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Статті в журналах з теми "Exploration des séquences"
Bidart, Claire, and Catherine Gosselin. "Rythmes sociaux et interférences temporelles - Exploration de séquences biographiques de calendriers et de récits." Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique 124, no. 1 (October 2014): 34–52. http://dx.doi.org/10.1177/0759106314543636.
Повний текст джерелаNgo Nlend, Nadeige, Ludovic Lado, Gishleine Oukouomi, Ewane Etah, and Eric Acha. "Enjeux de la pédagogie contrastée de l’histoire dans les sous-systèmes anglophone et francophone pour les politiques mémorielles au Cameroun." Africa Development 47, no. 4 (January 10, 2023): 211–37. http://dx.doi.org/10.57054/ad.v47i4.2983.
Повний текст джерелаRoss, Pierre-Simon, and Patrick Mercier-Langevin. "Igneous Rock Associations 14. The Volcanic Setting of VMS and SMS Deposits: A Review." Geoscience Canada 41, no. 3 (August 29, 2014): 365. http://dx.doi.org/10.12789/geocanj.2014.41.045.
Повний текст джерелаMiller, Roy McG. "Comparative Stratigraphic and Geochronological Evolution of the Northern Damara Supergroup in Namibia and the Katanga Supergroup in the Lufilian Arc of Central Africa." Geoscience Canada 40, no. 2 (August 24, 2013): 118. http://dx.doi.org/10.12789/geocanj.2013.40.007.
Повний текст джерелаFlorey, Sonya, and Vincent Capt. "RESSOURCES NUMÉRIQUES POUR L’ENSEIGNEMENT DE LA LITTÉRATURE DE JEUNESSE. PROMESSES DU TEMPS JADIS, REPRÉSENTATIONS ENSEIGNANTES ET ESSAI MANQUÉ DE TYPOLOGIE." La littérature de jeunesse, à l’ère numérique 8 (August 20, 2018). http://dx.doi.org/10.7202/1050935ar.
Повний текст джерелаFallenbacher-Clavien, Francine, and Valérie Michelet. "L’annotation de poème et sa mise en voix : une approche sensible au service de l’oralité." Carnets de Poédiles, no. 1 (March 14, 2023). http://dx.doi.org/10.56078/carnets-poediles.156.
Повний текст джерелаДисертації з теми "Exploration des séquences"
Faisan, Sylvain. "Analyse et fusion markovienne de séquences en imagerie 3D+t : Application à l'analyse de séquences d'images IRM fonctionnelles cérébrales." Université Louis Pasteur (Strasbourg) (1971-2008), 2004. https://publication-theses.unistra.fr/public/theses_doctorat/2004/FAISAN_Sylvain_2004.pdf.
Повний текст джерелаHidden Markov Models (HMMs) which are widely used to process signals or images, are well-suited to the analysis of random processes that are segmental in nature. However, many processes, met in particular in the biomedical field, are event-based processes making the HMMs ill-suited. We present in this PHD two markovian approaches dedicated to the modeling and analysis of an event-based process or of multiple interacting event-based processes. Both approaches proceed in two steps. First, a preprocessing step detects and characterizes events of interest in the raw input data. Then, detected events are analyzed based on an adapted hidden Markov model. The two modeling approaches can be distinguished by the number of event sequences they can handle. The first approach, which is based on a hidden semi-Markov event sequence model(HSMESM), considers a single event sequence whereas the second approach,which is based on a hidden Markov multiple event sequence model (HMMESM),handles multiple observation channels at once, within a rich mathematical framework of fusion--association of asynchronous events across channels. From these models, two unsupervised functional MRI (fMRI) brain mapping methods have been developed. Both methods rely on the same, novel principle of temporal alignment between event sequences. By accounting for spatial information within a statistical framework of multiple event sequence detection- multiple event sequence fusion, the HMMESM-based mapping method shows high robustness to noise and variability of the active fMRI signal across space, time, experiments, and subjects. Besides, the HMMESM method clearly outperforms the HSMESM method as well as the widely used Statistical Parametric Mapping (SPM) approach
Levivier, Emilie. "Exploration des similitudes de séquences protéiques à haut niveau de divergence évolutive : perspectives de l'approche Hydrophobic Cluster Analysis (HCA)." Paris 7, 2003. http://www.theses.fr/2003PA077069.
Повний текст джерелаLi, Dong Haoyuan. "Extraction de séquences inattendues : des motifs séquentiels aux règles d’implication." Montpellier 2, 2009. http://www.theses.fr/2009MON20253.
Повний текст джерелаThe sequential patterns can be viewed as an extension of the notion of association rules with integrating temporal constraints, which are effective for representing statistical frequency based behaviors between the elements contained in sequence data, that is, the discovered patterns are interesting because they are frequent. However, with considering prior domain knowledge of the data, another reason why the discovered patterns are interesting is because they are unexpected. In this thesis, we investigate the problems in the discovery of unexpected sequences in large databases with respect to prior domain expertise knowledge. We first methodically develop the framework Muse with integrating the approaches to discover the three forms of unexpected sequences. We then extend the framework Muse by adopting fuzzy set theory for describing sequence occurrence. We also propose a generalized framework SoftMuse with respect to the concept hierarchies on the taxonomy of data. We further propose the notions of unexpected sequential patterns and unexpected implication rules, in order to evaluate the discovered unexpected sequences by using a self-validation process. We finally propose the discovery and validation of unexpected sentences in free format text documents. The usefulness and effectiveness of our proposed approaches are shown with the experiments on synthetic data, real Web server access log data, and text document classification
Jaziri, Rakia. "Modèles de mélanges topologiques pour la classification de données structurées en séquences." Paris 13, 2013. http://scbd-sto.univ-paris13.fr/secure/edgalilee_th_2013_jaziri.pdf.
Повний текст джерелаRecent years have seen the development of data mining techniques in various application areas, with the purpose of analyzing sequential, large and complex data. In this work, the problem of clustering, visualization and structuring data is tackled by a three-stage proposal. The first proposal present a generative approach to learn a new probabilistic Self-Organizing Map (PrSOMS) for non independent and non identically distributed data sets. Our model defines a low dimensional manifold allowing friendly visualizations. To yield the topology preserving maps, our model exhibits the SOM like learning behavior with the advantages of probabilistic models. This new paradigm uses HMM (Hidden Markov Models) formalism and introduces relationships between the states. This allows us to take advantage of all the known classical views associated to topographic map. The second proposal concerns a hierarchical extension of the approach PrSOMS. This approach deals the complex aspect of the data in the classification process. We find that the resulting model ”H-PrSOMS” provides a good interpretability of classes built. The third proposal concerns an alternative approach statistical topological MGTM-TT, which is based on the same paradigm than HMM. It is a generative topographic modeling observation density mixtures, which is similar to a hierarchical extension of time GTM model. These proposals have then been applied to test data and real data from the INA (National Audiovisual Institute). This work is to provide a first step, a finer classification of audiovisual broadcast segments. In a second step, we sought to define a typology of the chaining of segments (multiple scattering of the same program, one of two inter-program) to provide statistically the characteristics of broadcast segments. The overall framework provides a tool for the classification and structuring of audiovisual programs
Nicolas, Renaud. "Développement de nouvelles séquences d'IRM de diffusion dédiées à la neuro-imagerie." Toulouse 3, 2012. http://www.theses.fr/2012TOU30283.
Повний текст джерелаThis PhD thesis is dedicated to a technique, diffusion MRI, which allow to obtain images of micro-structural properties (inferior to the MRI voxel size) of biological media, and to the application of this technique to study brain. Because of its ability to reveal early micro-structural changes (associated with complex energetic metabolism changes), diffusion MRI is become a reference method to detect focal diseases like ischemic stroke. The reader can find in this thesis a complete introduction to the physical phenomenon related to brownian motion in biological media and those related to diffusion NMR and MRI, and an original synthesis of the biological and biophysical determinisms of the changes of apparent diffusion coefficients observed in stroke animal models. To extend the field of the technique from stroke focal phenomenon (studied experimentally in man an rodents) to non focal pathologies, the study of the deviation of diffusion from Gaussian behaviour has been studied theoretically and experimentally. Pratical methodologies allowing the preparation of diffusion images for non-gaussian diffusion imaging, and artefacts corrections are described here. This work has lead to a study of non-gaussian diffusion MRI signal treated as an inverse problem and to applications for Alzheimer's disease detection, characterized by non-focal and microscopic lesions. Finally, we have developed three original approaches for technological developments of MRI sequences (with the associated image treatment necessary to use them). The first is the development of non-gaussian diffusion together with variation of diffusion time applied to imaging at 4. 7 and 7 T. The second concern the development of magnetization transfer and diffusion imaging that give additional information about water probed by MRI. The latter approach is the development of fonctionnal diffusion MRI at 3 T in DTI mode dedicated to apply the biological hypothesis resumed in the first part of this thesis, concerning the particular role of water in brain activation. With a progression for the experimental validations, hypothesis concerning micro-structures of biological media are tested and validated with different approaches (in vivo, ex vivo, in silico), to apply the recent discoveries concerning the physic of diffusion MRI in order to detect focal and non-focal pathologies and to interpret them
Hérisson, Joan. "Représentation spatiale et exploration virtuelle des génomes : une approche globale pour l'analyse des éléments architecturaux des séquences." Paris 11, 2004. http://www.theses.fr/2004PA112147.
Повний текст джерелаDNA sequences are often represented by a succession of four nucleotides: A, C, G and T. Even if this representation allows to study the linguistics and syntax of DNA sequences, it remains textual, local and monodimensional and does not provide any visual, local nor spatial information. However, DNA is a three-dimensional structure forming a double helix which can bend and create long distance interactions. The aim of this thesis is to propose a new approach of the genomic sequences in order to enrich classic analyses with three-dimensonal criteria. The modelling of these 3D DNA sequences is based on a biophysical model of spatial conformation of DNA. Such a representation raises problematics both in computer science - concerning Virtual Reality for scene management, interaction, data representation and associated algorithms - and in Bioinformatics of genomes. These different aspects, which form the pluridisciplinary nature of this thesis, have been treated through the software program tool ADN-Viewer that I have developed. Two directions have been taken during this work and should endure after this thesis. The first one is to come close as much as possible to the DNA biological reality. Our work represents a very first step in this sense and has to be enriched by new criteria of spatial conformation and by the integration of biological partners of DNA. The second direction is to exploit the three-dimensional structure of DNA as a representation among others to explore, treat and analyze the biological content of sequences
Guillame-Bert, Mathieu. "Apprentissage de règles associatives temporelles pour les séquences temporelles de symboles." Thesis, Grenoble, 2012. http://www.theses.fr/2012GRENM081/document.
Повний текст джерелаThe learning of temporal patterns is a major challenge of Data mining. We introduce a temporal pattern model called Temporal Interval Tree Association Rules (Tita rules or Titar). This pattern model can be used to express both uncertainty and temporal inaccuracy of temporal events. Among other things, Tita rules can express the usual time point operators, synchronicity, order, and chaining,disjunctive time constraints, as well as temporal negation. Tita rules are designed to allow predictions with optimum temporal precision. Using this representation, we present the Titar learner algorithm that can be used to extract Tita rules from large datasets expressed as Symbolic Time Sequences. This algorithm based on entropy minimization, apriori pruning and statistical dependence analysis. We evaluate our technique on simulated and real world datasets. The problem of temporal planning with Tita rules is studied. We use Tita rules as world description models for a Planning and Scheduling task. We present an efficient temporal planning algorithm able to deal with uncertainty, temporal inaccuracy, discontinuous (or disjunctive) time constraints and predictable but imprecisely time located exogenous events. We evaluate our technique by joining a learning algorithm and our planning algorithm into a simple reactive cognitive architecture that we apply to control a robot in a virtual world
Guillame-bert, Mathieu. "Apprentissage de règles associatives temporelles pour les séquences temporelles de symboles." Phd thesis, Université de Grenoble, 2012. http://tel.archives-ouvertes.fr/tel-00849087.
Повний текст джерелаWeber, Jonathan. "Segmentation morphologique interactive pour la fouille de séquences vidéo." Phd thesis, Université de Strasbourg, 2011. http://tel.archives-ouvertes.fr/tel-00643585.
Повний текст джерелаBastide, Nathalie. "Segmentation et analyse du mouvement du ventricule gauche à partir de séquences d'images cardiaques de scanographie ultra-rapide." Paris 12, 1993. http://www.theses.fr/1993PA120021.
Повний текст джерелаЧастини книг з теми "Exploration des séquences"
KAUFMANN, Vincent, and Guillaume DREVON. "Penser ensemble les échelles de la mobilité." In Échelles spatiales et temporelles de la mobilité, 1–13. ISTE Group, 2022. http://dx.doi.org/10.51926/iste.9064.ch1.
Повний текст джерела