this context\, a phenotype ontology and a drug ontology cooperate to allow a semantic comparison of these complex adverse events\, and leading to the discovery of associations between such events at varying degrees of generalization\, for instance\, at the drug or drug class level.\nA second contribution uses a numeric method based on semantic similarity measures to classify different types of genetic intellectual disabilities\, characterized by both their phenotypes and the functions of their linked genes. We study two different similarity measures\, applied with different combinations of phenotypic and gene function ontologies. In particular\, we investigate the influence of each domain of knowledge represented in each ontology on the classification process\, and how they can cooperate to improve that process.\nFinally\, a third contribution uses the data component of the semantic Web\, the Linked Open Data (LOD)\, together with linked ontologies\, to characterize genes responsible for intellectual deficiencies. We use Inductive Logic Programming\, a suitable method to mine relational data such as LOD while exploiting domain knowledge from ontologies by using reasoning mechanisms. Here\, ILP allows to extract from LOD and ontologies a descriptive and predictive model of genes responsible for intellectual disabilities.\nThese contributions illustrates the possibility of having several ontologies cooperate to improve various data mining processes.
URL:https://www.loria.fr/event/phd-defense-gabin-personeni/
CATEGORIES:Soutenance
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BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20181030T140000
DTEND;TZID=Europe/Paris:20181030T160000
DTSTAMP:20181026T140216Z
CREATED:20181026T135222Z
LAST-MODIFIED:20181026T140216Z
UID:6147-1540908000-1540915200@www.loria.fr
SUMMARY:PhD Defense : Hayat Nasser
DESCRIPTION:Hayat Nasser will defend her thesis on Tuesday\, October 30th at 2pm in room C005. \nHer presentation is entitled « Tools for the analysis of noisy discrete curves ». \n \nDissertation committee:\n\n\n\n\n\nIsabelle DEBLED-RENNESSON\n\nProfesseure des Universités\n\nUniversité de Lorraine\n\nDirectrice de thèse\n\n\nFabien FESCHET\n\nProfesseur des Universités\n\nUniversité Clermont Auvergne\n\nRapporteur\n\n\nEric ANDRES\n\nProfesseur des Universités\n\nUniversité de Poitiers\n\nRapporteur\n\n\nYukiko KENMOCHI\n\nChargée de Recherche\n\nUniversité Paris-Est\n\nExaminatrice\n\n\nLaurent WENDLING\n\nProfesseur des Universités\n\nUniversité Paris Descartes (Paris V)\n\nExaminateur\n\n\nSalvatore-Antoine TABBONE\n\nProfesseur des Universités\n\nUniversité de Lorraine\n\nExaminateur\n\n\nPhuc NGO\n\nMaître de Conférences\n\nUniversité de Lorraine\n\nExaminatrice\n\n\n\n\nAbstract:\n\n\n\n\nIn this thesis\, we are interested in the study of noisy discrete curves that correspond to the contours of objects in images. We have proposed several tools to analyze them. The dominant points (points whose curvature estimation is locally maximal) play a very important role in pattern recognition and we have developed a non-heuristic\, fast and reliable method to detect them in a discrete curve. This method is an improvement of an existing method introduced by Nguyen et al.. The new method consists in calculating a measure of angle. We have also proposed two approaches for polygonal simplification: an automatic method minimizing\, and another fixing the vertex number of the resulting polygon.\n\nThen we proposed a new geometric tool\, called adaptive tangential cover ATC\, based on the detection of meaningful thickness introduced by Kerautret et al.. These thicknesses are calculated at each point of the contours allow to locally estimate the noise level. In this context our construction algorithm of adaptive tangential cover takes into account the different levels of noise present in the curve to be studied and does not require a parameter.\n\nTwo applications of ATC in image analysis are proposed: on the one hand the decomposition of the contours of a shape in an image into arcs and right segments and on the other hand\, within the framework of a project with an Indian university about the sign language and recognition of hand gestures. Firstly\, the method to decompose discrete curves into arcs and straight segments is based on two tools: dominant point detection using adaptive tangential cover and tangent space representation of the polygon issued from detected dominant points. The experiments demonstrate the robustness of the method w.r.t. noise. Secondly\, from the outlines of the hands extracted from images taken by a Kinect\, we propose several descriptors from the selected dominant points computed from the adaptive tangential cover. The proposed descriptors\, which are a combination of statistical descriptors and topological descriptors\, are effective and suitable for gesture recognition. \n\n\n\nKeywords: Discret geometry\, dominant points\, tangential cover\, polygonal simplification\, image processing
URL:https://www.loria.fr/event/phd-defense-hayat-nasser/
CATEGORIES:Soutenance
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BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20180925T131500
DTEND;TZID=Europe/Paris:20180925T153000
DTSTAMP:20180919T083645Z
CREATED:20180917T110627Z
LAST-MODIFIED:20180919T083645Z
UID:5950-1537881300-1537889400@www.loria.fr
SUMMARY:PhD Defense : Baldwin Dumortier
DESCRIPTION:Baldwin Dumortier (Multispeech) will defend his thesis on Tuesday\, September 25th at 1.15pm in room C005. \nHis thesis is entitled « Acoustic control of wind farms ». \n \n« Contrôle acoustique d’un parc éolien » \nRapporteurs :\nChristophe Gonzales\, Professeur\, Université Pierre et Marie Curie\, Paris.\nPatrick Danès\, Professeur\, Université Paul Sabatier\, Toulouse.\n\nExaminateurs :\nMathieu Lagrange\, Chargé de recherche CNRS\, Laboratoire des Sciences du Numérique de Nantes\, Nantes.\nMarianne Clausel\, Professeur\, Université de Lorraine\, IECL\, Nancy.\n\nDirecteurs de thèse :\nEmmanuel Vincent\, Directeur de Recherche Inria\, LORIA\, Nancy.\nMadalina Deaconu\, Chargée de Recherche Inria\, IECL\, Nancy.\n\n\nActuellement\, la construction d’un parc éolien nécessite une étude acoustique qui doit assurer la tranquillité des habitants aux alentours et la conformité au regard de la réglementation en vigueur. Pour ce faire\, des mesures acoustiques sont réalisées sur une période d’environ deux semaines. Durant ces mesures\, des cycles de marche et d’arrêt des machines sont réalisés afin de mesurer la différence de niveau sonore entre le bruit ambiant (éoliennes en fonctionnement) et le bruit résiduel (éoliennes à l’arrêt). Un plan de bridage des machines est alors calculé et fourni à l’exploitant afin de l’implémenter dans le système de contrôle local des éoliennes (SCADA).\nActuellement\, ce plan dépend grossièrement des conditions météorologiques et des périodes de la journée\, supposées corrélées aux conditions acoustiques. En pratique\, cette manière de procéder engendre fréquemment des dépassements du critère réglementaire et/ou des pertes de production électrique. Ceci est dû aux conditions acoustiques qui évoluent sans cesse\, à la fois pour le bruit particulier (bruit des éoliennes seules) qui dépend finement des conditions météorologiques\, et\npour le bruit résiduel qui dépend de toutes les autres sources de l’environnement et qui est fondamentalement de nature stochastique.\nLa thèse vise à proposer un algorithme de contrôle du parc éolien en temps réel basé sur un nouveau paradigme de contrôle. On y étudie la possibilité de contrôler un parc éolien à partir d’un système en boite noire d’estimation temps-réel du niveau résiduel et du niveau particulier par séparation de sources. Dans le manuscrit\, on définit tout d’abord une formulation du problème dans le cadre du contrôle en identifiant les problématiques propres à ce sujet\, une définition des variables du problème et en se rattachant à l’état de l’art du contrôle. Ensuite\, on propose deux solutions complètes de contrôle et une évaluation expérimentale. La première est une solution déterministe\, qui s’appuie sur un algorithme d’optimisation combinatoire sous contrainte\, et qui s’inspire du contrôle actuel des parcs éoliens tout en tenant compte de l’estimation par séparation de sources\, alors supposée exacte. On y propose en outre une étude de la capacité du système\ndéterministe à satisfaire le critère réglementaire français qui est aujourd’hui calculé à l’aide de médianes temporelles des variables acoustiques. La seconde est une solution stochastique\, qui est basée sur une représentation d’état des variables acoustiques et des incertitudes gaussiennes. Elle inclut un filtrage de Kalman non-linéaire\, afin de fusionner l’incertitude sur le modèle acoustique et l’incertitude de séparation de sources\, un algorithme espérance-maximisation afin de ré-estimer les incertitudes du problème qui varient d’un parc à un autre\, et une adaptation robuste de l’algorithme combinatoire afin de prendre en compte les incertitudes estimées.\n\n\n\n(EN)\nCurrently\, acoustic studies are required to set wind farms up. They must ensure the tranquility of the inhabitants around the farms in accordance with current regulations. For this purpose\, acoustic measurements are made during a couple of weeks. When measuring\, the wind turbines are periodically stopped in order to evaluate the difference between ambient noise levels (with the turbines on) and residual noise levels (with the turbines off). A curtailment plan is then computed and sent to the wind farm owner in order to set it up in the local turbine control system (SCADA). Currently\, the curtailment plan roughly depends on the weather conditions and the time of the day which are allegedly correlated to the acoustic variables. In practice\, it frequently leads to violations of the acoustic constraints or electrical power loss. This is because\nthe acoustic conditions constantly and strongly evolve over time : the wind turbine noise level finely depends on the weather conditions and the residual noise level depends on all the other acoustic sources and has therefore a stochastic nature. The goal of the thesis is to design a principled real-time control algorithm for wind farms.\nTo do so\, we investigate the use of a black-box source separation system that estimates the residual noise level and the wind turbine noise level. We first provide a theoretical formulation of the problem by accounting for specific practical issues\, by defining the variables of the problem and by binding these issues to the state of the art. Then\, we propose two complete control solutions and run an experimental evaluation. The first solution is a deterministic algorithm based on a constrained combinatorial optimization algorithm\, which is inspired by the current approach for controlling wind farms while exploiting the source separation system. Moreover\, we present a study of its ability to fulfill the French acoustic constraints that are computed as temporal medians of the acoustic variables. The second solution is stochastic and based on a state-space model defined by means of Gaussian uncertainties. It features a nonlinear Kalman filter in order to fuse the uncertainties of the model and of the source separation system\, an Expectation-Maximization algorithm that computes the uncertainties for a specific farm\, and a robust variant of the deterministic algorithm that takes the estimated uncertainties into account when computing the optimal command.
URL:https://www.loria.fr/event/phd-defense-baldwin-dumortier/
CATEGORIES:Soutenance
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DTSTART;TZID=Europe/Paris:20180907T143000
DTEND;TZID=Europe/Paris:20180907T163000
DTSTAMP:20180903T111134Z
CREATED:20180903T111134Z
LAST-MODIFIED:20180903T111134Z
UID:5901-1536330600-1536337800@www.loria.fr
SUMMARY:PhD Defense : Simon Abelard
DESCRIPTION:Simon Abelard will defend his thesis on Friday\, September 7th at 2.30pm in room C005. \nHis presentation is entitled « Point-counting on hyperelliptic curves defined over finite fields of large characteristic: algorithms and complexities« . \nReferees:\nChristophe Ritzenthaler\, Professor\, Université Rennes 1\nFréderik Vercauteren\, Associate Professor\, KU Leuven \nExaminers:\nMagali Bardet\, Associate Professor\, Université de Rouen\nElisa Gorla\, Professor\, Université de Neuchatel\nGuillaume Hanrot\, Professor\, ÉNS Lyon \nAdvisors:\nPierrick Gaudry\, Senior Research Scientist CNRS\, Nancy\nPierre-Jean Spaenlehauer\, Research Scientist Inria\, Nancy \nAbstract:\nCounting points on algebraic curves has drawn a lot of attention due to its many applications from number theory and arithmetic geometry to cryptography and coding theory. In this thesis\, we focus on counting points on hyperelliptic curves over finite fields of large characteristic p. In this setting\, the most suitable algorithms are currently those of Schoof and Pila\, because their complexities are polynomial in log p. However\, their dependency in the genus g of the curve is exponential\, and this is already painful even in genus 3. \nOur contributions mainly consist of establishing new complexity bounds with a smaller dependency in g of the exponent of log p. For hyperelliptic curves\, previous work showed that it was quasi-quadratic\, and we reduced it to a linear dependency. Restricting to more special families of hyperelliptic curves with explicit real multiplication (RM)\, we obtained a constant bound for this exponent. \nIn genus 3\, we proposed an algorithm based on those of Schoof and Gaudry-Harley-Schost whose complexity is prohibitive in general\, but turns out to be reasonable when the input curves have explicit RM. In this more favorable case\, we were able to count points on a hyperelliptic curve defined over a 64-bit prime field.
URL:https://www.loria.fr/event/phd-defense-simon-abelard/
CATEGORIES:Soutenance
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