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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Shang, Guokan;

    Grâce aux progrès impressionnants qui ont été réalisés dans la transcription du langage parlé, il est de plus en plus possible d'exploiter les données transcrites pour des tâches qui requièrent la compréhension de ce que l'on dit dans une conversation. Le travail présenté dans cette thèse, réalisé dans le cadre d'un projet consacré au développement d'un assistant de réunion, contribue aux efforts en cours pour apprendre aux machines à comprendre les dialogues des réunions multipartites. Nous nous sommes concentrés sur le défi de générer automatiquement les résumés abstractifs de réunion.Nous présentons tout d'abord nos résultats sur le Résumé Abstractif de Réunion (RAR), qui consiste à prendre une transcription de réunion comme entrée et à produire un résumé abstractif comme sortie. Nous introduisons une approche entièrement non-supervisée pour cette tâche, basée sur la compression multi-phrases et la maximisation sous-modulaire budgétisée. Nous tirons également parti des progrès récents en vecteurs de mots et dégénérescence de graphes appliqués au TAL, afin de prendre en compte les connaissances sémantiques extérieures et de concevoir de nouvelles mesures de diversité et d'informativité.Ensuite, nous discutons de notre travail sur la Classification en Actes de Dialogue (CAD), dont le but est d'attribuer à chaque énoncé d'un discours une étiquette qui représente son intention communicative. La CAD produit des annotations qui sont utiles pour une grande variété de tâches, y compris le RAR. Nous proposons une couche neuronale modifiée de Champ Aléatoire Conditionnel (CAC) qui prend en compte non seulement la séquence des énoncés dans un discours, mais aussi les informations sur les locuteurs et en particulier, s'il y a eu un changement de locuteur d'un énoncé à l'autre.La troisième partie de la thèse porte sur la Détection de Communauté Abstractive (DCA), une sous-tâche du RAR, dans laquelle les énoncés d'une conversation sont regroupés selon qu'ils peuvent être résumés conjointement par une phrase abstractive commune. Nous proposons une nouvelle approche de la DCA dans laquelle nous introduisons d'abord un encodeur neuronal contextuel d'énoncé qui comporte trois types de mécanismes d'auto-attention, puis nous l'entraînons en utilisant les méta-architectures siamoise et triplette basées sur l'énergie. Nous proposons en outre une méthode d'échantillonnage générale qui permet à l'architecture triplette de capturer des motifs subtils (p. ex., des groupes qui se chevauchent et s'emboîtent). With the impressive progress that has been made in transcribing spoken language, it is becoming increasingly possible to exploit transcribed data for tasks that require comprehension of what is said in a conversation. The work in this dissertation, carried out in the context of a project devoted to the development of a meeting assistant, contributes to ongoing efforts to teach machines to understand multi-party meeting speech. We have focused on the challenge of automatically generating abstractive meeting summaries.We first present our results on Abstractive Meeting Summarization (AMS), which aims to take a meeting transcription as input and produce an abstractive summary as output. We introduce a fully unsupervised framework for this task based on multi-sentence compression and budgeted submodular maximization. We also leverage recent advances in word embeddings and graph degeneracy applied to NLP, to take exterior semantic knowledge into account and to design custom diversity and informativeness measures.Next, we discuss our work on Dialogue Act Classification (DAC), whose goal is to assign each utterance in a discourse a label that represents its communicative intention. DAC yields annotations that are useful for a wide variety of tasks, including AMS. We propose a modified neural Conditional Random Field (CRF) layer that takes into account not only the sequence of utterances in a discourse, but also speaker information and in particular, whether there has been a change of speaker from one utterance to the next.The third part of the dissertation focuses on Abstractive Community Detection (ACD), a sub-task of AMS, in which utterances in a conversation are grouped according to whether they can be jointly summarized by a common abstractive sentence. We provide a novel approach to ACD in which we first introduce a neural contextual utterance encoder featuring three types of self-attention mechanisms and then train it using the siamese and triplet energy-based meta-architectures. We further propose a general sampling scheme that enables the triplet architecture to capture subtle patterns (e.g., overlapping and nested clusters).

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    Other literature type . 2021
    Hal-Diderot
    Doctoral thesis . 2021
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      Other literature type . 2021
      Hal-Diderot
      Doctoral thesis . 2021
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    Authors: Winston, Cynthia; Winston, Michael; Boyd, Alexis;

    More than ever before in human history, rapid increases in innovation and discovery are critical to solving the world’s most pressing economic, climate, health, and human problems. Although women in the United States are earning more doctoral degrees in science and engineering fields than ever before, less then 24% of the science and engineering workforce includes women (U.S. Department of Commerce, 2011). While in the last decade there has been an increase in national programs to recruit more women in science careers, women of color have largely been excluded and often are not specified in federal statistics on the science workforce (Mack, Rankins, & Winston, 2011). Moreover, among those programs that do exist, few adopt a synergistic psychologically grounded approach to sustained and culturally responsive professional development for women of color. The lives of women of color demand complex psychological negotiation and strategic life management of simultaneous experiences of racism, sexism, classism, and unique cultural imperatives (Cole, 2009). Thus, not only is getting them into the science workforce important, it is critical to generate scholarship guided by intersectionality theoretical frameworks that can inform the design of mechanisms for their retention, leadership training, and acquisition of knowledge and skills to sustain a healthy career and family life balance. Historical and biographical studies of women of color in science do not generally make reference to the history of White women in science in the United States. This neglect tends to underestimate the effect of gender per se on access to science education and careers in science. These biographical accounts focus principally on individuals with no attempt to identify systems of exclusion or patterns of success in overcoming exclusion. While the narratives about individual careers have real importance as documentation, those accounts by themselves cannot disclose the ways in which the social system and the educational matrix functioned to produce the result that few women of any race and ethnicity became scientists in one period of history. This paper demonstrates the theoretical and practical utility of the integration of narratives of the experiences of both white and women of color in science with systems level historical analysis of institutionalized gender prejudice in all women gaining access to science education and scientific careers. Vers Une Compréhension Accrue des Expériences Vécues par les Femmes de Couleur en matière de formation et de carrières scientifiques : Quelle est l’Utilité de l’Intégration des Récits d’ Expériences Diverses dans l’Analyse Historique des En général, les études historiques et biographiques des femmes de couleur dans le domaine des sciences ne font pas référence à l’histoire des femmes Blanches dans le domaine des sciences aux Etats-Unis. Cette lacune a souvent pour effet de sous-estimer l’ impacte du genre sur l’accès à l’enseignement des sciences et aux carrières scientifiques. Les biographies mettent principalement l’accent sur les individus et ne tentent pas d’identifier les systèmes d’exclusion ou les modèles de succès dans la lutte contre l’exclusion. Tandis que les récits portant sur des carrières individuelles ont une importance réelle en tant que documents, ces récits en tant que tels ne peuvent pas révéler comment le système social et la matrice de l’éducation ont fonctionné pour ne produire que peu de femmes de science, toutes races et ethnies confondues, durant une période donnée de l’histoire. Cet article démontre l’utilité théorique et pratique d’intégrer les récits des expériences des femmes de science tant blanches que de couleur dans l’analyse historique du préjugé sexiste institutionnalisé auquel les femmes sont confrontées lorsqu’elles poursuivent un cursus et une carrière scientifiques. Plus que jamais dans l‘histoire humaine, l’augmentation rapide de l’innovation et des découvertes est cruciale pour résoudre les problèmes économiques, climatiques, sanitaires, et humains les plus urgents du monde. Bien que les femmes aux Etats-Unis obtiennent davantage de doctorats en science et en ingénierie que jamais auparavant, elles ne constituent néanmoins que moins de 24% des salariés employés dans les domaines de la science et de l’ingénierie (Département Américain du Commerce, 2011).

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    Other literature type . 2014
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    Other literature type . 2014
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Hyper Article en Lig...arrow_drop_down
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      Hal-Diderot
      Other literature type . 2014
      Data sources: Hal-Diderot
  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Simon Chane, Camille, Simon;

    Cette thèse s'intéresse au recalage de données issues de capteurs 3D et multispectraux pour l'étude du patrimoine.Lorsque l'on étudie ce type d'objet, il y a souvent peu de points saillants naturels entre ces jeux de données complémentaires. Par ailleurs, l'utilisation de mires optiques est proscrite.Notre problème est donc de recaler des données multimodales sans points caractéristiques.Nous avons développé une méthode de recalage basé sur le suivi des systèmes d'acquisition en utilisant des techniques issues de la photogrammétrie.Des simulations nous ont permis d'évaluer la précision de la méthode dans trois configurations qui représentent des cas typiques dans l'étude d'objets du patrimoine.Ces simulations ont montré que l'on peut atteindre une précision du suivi de 0.020 mm spatialement et 0.100 mrad angulairement en utilisant quatre caméras 5 Mpx lorsque l'on numérise une zone de 400 mm x 700 mm.La précision finale du recalage repose sur le succès d'une série de calibrations optiques et géométriques, ainsi que sur leur stabilité pour la durée du processus d'acquisition.Plusieurs tests ont permis d'évaluer la précision du suivi et du recalage de plusieurs jeux de données indépendants; d'abord seulement 3D, puis 3D et multispecrales.Enfin, nous avons étendu notre méthode d'estimation de la réflectance à partir des données multispectrales lorsque celles-ci sont recalées sur un modèle 3D. The concern and interest of this PhD thesis is the registration of featureless 3D and multispectral datasets describing cultural heritage objects.In this context, there are few natural salient features between the complementary datasets, and the use of targets is generally proscribed.We thus develop a technique based on the photogrammetric tracking of the acquisition systems in use.A series of simulations was performed to evaluate the accuracy of our method in three configurations chosen to represent a variety of cultural heritage objects.These simulations show that we can achieve a spatial tracking accuracy of 0.020 mm and an angular accuracy of 0.100 mrad using four 5 Mpx cameras when digitizing an area of 400 mm x 700 mm. The accuracy of the final registration relies on the success of a series of optical and geometrical calibrations and their stability for the duration of the full acquisition process.The accuracy of the tracking and registration was extensively tested in laboratory settings. We first evaluated the potential for multiview 3D registration. Then, the method was used for to project of multispectral images on 3D models.Finally, we used the registered data to improve the reflectance estimation from the multispectral datasets

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    Authors: Grandjean, Martin;

    International audience

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    Other literature type . 2013
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    Authors: Drap, Pierre; Durand, Anne; Nedir, Malika; Seinturier, Julien; +9 Authors

    The paper presents an interdisciplinary project which is the first step towards a 3D Geographical Information System (GIS) dedicated to Cultural Heritage with a specific focus application on the Castle of Shawbak, also known as the ”Crac de Montral” in Jordan. The project continues to grow thanks to a synergy between a set of laboratories: The LSIS laboratory, France in charge of the pho- togrammetric survey phase connected with the knowledge based approach; ITABC, CNR lab in Roma, Italy in charge of the topometric survey, with DGPS and aerial photography with gas balloon, National Institute of Information and Communications Technology, Kyoto, Japan for the 3D view point seek connected to the database, the image processing aspect managed by Stratos documentation, SimVis from The Department of Computer Science, University of Hull, UK, for the virtual reality aspect and of course the Dipartimento di Studi storici e Geografici from the University of Florence, Italy, in charge of the archaeological part. Our project focuses on a building scale encompassing its atomic elements such as ashlars blocks, cement, stratigraphic units and archi- tectonic elements. At this scale we need a full 3D interface in order to manage accurate measurements, a huge quantity of observations and a mainly heterogeneous archaeological documentation. This project described in this paper is work in progress. After four photogrammetric campaigns in Jordan the first results are available on the project web site: http://www.shawbak.net

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    Other literature type . 2007
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    Authors: Barret, Sébastien; Helias-Baron, Marlène; Stutzmann, Dominique; Tscherne, Niklas; +2 Authors

    The poster will present the project "Between Composition and Reception: the Authority of Medieval Charters" and discuss what role machine learning methods can have for the human interpretation of late medieval charters as means to convey authority, esp. regarding their graphical aspects

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    Authors: Lopez, Cédric; Prince, Violaine; Roche, Mathieu;

    International audience; This paper deals with an application allowing the automatic titling of texts. This one consists of four stages: Corpus acquisition, candidate sentence determination for the titling, extraction of noun phrases among the candidate sentences, and finally the choice of the title.

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    Authors: Adell, Nicolas;
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    HAL CY Cergy Paris Université
    Other literature type . Part of book or chapter of book . 2015
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      HAL CY Cergy Paris Université
      Other literature type . Part of book or chapter of book . 2015
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    Authors: Amoia, Marilisa;

    In this thesis, I investigate how lexical resources based on the organisation of lexical knowledge in classes which share common (syntactic, semantic, etc.) features support natural language processing and in particular symbolic recognition of textual entailment. First, I present a robust and wide coverage approach to lexico-structural verb paraphrase recognition based on Levin's (1993) classification of English verbs. Then, I show that by extending Levin's framework to general inference patterns, a classification of English adjectives can be obtained that compared with previous approaches, provides a more fine grained semantic characterisation of their inferential properties. Further, I develop a compositional semantic framework to assign a semantic representation to adjectives based on an ontologically promiscuous approach (Hobbs, 1985) and thereby supporting first order inference for all types of adjectives including extensional ones. Finally, I present a test suite for adjectival inference I developed as a resource for the evaluation of computational systems handling natural language inference. In der vorliegenden Dissertation habe ich untersucht, wie lexikalische Ressourcen, die auf der Gliederung lexikalischen Wissens in Klassen mit gemeinsamen Eigenschaften (lexikalische, semantische etc,) basieren, die computergestützte Verarbeitung natürlicher Sprache und insbesondere die symbolische Erkennung von Entailment unterstützen. Basierend auf Levins (1993) Klassifikation englischer Verben, wurde zuerst ein robuster, für die Verarbeitung beliebiger Texte geeigneter Ansatz zur Paraphrasenerkennung vorgestellt. Dann habe ich aufgezeigt, dass man durch eine Erweiterung von Levins Systematik zur Behandlung allgemeiner Inferenzmuster, eine Klassifikation von englischen Adjektiven erhält, die verglichen mit früheren Ansätzen, eine feinkörnige semantische Charakterisierung ihrer inferentiellen Eigenschaften gestattet und so die Basis für die computergestützte Behandlung von Inferenz bei Adjektiven bildet. Ein anderes beachtliches Ergebnis der vorliegenden Arbeit ist die Test Suite, die ich entwickelt habe und die als Ressource für NPL Anwendungen, die Inferenzen (insbesondere Inferenzen bei Adjektiven) behandeln, genutzt werden kann. Durch die Konstruktion dieser Test Suite beabsichtige ich, den Weg für die Schaffung von Ressourcen zu ebnen, die einen tieferen Einblick in die für Inferenz verantwortlichen Phänomene ermöglichen.

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    https://doi.org/10.22028/d291-...
    Doctoral thesis . 2009
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    Authors: Munch, Damien; Dessalles, Jean-Louis;

    International audience; Current models of temporality in language are either inaccurate or too complex to be cognitively plausible. We present a cognitive model of the computation of aspect in French. Our approach emphasizes the importance of minimalism for cognitive plausibility: structures and computation are kept simple and combinatorial explosion is avoided. Though the model and its current implementation remain partial for now, our approach opens the way to a generic and cognitively plausible method for the determination of aspect.

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    Other literature type . 2012
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Shang, Guokan;

    Grâce aux progrès impressionnants qui ont été réalisés dans la transcription du langage parlé, il est de plus en plus possible d'exploiter les données transcrites pour des tâches qui requièrent la compréhension de ce que l'on dit dans une conversation. Le travail présenté dans cette thèse, réalisé dans le cadre d'un projet consacré au développement d'un assistant de réunion, contribue aux efforts en cours pour apprendre aux machines à comprendre les dialogues des réunions multipartites. Nous nous sommes concentrés sur le défi de générer automatiquement les résumés abstractifs de réunion.Nous présentons tout d'abord nos résultats sur le Résumé Abstractif de Réunion (RAR), qui consiste à prendre une transcription de réunion comme entrée et à produire un résumé abstractif comme sortie. Nous introduisons une approche entièrement non-supervisée pour cette tâche, basée sur la compression multi-phrases et la maximisation sous-modulaire budgétisée. Nous tirons également parti des progrès récents en vecteurs de mots et dégénérescence de graphes appliqués au TAL, afin de prendre en compte les connaissances sémantiques extérieures et de concevoir de nouvelles mesures de diversité et d'informativité.Ensuite, nous discutons de notre travail sur la Classification en Actes de Dialogue (CAD), dont le but est d'attribuer à chaque énoncé d'un discours une étiquette qui représente son intention communicative. La CAD produit des annotations qui sont utiles pour une grande variété de tâches, y compris le RAR. Nous proposons une couche neuronale modifiée de Champ Aléatoire Conditionnel (CAC) qui prend en compte non seulement la séquence des énoncés dans un discours, mais aussi les informations sur les locuteurs et en particulier, s'il y a eu un changement de locuteur d'un énoncé à l'autre.La troisième partie de la thèse porte sur la Détection de Communauté Abstractive (DCA), une sous-tâche du RAR, dans laquelle les énoncés d'une conversation sont regroupés selon qu'ils peuvent être résumés conjointement par une phrase abstractive commune. Nous proposons une nouvelle approche de la DCA dans laquelle nous introduisons d'abord un encodeur neuronal contextuel d'énoncé qui comporte trois types de mécanismes d'auto-attention, puis nous l'entraînons en utilisant les méta-architectures siamoise et triplette basées sur l'énergie. Nous proposons en outre une méthode d'échantillonnage générale qui permet à l'architecture triplette de capturer des motifs subtils (p. ex., des groupes qui se chevauchent et s'emboîtent). With the impressive progress that has been made in transcribing spoken language, it is becoming increasingly possible to exploit transcribed data for tasks that require comprehension of what is said in a conversation. The work in this dissertation, carried out in the context of a project devoted to the development of a meeting assistant, contributes to ongoing efforts to teach machines to understand multi-party meeting speech. We have focused on the challenge of automatically generating abstractive meeting summaries.We first present our results on Abstractive Meeting Summarization (AMS), which aims to take a meeting transcription as input and produce an abstractive summary as output. We introduce a fully unsupervised framework for this task based on multi-sentence compression and budgeted submodular maximization. We also leverage recent advances in word embeddings and graph degeneracy applied to NLP, to take exterior semantic knowledge into account and to design custom diversity and informativeness measures.Next, we discuss our work on Dialogue Act Classification (DAC), whose goal is to assign each utterance in a discourse a label that represents its communicative intention. DAC yields annotations that are useful for a wide variety of tasks, including AMS. We propose a modified neural Conditional Random Field (CRF) layer that takes into account not only the sequence of utterances in a discourse, but also speaker information and in particular, whether there has been a change of speaker from one utterance to the next.The third part of the dissertation focuses on Abstractive Community Detection (ACD), a sub-task of AMS, in which utterances in a conversation are grouped according to whether they can be jointly summarized by a common abstractive sentence. We provide a novel approach to ACD in which we first introduce a neural contextual utterance encoder featuring three types of self-attention mechanisms and then train it using the siamese and triplet energy-based meta-architectures. We further propose a general sampling scheme that enables the triplet architecture to capture subtle patterns (e.g., overlapping and nested clusters).

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    Other literature type . 2021
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    Doctoral thesis . 2021
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    Authors: Winston, Cynthia; Winston, Michael; Boyd, Alexis;

    More than ever before in human history, rapid increases in innovation and discovery are critical to solving the world’s most pressing economic, climate, health, and human problems. Although women in the United States are earning more doctoral degrees in science and engineering fields than ever before, less then 24% of the science and engineering workforce includes women (U.S. Department of Commerce, 2011). While in the last decade there has been an increase in national programs to recruit more women in science careers, women of color have largely been excluded and often are not specified in federal statistics on the science workforce (Mack, Rankins, & Winston, 2011). Moreover, among those programs that do exist, few adopt a synergistic psychologically grounded approach to sustained and culturally responsive professional development for women of color. The lives of women of color demand complex psychological negotiation and strategic life management of simultaneous experiences of racism, sexism, classism, and unique cultural imperatives (Cole, 2009). Thus, not only is getting them into the science workforce important, it is critical to generate scholarship guided by intersectionality theoretical frameworks that can inform the design of mechanisms for their retention, leadership training, and acquisition of knowledge and skills to sustain a healthy career and family life balance. Historical and biographical studies of women of color in science do not generally make reference to the history of White women in science in the United States. This neglect tends to underestimate the effect of gender per se on access to science education and careers in science. These biographical accounts focus principally on individuals with no attempt to identify systems of exclusion or patterns of success in overcoming exclusion. While the narratives about individual careers have real importance as documentation, those accounts by themselves cannot disclose the ways in which the social system and the educational matrix functioned to produce the result that few women of any race and ethnicity became scientists in one period of history. This paper demonstrates the theoretical and practical utility of the integration of narratives of the experiences of both white and women of color in science with systems level historical analysis of institutionalized gender prejudice in all women gaining access to science education and scientific careers. Vers Une Compréhension Accrue des Expériences Vécues par les Femmes de Couleur en matière de formation et de carrières scientifiques : Quelle est l’Utilité de l’Intégration des Récits d’ Expériences Diverses dans l’Analyse Historique des En général, les études historiques et biographiques des femmes de couleur dans le domaine des sciences ne font pas référence à l’histoire des femmes Blanches dans le domaine des sciences aux Etats-Unis. Cette lacune a souvent pour effet de sous-estimer l’ impacte du genre sur l’accès à l’enseignement des sciences et aux carrières scientifiques. Les biographies mettent principalement l’accent sur les individus et ne tentent pas d’identifier les systèmes d’exclusion ou les modèles de succès dans la lutte contre l’exclusion. Tandis que les récits portant sur des carrières individuelles ont une importance réelle en tant que documents, ces récits en tant que tels ne peuvent pas révéler comment le système social et la matrice de l’éducation ont fonctionné pour ne produire que peu de femmes de science, toutes races et ethnies confondues, durant une période donnée de l’histoire. Cet article démontre l’utilité théorique et pratique d’intégrer les récits des expériences des femmes de science tant blanches que de couleur dans l’analyse historique du préjugé sexiste institutionnalisé auquel les femmes sont confrontées lorsqu’elles poursuivent un cursus et une carrière scientifiques. Plus que jamais dans l‘histoire humaine, l’augmentation rapide de l’innovation et des découvertes est cruciale pour résoudre les problèmes économiques, climatiques, sanitaires, et humains les plus urgents du monde. Bien que les femmes aux Etats-Unis obtiennent davantage de doctorats en science et en ingénierie que jamais auparavant, elles ne constituent néanmoins que moins de 24% des salariés employés dans les domaines de la science et de l’ingénierie (Département Américain du Commerce, 2011).

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    Other literature type . 2014
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    Authors: Simon Chane, Camille, Simon;

    Cette thèse s'intéresse au recalage de données issues de capteurs 3D et multispectraux pour l'étude du patrimoine.Lorsque l'on étudie ce type d'objet, il y a souvent peu de points saillants naturels entre ces jeux de données complémentaires. Par ailleurs, l'utilisation de mires optiques est proscrite.Notre problème est donc de recaler des données multimodales sans points caractéristiques.Nous avons développé une méthode de recalage basé sur le suivi des systèmes d'acquisition en utilisant des techniques issues de la photogrammétrie.Des simulations nous ont permis d'évaluer la précision de la méthode dans trois configurations qui représentent des cas typiques dans l'étude d'objets du patrimoine.Ces simulations ont montré que l'on peut atteindre une précision du suivi de 0.020 mm spatialement et 0.100 mrad angulairement en utilisant quatre caméras 5 Mpx lorsque l'on numérise une zone de 400 mm x 700 mm.La précision finale du recalage repose sur le succès d'une série de calibrations optiques et géométriques, ainsi que sur leur stabilité pour la durée du processus d'acquisition.Plusieurs tests ont permis d'évaluer la précision du suivi et du recalage de plusieurs jeux de données indépendants; d'abord seulement 3D, puis 3D et multispecrales.Enfin, nous avons étendu notre méthode d'estimation de la réflectance à partir des données multispectrales lorsque celles-ci sont recalées sur un modèle 3D. The concern and interest of this PhD thesis is the registration of featureless 3D and multispectral datasets describing cultural heritage objects.In this context, there are few natural salient features between the complementary datasets, and the use of targets is generally proscribed.We thus develop a technique based on the photogrammetric tracking of the acquisition systems in use.A series of simulations was performed to evaluate the accuracy of our method in three configurations chosen to represent a variety of cultural heritage objects.These simulations show that we can achieve a spatial tracking accuracy of 0.020 mm and an angular accuracy of 0.100 mrad using four 5 Mpx cameras when digitizing an area of 400 mm x 700 mm. The accuracy of the final registration relies on the success of a series of optical and geometrical calibrations and their stability for the duration of the full acquisition process.The accuracy of the tracking and registration was extensively tested in laboratory settings. We first evaluated the potential for multiview 3D registration. Then, the method was used for to project of multispectral images on 3D models.Finally, we used the registered data to improve the reflectance estimation from the multispectral datasets

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    Authors: Grandjean, Martin;

    International audience

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    Authors: Drap, Pierre; Durand, Anne; Nedir, Malika; Seinturier, Julien; +9 Authors

    The paper presents an interdisciplinary project which is the first step towards a 3D Geographical Information System (GIS) dedicated to Cultural Heritage with a specific focus application on the Castle of Shawbak, also known as the ”Crac de Montral” in Jordan. The project continues to grow thanks to a synergy between a set of laboratories: The LSIS laboratory, France in charge of the pho- togrammetric survey phase connected with the knowledge based approach; ITABC, CNR lab in Roma, Italy in charge of the topometric survey, with DGPS and aerial photography with gas balloon, National Institute of Information and Communications Technology, Kyoto, Japan for the 3D view point seek connected to the database, the image processing aspect managed by Stratos documentation, SimVis from The Department of Computer Science, University of Hull, UK, for the virtual reality aspect and of course the Dipartimento di Studi storici e Geografici from the University of Florence, Italy, in charge of the archaeological part. Our project focuses on a building scale encompassing its atomic elements such as ashlars blocks, cement, stratigraphic units and archi- tectonic elements. At this scale we need a full 3D interface in order to manage accurate measurements, a huge quantity of observations and a mainly heterogeneous archaeological documentation. This project described in this paper is work in progress. After four photogrammetric campaigns in Jordan the first results are available on the project web site: http://www.shawbak.net

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    Authors: Barret, Sébastien; Helias-Baron, Marlène; Stutzmann, Dominique; Tscherne, Niklas; +2 Authors

    The poster will present the project "Between Composition and Reception: the Authority of Medieval Charters" and discuss what role machine learning methods can have for the human interpretation of late medieval charters as means to convey authority, esp. regarding their graphical aspects

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