Dissertations / Theses on the topic 'Analyse des données géométriques'
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Feydy, Jean. "Analyse de données géométriques, au delà des convolutions." Thesis, université Paris-Saclay, 2020. http://www.theses.fr/2020UPASN017.
Full textGeometric data analysis, beyond convolutionsTo model interactions between points, a simple option is to rely on weighted sums known as convolutions. Over the last decade, this operation has become a building block for deep learning architectures with an impact on many applied fields. We should not forget, however, that the convolution product is far from being the be-all and end-all of computational mathematics.To let researchers explore new directions, we present robust, efficient and principled implementations of three underrated operations: 1. Generic manipulations of distance-like matrices, including kernel matrix-vector products and nearest-neighbor searches.2. Optimal transport, which generalizes sorting to spaces of dimension D > 1.3. Hamiltonian geodesic shooting, which replaces linear interpolation when no relevant algebraic structure can be defined on a metric space of features.Our PyTorch/NumPy routines fully support automatic differentiation and scale up to millions of samples in seconds. They generally outperform baseline GPU implementations with x10 to x1,000 speed-ups and keep linear instead of quadratic memory footprints. These new tools are packaged in the KeOps (kernel methods) and GeomLoss (optimal transport) libraries, with applications that range from machine learning to medical imaging. Documentation is available at: www.kernel-operations.io/keops and /geomloss
Chaouch, Mohamed. "Contribution à l'estimation non paramétrique des quantiles géométriques et à l'analyse des données fonctionnelles." Phd thesis, Université de Bourgogne, 2008. http://tel.archives-ouvertes.fr/tel-00364538.
Full textRoudet, Céline. "Compression adaptative de surfaces par ondelettes géométriques." Phd thesis, Université Claude Bernard - Lyon I, 2008. http://tel.archives-ouvertes.fr/tel-00589400.
Full textBonaccorsi, Thomas. "Modélisation pluridisciplinaire d'expériences d'irradiation dans un réacteur d'irradiation technologique." Aix-Marseille 2, 2007. http://theses.univ-amu.fr.lama.univ-amu.fr/2007AIX22051.pdf.
Full textA Material Testing Reactor (MTR) makes it possible to irradiate material samples under intense neutron and photonic fluxes. These experiments are carried out in experimental devices localised in the reactor core or in periphery (reflector). Available physics simulation tools only treat, most of the time, one physics field in a very precise way. Multiphysic simulations of irradiation experiments therefore require a sequential use of several calculation codes and data exchanges between these codes: this corresponds to problems coupling. In order to facilitate multiphysic simulations, this thesis sets up a data model based on data-processing objects, called Technological Entities. This data model is common to all of the physics fields. It permits defining the geometry of an irradiation device in a parametric way and to associate informations about materials to it. Numerical simulations are encapsulated into interfaces providing the ability to call specific functionalities with the same command ( to initialize data, to launch calculations, to post-treat, to get results,. . . ). Thus, once encapsulated, numerical simulations can be re-used for various studies. This data model is developed in a SALOME platform component. The first application case made it possible to perform neutronic simulations (OSIRIS reactor and RJH) coupled with fuel behavior simulations. In a next step, thermalhydraulics could also be taken into account. In addition to the improvement of the calculation accuracy due to the physical phenomena coupling, the time spent in the development phase of the simulation is largely reduced and the possibilities of uncertainty treatment are under consideration
Bonis, Thomas. "Algorithmes d'apprentissage statistique pour l'analyse géométrique et topologique de données." Thesis, Université Paris-Saclay (ComUE), 2016. http://www.theses.fr/2016SACLS459/document.
Full textIn this thesis, we study data analysis algorithms using random walks on neighborhood graphs, or random geometric graphs. It is known random walks on such graphs approximate continuous objects called diffusion processes. In the first part of this thesis, we use this approximation result to propose a new soft clustering algorithm based on the mode seeking framework. For our algorithm, we want to define clusters using the properties of a diffusion process. Since we do not have access to this continuous process, our algorithm uses a random walk on a random geometric graph instead. After proving the consistency of our algorithm, we evaluate its efficiency on both real and synthetic data. We then deal tackle the issue of the convergence of invariant measures of random walks on random geometric graphs. As these random walks converge to a diffusion process, we can expect their invariant measures to converge to the invariant measure of this diffusion process. Using an approach based on Stein's method, we manage to obtain quantitfy this convergence. Moreover, the method we use is more general and can be used to obtain other results such as convergence rates for the Central Limit Theorem. In the last part of this thesis, we use the concept of persistent homology, a concept of algebraic topology, to improve the pooling step of the bag-of-words approach for 3D shapes
Poupeau, Benoît. "Analyse et requêtes de données géographiques 3 D : contributions de la cristallographie géométrique." Phd thesis, Université Paris-Est, 2008. http://tel.archives-ouvertes.fr/tel-00481924.
Full textAamari, Eddie. "Vitesses de convergence en inférence géométrique." Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLS203.
Full textSome datasets exhibit non-trivial geometric or topological features that can be interesting to infer.This thesis deals with non-asymptotic rates for various geometric quantities associated with submanifolds M ⊂ RD. In all the settings, we are given an i.i.d. n-sample with common distribution P having support M. We study the optimal rates of estimation of the submanifold M for the loss given by the Hausdorff metric, of the reach τM, of the tangent space TX M and the second fundamental form I I MX, for X ∈ M both deterministic and random.The rates are given in terms of the sample size n, the instrinsic dimension of M, and its smoothness.In the process, we obtain stability results for existing reconstruction techniques, a denoising procedure and results on the geometry of the reach τM. An extension of Assouad's lemma is presented, allowing to derive minimax lower bounds in singular frameworks
Magnet, Robin. "Robust spectral methods for shape analysis and deformation assessment." Electronic Thesis or Diss., Institut polytechnique de Paris, 2024. http://www.theses.fr/2024IPPAX043.
Full textAutomatically processing and analyzing 3D shapes is an active area in modern research with implications in various fields.A key challenge in shape analysis lies in efficiently comparing shapes, for example to detect abnormalities in scans of organs, which often requires automatically deforming one shape into another, or establishing correspondences between surfaces.In this context, the functional map framework, based on spectral shape analysis, offers a flexible approach to representing and computing these correspondences, serving as a foundation for subsequent analysis.This thesis seeks to address the limitations of existing spectral methods, with the ultimate goal to achieve robust and efficient shape comparisons applicable to real-world data. In the first part, we concentrate on assessing deformations between shapes effectively, and introduce a descriptor of differences between shapes, capturing information about the distortion around each point.Next, we apply similar tools on a set of skull scans for craniofacial disease detection, highlighting the specific requirements of shape matching practitioners. Notably, we underscore the significance of correspondence smoothness and scalability to dense meshes.In the second part, we address these needs by extending existing functional map methods. Firstly, we introduce a novel shape correspondence pipeline, which explicitly promotes smoothness of computed correspondences, alongside a new challenging shape matching dataset. Secondly, we focus on enhancing the scalability of functional map pipelines to handle real-world dense meshes.For this, we present an approximation of the functional map, enabling the computation of correspondences on meshes with hundreds of thousands of vertices in a fraction of the processing time required by standard algorithms. Finally, we introduce a new learning-based approach, by modifying existing techniques for functional map computations, eliminating the need for large dense matrix storage in GPU memory, thereby improving scalability and numerical stability.Overall, our work contributes efficient tools for analyzing differences between shapes and provides general methods to simplify and accelerate correspondence computations, facilitating downstream applications
Dary, Christophe. "Analyse géométrique d'image : application à la segmentation multi-échelle des images médicales." Nantes, 1992. http://www.theses.fr/1992NANT07VS.
Full textNérot, Agathe. "Modélisation géométrique du corps humain (externe et interne) à partir des données externes." Thesis, Lyon, 2016. http://www.theses.fr/2016LYSE1133.
Full textDigital human models have become instrumental tools in the analysis of posture and motion in many areas of biomechanics, including ergonomics and clinical settings. These models include a geometric representation of the body surface and an internal linkage composed of rigid segments and joints allowing simulation of human movement. The customization of human models first starts with the adjustment of external anthropometric dimensions, which are then used as input data to the adjustment of internal skeletal segments lengths. While the external data points are more readily measurable using current 3D scanning tools, the scientific challenge is to predict the characteristic points of the internal skeleton from external data only. The Institut de Biomécanique Humaine Georges Charpak (Arts et Métiers ParisTech) has developed 3D reconstruction methods of bone and external envelope from biplanar radiographs obtained from the EOS system (EOS Imaging, Paris), a low radiation dose technology. Using this technology, this work allowed proposing new external-internal statistical relationships to predict points of the longitudinal skeleton, particularly the complete set of spine joint centers, from a database of 80 subjects. The implementation of this work could improve the realism of current digital human models used for biomechanical analysis requiring information of joint center location, such as the estimation of range of motion and joint loading
Bienaise, Solène. "Tests combinatoires en analyse géométrique des données - Etude de l'absentéisme dans les industries électriques et gazières de 1995 à 2011 à travers des données de cohorte." Phd thesis, Université Paris Dauphine - Paris IX, 2013. http://tel.archives-ouvertes.fr/tel-00941220.
Full textBauchet, Jean-Philippe. "Structures de données cinétiques pour la modélisation géométrique d’environnements urbains." Thesis, Université Côte d'Azur (ComUE), 2019. http://www.theses.fr/2019AZUR4091.
Full textThe geometric modeling of urban objects from physical measurements, and their representation in an accurate, compact and efficient way, is an enduring problem in computer vision and computer graphics. In the literature, the geometric data structures at the interface between physical measurements and output models typically suffer from scalability issues, and fail to partition 2D and 3D bounding domains of complex scenes. In this thesis, we propose a new family of geometric data structures that rely on kinetic frameworks. More precisely, we compute partitions of bounding domains by detecting geometric shapes such as line-segments and planes, and extending these shapes until they collide with each other. This process results in light partitions, containing a low number of polygonal cells. We propose two geometric modeling pipelines, one for the vectorization of regions of interest in images, another for the reconstruction of concise polygonal meshes from point clouds. Both approaches exploit kinetic data structures to decompose efficiently either a 2D image domain or a 3D bounding domain into cells. Then, we extract objects from the partitions by optimizing a binary labelling of cells. Conducted on a wide range of data in terms of contents, complexity, sizes and acquisition characteristics, our experiments demonstrate the scalability and the versatility of our methods. We show the applicative potential of our method by applying our kinetic formulation to the problem of urban modeling from remote sensing data
Brécheteau, Claire. "Vers une vision robuste de l'inférence géométrique." Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLS334/document.
Full textIt is primordial to establish effective and robust methods to extract pertinent information from datasets. We focus on datasets that can be represented as point clouds in some metric space, e.g. Euclidean space R^d; and that are generated according to some distribution. Of the natural questions that may arise when one has access to data, three are addressed in this thesis. The first question concerns the comparison of two sets of points. How to decide whether two datasets have been generated according to similar distributions? We build a statistical test allowing to one to decide whether two point clouds have been generated from distributions that are equal (up to some rigid transformation e.g. symmetry, translation, rotation...).The second question is about the decomposition of a set of points into clusters. Given a point cloud, how does one make relevant clusters? Often, it consists of selecting a set of k representatives, and associating every point to its closest representative (in some sense to be defined). We develop methods suited to data sampled according to some mixture of k distributions, possibly with outliers. Finally, when the data can not be grouped naturally into $k$ clusters, e.g. when they are generated in a close neighborhood of some sub-manifold in R^d, a more relevant question is the following. How to build a system of $k$ representatives, with k large, from which it is possible to recover the sub-manifold? This last question is related to the problems of quantization and compact set inference. To address it, we introduce and study a modification of the $k$-means method adapted to the presence of outliers, in the context of quantization. The answers we bring in this thesis are of two types, theoretical and algorithmic. The methods we develop are based on continuous objects built from distributions and sub-measures. Statistical studies allow us to measure the proximity between the empirical objects and the continuous ones. These methods are easy to implement in practice, when samples of points are available. The main tool in this thesis is the function distance-to-measure, which was originally introduced to make topological data analysis work in the presence of outliers
Abergel, Violette. "Relevé numérique d’art pariétal : définition d’une approche innovante combinant propriétés géométriques, visuelles et sémantiques au sein d’un environnement de réalité mixte." Thesis, Paris, HESAM, 2020. http://www.theses.fr/2020HESAE021.
Full textThe advances of the last decades in the fields of computer science and metrology have led to the development of efficient measurement tools allowing the digitization of the environment. Although digital technology has not fundamentally overhauled the principles of metric measurement, the improvement of their accuracy, automation and storage capacity has, on the other hand, been a decisive development in many fields. In the case of rock art surveying, their introduction has allowed a massive gathering of 2D and 3D data, meeting various needs for study, monitoring, documentation, archiving, or dissemination. These data provide new and valuable supports for the understanding of the objects of study, in particular concerning their morphological characterization. However, in spite of their great potentials, they often remain under-exploited due to the lack of tools facilitating their manipulation, analysis, and semantic enrichment in multidisciplinary study contexts. Moreover, these methods tend to relegate the cognitive and analytical engagement of the observer behind the measurement tool, causing a deep break between on-site study moments and all off-site processing, or in other words, between real and virtual work environments.This thesis proposes to address these problems by defining an integrated approach allowing the fusion of the geometric, visual and semantic aspects of surveying within a single multimodal mixed reality environment. At the crossroads of the fields of heritage information systems and mixed reality, our goal is to ensure an informational continuity between in situ and ex situ analysis activities. This study led to the development of a functional proof of concept allowing the visualization of 2D and 3D digital data from surveys and their semantic annotation in augmented reality through a web interface
Minguely, Bruno. "Caractérisation géométrique 3-D de la couverture sédimentaire méso-cénozoïque et du substratum varisque dans le Nord de la France : apports des données de sondages et des données géophysiques." Lille 1, 2007. https://pepite-depot.univ-lille.fr/LIBRE/Th_Num/2007/50376-2007-Minguely.pdf.
Full textDa, Silva Sébastien. "Fouille de données spatiales et modélisation de linéaires de paysages agricoles." Thesis, Université de Lorraine, 2014. http://www.theses.fr/2014LORR0156/document.
Full textThis thesis is part of a partnership between INRA and INRIA in the field of knowledge extraction from spatial databases. The study focuses on the characterization and simulation of agricultural landscapes. More specifically, we focus on linears that structure the agricultural landscape, such as roads, irrigation ditches and hedgerows. Our goal is to model the spatial distribution of hedgerows because of their role in many ecological and environmental processes. We more specifically study how to characterize the spatial structure of hedgerows in two contrasting agricultural landscapes, one located in south-Eastern France (mainly composed of orchards) and the second in Brittany (western France, \emph{bocage}-Type). We determine if the spatial distribution of hedgerows is structured by the position of the more perennial linear landscape features, such as roads and ditches, or not. In such a case, we also detect the circumstances under which this spatial distribution is structured and the scale of these structures. The implementation of the process of Knowledge Discovery in Databases (KDD) is comprised of different preprocessing steps and data mining algorithms which combine mathematical and computational methods. The first part of the thesis focuses on the creation of a statistical spatial index, based on a geometric neighborhood concept and allowing the characterization of structures of hedgerows. Spatial index allows to describe the structures of hedgerows in the landscape. The results show that hedgerows depend on more permanent linear elements at short distances, and that their neighborhood is uniform beyond 150 meters. In addition different neighborhood structures have been identified depending on the orientation of hedgerows in the South-East of France but not in Brittany. The second part of the thesis explores the potential of coupling linearization methods with Markov methods. The linearization methods are based on the use of alternative Hilbert curves: Hilbert adaptive paths. The linearized spatial data thus constructed were then treated with Markov methods. These methods have the advantage of being able to serve both for the machine learning and for the generation of new data, for example in the context of the simulation of a landscape. The results show that the combination of these methods for learning and automatic generation of hedgerows captures some characteristics of the different study landscapes. The first simulations are encouraging despite the need for post-Processing. Finally, this work has enabled the creation of a spatial data mining method based on different tools that support all stages of a classic KDD, from the selection of data to the visualization of results. Furthermore, this method was constructed in such a way that it can also be used for data generation, a component necessary for the simulation of landscapes
Da, Silva Sébastien. "Fouille de données spatiales et modélisation de linéaires de paysages agricoles." Electronic Thesis or Diss., Université de Lorraine, 2014. http://docnum.univ-lorraine.fr/prive/DDOC_T_2014_0156_DA_SILVA.pdf.
Full textThis thesis is part of a partnership between INRA and INRIA in the field of knowledge extraction from spatial databases. The study focuses on the characterization and simulation of agricultural landscapes. More specifically, we focus on linears that structure the agricultural landscape, such as roads, irrigation ditches and hedgerows. Our goal is to model the spatial distribution of hedgerows because of their role in many ecological and environmental processes. We more specifically study how to characterize the spatial structure of hedgerows in two contrasting agricultural landscapes, one located in south-Eastern France (mainly composed of orchards) and the second in Brittany (western France, \emph{bocage}-Type). We determine if the spatial distribution of hedgerows is structured by the position of the more perennial linear landscape features, such as roads and ditches, or not. In such a case, we also detect the circumstances under which this spatial distribution is structured and the scale of these structures. The implementation of the process of Knowledge Discovery in Databases (KDD) is comprised of different preprocessing steps and data mining algorithms which combine mathematical and computational methods. The first part of the thesis focuses on the creation of a statistical spatial index, based on a geometric neighborhood concept and allowing the characterization of structures of hedgerows. Spatial index allows to describe the structures of hedgerows in the landscape. The results show that hedgerows depend on more permanent linear elements at short distances, and that their neighborhood is uniform beyond 150 meters. In addition different neighborhood structures have been identified depending on the orientation of hedgerows in the South-East of France but not in Brittany. The second part of the thesis explores the potential of coupling linearization methods with Markov methods. The linearization methods are based on the use of alternative Hilbert curves: Hilbert adaptive paths. The linearized spatial data thus constructed were then treated with Markov methods. These methods have the advantage of being able to serve both for the machine learning and for the generation of new data, for example in the context of the simulation of a landscape. The results show that the combination of these methods for learning and automatic generation of hedgerows captures some characteristics of the different study landscapes. The first simulations are encouraging despite the need for post-Processing. Finally, this work has enabled the creation of a spatial data mining method based on different tools that support all stages of a classic KDD, from the selection of data to the visualization of results. Furthermore, this method was constructed in such a way that it can also be used for data generation, a component necessary for the simulation of landscapes
Castelli, Aleardi Luca. "Représentations compactes de structures de données géométriques." Phd thesis, Ecole Polytechnique X, 2006. http://tel.archives-ouvertes.fr/tel-00336188.
Full textDenis, Laurent. "Méthodes géométriques en analyse diophantienne." Paris 6, 1992. http://www.theses.fr/1992PA066656.
Full textGirardeau-Montaut, Daniel. "Détection de changement sur des données géométriques tridimensionnelles." Phd thesis, Télécom ParisTech, 2006. http://pastel.archives-ouvertes.fr/pastel-00001745.
Full textHamidouche, Mounia. "Analyse spectrale de graphes géométriques aléatoires." Thesis, Université Côte d'Azur, 2020. http://www.theses.fr/2020COAZ4019.
Full textWe study random geometric graphs (RGGs) to address key problems in complex networks. An RGG is constructed by uniformly distributing n nodes on a torus of dimension d and connecting two nodes if their distance does not exceed a certain threshold. Three regimes for RGGs are of particular interest. The connectivity regime in which the average vertex degree a_n grows logarithmically with n or faster. The dense regime in which a_n is linear with n. The thermodynamic regime in which a_n is a constant. We study the spectrum of RGGs normalized Laplacian (LN) and its regularized version in the three regimes. When d is fixed and n tends to infinity we prove that the limiting spectral distribution (LSD) of LN converges to Dirac distribution at 1 in the connectivity regime. In the thermodynamic regime we propose an approximation for LSD of the regularized NL and we provide an error bound on the approximation. We show that LSD of the regularized LN of an RGG is approximated by LSD of the regularized LN of a deterministic geometric graph (DGG). We study LSD of RGGs adjacency matrix in the connectivity regime. Under some conditions on a_n we show that LSD of DGGs adjacency matrix is a good approximation for LSD of RGGs for n large. We determine the spectral dimension (SD) that characterizes the return time distribution of a random walk on RGGs. We show that SD depends on the eigenvalue density (ED) of the RGG normalized Laplacian in the neighborhood of the minimum eigenvalues. Based on the analytical eigenvalues of the normalized Laplacian we show that ED in a neighborhood of the minimum value follows a power-law tail and we approximate SD of RGGs by d in the thermodynamic regime
Cordero-Erausquin, Dario. "Inégalités géométriques." Marne-la-Vallée, 2000. http://www.theses.fr/2000MARN0097.
Full textFlandin, Guillaume. "Utilisation d'informations géométriques pour l'analyse statistique des données d'IRM fonctionnelle." Phd thesis, Université de Nice Sophia-Antipolis, 2004. http://tel.archives-ouvertes.fr/tel-00633520.
Full textGirres, Jean-François, and Jean-François Girres. "Modèle d'estimation de l'imprécision des mesures géométriques de données géographiques." Phd thesis, Université Paris-Est, 2012. http://tel.archives-ouvertes.fr/tel-00809273.
Full textGirres, Jean-François. "Modèle d'estimation de l'imprécision des mesures géométriques de données géographiques." Thesis, Paris Est, 2012. http://www.theses.fr/2012PEST1080/document.
Full textMany GIS applications are based on length and area measurements computed from the geometry of the objects of a geographic database (such as route planning or maps of population density, for example). However, no information concerning the imprecision of these measurements is now communicated to the final user. Indeed, most of the indicators on geometric quality focuses on positioning errors, but not on measurement errors, which are very frequent. In this context, this thesis seeks to develop methods for estimating the imprecision of geometric measurements of length and area, in order to inform a user for decision support. To achieve this objective, we propose a model to estimate the impacts of representation rules (cartographic projection, terrain, polygonal approximation of curves) and production processes (digitizing error, cartographic generalisation) on geometric measurements of length and area, according to the characteristics and the spatial context of the evaluated objects. Methods for acquiring knowledge about the evaluated data are also proposed to facilitate the parameterization of the model by the user. The combination of impacts to produce a global estimation of the imprecision of measurement is a complex problem, and we propose approaches to approximate the cumulated error bounds. The proposed model is implemented in the EstIM prototype (Estimation of the Imprecision of Measurements)
Lehec, Joseph. "Inégalités géométriques et fonctionnelles." Phd thesis, Université Paris-Est, 2008. http://tel.archives-ouvertes.fr/tel-00365744.
Full textFrelin, Marcel. "Prévision des caractéristiques d'une turbine radiale à partir des données géométriques." Paris 6, 1991. http://www.theses.fr/1991PA066489.
Full textFoare, Marion. "Analyse d'images par des méthodes variationnelles et géométriques." Thesis, Université Grenoble Alpes (ComUE), 2017. http://www.theses.fr/2017GREAM043/document.
Full textIn this work, we study both theoretical and numerical aspects of an anisotropic Mumford-Shah problem for image restoration and segmentation. The Mumford-Shah functional allows to both reconstruct a degraded image and extract the contours of the region of interest. Numerically, we use the Amborsio-Tortorelli approximation to approach a minimizer of the Mumford-Shah functional. It Gamma-converges to the Mumford-Shah functional and allows also to extract the contours. However, the minimization of the Ambrosio-Tortorelli functional using standard discretization schemes such as finite differences or finite elements leads to difficulties. We thus present two new discrete formulations of the Ambrosio-Tortorelli functional using the framework of discrete calculus. We use these approaches for image restoration and for the reconstruction of normal vector field and feature extraction on digital data. We finally study another similar shape optimization problem with Robin boundary conditions. We first prove existence and partial regularity of solutions and then construct and demonstrate the Gamma-convergence of two approximations. Numerical analysis shows once again the difficulties dealing with Gamma-convergent approximations
Jeanne, Hadrien. "Langages géométriques et polycubes." Rouen, 2010. http://www.theses.fr/2010ROUES007.
Full textThis thesis falls into two parts. The first one is about the study of geometrical languages using formal languages and automata theory, as well as discrete geometry tools. A geometrical language is composed of words over an alphabet of size d, using the Parikh images of the set of prefixes of the words. Those images define a figure of dimension d. The second part refers to the study of 3-dimensional polycubes. We define 3-dimensional extensions of some properties of polyominoes. That allow us to define subclasses of polycubes : plateau polycubes, s-directed polycubes and vertically-convex s-directed polycubes. We define an enumeration method over directed polycubes, based on the strate decomposition of polyominoes defined by Temperley, and we use it in order to give the generating functions of the classes of polycubes defined above
Bendjebla, Soumiya. "Traitements géométriques et fouille de données pour la reconnaissance d’entités d’usinage complexes." Thesis, université Paris-Saclay, 2020. http://www.theses.fr/2020UPASN002.
Full textIn response to competition and new industrial challenges, companies are forced to be more and more efficient, productive and competitive. Managing industrial know-how and the data flow of the manufacturing digital chain must be explored in order to shorten the industrialisation time while ensuring better quality.In this context, this thesis focuses on digital chain data exploration for the capture of good practices in NC machining using a feature-based approach. Several issues related to machining feature characterisation and digital chain data exploitation for machining process knowledge reuse have been identified.To address these issues, a new characterization of multi-level complex machining feature has been proposed. The proposed approach is characterized by a hierarchical structuring of digital chain data and a mapping between the geometrical and machining data. A statistical analysis is then carried out to analyse and exploit this data. Curvature-based segmentation and statistical clustering of machining data were combined to define new machining regions based technological segmentation approach. These regions were then used to characterize the machining feature and thus ensure the reuse of machining data through a feature based and a region based approach exploiting similarity measures a similarity measure. Finally, the developed approach was applied on an industrial case in aeronautics
Huet, Nolwen. "Inégalités géométriques pour des mesures long-concaves." Toulouse 3, 2009. http://thesesups.ups-tlse.fr/737/.
Full textIn most of this thesis, we study geometric inequalities for some log-concave measures. We give a streamlined semigroup proof of Gaussian Brunn-Minkowski inequality in the case of several sets, with a characterization of the coefficients. Our method also yields semigroup proofs of Brascamp-Lieb inequality and of its reverse form. Then, we show an isoperimetric inequality with a universal constant for isotropic log-concave measures whose density depends only on the radius. This result improves the Cheeger inequality proved by Bobkov. Kannan, Lovász et Simonovits conjectured that any isotropic log-concave measures satisfy a Cheeger inequality with a universal constant. We give new examples for which the conjecture comes true, as uniform measures on convex sets of revolution, and methods to construct other ones. The last part deal with the hypergroup property. It allows the description of all Markov kernels whose eigenvectors are given
Marine, Cadoret. "Analyse factorielle de données de catégorisation. : Application aux données sensorielles." Rennes, Agrocampus Ouest, 2010. http://www.theses.fr/2010NSARG006.
Full textIn sensory analysis, holistic approaches in which objects are considered as a whole are increasingly used to collect data. Their interest comes on a one hand from their ability to acquire other types of information as the one obtained by traditional profiling methods and on the other hand from the fact they require no special skills, which makes them feasible by all subjects. Categorization (or free sorting), in which subjects are asked to provide a partition of objects, belongs to these approaches. The first part of this work focuses on categorization data. After seeing that this method of data collection is relevant, we focus on the statistical analysis of these data through the research of Euclidean representations. The proposed methodology which consists in using factorial methods such as Multiple Correspondence Analysis (MCA) or Multiple Factor Analysis (MFA) is also enriched with elements of validity. This methodology is then illustrated by the analysis of two data sets obtained from beers on a one hand and perfumes on the other hand. The second part is devoted to the study of two data collection methods related to categorization: sorted Napping® and hierarchical sorting. For both data collections, we are also interested in statistical analysis by adopting an approach similar to the one used for categorization data. The last part is devoted to the implementation in the R software of functions to analyze the three kinds of data that are categorization data, hierarchical sorting data and sorted Napping® data
Astart, Laurent. "Représentation de surfaces ayant une structure arborescente par un modèle paramétrique." Aix-Marseille 2, 2004. http://www.theses.fr/2004AIX22003.
Full textCanivet, Yvain. "Analyse entropique et exergétique des systèmes énergétiques par des représentations géométriques." Thesis, Paris 10, 2017. http://www.theses.fr/2017PA100141/document.
Full textAt this time of awareness of the finiteness of resources, and of increasing needs for energy, the concept of sustainable development must play a central role in the forthcoming developments of our society. To do so, it is now an accepted fact that a deep change of our consumption habits is necessary; whether it is energy, food or final goods consumption. We believe this paradigm shift is only possible if all actors face together the various issues we are dealing with. Everyone, at one own scale, must be able to make informed decision. This is the idea that leads to the exergo-graphy tool presented in chapter 3. In line with the so called Sankey diagrams, it allows to graphically represent exergy balances in order to communicate more easily on their lessons. We apply it to two analysis done on the heating and DHW installations of the building A of the UPN. For each, we investigate the possibility of a sustainable heat production solution (geothermal heat pump and solar thermal energy). After presenting the analyses, we draw their graphical representations which we then compare to those of the current system. Beforehand, the first chapter introduces the basic notions of exergetic analysis, discussed further in chapter 2, through a model for static and dynamic fluid systems. Finally, in chapter 4, we introduce a toy-model which, proposing a fractal representation of exergy, tries to establish a conceptual link between microscopic, statistical, behaviour of heat background support, and the macroscopic observables that characterize it
Vilmart, Gilles. "Étude d’intégrateurs géométriques pour des équations différentielles." Rennes 1, 2008. ftp://ftp.irisa.fr/techreports/theses/2008/vilmart.pdf.
Full textThe aim of the work described in this thesis is the construction and the study of structure-preserving numerical integrators for differential equations, which share some geometric properties of the exact flow, for instance symmetry, symplecticity of Hamiltonian systems, preservation of first integrals, Poisson structure, etc. . . In the first part, we introduce a new approach to high-order structure-preserving numerical integrators, inspired by the theory of modified equations (backward error analysis). We focus on the class of B-series methods for which a new composition law called substitution law is introduced. This approach is illustrated with the derivation of the Preprocessed Discrete Moser-Veselov algorithm, an efficient and high-order geometric integrator for the motion of a rigid body. We also obtain an accurate integrator for the computation of conjugate points in rigid body geodesics. In the second part, we study to which extent the excellent performance of symplectic integrators for long-time integrations in astronomy and molecular dynamics carries over to problems in optimal control. We also discuss whether the theory of backward error analysis can be extended to symplectic integrators for optimal control. The third part is devoted to splitting methods. In the spirit of modified equations, we consider splitting methods for perturbed Hamiltonian systems that involve modified potentials. Finally, we construct splitting methods involving complex coefficients for parabolic partial differential equations with special attention to reaction-diffusion problems in chemistry
Leboucher, Julien. "Développement et évaluation de méthodes d'estimation des masses segmentaires basées sur des données géométriques et sur les forces externes : comparaison de modèles anthropométriques et géométriques." Valenciennes, 2007. http://ged.univ-valenciennes.fr/nuxeo/site/esupversions/e2504d99-e61b-4455-8bb3-2c47771ac853.
Full textUse of body segment parameters close to reality is of the utmost importance in order to obtain reliable kinetics during human motion analysis. Human body is modeled as a various number of solids in the majority of human movement studies. This research aims at developing and testing two methods for the estimation of these solid masses, also known as segment masses. Both methods are based on the static equilibrium principle for several solids. The first method’s goal is to provide with limb masses using total limb centre of mass and centre of pressure, projection on the horizontal plane of the total subject’s body centre of gravity, displacements. Ratio between these displacement being the same as the ratio of limb and total body masses, the knowledge of the latter allows for the calculation of the former. The second method aims at estimation all segment masses simultaneously by resolving series of static equilibrium equations, making the same assumption that centre of pressure is total body centre of mass projection and using segment centre of mass estimations. Interest of the new methods used in this research is due to the use of individual segment centre of mass estimations using a geometrical model together with material routinely utilized in human motion analysis in order to obtain estimates of body segment masses. Limb mass estimations method performs better predicting a posteriori center of mass displacement when compared to other methods. Some of the potential causes of the second method’s failure have been investigated through the study of centre of pressure location uncertainty
Gomes, Da Silva Alzennyr. "Analyse des données évolutives : application aux données d'usage du Web." Phd thesis, Université Paris Dauphine - Paris IX, 2009. http://tel.archives-ouvertes.fr/tel-00445501.
Full textGomes, da Silva Alzennyr. "Analyse des données évolutives : Application aux données d'usage du Web." Paris 9, 2009. https://portail.bu.dauphine.fr/fileviewer/index.php?doc=2009PA090047.
Full textNowadays, more and more organizations are becoming reliant on the Internet. The Web has become one of the most widespread platforms for information change and retrieval. The growing number of traces left behind user transactions (e. G. : customer purchases, user sessions, etc. ) automatically increases the importance of usage data analysis. Indeed, the way in which a web site is visited can change over time. These changes can be related to some temporal factors (day of the week, seasonality, periods of special offer, etc. ). By consequence, the usage models must be continuously updated in order to reflect the current behaviour of the visitors. Such a task remains difficult when the temporal dimension is ignored or simply introduced into the data description as a numeric attribute. It is precisely on this challenge that the present thesis is focused. In order to deal with the problem of acquisition of real usage data, we propose a methodology for the automatic generation of artificial usage data over which one can control the occurrence of changes and thus, analyse the efficiency of a change detection system. Guided by tracks born of some exploratory analyzes, we propose a tilted window approach for detecting and following-up changes on evolving usage data. In order measure the level of changes, this approach applies two external evaluation indices based on the clustering extension. The proposed approach also characterizes the changes undergone by the usage groups (e. G. Appearance, disappearance, fusion and split) at each timestamp. Moreover, the refereed approach is totally independent of the clustering method used and is able to manage different kinds of data other than usage data. The effectiveness of this approach is evaluated on artificial data sets of different degrees of complexity and also on real data sets from different domains (academic, tourism, e-business and marketing)
Ghazo, Hanna Zeina. "Cycles combinatoires et géométriques." Thesis, Brest, 2020. http://www.theses.fr/2020BRES0006.
Full textThe work in this thesis concerns the combinatorial theory of graphs, algebraic combinatorics and discrete geometry. On one side, it is about enumerating Hamiltonian paths and cycles of a given type in a tournament; On the other side, it studies numerical sequences verifying a quadratic difference equation.Concerning the results of the first part, we find: an equality between the number of Hamiltonians paths (resp. cycles) of a given type, in a tournament and its complement; an expression of the number of Hamiltonian oriented paths of a given type in a transitive tournament in terms of a recursive function F called the « path-function »; and the construction of an algorithm to compute F.In the second part of the work, we study cyclic graphs altogether with a solution to a quadratic difference equation.A parameter of this equation distinguishes real and complex sequences. A correspondence between real solutions and a class of polynomials with positive integer coefficients is established. To complete the correspondence, 1-step Eulerian digraphs interfere. A complex solution determines a closed planar walk in the plane, for which at each step we turn either left or right by a constant angle (the turning angle). This time, cyclotomic polynomials play a major role. Characterizing polynomials that determine such a solution is a problem that we study to the end of finding geometric properties of such polygonal cycles.When the walk exploits the sides of a regular polygon with exterior angle 2 π/n, we find unexpected phenomena when n≥ 12
Pino, Laurent. "Modélisation et analyse cinématique des tolérances géométriques pour l'assemblage de systèmes mécaniques." Phd thesis, Université de Nantes, 2000. http://tel.archives-ouvertes.fr/tel-00534108.
Full textVieilleville, François de. "Analyse des parties linéaires des objets discrets et estimateurs de caractéristiques géométriques." Bordeaux 1, 2007. http://www.theses.fr/2007BOR13405.
Full textZhu, Zuowei. "Modèles géométriques avec defauts pour la fabrication additive." Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLN021/document.
Full textThe intricate error sources within different stages of the Additive Manufacturing (AM) process have brought about major issues regarding the dimensional and geometrical accuracy of the manufactured product. Therefore, effective modeling of the geometric deviations is critical for AM. The Skin Model Shapes (SMS) paradigm offers a comprehensive framework aiming at addressing the deviation modeling problem at different stages of product lifecycle, and is thus a promising solution for deviation modeling in AM. In this thesis, considering the layer-wise characteristic of AM, a new SMS framework is proposed which characterizes the deviations in AM with in-plane and out-of-plane perspectives. The modeling of in-plane deviation aims at capturing the variability of the 2D shape of each layer. A shape transformation perspective is proposed which maps the variational effects of deviation sources into affine transformations of the nominal shape. With this assumption, a parametric deviation model is established based on the Polar Coordinate System which manages to capture deviation patterns regardless of the shape complexity. This model is further enhanced with a statistical learning capability to simultaneously learn from deviation data of multiple shapes and improve the performance on all shapes.Out-of-plane deviation is defined as the deformation of layer in the build direction. A layer-level investigation of out-of-plane deviation is conducted with a data-driven method. Based on the deviation data collected from a number of Finite Element simulations, two modal analysis methods, Discrete Cosine Transform (DCT) and Statistical Shape Analysis (SSA), are adopted to identify the most significant deviation modes in the layer-wise data. The effect of part and process parameters on the identified modes is further characterized with a Gaussian Process (GP) model. The discussed methods are finally used to obtain high-fidelity SMSs of AM products by deforming the nominal layer contours with predicted deviations and rebuilding the complete non-ideal surface model from the deformed contours. A toolbox is developed in the MATLAB environment to demonstrate the effectiveness of the proposed methods
Peng, Tao. "Analyse de données loT en flux." Electronic Thesis or Diss., Aix-Marseille, 2021. http://www.theses.fr/2021AIXM0649.
Full textSince the advent of the IoT (Internet of Things), we have witnessed an unprecedented growth in the amount of data generated by sensors. To exploit this data, we first need to model it, and then we need to develop analytical algorithms to process it. For the imputation of missing data from a sensor f, we propose ISTM (Incremental Space-Time Model), an incremental multiple linear regression model adapted to non-stationary data streams. ISTM updates its model by selecting: 1) data from sensors located in the neighborhood of f, and 2) the near-past most recent data gathered from f. To evaluate data trustworthiness, we propose DTOM (Data Trustworthiness Online Model), a prediction model that relies on online regression ensemble methods such as AddExp (Additive Expert) and BNNRW (Bagging NNRW) for assigning a trust score in real time. DTOM consists: 1) an initialization phase, 2) an estimation phase, and 3) a heuristic update phase. Finally, we are interested predicting multiple outputs STS in presence of imbalanced data, i.e. when there are more instances in one value interval than in another. We propose MORSTS, an online regression ensemble method, with specific features: 1) the sub-models are multiple output, 2) adoption of a cost sensitive strategy i.e. the incorrectly predicted instance has a higher weight, and 3) management of over-fitting by means of k-fold cross-validation. Experimentation with with real data has been conducted and the results were compared with reknown techniques
Sibony, Eric. "Analyse mustirésolution de données de classements." Thesis, Paris, ENST, 2016. http://www.theses.fr/2016ENST0036/document.
Full textThis thesis introduces a multiresolution analysis framework for ranking data. Initiated in the 18th century in the context of elections, the analysis of ranking data has attracted a major interest in many fields of the scientific literature : psychometry, statistics, economics, operations research, machine learning or computational social choice among others. It has been even more revitalized by modern applications such as recommender systems, where the goal is to infer users preferences in order to make them the best personalized suggestions. In these settings, users express their preferences only on small and varying subsets of a large catalog of items. The analysis of such incomplete rankings poses however both a great statistical and computational challenge, leading industrial actors to use methods that only exploit a fraction of available information. This thesis introduces a new representation for the data, which by construction overcomes the two aforementioned challenges. Though it relies on results from combinatorics and algebraic topology, it shares several analogies with multiresolution analysis, offering a natural and efficient framework for the analysis of incomplete rankings. As it does not involve any assumption on the data, it already leads to overperforming estimators in small-scale settings and can be combined with many regularization procedures for large-scale settings. For all those reasons, we believe that this multiresolution representation paves the way for a wide range of future developments and applications
Vidal, Jules. "Progressivité en analyse topologique de données." Electronic Thesis or Diss., Sorbonne université, 2021. http://www.theses.fr/2021SORUS398.
Full textTopological Data Analysis (TDA) forms a collection of tools that enable the generic and efficient extraction of features in data. However, although most TDA algorithms have practicable asymptotic complexities, these methods are rarely interactive on real-life datasets, which limits their usability for interactive data analysis and visualization. In this thesis, we aimed at developing progressive methods for the TDA of scientific scalar data, that can be interrupted to swiftly provide a meaningful approximate output and that are able to refine it otherwise. First, we introduce two progressive algorithms for the computation of the critical points and the extremum-saddle persistence diagram of a scalar field. Next, we revisit this progressive framework to introduce an approximation algorithm for the persistence diagram of a scalar field, with strong guarantees on the related approximation error. Finally, in a effort to perform visual analysis of ensemble data, we present a novel progressive algorithm for the computation of the discrete Wasserstein barycenter of a set of persistence diagrams, a notoriously computationally intensive task. Our progressive approach enables the approximation of the barycenter within interactive times. We extend this method to a progressive, time-constraint, topological ensemble clustering algorithm
Sibony, Eric. "Analyse mustirésolution de données de classements." Electronic Thesis or Diss., Paris, ENST, 2016. http://www.theses.fr/2016ENST0036.
Full textThis thesis introduces a multiresolution analysis framework for ranking data. Initiated in the 18th century in the context of elections, the analysis of ranking data has attracted a major interest in many fields of the scientific literature : psychometry, statistics, economics, operations research, machine learning or computational social choice among others. It has been even more revitalized by modern applications such as recommender systems, where the goal is to infer users preferences in order to make them the best personalized suggestions. In these settings, users express their preferences only on small and varying subsets of a large catalog of items. The analysis of such incomplete rankings poses however both a great statistical and computational challenge, leading industrial actors to use methods that only exploit a fraction of available information. This thesis introduces a new representation for the data, which by construction overcomes the two aforementioned challenges. Though it relies on results from combinatorics and algebraic topology, it shares several analogies with multiresolution analysis, offering a natural and efficient framework for the analysis of incomplete rankings. As it does not involve any assumption on the data, it already leads to overperforming estimators in small-scale settings and can be combined with many regularization procedures for large-scale settings. For all those reasons, we believe that this multiresolution representation paves the way for a wide range of future developments and applications
Périnel, Emmanuel. "Segmentation en analyse de données symboliques : le cas de données probabilistes." Paris 9, 1996. https://portail.bu.dauphine.fr/fileviewer/index.php?doc=1996PA090079.
Full textCailhol, Simon. "Planification interactive de trajectoire en Réalité Virtuelle sur la base de données géométriques, topologiques et sémantiques." Thesis, Toulouse, INPT, 2015. http://www.theses.fr/2015INPT0058/document.
Full textTo save time and money while designing new products, industry needs tools to design, test and validate the product using virtual prototypes. These virtual prototypes must enable to test the product at all Product Lifecycle Management (PLM) stages. Many operations in product’s lifecycle involve human manipulation of product components (product assembly, disassembly or maintenance). Cue to the increasing integration of industrial products, these manipulations are performed in cluttered environment. Virtual Reality (VR) enables real operators to perform these operations with virtual prototypes. This research work introduces a novel path planning architecture allowing collaboration between a VR user and an automatic path planning system. This architecture is based on an original environment model including semantic, topological and geometric information. The automatic path planning process split in two phases. First, coarse planning uses semantic and topological information. This phase defines a topological path. Then, fine planning uses semantic and geometric information to define a geometrical trajectory within the topological path defined by the coarse planning. The collaboration between VR user and automatic path planner is made of two modes: on one hand, the user is guided along a pre-computed path through a haptic device, on the other hand, the user can go away from the proposed solution and doing it, he starts a re-planning process. Efficiency and ergonomics of both interaction modes is improved thanks to control sharing methods. First, the authority of the automatic system is modulated to provide the user with a sensitive guidance while he follows it and to free the user (weakened guidance) when he explores possible better ways. Second, when the user explores possible better ways, his intents are predicted (thanks to geometrical data associated to topological elements) and integrated in the re-planning process to guide the coarse planning. This thesis is divided in five chapters. The first one exposes the industrial context that motivated this work. Following a description of environment modeling tools, the second chapter introduces the multi-layer environment model proposed. The third chapter presents the path planning techniques from robotics research and details the two phases path planning process developed. The fourth introduce previous work on interactive path planning and control sharing techniques before to describe the interaction modes and control sharing techniques involved in our interactive path planner. Finally, last chapter introduces the experimentations performed with our path planner and analyses their results
Untereiner, Lionel. "Représentation des maillages multirésolutions : application aux volumes de subdivision." Phd thesis, Université de Strasbourg, 2013. http://tel.archives-ouvertes.fr/tel-00951049.
Full textLepoultier, Guilhem. "Transport numérique de quantités géométriques." Thesis, Paris 11, 2014. http://www.theses.fr/2014PA112202/document.
Full textIn applied mathematics, question of moving quantities by vector is an important question : fluid mechanics, kinetic theory… Using particle methods, we're going to move an additional quantity giving more information on the problem. First part of the work is the theorical formulation for this kind of transport. It's going to use the differential in space of the vector field to compute the differential of the flow. An immediate and natural application is density who are parametrized by and point and a tensor, like gaussians. We're going to move such densities by moving point and tensor. Natural question is now the accuracy of such approximation. It's second part of our work , which discuss of distance to estimate such type of densities