L’influence De La Professionnalisation De La GRH Sur La Valorisation Du Métier De L’enseignant- Chercheur : Le Rôle De L’approche Compétence, Cas Des Enseignants Des Grandes Écoles Revue De Littérature Et Essai De Proposition D’un Cadre Conceptuel

Teaching in universities is currently the main subject of this study, whereby the notions of professionalization and academic pedagogy is considered. The desire to promote the profession of university professor is remarkable as it comes against logics of recognition that are not very compatible. For this reason, particular attention must be paid to the human resource management policy concerning university professors in all aspects of their professional life: their careers, their training needs, their working conditions, and so on. It must also be thought out and focused on results and competitiveness, particularly with regard to the attractiveness and management of positions. This is with a view to ensure better professionalization of the public it trains. The originality of this paper lies in proposing a conceptual framework of reflection and analysis. It aims to understand to what extent the valorization of the profession depends on the professionalization of the HR practices through the setting up of a true competency approach. This approach aims at defining the skills profile of the Moroccan university professors who will serve to better guide and professionalize human resources management activities. Also, the study aims to replace pedagogy as the fundamental competence of the profile of university professor at the heart of the teaching-learning processes of the Moroccan higher education schools

Algebraic treatment of the confluent Natanzon potentials

Using the so(2,1) Lie algebra and the Baker, Campbell and Hausdorff formulas, the Green's function for the class of the confluent Natanzon potentials is constructed straightforwardly. The bound-state energy spectrum is then determined. Eventually, the three-dimensional harmonic potential, the three-dimensional Coulomb potential and the Morse potential may all be considered as particular cases.Comment: 9 page

Combinaison de codeurs par algorithme génétique : Application à la vérification du locuteur

Le domaine de la vérification du locuteur regroupe les applications pour lesquelles on désire identifier l'identité d'une personne à partir de sa voix. Le champ d'application couvre de nombreux secteurs tels que l'accès sécurisé, les transactions téléphoniques, la surveillance, l'indexation audio ou encore l'expertise judiciaire. Notre étude porte sur l'étape d'extraction de caractéristiques du système de reconnaissance du locuteur. Ce module a pour fonction d'extraire du signal de parole les informations pertinentes du point de vue de la discrimination inter-locuteur. Nous proposons dans cet article d'utiliser un algorithme génétique pour optimiser un système d'extraction de caractéristiques adapté à la reconnaissance du locuteur. La méthode proposée permet d'obtenir une amélioration significative du taux de reconnaissance sur la base Nist SRE 2005

Kernelized dense layers for facial expression recognition

Fully connected layer is an essential component of Convolutional Neural Networks (CNNs), which demonstrates its efficiency in computer vision tasks. The CNN process usually starts with convolution and pooling layers that first break down the input images into features, and then analyze them independently. The result of this process feeds into a fully connected neural network structure which drives the final classification decision. In this paper, we propose a Kernelized Dense Layer (KDL) which captures higher order feature interactions instead of conventional linear relations. We apply this method to Facial Expression Recognition (FER) and evaluate its performance on RAF, FER2013 and ExpW datasets. The experimental results demonstrate the benefits of such layer and show that our model achieves competitive results with respect to the state-of-the-art approaches

3D wedge filling and 2D random-bond wetting

Fluids adsorbed in 3D wedges are shown to exhibit two types of continuous interfacial unbinding corresponding to critical and tricritical filling respectively. Analytic solution of an effective interfacial model based on the transfer-matrix formalism allows us to obtain the asymptotic probability distribution functions for the interfacial height when criticality and tricriticality are approached. Generalised random walk arguments show that, for systems with short-ranged forces, the critical singularities at these transitions are related to 2D complete and critical wetting with random bond disorder respectively.Comment: 7 pages, 3 figures, accepted for publication in Europhysics Letter

Fully Automatic Analysis of Engagement and Its Relationship to Personality in Human-Robot Interactions

Engagement is crucial to designing intelligent systems that can adapt to the characteristics of their users. This paper focuses on automatic analysis and classification of engagement based on humans’ and robot’s personality profiles in a triadic human-human-robot interaction setting. More explicitly, we present a study that involves two participants interacting with a humanoid robot, and investigate how participants’ personalities can be used together with the robot’s personality to predict the engagement state of each participant. The fully automatic system is firstly trained to predict the Big Five personality traits of each participant by extracting individual and interpersonal features from their nonverbal behavioural cues. Secondly, the output of the personality prediction system is used as an input to the engagement classification system. Thirdly, we focus on the concept of “group engagement”, which we define as the collective engagement of the participants with the robot, and analyse the impact of similar and dissimilar personalities on the engagement classification. Our experimental results show that (i) using the automatically predicted personality labels for engagement classification yields an F-measure on par with using the manually annotated personality labels, demonstrating the effectiveness of the automatic personality prediction module proposed; (ii) using the individual and interpersonal features without utilising personality information is not sufficient for engagement classification, instead incorporating the participants’ and robot’s personalities with individual/interpersonal features increases engagement classification performance; and (iii) the best classification performance is achieved when the participants and the robot are extroverted, while the worst results are obtained when all are introverted.This work was performed within the Labex SMART project (ANR-11-LABX-65) supported by French state funds managed by the ANR within the Investissements d’Avenir programme under reference ANR-11-IDEX-0004-02. The work of Oya Celiktutan and Hatice Gunes is also funded by the EPSRC under its IDEAS Factory Sandpits call on Digital Personhood (Grant Ref.: EP/L00416X/1).This is the author accepted manuscript. The final version is available from Institute of Electrical and Electronics Engineers via http://dx.doi.org/10.1109/ACCESS.2016.261452

Assessment of dysarthric speech through rhythm metrics

AbstractThis paper reports the results of acoustic investigation based on rhythmic classifications of speech from duration measurements carried out to distinguish dysarthric speech from healthy speech. The Nemours database of American dysarthric speakers is used throughout experiments conducted for this study. The speakers are eleven young adult males with dysarthria caused by cerebral palsy (CP) or head trauma (HT) and one non-dysarthric adult male. Eight different sentences for each speaker were segmented manually to vocalic and intervocalic segmentation (176 sentences). Seventy-four different sentences for each speaker were automatically segmented to voiced and non-voiced intervals (1628 sentences). A two-parameters classification related to rhythm metrics was used to determine the most relevant measures investigated through bi-dimensional representations. Results show the relevance of rhythm metrics to distinguish healthy speech from dysarthrias and to discriminate the levels of dysarthria severity. The majority of parameters was more than 54% successful in classifying speech into its appropriate group (90% for the dysarthric patient classification in the feature space (%V, ΔV)). The results were not significant for voiced and unvoiced intervals relatively to the vocalic and intervocalic intervals (the highest recognition rates were: 62.98 and 90.30% for dysarthric patient and healthy control classification respectively in the feature space (ΔDNV, %DV))