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Professionnalisation : une entrée pour comprendre l'expérience infirmière en psychiatrie
No full textConférence à la 5ème journée régionale du tutorat en psychiatrie. "Quelles expériences pour quelle professionnalisation ?"International audienc
PALEONTOLOGIE, SCIENCE DU FUTUR
No full textArticle paru dans Pop-en-Stock dossier Dinosaures et dinomaniaques dirigé par Matthieu Freyhei
Le symbole est-il diabolique? Duplicité(s) du signe en question
No full textThe linguistic sign, traditionally conceived as a symbol (from the Greek sym + bole “to put two sides together”), might it not also be diabolic (from the Greek dia “to separate”)? This is the question posed by issue 2 of Signifiances (Signifying), which explores the duplicity, or more precisely, the duplicities of the sign. The works presented are from researchers with diverse theoretical backgrounds; however, the studies gathered here reveal a shared concern: the desire to question, to challenge, what is habitually considered a given. All elements of the definition of the sign as the arbitrary union of a signifier and a signified, symbolizing a segment of reality, are examined here, each article focusing more particularly on some aspect of this concept. The elements of the definition are not viewed as objects with positive existence but rather as dynamic processes (speaker experience) or as the result of viewpoints that shape linguistic entities (the linguist’s perspective), and most contributions begin with the signifier as a dynamic process.El signo lingüístico, tradicionalmente concebido como un símbolo (del griego sym + bole “poner dos caras juntas”), ¿no podría ser también diabólico (del griego dia “separar”)? Esta es la pregunta que plantea el número 2 de Signifiances (Significación), que explora la duplicidad o, más precisamente, las duplicidades del signo. Los trabajos presentados provienen de investigadores con diversos enfoques teóricos; sin embargo, los estudios aquí reunidos reflejan una preocupación compartida: la voluntad de cuestionar y desafiar lo que habitualmente se considera como dado. Todos los términos de la definición del signo como la unión arbitraria de un significante y un significado, simbolizando una porción de la realidad, son examinados aquí, y cada artículo se enfoca más particularmente en algún aspecto de esta concepción. Los elementos de la definición no se consideran como objetos con existencia positiva, sino más bien como procesos dinámicos (experiencia del hablante) o como el resultado de perspectivas que constituyen las entidades lingüísticas (la perspectiva del lingüista), y la mayoría de las contribuciones parten del significante como proceso dinámico.Le signe linguistique, traditionnellement conçu comme un symbole (du grec sym + bole ‘mettre ensemble deux faces’), ne serait-il pas diabolique (du grec dia ‘séparer’) ? Telle est la question que pose ce numéro 2 de Signifiances (Signifying), qui se penche sur la duplicité ou, plus exactement, les duplicités du signe. Les travaux présentés émanent de chercheurs d’horizons théoriques divers ; mais les études réunies ici témoignent d’une même préoccupation : la volonté de questionner, de remettre en cause, ce qui est habituellement considéré comme relevant du donné. Tous les termes de la définition du signe comme union arbitraire d’un signifiant et d’un signifié, symbolisant une portion du réel, sont ici interrogés, chaque article s’intéressant plus particulièrement à tel ou tel aspect de cette conception. Les éléments de la définition ne sont pas envisagés comme des objets ayant une existence positive mais plutôt comme des processus dynamiques (expérience du locuteur) ou comme le résultat de points de vue constitutifs des entités linguistiques (parti pris du linguiste), et la plupart des contributions ont pour point de départ le signifiant en tant que processus dynamique
Cornutus, nouveau Socrate : dangers et réactivation du dialogue moral entre maître et élève dans les satires IV et V de Perse
No full textInternational audienc
Lynn Comella, Vibrator Nation: How Feminist Sex-Toy Stores Changed the Business of Pleasure
No full textInternational audienc
Visual Program Manipulation in the Polyhedral Model
No full textInternational audienceParallelism is one of the key performance sources in modern computer systems. When heuristics-based automatic parallelization fails to improve performance, a cumbersome and error-prone manual transformation is often required. As a solution, we propose an interactive visual approach building on the polyhedral model that visualizes exact dependences and parallelism; decomposes and replays a complex automatically-computedtransformation step by step; and allows for directly manipulating the visual representation as a means of transforming the program with immediate feedback. User studies suggest that our visualization is understood by experts and non-experts alike, and that it may favor an exploratory approach
Non-rigid 3D Model Classification Using 3D Hahn Moment Convolutional Neural Networks
No full textInternational audienceIn this paper, we propose a new architecture of 3D deep neural network called 3D Hahn Moments Convolutional Neural Network (3D HMCNN) to enhance the classification accuracy and reduce the computational complexity of a 3D pattern recognition system. The proposed architecture is derived by combining the concepts of image Hahn moments and convolutional neural network (CNN), frequently utilized in pattern recognition applications. Indeed, the advantages of the moments concerning their global information coding mechanism even in lower orders, along with the high effectiveness of the CNN, are combined to make up the proposed robust network. The aim of this work is to investigate the classification capabilities of 3D HMCNN on small 3D datasets. The experiment simulations with 3D HMCNN have been performed on the articulated parts of McGill 3D shape Benchmark database and SHREC 2011 database. The obtained results show the significantly high performance in the classification rates of the proposed model and its ability to decrease the computational cost by training low number of features generated by the first 3D moments layer
