sentential negation in moroccan arabic

In this thesis I analyze the distribution of negative markers in sentential negation in Moroccan Arabic . Moroccan Arabic uses two negative markers to denote sentential negation: one in a preverbal position-ma, and another one following the verb-sh. I propose a structure based on the assumption that Moroccan Arabic has two NegPs. The lower NegP hosts ma in its Spec and the higher NegP is the position where sh moves. Moreover, I propose that ma is a clitic that left adjoins to the verb once the verb is in a c-commanding position (following Boˇskovi´c’s 2002 view on clitics). This analysis is successful at accounting for the distribution of negative markers in verbal and verbless sentences, and also at solving the problems exhibited by the previous analyses of bipartite negation (Pollock 1989, Rowlett 1998, Benmamoun 1997, Bell 2004). Furthermore, the same structure also accounts for the syntax of negative sentences containing N-words, under the assumption that sh and N-words cannot co-occur because they compete for the same position, namely the spec of the higher NegP. Finally, to account for the syntax of negative sentences that carry metalinguistic negation, I propose that the negators are in the CP field, rather than within the TP (following Martins’s 2014 view on metalinguistic negation in European Portuguese). This analysis is successful at accounting for the distribution of metalinguistic negators in both verbal and verbless sentences

Stage III en laboratoire au 1er cycle

Slime, T. (2010). Stage III en laboratoire au 1er cycle. http://hdl.handle.net/10251/8761.Archivo delegad

Nature, stockage et traitements des Big Data dans le domaine de la santé

International audienceActuellement, le traitement et l'analyse des big data dans les différents secteurs et domaines constitue un avantage majeur pour leurs développement et amélioration, notamment, le domaine de la santé pour lequel les études et recherches ont montré l'utilité et la grande valeur ajoutée des big data. En effet, l'exploitation des données massives du secteur médical ainsi que l'utilisation des algorithmes de machines Learning ont permis d'améliorer la qualité des services de soins et d'augmenter la précision des traitements médicaux et ils ont donné aussi la possibilité de prédire l'état de santé des patients. Dans notre article nous allons tout d'abord définir et préciser la notion des big data dans le domaine de santé, puis nous allons mettre le point sur les différents types de bases de données utilisées pour le stockage et le traitement des données tout en citant les avantages et inconvénients de chaque type. Nous allons par la suite étudier les techniques et algorithmes de classifications qui permettent le classement et la catégorisation des données médicales. Après, nous allons décrire les architectures big data qui ont été utilisés dans le secteur de santé, et nous allons conclure avec les challenges et les défis rencontrés

Exploring the Benefits of Representing Multiplayer Game Data in a Coordinate System

In the realm of game theory, a range of mathematical approaches exists for the representation of game data, with the extensive form (depicted as a game tree) and the normal form (illustrated as a payoff matrix) standing out as the most prevalent. However, a significant drawback associated with these approaches is their limited scalability. As the number of players or their strategic options increases, these techniques progressively lose their feasibility and become less practical for meaningful analysis. The present work proposes an alternative approach that significantly enhances the representation of data in two- or three-player games. Within this framework, the conventional payoff matrix is substituted with a payoff coordinate system, employing a coordinate plane for two-player games and a coordinate space for three-player games. This approach offers numerous advantages when compared to other methods. For instance, the Nash equilibrium can be readily identified within a game without requiring an extensive duration to exhaustively examine all strategies for its determination. By employing this approach, the representation of game data becomes more convenient and efficient, making it easier to analyze and comprehend the underlying strategies employed by players