5 research outputs found

    De la cosmologie à la formation des galaxies : que nous apprennent les grandes structures de l'Univers ?

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    This thesis by publication is devoted to the theoretical understanding of the large-scale structure of the Universe and its role in the context of cosmology and galaxy formation. The birth and evolution of galaxies occur within the large cosmic highways drawn by the cosmic web and the natural question which arises is whether galaxies retain a memory of the large-scale cosmic flows from which they emerge. To address this key question, we will first show that in cosmological simulations, the spin of galaxies and the direction of their host filament are correlated in a mass-dependent way. This signal will be shown to be qualitatively understood in the context of hierarchical structure formation. An analytic model which explicitly takes into account the anisotropy of the cosmic web will complement this qualitative understanding by reproducing the measured correlations. Those ideas are important to understand the evolution of galaxy morphology but also to understand the intrinsic alignments of galaxies that contaminate cosmological probes like cosmic shear experiments. We will in particular measure this contamination directly from a state-of-the-art hydrodynamical simulation. In a second part, we will address the question of how to efficiently use large-scale structure data to probe the cosmological model describing our Universe by measuring its topology and geometry and using perturbation theory in the weakly and even mildly non-linear regime. The major contribution of this work is to analytically study the effect of redshift space distortions and non-linear collapse of structures on the topology, geometry and statistics of the cosmic density field.Dans cette thèse sur articles, nous nous intéressons aux grandes structures de l’Univers et à leur rôle fondamental pour la cosmologie et la formation des galaxies. Les galaxies naissent et grandissent au sein des filaments de la toile cosmique soulevant la question de l’impact de ces filaments sur les propriétés galactiques telles que la morphologie. Pour étudier cette question fondamentale, nous allons dans un premier temps montrer que dans les simulations numériques de l’Univers, le spin des galaxies est fortement lié à la direction de leur filament hôte avec un comportement qui dépend de leur masse. Ces corrélations spin-filament seront expliquées qualitativement dans le contexte de la formation hiérarchique des structures cosmologiques. Un modèle analytique tenant compte de l’anisotropie de la toile cosmique complètera ce tableau en reproduisant les corrélations observées. Ces idées sont importantes pour comprendre la morphologie des galaxies mais aussi les alignements intrinsèques qui peuvent certaines sondes cosmologiques basées sur la mesure de l’astigmatisme cosmique. Nous allons en particulier mesurer cette contamination dans une simulation hydrodynamique. Dans la seconde partie de ce manuscrit, nous nous poserons la question de comment extraire efficacement de l’information de la toile cosmique en mesurant sa topologie et sa géométrie et en utilisant la théorie perturbative dans un régime quasi-linéaire, la pierre angulaire de ce travail reposant sur l’étude analytique de l’impact de l’effondrement non-linéaire des structures et des distorsions en espace des redshifts sur la statistique du champ de densité cosmique

    SPEECH TO CHART: SPEECH RECOGNITION AND NATURAL LANGUAGE PROCESSING FOR DENTAL CHARTING

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    Typically, when using practice management systems (PMS), dentists perform data entry by utilizing an assistant as a transcriptionist. This prevents dentists from interacting directly with the PMSs. Speech recognition interfaces can provide the solution to this problem. Existing speech interfaces of PMSs are cumbersome and poorly designed. In dentistry, there is a desire and need for a usable natural language interface for clinical data entry. Objectives. (1) evaluate the efficiency, effectiveness, and user satisfaction of the speech interfaces of four dental PMSs, (2) develop and evaluate a speech-to-chart prototype for charting naturally spoken dental exams. Methods. We evaluated the speech interfaces of four leading PMSs. We manually reviewed the capabilities of each system and then had 18 dental students chart 18 findings via speech in each of the systems. We measured time, errors, and user satisfaction. Next, we developed and evaluated a speech-to-chart prototype which contained the following components: speech recognizer; post-processor for error correction; NLP application (ONYX) and; graphical chart generator. We evaluated the accuracy of the speech recognizer and the post-processor. We then performed a summative evaluation on the entire system. Our prototype charted 12 hard tissue exams. We compared the charted exams to reference standard exams charted by two dentists. Results. Of the four systems, only two allowed both hard tissue and periodontal charting via speech. All interfaces required using specific commands directly comparable to using a mouse. The average time to chart the nine hard tissue findings was 2:48 and the nine periodontal findings was 2:06. There was an average of 7.5 errors per exam. We created a speech-to-chart prototype that supports natural dictation with no structured commands. On manually transcribed exams, the system performed with an average 80% accuracy. The average time to chart a single hard tissue finding with the prototype was 7.3 seconds. An improved discourse processor will greatly enhance the prototype's accuracy. Conclusions. The speech interfaces of existing PMSs are cumbersome, require using specific speech commands, and make several errors per exam. We successfully created a speech-to-chart prototype that charts hard tissue findings from naturally spoken dental exams

    Search beyond traditional probabilistic information retrieval

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    "This thesis focuses on search beyond probabilistic information retrieval. Three ap- proached are proposed beyond the traditional probabilistic modelling. First, term associ- ation is deeply examined. Term association considers the term dependency using a factor analysis based model, instead of treating each term independently. Latent factors, con- sidered the same as the hidden variables of ""eliteness"" introduced by Robertson et al. to gain understanding of the relation among term occurrences and relevance, are measured by the dependencies and occurrences of term sequences and subsequences. Second, an entity-based ranking approach is proposed in an entity system named ""EntityCube"" which has been released by Microsoft for public use. A summarization page is given to summarize the entity information over multiple documents such that the truly relevant entities can be highly possibly searched from multiple documents through integrating the local relevance contributed by proximity and the global enhancer by topic model. Third, multi-source fusion sets up a meta-search engine to combine the ""knowledge"" from different sources. Meta-features, distilled as high-level categories, are deployed to diversify the baselines. Three modified fusion methods are employed, which are re- ciprocal, CombMNZ and CombSUM with three expanded versions. Through extensive experiments on the standard large-scale TREC Genomics data sets, the TREC HARD data sets and the Microsoft EntityCube Web collections, the proposed extended models beyond probabilistic information retrieval show their effectiveness and superiority.

    Developing a distributed electronic health-record store for India

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    The DIGHT project is addressing the problem of building a scalable and highly available information store for the Electronic Health Records (EHRs) of the over one billion citizens of India

    Reliability and Maintainability model (RAM) user and maintenance manual

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    This report documents the procedures for utilizing and maintaining the Reliability and Maintainability Model (RAM) developed by the University of Dayton for the NASA Langley Research Center (LaRC). The RAM model predicts reliability and maintainability (R&M) parameters for conceptual space vehicles using parametric relationships between vehicle design and performance characteristics and subsystem mean time between maintenance actions (MTBM) and manhours per maintenance action (MH/MA). These parametric relationships were developed using aircraft R&M data from over thirty different military aircraft of all types. This report describes the general methodology used within the model, the execution and computational sequence, the input screens and data, the output displays and reports, and study analyses and procedures. A source listing is provided
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