Dissertations / Theses on the topic 'Modélisation hiérarchique'
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Mbobi, Mokhoo. "Modélisation hétérogène non-hiérarchique." Paris 11, 2004. http://www.theses.fr/2004PA112211.
Full textEmbedded systems are naturally heterogeneous. Currently, modeling tools used for modeling embedded systems use a hierarchical approach. This approach although avoiding the combinatorial explosion of the number of interfaces between models of Computation (MoCs) forces the change of hierarchical level when passing from one MoC to another. But, this coupling between hierarchy and model changing perturbs the structure of the model, affects the modularity and makes difficult the maintainability of the model. Moreover this coupling is harmfull to the reuse of the component. This thesis proposes a new approach that dissociates the MoC from this hierarchy. This approach uses two components : a "Heterogeneous Interface Components (HIC) " and a "Non-Hierarchical Heterogeneous Execution Model". A HIC have inputs and outputs of different nature to allow the heterogeneous communication in a system. The Execution Model reorganizes the system by partitionning, i. E. By creating homogenous subsystems at the border of the heterogeneous behavior. It schedules the activation of those subsystems and delegates their internal scheduling to their regular MoC. Finally it executes the system. This approach presents several advantages : the use of several components that use heterogeneous inputs or outputs at the same level of the hierarchy. The separation of control flow and data flow increases the reuse of the components. The explicit specification of the heterogeneous behavior of the system at the boundary between different MoCs as an integral part of the system, contributes efficiently to the modularity and the maintainability of the models
Olivares, Romero Javier. "Modélisation hiérarchique bayésienne des amas stellaires jeunes." Thesis, Université Grenoble Alpes (ComUE), 2017. http://www.theses.fr/2017GREAY071/document.
Full textThe origin and evolution of stellar populations is one of the greatest challenges in modern astrophysics. It is known that the majority of the stars has its origin in stellar clusters (Carpenter 2000; Porras et al. 2003; Lada & Lada 2003). However, only less than one tenth of these clusters remains bounded after the first few hundred million years (Lada & Lada 2003). Ergo, the understanding of the origin and evolution of stars demands meticulous analyses of stellar clusters in these crucial ages.The project Dynamical Analysis of Nearby Clusters (DANCe, Bouy et al. 2013), from which the present work is part of, provides the scientific framework for the analysis of Nearby Young Clusters (NYC) in the solar neighbourhood (< 500 pc). The DANCe carefully designed observations of the well known Pleiades cluster provide the perfect case study for the development and testing of statistical tools aiming at the analysis of the early phases of cluster evolution.The statistical tool developed here is a probabilistic intelligent system that performs Bayesian inference for the parameters governing the probability density functions (PDFs) of the cluster population (PDFCP). It has been benchmarked with the Pleiades photometric and astrometric data of the DANCe survey. As any Bayesian framework, it requires the setting up of priors. To avoid the subjectivity of these, the intelligent system establish them using the Bayesian Hierarchical Model (BHM) approach. In it, the parameters of prior distributions, which are also inferred from the data, are drawn from other distributions in a hierarchical way.In this BHM intelligent system, the true values of the PDFCP are specified by stochastic and deterministic relations representing the state of knowledge of the NYC. To perform the parametric inference, the likelihood of the data, given these true values, accounts for the properties of the data set, especially its heteroscedasticity and missing value objects. By properly accounting for these properties, the intelligent system: i) Increases the size of the data set, with respect to previous studies working exclusively on fully observed objects, and ii) Avoids biases associated to fully observed data sets, and restrictions to low-uncertainty objects (sigma-clipping procedures).The BHM returns the posterior PDFs of the parameters in the PDFCPs, particularly of the spatial, proper motions and luminosity distributions. In the BHM each object in the data set contributes to the PDFs of the parameters proportionally to its likelihood. Thus, the PDFCPs are free of biases resulting from typical high membership probability selections (sampling bias).As a by-product, the BHM also gives the PDFs of the cluster membership probability for each object in the data set. These PDFs together with an optimal probability classification threshold, which is obtained from synthetic data sets, allow the classification of objects into cluster and field populations. This by-product classifier shows excellent results when applied on synthetic data sets (with an area under the ROC curve of 0.99). From the analysis of synthetic data sets, the expected value of the contamination rate for the PDFCPs is 5.8 ± 0.2%.The following are the most important astrophysical results of the BHM applied tothe Pleiades cluster. First, used as a classifier, it finds ∼ 200 new candidate members, representing 10% new discoveries. Nevertheless, it shows outstanding agreement (99.6% of the 105 objects in the data set) with previous results from the literature. Second, the derived present day system mass distribution (PDSMD) is in general agreement with the previous results of Bouy et al. (2015).Thus, by better modelling the data set and eliminating unnecessary restrictions to it, the new intelligent system, developed and tested in the present work, represents the state of the art for the statistical analysis of NYC populations
Thourel, Pierre. "Segmentation d'images sonar par modélisation markovienne hiérarchique et analyse multirésolution." Brest, 1996. http://www.theses.fr/1996BRES2026.
Full textYvart, Alex. "Modélisation Hiérarchique de Surfaces à partir de Maillages Polyédriques et Applications." Phd thesis, Grenoble INPG, 2004. http://tel.archives-ouvertes.fr/tel-00009003.
Full textFokwa, Didier. "Matériaux hétérogènes : analyse expérimentale et modélisation numérique par une approche hiérarchique." Paris 6, 1992. http://www.theses.fr/1992PA066147.
Full textChehaibar, Ghassan. "Méthodes d'analyse hiérarchique des réseaux de Petri." Phd thesis, Ecole Nationale des Ponts et Chaussées, 1991. http://tel.archives-ouvertes.fr/tel-00519683.
Full textBoubekeur, Tamy. "Traitement Hiérarchique, Edition et Synthèse de Géométrie Numérisée." Phd thesis, Université Sciences et Technologies - Bordeaux I, 2007. http://tel.archives-ouvertes.fr/tel-00260917.
Full textAbdelfattah, Nahed. "Modélisation 2D 1/2 hiérarchique basée sur les cartes planaires : réalisation et évaluation d'une interface graphique utilisant cette modélisation." Phd thesis, Ecole Nationale Supérieure des Mines de Saint-Etienne, 1994. http://tel.archives-ouvertes.fr/tel-00820994.
Full textNahed, Abdelfattah. "Modélisation 2D 1/2 hiérarchique basée sur les cartes planaires : réalisation et évaluation d'une interface graphique utilisant cette modélisation." Saint-Etienne, 1994. http://tel.archives-ouvertes.fr/docs/00/82/09/94/PDF/1994_Nahed_Abdelfattah.pdf.
Full textThis thesis proposes a model based on the planar map notion. Data of the same plane level are modeled by severa! planar maps each of which corresponding to a class of semantics. These maps are independent and superposed. Modeling of data belonging to parallel planes is also allowed by planar maps superposing. Display and manipulation of data belonging to parallel planes are ensured thanks to a three-dimensional representation that is inspired by perspective techniques in draughtmanship domain. A hierarchical data structure offers the possibility to detail one zone of the plane (a face in planar map notion) by many planar maps corresponding to the different semantics. Furthermore, this model handles perfectly the semantic links that could lie abjects modeled in different planar maps. Hence, it preserves the whole meaning of the modeled scene. The proposed medel has been used to design a graphical interface within the scope of an european Esprit project MMI2. An ergonomie evaluation of that interface and refinements made in it as consequence of the evaluation are also presented in this thesis
Karray, Mohamed. "Contribution à la modélisation hiérarchique de systèmes opto-électroniques à base de VHDL-AMS." Phd thesis, Télécom ParisTech, 2004. http://pastel.archives-ouvertes.fr/pastel-00001576.
Full textKarray, Mohamed. "Contribution à la modélisation hiérarchique de systèmes opto-électroniques à base de VHD-AMS." Paris, ENST, 2004. http://www.theses.fr/2004ENST0044.
Full textIn a technological context in which the integration degree in micro and optoelectronic circuits increases more and more, it becomes necessary for the designers to get complete simulation tools, in order to study not only the behavior of different constitutive elements of sub-systems that they design, but also to evaluate global performances of the system. This thesis work concerns the design of opto-electronic component models, by using VHDL-AMS language. This language is very convenient for multi-domain modelling : electronics, optics, thermics or mechanics. It gives also the capability to get models at different abstraction levels in the system. Our work is a part of SHAMAN project. Its objective is to model every component of an opto-electronic system with the conditions of high speed, short distance, and strong thermal and mechanical interactions. The methodology used is hierarchical, combining top-down and bottom-up design flow in order to get optimal solutions about performances, cost and design time, and by re-using virtual components following intellectual property rules (IP)
Ancelet, Sophie. "Exploiter l'approche hiérarchique bayésienne pour la modélisation statistique de structures spatiales: application en écologie des populations." Phd thesis, AgroParisTech, 2008. http://pastel.archives-ouvertes.fr/pastel-00004396.
Full textParis, Thomas. "Modélisation de systèmes complexes par composition : une démarche hiérarchique pour la co-simulation de composants hétérogènes." Thesis, Université de Lorraine, 2019. http://www.theses.fr/2019LORR0035/document.
Full textThis work deals with complex system Modeling and Simulation (M&S). The particularity of such systems is the numerous heterogeneous entities in interaction involved inside them. This particularity leads to several organization layers and scientific domains. As a consequence, their study requests many perspectives (different temporal and spatial scales, different domains and formalisms, different granularities...). The challenge is the rigorous integration of these various system perspectives inside an M&S process. Multi-modeling and co-simulation are promising approaches to do so. The underlying problem is to define a modular and hierarchical process fitted with a rigorous way to integrate heterogeneous components and which is supported by a software environment that covers the whole M&S cycle. MECSYCO (Multi-agent Environment for Complex SYstem CO-simulation) is a co-simulation middleware focusing on the reuse of existing models from other software. It relies on a software and formal DEVS-based wrapping, provides heterogeneity handling mechanisms and ensures a decentralized and modular co-simulation. MECSYCO deals with the heterogeneous component integration need but its M&S process does not have all the properties above-mentioned. Notably, the hierarchical modeling ability is missing. To overcome this, we propose to fit MECSYCO with a descriptive multi-modeling and co-simulation process that allows the hierarchical design of multi-models using models from other software. Our process is split into three steps: integration, multi-modeling and finally the experimentation. We adopt a descriptive approach where a description file is linked to each product of these steps, these documents enable to manipulate them. The use of description files completes the integration steps, allows a hierarchical and modular multi-model design and isolates the experiments. Then we set up a development environment based on Domain Specific Languages to support the description work, and we automate the transition from an experiment description to its effective co-simulation. This is a Model-Driven Engineering approach which allows us to put into practice our contribution by facilitating the work of modelers and by avoiding implementation mistakes. Our contributions are evaluated on several experiments including a hybrid highway model and a thermal regulation example
Paris, Thomas. "Modélisation de systèmes complexes par composition : une démarche hiérarchique pour la co-simulation de composants hétérogènes." Electronic Thesis or Diss., Université de Lorraine, 2019. http://www.theses.fr/2019LORR0035.
Full textThis work deals with complex system Modeling and Simulation (M&S). The particularity of such systems is the numerous heterogeneous entities in interaction involved inside them. This particularity leads to several organization layers and scientific domains. As a consequence, their study requests many perspectives (different temporal and spatial scales, different domains and formalisms, different granularities...). The challenge is the rigorous integration of these various system perspectives inside an M&S process. Multi-modeling and co-simulation are promising approaches to do so. The underlying problem is to define a modular and hierarchical process fitted with a rigorous way to integrate heterogeneous components and which is supported by a software environment that covers the whole M&S cycle. MECSYCO (Multi-agent Environment for Complex SYstem CO-simulation) is a co-simulation middleware focusing on the reuse of existing models from other software. It relies on a software and formal DEVS-based wrapping, provides heterogeneity handling mechanisms and ensures a decentralized and modular co-simulation. MECSYCO deals with the heterogeneous component integration need but its M&S process does not have all the properties above-mentioned. Notably, the hierarchical modeling ability is missing. To overcome this, we propose to fit MECSYCO with a descriptive multi-modeling and co-simulation process that allows the hierarchical design of multi-models using models from other software. Our process is split into three steps: integration, multi-modeling and finally the experimentation. We adopt a descriptive approach where a description file is linked to each product of these steps, these documents enable to manipulate them. The use of description files completes the integration steps, allows a hierarchical and modular multi-model design and isolates the experiments. Then we set up a development environment based on Domain Specific Languages to support the description work, and we automate the transition from an experiment description to its effective co-simulation. This is a Model-Driven Engineering approach which allows us to put into practice our contribution by facilitating the work of modelers and by avoiding implementation mistakes. Our contributions are evaluated on several experiments including a hybrid highway model and a thermal regulation example
Awasthi, Anjali. "Développement d'un système de routage hiérarchique pour les réseaux urbains." Phd thesis, Université de Metz, 2004. http://tel.archives-ouvertes.fr/tel-00007751.
Full textLa deuxième partie de la thèse est consacrée au problème de décomposition d'un réseau urbain en sous réseaux de taille raisonnable et aussi indépendants les uns des autres que possible, c'est-à-dire ayant un nombre de connexions
aussi faible que possible.
Dans la troisième partie de la thèse nous présentons un programme de simulation pour générer les données qui, à leur tour, vont servir à constituer une mémoire. Cette mémoire a pour objectif de proposer le chemin le plus rapide à l'intérieur d'un sous-réseau dès que l'on connaît l'état du sous-réseau ainsi que l'origine et la destination du véhicule.
Enfin, la dernière partie de la thèse est la plus novatrice. Elle fait intervenir les techniques de l'analyse des données pour constituer la mémoire et permettre ainsi de choisir le chemin le plus rapide en temps réel.
Sall, Ciré Elimane. "Modélisation spatiale hiérarchique bayésienne de l'apparentement génétique et de l'héritabilité en milieu naturel à l'aide de marqueurs moléculaires." Montpellier 2, 2009. http://www.theses.fr/2009MON20259.
Full textKnowledge of genetic relatedness between individuals combined with phenotypic information allows estimating the heritability of character of interest. Estimate the heritability in natural populations remains an actual challenge. But, in natural populations, pedigree is unknown. The use of molecular markers allows estimating first relatedness and then the heritability. However, classical approaches do not allow introducing exogeneous information such as geographical information. Nevertheless, we can assume that more two individuals are spatially closed more they are genetically closed. The aim of this study was to develop statistical models allowing the estimation of the relatedness and the heritability simultaneously using molecular markers as well as the spatial information. In the first part, we developed a hierarchical spatial bayesian model for relatedness taking into account spatial information. As the likelihood of data given by the identity-by-state mode of pairs of genotypes, is not tractable, we proposed the use of the composite likelihood approaches. The link between identity-by-descent mode and spatial distance is made using ordinal Probit models belonging to the generalized linear models. In the second part, we proposed to model relatedness and heritability simultaneously. We gave, in the third part, different MCMC algorithms for model inference. Finally, the spatial model for relatedness interest is emphasized by an application on Shea tree (Vitellaria paradoxa) data
Diard, Julien. "La carte bayésienne : un modèle probabiliste hiérarchique pour la navigation en robotique mobile." Phd thesis, Grenoble INPG, 2003. http://tel.archives-ouvertes.fr/tel-00004369.
Full textcomportement ? Qu'est-ce-que naviguer, se localiser et prédire, pour un
robot mobile devant accomplir une tâche donnée ?
Ces questions n'ont pas de réponses uniques ou évidentes à ce jour, et
restent centrales à de nombreux domaines de recherches.
La robotique, par exemple, souhaite y répondre en vue de la synthèse de
systèmes sensori-moteurs performants. Les sciences cognitives placent ces
questions comme essentielles à la compréhension des êtres vivants, de leurs
compétences, et au-delà, de leurs intelligences.
Notre étude se situe à la croisée de ces disciplines. Nous étudions tout
d'abord les méthodes probabilistes classiques (Localisation Markovienne,
PDMPOs, MMCs, etc.), puis certaines approches dites "bio-inspirées"
(Berthoz, Franz, Kuipers). Nous analysons les avantages et inconvénients
respectifs de ces approches en les replaçant dans un cadre général de
programmation des robots basé sur l'inférence bayésienne (PBR).
Nous proposons un formalisme original de modélisation probabiliste de
l'interaction entre un robot et son environnement : la carte bayésienne.
Dans ce cadre, définir une carte revient à spécifier une distribution de
probabilités particulière. Certaines des questions évoquées ci-dessus se
ramènent alors à la résolution de problèmes d'inférence probabiliste.
Nous définissons des opérateurs d'assemblage de cartes bayésiennes,
replaçant ainsi les notions de "hiérarchie de cartes" et de développement
incrémental comme éléments centraux de notre approche, en accord avec les
données biologiques. En appuyant l'ensemble de notre travail sur le
formalisme bayésien, nous profitons d'une part d'une capacité de traitement
unifié des incertitudes, et d'autre part, de fondations mathématiques
claires et rigoureuses. Notre formalisme est illustré par des exemples
implantés sur un robot mobile Koala.
Brière, Alexandre. "Modélisation système d'une architecture d'interconnexion RF reconfigurable pour les many-cœurs." Thesis, Paris 6, 2017. http://www.theses.fr/2017PA066296/document.
Full textThe growing number of cores in a single chip goes along with an increase in com-munications. The variety of applications running on the chip causes spatial andtemporal heterogeneity of communications. To address these issues, we presentin this thesis a dynamically reconfigurable interconnect based on Radio Frequency(RF) for intra chip communications. The use of RF allows to increase the bandwidthwhile minimizing the latency. Dynamic reconfiguration of the interconnect allowsto handle the heterogeneity of communications. We present the rationale for choos-ing RF over optics and 3D, the detailed architecture of the network and the chipimplementing it, the evaluation of its feasibility and its performances. During theevaluation phase we were able to show that for a CMP of 1 024 tiles, our solutionallowed a performance gain of 13 %. One advantage of this RF interconnect is theability to broadcast without additional cost compared to point-to-point communi-cations, opening new perspectives in terms of cache coherence
Lafon, Marc. "Modélisation de la propagation de l'information cérébrale par graphes causaux qualitatifs." Phd thesis, Université Paul Sabatier - Toulouse III, 2000. http://tel.archives-ouvertes.fr/tel-00010176.
Full textZhong, Zeling. "Comprendre l’appropriation des objets connectés grand public : une approche de modélisation à composants hiérarchiques." Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLE017.
Full textAccording to Hoffman & Novak (2018), the smart connected object is presenting new opportunities for usage experience that have the potential to revolutionize consumers' lives. The main challenge for smart connected objects is to integrate their use into the daily practices of consumers by actively producing usage data in the long-term, namely appropriation. This research has validated the explanatory model of consumer smart connected object appropriation through the psychological needs of French consumers regarding their smart connected objects. Our results show that the smart connected object appropriation is strongly correlated with the need for self-identity, the need for having a place, the need for efficacy and effectance. And the smart connected object appropriation has a positive impact on perceived value of smart connected objects by consumers, their extra-role behaviors, as well as satisfaction of their daily life. Moreover, the mediating role of extra-role behaviors in the relationship between appropriation and perceived value allows us to understand in a complementary way the value cocreation mechanisms from the viewpoint of consumers, concerning how the smart connected object appropriation contributes to value creation by consumers
Firmo, Drumond Thalita. "Apports croisées de l'apprentissage hiérarchique et la modélisation du système visuel : catégorisation d'images sur des petits corpus de données." Thesis, Bordeaux, 2020. https://tel.archives-ouvertes.fr/tel-03129189.
Full textDeep convolutional neural networks (DCNN) have recently protagonized a revolution in large-scale object recognition. They have changed the usual computer vision practices of hand-engineered features, with their ability to hierarchically learn representative features from data with a pertinent classifier. Together with hardware advances, they have made it possible to effectively exploit the ever-growing amounts of image data gathered online. However, in specific domains like healthcare and industrial applications, data is much less abundant, and expert labeling costs higher than those of general purpose image datasets. This scarcity scenario leads to this thesis' core question: can these limited-data domains profit from the advantages of DCNNs for image classification? This question has been addressed throughout this work, based on an extensive study of literature, divided in two main parts, followed by proposal of original models and mechanisms.The first part reviews object recognition from an interdisciplinary double-viewpoint. First, it resorts to understanding the function of vision from a biological stance, comparing and contrasting to DCNN models in terms of structure, function and capabilities. Second, a state-of-the-art review is established aiming to identify the main architectural categories and innovations in modern day DCNNs. This interdisciplinary basis fosters the identification of potential mechanisms - inspired both from biological and artificial structures — that could improve image recognition under difficult situations. Recurrent processing is a clear example: while not completely absent from the "deep vision" literature, it has mostly been applied to videos — due to their inherently sequential nature. From biology however it is clear such processing plays a role in refining our perception of a still scene. This theme is further explored through a dedicated literature review focused on recurrent convolutional architectures used in image classification.The second part carries on in the spirit of improving DCNNs, this time focusing more specifically on our central question: deep learning over small datasets. First, the work proposes a more detailed and precise discussion of the small sample problem and its relation to learning hierarchical features with deep models. This discussion is followed up by a structured view of the field, organizing and discussing the different possible paths towards adapting deep models to limited data settings. Rather than a raw listing, this review work aims to make sense out of the myriad of approaches in the field, grouping methods with similar intent or mechanism of action, in order to guide the development of custom solutions for small-data applications. Second, this study is complemented by an experimental analysis, exploring small data learning with the proposition of original models and mechanisms (previously published as a journal paper).In conclusion, it is possible to apply deep learning to small datasets and obtain good results, if done in a thoughtful fashion. On the data path, one shall try gather more information from additional related data sources if available. On the complexity path, architecture and training methods can be calibrated in order to profit the most from any available domain-specific side-information. Proposals concerning both of these paths get discussed in detail throughout this document. Overall, while there are multiple ways of reducing the complexity of deep learning with small data samples, there is no universal solution. Each method has its own drawbacks and practical difficulties and needs to be tailored specifically to the target perceptual task at hand
Wacongne, Catherine. "Traitements conscient et non-conscient des régularités temporelles : Modélisation et neuroimagerie." Thesis, Paris 6, 2014. http://www.theses.fr/2014PA066290/document.
Full textWhat is going to happen next? Natural stimuli tend to follow each other in a reproducible way. Multiple fields of neuroscience and psychology bring evidence that human’s brain and behavior are sensitive to the temporal structure of stimuli and are able to exploit them in multiple ways: to make appropriate decisions, encode efficiently information, react faster to predictable stimuli or orient attention towards surprising ones… Multiple brain areas show sensitivity to the temporal structure of events. However, all areas do not seem to be sensitive to the same kind of temporal regularities. Conscious access to the stimuli seems to play a key role in some of these dissociations and better understanding this role could improve the current diagnostic tools for non-communicative patients. This thesis explores the hierarchical organization of the processing of temporal regularities and the computational properties of conscious and unconscious levels of processing by combining a modeling approach with neuroimaging experiments using magnetoencephalography and electroencephalography (MEEG). First, a plausible neuronal model based on predictive coding principles reproduces the main properties of the preattentive processing of pure tones in the auditory cortex indexed by the evoked potential mismatch negativity (MMN). Second, a MEEG experiment provides evidence for a hierarchical organization of multiple predictive processes in the auditory cortex. Finally, a second model explores the new computational properties and constraints associated to the access of stimuli to a conscious space with a working memory able to maintain information for an arbitrary time but with limited capacity
Plemenos, Dimitrios. "Contribution à l'étude et au développement des techniques de modélisation, génération et visualisation de scènes : le projet multiformes." Nantes, 1991. http://www.theses.fr/1991NANT2041.
Full textBrière, Alexandre. "Modélisation système d'une architecture d'interconnexion RF reconfigurable pour les many-cœurs." Electronic Thesis or Diss., Paris 6, 2017. http://www.theses.fr/2017PA066296.
Full textThe growing number of cores in a single chip goes along with an increase in com-munications. The variety of applications running on the chip causes spatial andtemporal heterogeneity of communications. To address these issues, we presentin this thesis a dynamically reconfigurable interconnect based on Radio Frequency(RF) for intra chip communications. The use of RF allows to increase the bandwidthwhile minimizing the latency. Dynamic reconfiguration of the interconnect allowsto handle the heterogeneity of communications. We present the rationale for choos-ing RF over optics and 3D, the detailed architecture of the network and the chipimplementing it, the evaluation of its feasibility and its performances. During theevaluation phase we were able to show that for a CMP of 1 024 tiles, our solutionallowed a performance gain of 13 %. One advantage of this RF interconnect is theability to broadcast without additional cost compared to point-to-point communi-cations, opening new perspectives in terms of cache coherence
Dortel, Emmanuelle. "Croissance de l'albacore (Thunnus albacares) de l'Océan Indien : de la modélisation statistique à la modélisation bio-énergétique." Thesis, Montpellier 2, 2014. http://www.theses.fr/2014MON20035/document.
Full textSince the early 1960s, the growth of yellowfin has been enjoyed a particular attention both in the research field and for fisheries management. In the Indian Ocean, the management of yellowfin stock, under the jurisdiction of the Indian Ocean Tuna Commission (IOTC), suffers from much uncertainty associated with the growth curve currently considered. In particular, there remain gaps in our knowledge of basic biological and ecological processes regulating growth. Their knowledge is however vital for understanding the stocks productivity and their resilience abilities to fishing pressure and oceanographic changes underway.Through modelling, this study aims to improve current knowledge on the growth of yellowfin population of the Indian Ocean and thus strengthen the scientific advice on the stock status. Whilst most studies on yellowfin growth only rely on one data source, we implemented a hierarchical Bayesian model that exploits various information sources on growth, i.e. direct age estimates obtained through otolith readings, analyzes of modal progressions and individual growth rates derived from mark-recapture experiments, and takes explicitely into account the expert knowledge and the errors associated with each dataset and the growth modelling process. In particular, the growth model was coupled with an ageing error model from repeated otolith readings which significantly improves the age estimates as well as the resulting growth estimates and allows a better assessment of the estimates reliability. The growth curves obtained constitute a major improvement of the growth pattern currently used in the yellowfin stock assessment. They demonstrates that yellowfin exhibits a two-stanzas growth, characterized by a sharp acceleration at the end of juvenile stage. However, they do not provide information on the biological and ecological mechanisms that lie behind the growth acceleration.For a better understanding of factors involved in the acceleration of growth, we implemented a bioenergetic model relying on the principles of Dynamic Energy Budget theory (DEB). Two major assumptions were investigated : (i) a low food availability during juvenile stage in relation with high intra and inter-specific competition and (ii) changes in food diet characterized by the consumption of more energetic prey in older yellowfin. It appears that these two assumption may partially explain the growth acceleration
Holzschuch, Nicolas. "Le contrôle de l'erreur dans la méthode de radiosité hiérarchique." Phd thesis, Université Joseph Fourier (Grenoble), 1996. http://tel.archives-ouvertes.fr/tel-00004994.
Full textSimon, Maximilien. "Modélisation hiérarchique bayésienne pour l'évaluation des populations de thonidés : intérêts et limites de la prise en compte de distributions a priori informatives." Thesis, Paris, AgroParisTech, 2012. http://www.theses.fr/2012AGPT0080/document.
Full textModelisation of the population dynamics of tunas and tuna like species for stock assessment is facing two issues. (1) The hypothesis of proportionality between Catch Per Unit Effort (CPUE) and abundance (constant catchability). CPUEs from commercial fisheries appear to be the only relative measure of abundance in spite of their lack of representativity of the abundances of the populations. (2) The lack of informative data for the modelisation of the Stock-Recruit (SR) relationship, which leads to constraint this function on its steepness. The introduction of fisheries-independent sources of information is investigated in order to relax the assumption of constant catchability and to provide better justification of steepness choice for the SR relationship. The Bayesian statistical framework allows the consideration of additional information a priori via informative distributions (priors). This work investigate the elicitation of informative priors for demographic parameters and parameters related to the catchability of fishing gear, as well as the use of these priors into a surplus production model. The cases of the Atlantic bluefin tuna (Thunnus thynnus) and of the yellowfin tuna (Thunnus albacares}) were taken as examples. The large natural variability of pre-recruits mortality rates limits the use of life history traits for eliciting priors for demographic parameters. In addition, the SR relationship for tuna is challenged by a steepness value close to 1. It appears that informative priors on catchability parameters, in a hierarchical surplus production model, reduce uncertainties in the diagnosis on the status of tuna stocks. We show that the status of the Atlantic yellowfin tuna stock is more critical taking into account upward trends in the main fishing gears catchabilities. We conclude that prior elicitation is a reliable tool to take into account additionnal information and to improve tunas stock assessment
Nelakanti, Anil Kumar. "Modélisation du langage à l'aide de pénalités structurées." Phd thesis, Université Pierre et Marie Curie - Paris VI, 2014. http://tel.archives-ouvertes.fr/tel-01001634.
Full textPiffady, Jérémy. "Etude des réponses des assemblages de poissons aux variations de l'environnement par modélisation hiérarchique bayésienne : Application aux juvéniles de cyprinidés du Haut-Rhône." Phd thesis, AgroParisTech, 2010. http://pastel.archives-ouvertes.fr/pastel-00566444.
Full textDemonceaux, Cédric. "Etude du mouvement dans les séquences d'images par analyse d'ondelettes et modélisation markovienne hiérarchique : application à la détection d'obstacles dans un milieu routier." Phd thesis, Université de Picardie Jules Verne, 2004. http://tel.archives-ouvertes.fr/tel-00862980.
Full textReda, Fatima Al. "Modélisation de mouvement de foules avec contraintes variées." Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLS235/document.
Full textWe are interested in the modeling of crowd motion. We propose a microscopic model based on game theoretic principles. Each individual is supposed to have a desired velocity, it is the one he would like to have in the absence of others. We consider that each individual is influenced by some of his neighbors, practically the ones that he sees. A possible actual velocity is an instantaneous Nash equilibrium: each individual does its best with respect to a personal objective (desired velocity), considering the behavior of the neighbors that influence him. We address theoretical and modeling issues in various situations, in particular when each individual is influenced by all the others, and in the case where the influence relations between individuals are hierarchical. We develop a numerical strategy to solve the problem in the second case (hierarchical model) and propose numerical simulations to illustrate the behavior of the model. We confront our numerical results with real experiments and prove the ability of the hierarchical model to reproduce some phenomena.We also propose to write a macroscopic counterpart of the hierarchical model by translating the same modeling principles to the macroscopic level and make the first steps towards writing such model.The last problem tackled in this thesis is related to gradient flow frameworks in the continuous and discrete Wasserstein spaces. It is known that the Fokker-Planck equation can be interpreted as a gradient flow for the continuous Wasserstein distance. We establish a link between some space discretization strategies of the Finite Volume type for the Fokker- Planck equation in general meshes (Voronoï tesselations) and gradient flows on the underlying networks of cells, in the framework of discrete Wasserstein-like distance on graphs recently introduced
Vautard, Jérémie. "Modélisation et résolution de problèmes de décision et d'optimisation hiérarchiques en utilisant des contraintes quantifiées." Phd thesis, Université d'Orléans, 2010. http://tel.archives-ouvertes.fr/tel-00486721.
Full textAlves, da Silva Lucas. "Estimation de la consommation d'énergie et du taux d'erreur bit d'un système Bluetooth LE basée sur la modélisation hiérarchique d'un amplificateur de puissance à 2,4 GHz." Nice, 2011. http://www.theses.fr/2011NICE4103.
Full textThe different results presented in this thesis focus on considering the energy consumption, during the development of hierarchical models for the design and verification of complex electronic systems. A wireless communication system was developed, complying to the Bluetooth Low-Energy (B-LE) standard, to estimate the whole system’s energy consumption, during the development phases. Initially, the energetic behaviour of the digital segment was studied, following the virtual prototyping approach. At the network level, an analysis of the different scan and advertisement strategies could be conducted, considering the device’s average power consumption as the optimization factor. Following, the radio transceiver’s modelling, using behavioural blocks, allows the estimation of the whole system’s energy consumption, as well as its influence over the system’s bit-error rate (BER). Finally the design of a power amplifier is presented, starting with its specification, through the architectural exploration and choice, until the circuit’s design and tape-out. Two methods are then proposed for the extraction of the power consumption, leading to refined accurate behavioural models, with minimal increase in simulation times
Eckert, Nicolas. "Couplage données historiques - modélisation numérique pour la prédétermination des avalanches : une approche bayésienne." Phd thesis, AgroParisTech, 2007. http://pastel.archives-ouvertes.fr/pastel-00003404.
Full textNelakanti, Anil Kumar. "Modélisation du langage à l'aide de pénalités structurées." Electronic Thesis or Diss., Paris 6, 2014. http://www.theses.fr/2014PA066033.
Full textModeling natural language is among fundamental challenges of artificial intelligence and the design of interactive machines, with applications spanning across various domains, such as dialogue systems, text generation and machine translation. We propose a discriminatively trained log-linear model to learn the distribution of words following a given context. Due to data sparsity, it is necessary to appropriately regularize the model using a penalty term. We design a penalty term that properly encodes the structure of the feature space to avoid overfitting and improve generalization while appropriately capturing long range dependencies. Some nice properties of specific structured penalties can be used to reduce the number of parameters required to encode the model. The outcome is an efficient model that suitably captures long dependencies in language without a significant increase in time or space requirements. In a log-linear model, both training and testing become increasingly expensive with growing number of classes. The number of classes in a language model is the size of the vocabulary which is typically very large. A common trick is to cluster classes and apply the model in two-steps; the first step picks the most probable cluster and the second picks the most probable word from the chosen cluster. This idea can be generalized to a hierarchy of larger depth with multiple levels of clustering. However, the performance of the resulting hierarchical classifier depends on the suitability of the clustering to the problem. We study different strategies to build the hierarchy of categories from their observations
Minois, Nathan. "Etude de consistance et applications du modèle Poisson-gamma : modélisation d'une dynamique de recrutement multicentrique." Thesis, Toulouse 3, 2016. http://www.theses.fr/2016TOU30396/document.
Full textA clinical trial is a biomedical research which aims to consolidate and improve the biological and medical knowledges. The number of patients required il the minimal number of patients to include in the trial in order to insure a given statistical power of a predefined test. The constitution of this patients' database is one of the fundamental issues of a clinical trial. To do so several investigation centres are opened. The duration between the first opening of a centre and the last recruitment of the needed number of patients is called the recruitemtn duration that we aim to model. The fisrt model goes back 50 years ago with the work of Lee, Williford et al. and Morgan with the idea to model the recruitment dynamic using Poisson processes. One problem emerge, that is the lack of caracterisation of the variabliity of recruitment between centers that is mixed with the mean of the recruitment rates. The most effective model is called the Poisson-gamma model which is based on Poisson processes with random rates (Cox process) with gamma distribution. This model is at the very heart of this project. Different objectives have motivated the realisation of this thesis. First of all the validity of the Poisson-gamma model is established asymptotically. A simulation study that we made permits to give precise informations on the model validity in specific cases (function of the number of centers, the recruitement duration and the mean rates). By studying database, one can observe that there can be breaks during the recruitment dynamic. A question that arise is : How and must we take into account this phenomenon for the prediction of the recruitment duration. The study made tends to show that it is not necessary to take them into account when they are random but their law is stable in time. It also veered around to measure the impact of these breaks on the estimations of the model, that do not impact its validity under some stability hypothesis. An other issue inherent to a patient recruitment dynamic is the phenomenon of screening failure. An empirical Bayesian technique analogue to the one of the recruitment process is used to model the screening failure issue. This hierarchical Bayesian model permit to estimate the duartion of recruitment with screening failure consideration as weel as the probability to drop out from the study using the data at some interim time of analysis, giving predictions on the randomisation dynamic. The recruitment dynamic can be studied in many different ways than just the duration of recruitment. These fundamental aspects coupled with the Poisson-gamma model give relevant indicators for the study follow-up. Multiples applications in this sense are computed. It is therefore possible to adjust the number of centers according to predefined objectives, to model the drug's supply chain per region or center and to predict the effect of the randomisation on the power of the test's study. It also allows to model the folow-up period of the patients by means of transversal or longitudinal methods, that can serve to adjust the number of patients if too many quit during the foloww-up period, or to stop the study if dangerous side effects or no effects are observed on interim data. The problematic of the recruitment dynamic can also be coupled with the dynamic of the study itself when it is longitudinal. The independance between these two processes allows easy estimations of the different parameters. The result is a global model of the patient pathway in the trail. Two key examples of such situations are survival data - the model permit to estimate the duration of the trail when the stopping criterion is the number of events observed, and the Markov model - the model permit to estimate the number of patients in a certain state for a given duartion of analysis
Le, Goc Romain. "Caractérisation et modélisation des écoulements dans les milieux fracturés." Phd thesis, Université Rennes 1, 2009. http://tel.archives-ouvertes.fr/tel-00467417.
Full textChagneau, Pierrette. "Modélisation bayésienne hiérarchique pour la prédiction multivariée de processus spatiaux non gaussiens et processus ponctuels hétérogènes d'intensité liée à une variable prédite : application à la prédiction de la régénération en forêt tropicale humide." Montpellier 2, 2009. http://www.theses.fr/2009MON20157.
Full textOne of the weak points of forest dynamics models is the recruitment. Classically, ecologists make the assumption that recruitment mainly depends on both spatial pattern of mature trees and environment. A detailed inventory of the stand and the environmental conditions enabled them to show the effects of these two factors on the local density of seedlings. In practice, such information is not available: only a part of seedlings is sampled and the environment is partially observed. The aim of the paper is to propose an approach in order to predict the spatial distribution and the seedlings genotype on the basis of a reasonable sampling of seedling, mature trees and environmental conditions. The spatial pattern of the seedlings is assumed to be a realization of a marked point process. The intensity of the process is not only related to the seed and pollen dispersal but also to the sapling survival. The sapling survival depends on the environment; so the environment must be predicted on the whole study area. The environment is characterized through spatial variables of different nature and predictions are obtained using a spatial hierarchical model. Unlike the existing models which assume the environmental covariables as exactly known, the recruitment model we propose takes into account the error related to the prediction of the environment. The prediction of seedling recruitment in tropical rainforest in French Guiana illustrates our approach
Galtié, Jean-François. "Information géographique numérique pour l'environnement : approche hiérarchique, modélisation et gestion prévisionnelle du risque incendie en région méditerranéenne : couplage données terrain : données de télédétection-video et intégration opérationnelle sous SIG." Toulouse 2, 1997. http://www.theses.fr/1997TOU20045.
Full textThis research aims at improving fire risk forecast in mediterranean shrubs environment. It has been carried out in the hilly wildlands of aspres, in the french eastern pyrenees, a region which is, at regular intervals, devastated by wildfires. The research project was designed in order to achieve two purposes : - on the one hand, the effectiviness of early detection of fire risk by remote sensing, from fuel spectral responses charateristics, had to be checked and confirmed according to the range of observation scales, within a hierarchical approach. - on the other hand, the final purpose of the work was to implement a methodological and operational framework for forecasting and managing fire risk according to the needs of the fire-fighting authorities in relation to decision support. The first objective was carried through by means of coupling both ground and remotly sensed data and of modelling plant fire susceptibility, controlled by fuel inflammability and combustibility, from relationships between biological and plant water status parameters on the one hand and, on the other hand, the potentially dectectable spectral charateristics of fuel. The three spectral bands of the experimental video device were then put to the test. A fire susceptibility biological index (fisbi), worked from mir data, has been suggested. Modelling was realized according the growing observation scales, from elementary plant particle to plant and vegetation cover. The design of the early fire detection and warning system rest on the previous modelling features and was built from and airbone video sensor with real-time ground data transmission, a gps and a gis for managing and bringing up-to-and date the fire risk maps. A full-size validation was carried through in the aspres during the summer of 1996 with the regional fire-fighting authorities
Li, Shuxian. "Modélisation spatio-temporelle pour l'esca de la vigne à l'échelle de la parcelle." Thesis, Bordeaux, 2015. http://www.theses.fr/2015BORD0313/document.
Full textEsca grapevine disease is one of the incurable dieback disease with the etiology not completely elucidated. It represents one of the major threats for viticulture around the world. To better understand the underlying process of esca spread and the risk factors of this disease, we carried out quantitative analyses of the spatio-temporal development of esca at vineyard scale. In order to detect the spatial correlation among the diseased vines, the non-parametric statistical tests were applied to the spatio-temporal data of esca foliar symptom expression for 15 vineyards in Bordeaux region. Among vineyards, a large range of spatial patterns, from random to strongly structured, were found. In the vineyards with strongly aggregated patterns, no significant increase in the size of cluster and local spread from symptomatic vines was shown, suggesting an effect of the environment in the explanation of this aggregation. To model the foliar symptom occurrence, we developed hierarchical logistic regression models by integrating exogenous covariates, covariates of neighboring symptomatic vines already diseased, and also a latent process with spatio-temporal auto-correlation. The Bayesian inferences of these models were performed by INLA (Inverse Nested Laplace Approximation) approach. The results confirmed the effect of environmental factors on the occurrence risk of esca symptom. The secondary locally spread of esca from symptomatic vines located on the same row or out of row was not shown. A two-step centered auto-logistic regression model, which explicitly integrated the spatio-temporal neighboring structure, was also developed. At last, a geostatistical method was proposed to interpolate data with a particular anisotropic structure. It allowed interpolating the ancillary variable, electrical resistivity of soil, which were used to estimate the available soil water content at vine-scale. These geostatistical methods and spatio-temporal statistical methods developed in this thesis offered outlook to identify risk factors, and thereafter to predict the development of esca grapevine disease in different agronomical contexts
Bimou, Charlotte. "Analyse de trajectoires, perte d'autonomie et facteurs prédictifs : Modélisation de trajectoires." Thesis, Limoges, 2019. http://www.theses.fr/2019LIMO0030/document.
Full textThe increase in life expectancy of baby boom generations in developed countries would often be accompanied by functional limitations, disability, increasingly observed in the geriatric population. The general objective of this thesis was to contribute to the knowledge of the evolution of the functional independence of older people in a heterogeneous population. First, it was to identify homogeneous groups in a heterogeneous population of elderly people following the same functional independence trajectory over a two-year period, and potential predictive factors. Second, it was to analyze the clinical consequences of trajectories and patient survival over the same observation period. The SMAF (Système de Mesure de l'Autonomie Fonctionnelle) and ADL (Activities of Daily Living) scales were used as indicators for measuring independence. Analysis were performed from a sample of 221 patients of UPSAV (Unit for Prevention, Monitoring and Analysis of Aging) cohort. We used three methods including trajectory analysis including GBTM (Group-Based Trajectory Modeling), k-means and ascending hierarchical classification. The results suggest three distinct trajectories of functional independence: stable, stable then decline, continuously decline. The predictors of trajectories obtained using logistic regression are socio-demographic, medical and biological criteria. Patients assigned to the loss of independence trajectory (continuously altered trajectory) reported high proportions of injurious falls. Based on a Cox model, neurocognitive disorders, heart failure, involuntary weight loss and alcohol were revealed as predictors of death. We conclude from this work that the two-year longitudinal analysis identified homogeneous subgroups of elderly people in terms of changes in functional independence. The prevention of UPSAV becomes a useful even if the utility level is not the same. Prevention and screening of the loss of independence of the elderly person followed at home must be anticipated in order to delay the deterioration and to maintaining the autonomy. Future analyses should focus on exploring large cohorts of older people to confirm and generalize our research
Pock, Michael. "A Hierarchical Modelling and Evaluation Technique for Safety Critical Systems." Electronic Thesis or Diss., Université de Lorraine, 2012. http://www.theses.fr/2012LORR0103.
Full textThis thesis presents a novel approach for modelling safety critical systems which takes into account several failure modes both for components and the global system. The so called Information Flow Diagrams (IFDs) were originally developed in a previous PhD-thesis. In this work, the evaluation if the IFD-approach should be made more efficient by using Binary Decision Diagrams (BDDs).This thesis will explain why such a model is necessary and practical, followed by a detailed explanation of the IFD-model. This includes its hierarchical structure and how this model can be applied. The next step is to formalise the original IFD-model in order to enable more efficient evaluation techniques. It will be explained why these formalisation steps were taken and what was gained by using them. Afterwards a detailed explanation of the developed algorithms is presented. These algorithms are based on a combination of different BDD-techniques. Zero Suppressed BDDs (ZBDDs) are combined with Boolean Expression Diagrams (BEDs). Furthermore, the structure of the IFDs is used in order to construct a large BDD out of several smaller BDDs. This increases the efficiency of the evaluation process.The presented techniques are evaluated by analysing several use cases which are explained in this work
Maleki, Mohammad. "Modélisation hiérarchisée du comportement des sols." Ecully, Ecole centrale de Lyon, 1998. http://www.theses.fr/1998ECDL0052.
Full textGarreta, Vincent. "Approche bayésienne de la reconstruction des paléoclimats à partir du pollen : Vers la modélisation des mécanismes écologiques." Phd thesis, Université Paul Cézanne - Aix-Marseille III, 2010. http://tel.archives-ouvertes.fr/tel-00495890.
Full textHoffmann, Sabine. "Approche hiérarchique bayésienne pour la prise en compte d’erreurs de mesure d’exposition chronique et à faible doses aux rayonnements ionisants dans l’estimation du risque de cancers radio-induits : Application à une cohorte de mineurs d’uranium." Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLS532/document.
Full textIn radiation epidemiology, exposure measurement error and uncertain input parameters in the calculation of absorbed organ doses are among the most important sources of uncertainty in the modelling of the health effects of ionising radiation. As the structures of exposure and dose uncertainty arising in occupational cohort studies may be complex, these uncertainty components are only rarely accounted for in this domain. However, when exposure measurement is not or only poorly accounted for, it may lead to biased risk estimates, a loss in statistical power and a distortion of the exposure-response relationship. The aim of this work was to promote the use of the Bayesian hierarchical approach to account for exposure and dose uncertainty in the estimation of the health effects associated with exposure to ionising radiation in occupational cohorts. More precisely, we proposed several hierarchical models and conducted Bayesian inference for these models in order to obtain corrected risk estimates on the association between exposure to radon and its decay products and lung cancer mortality in the French cohort of uranium miners. The hierarchical appraoch, which is based on the combination of sub-models that are linked via conditional independence assumptions, provides a flexible and coherent framework for the modelling of complex phenomena which may be prone to multiple sources of uncertainty. In order to compare the effects of shared and unshared exposure uncertainty on risk estimation and on the exposure-response relationship we conducted a simulation study in which we supposed complex and potentially time-varying error structures that are likely to arise in an occupational cohort study. We elicited informative prior distributions for average breathing rate, which is an important input parameter in the calculation of absorbed lung dose, based on the knowledge of three experts on the conditions in French uranium mines. In this context, we implemented and compared three approaches for the combination of expert opinion. Finally, Bayesian inference for the different hierarchical models was conducted via a Markov chain Monte Carlo algorithm implemented in Python to obtain corrected risk estimates on the lung cancer mortality in the French cohort of uranium miners associated with exposure to radon and its progeny
Delhumeau, Cécile. "Contribution à la modélisation des durées de séjour du CHU de Grenoble." Phd thesis, Université Joseph Fourier (Grenoble), 2002. http://tel.archives-ouvertes.fr/tel-00004392.
Full textPerret, Benjamin. "Caractérisation multibande de galaxies par hiérarchie de modèles et arbres de composantes connexes." Phd thesis, Université de Strasbourg, 2010. http://tel.archives-ouvertes.fr/tel-00559584.
Full textPock, Michael. "A Hierarchical Modelling and Evaluation Technique for Safety Critical Systems." Thesis, Université de Lorraine, 2012. http://www.theses.fr/2012LORR0103/document.
Full textThis thesis presents a novel approach for modelling safety critical systems which takes into account several failure modes both for components and the global system. The so called Information Flow Diagrams (IFDs) were originally developed in a previous PhD-thesis. In this work, the evaluation if the IFD-approach should be made more efficient by using Binary Decision Diagrams (BDDs).This thesis will explain why such a model is necessary and practical, followed by a detailed explanation of the IFD-model. This includes its hierarchical structure and how this model can be applied. The next step is to formalise the original IFD-model in order to enable more efficient evaluation techniques. It will be explained why these formalisation steps were taken and what was gained by using them. Afterwards a detailed explanation of the developed algorithms is presented. These algorithms are based on a combination of different BDD-techniques. Zero Suppressed BDDs (ZBDDs) are combined with Boolean Expression Diagrams (BEDs). Furthermore, the structure of the IFDs is used in order to construct a large BDD out of several smaller BDDs. This increases the efficiency of the evaluation process.The presented techniques are evaluated by analysing several use cases which are explained in this work
Yirci, Murat. "Arrangements 2D pour la Cartographie de l’Espace Public et des Transports." Thesis, Paris Est, 2016. http://www.theses.fr/2016PESC1075/document.
Full textThis thesis addresses easy and effective development of mapping and transportation applications which especially focuses on the generation of pedestrian networks for applications like navigation, itinerary calculation, accessibility analysis and urban planning. In order to achieve this goal, we proposed a two layered data model which encodes the public space into a hierarchy of semantic geospatial objects. At the lower level, the 2D geometry of the geospatial objects are captured using a planar partition which is represented as a topological 2D arrangement. This representation of a planar partition allows efficient and effective geometry processing and easy maintenance and validation throughout the editions when the geometry or topology of an object is modified. At the upper layer, the semantic and thematic aspects of geospatial objects are modelled and managed. The hierarchy between these objects is maintained using a directed acyclic graph (DAG) in which the leaf nodes correspond to the geometric primitives of the 2D arrangement and the higher level nodes represent the aggregated semantic geospatial objects at different levels. We integrated the proposed data model into our GIS framework called StreetMaker together with a set of generic algorithms and basic GIS capabilities. This framework is then rich enough to generate pedestrian network graphs automatically. In fact, within an accessibility analysis project, the full proposed pipeline was successfully used on two sites to produce pedestrian network graphs from various types of input data: existing GIS vector maps, semi-automatically created vector data and vector objects extracted from Mobile Mapping lidar point clouds.While modelling 2D ground surfaces may be sufficient for 2D GIS applications, 3D GIS applications require 3D models of the environment. 3D modelling is a very broad topic but as a first step to such 3D models, we focused on the semi-automatic modelling of objects which can be modelled or approximated by generalized cylinders (such as poles, lampposts, tree trunks, etc.) from single images. The developed methods and techniques are presented and discussed
Chiron, Guillaume. "Système complet d’acquisition vidéo, de suivi de trajectoires et de modélisation comportementale pour des environnements 3D naturellement encombrés : application à la surveillance apicole." Thesis, La Rochelle, 2014. http://www.theses.fr/2014LAROS030/document.
Full textThis manuscript provides the basis for a complete chain of videosurveillence for naturally cluttered environments. In the latter, we identify and solve the wide spectrum of methodological and technological barriers inherent to : 1) the acquisition of video sequences in natural conditions, 2) the image processing problems, 3) the multi-target tracking ambiguities, 4) the discovery and the modeling of recurring behavioral patterns, and 5) the data fusion. The application context of our work is the monitoring of honeybees, and in particular the study of the trajectories bees in flight in front of their hive. In fact, this thesis is part a feasibility and prototyping study carried by the two interdisciplinary projects EPERAS and RISQAPI (projects undertaken in collaboration with INRA institute and the French National Museum of Natural History). It is for us, computer scientists, and for biologists who accompanied us, a completely new area of investigation for which the scientific knowledge, usually essential for such applications, are still in their infancy. Unlike existing approaches for monitoring insects, we propose to tackle the problem in the three-dimensional space through the use of a high frequency stereo camera. In this context, we detail our new target detection method which we called HIDS segmentation. Concerning the computation of trajectories, we explored several tracking approaches, relying on more or less a priori, which are able to deal with the extreme conditions of the application (e.g. many targets, small in size, following chaotic movements). Once the trajectories are collected, we organize them according to a given hierarchical data structure and apply a Bayesian nonparametric approach for discovering emergent behaviors within the colony of insects. The exploratory analysis of the trajectories generated by the crowded scene is performed following an unsupervised classification method simultaneously over different levels of semantic, and where the number of clusters for each level is not defined a priori, but rather estimated from the data only. This approach is has been validated thanks to a ground truth generated by a Multi-Agent System. Then we tested it in the context of real data