|
|
|
Conférences
Pr Mohamed BERGHOUT Département de Mathématiques et Informatique Faculté des Sciences Ben M'Sick Université Hassan II de Casablanca Densité, traces et comportement à la frontière dans les espaces de Sobolev à exposant variable En utilisant la théorie des espaces modulaires et la théorie non linéaire du potentiel, nous donnons une analyse fine des espaces de Sobolev à exposant variable
Pr Abdoul Salam Diallo Université Alioune Diop Théorie globale des courbes planes fermées
Pr Ahmed ASIMI Département de Mathématiques et Informatique Faculté des Sciences Agadir Université Ibn Zohr Agadir Intelligent Education: Cloud Architecture of Soft Skills based on Deep Reinforcement Learning Nowadays, Soft skills remain a very important area for the development and the construction of society which represents a fundamental challenge for universities. They mainly aim to become an organization capable of providing human capital for the development of countries either at the level of research or creation, especially in the field of industry. In this sense, universities should have academic, relevant, adequate, practical and appropriate programs which facilitate students' access to the world of work which requires a high level of soft skills; namely, critical thinking, problem solving, leadership, professionalism / work ethic, teamwork / collaboration and adaptability / flexibility. Our objective in this conference is to provide a supervised, iterative and intra-recursive architecture in terms of learning loops, and multi-hybrid in terms of deployment. Its aim is to complete the spirit of self-training of the learner based on beneficial analysis and detection, improvement and development of its technical and non-technical skills, regardless of physical constraints (handicap or different learning styles), called Soft Skills Cloud Architecture based on Deep Reinforcement Learning "ACSS". It is defined by sex main phases. 1) Initialing phase, 2) Planning or creation phase of a reference basis which makes it possible to define the most important skills demanded in the job market, 3) Skills detection phase, 4) Skills classification phase, 5) Decision phase and 6) Implementation phase. In addition, our diagram presents a supervised orientation process in which the learner can, in each phase, consult the different means and methods of improvement, thus, it offers the advantage of self-evolution.
|
