The demand for electricity is increased due to the development of the industry, the electrification of transport, the rise of household demand, and the increase in demand for digitally connected devices and air conditioning systems. For that, solutions and actions should be developed for greater consumers of electricity. For instance, MG (Micro-grid) buildings are one of the main consumers of electricity, and if they are correctly constructed, controlled, and operated, a significant energy saving can be attained. As a solution, hybrid RES (renewable energy source) systems are proposed, offering the possibility for simple consumers to be producers of electricity. This hybrid system contains different renewable generators connected to energy storage systems, making it possible to locally produce a part of energy in order to minimize the consumption from the utility grid. This work gives a concise state-of-the-art overview of the main control approaches for energy management in MG systems. Principally, this study is carried out in order to define the suitable control approach for MGs for energy management in buildings. A classification of approaches is also given in order to shed more light on the need for predictive control for energy management in MGs.

Cet article traite de style d’apprentissage en tant que critère d’adaptation d’un cours en ligne. Une première étape consiste à choisir le modèle des styles d’apprentissage. La sélection de ces styles est réalisée par un questionnaire dédié. D’autre part, les activités d’apprentissage sont conçues afin de refléter les dimensions liées aux styles d’apprentissage. Enfin, la présentation de ces activités est gérée par un module d’adaptation probabiliste. En nous appuyant sur les méthodes et les techniques proposées pour la modélisation et l’adaptation, nous avons conçu un système hypermédia d’enseignement adaptatif centré sur les styles d’apprentissage. L’approche a été validée expérimentalement et les résultats obtenus sont encourageants.This article discusses learning styles as a criterion of adaptation of a course online. A first step is to choose the model of learning styles. The identification of these styles is performed by a dedicated questionnaire. On the other hand, learning activities are designed to reflect the dimensions related to learning styles. Finally, the presentation of these activities is managed by a probabilistic adaptation module. Based on the methods and techniques proposed for modeling and adaptation, we designed an adaptive hypermedia system that focuses on learning styles. The approach was validated experimentally and the results are encouraging

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Multiple sinks routing is envisioned as a possible solution to the bottleneck research problem in Wireless Sensor Networks (WSN). In addition to focusing on minimizing the energy consumption in a WSN, it is also equally important to design routing protocols that fairly and evenly distribute the network traffic; in order to prolong the network life time and improve its scalability. In this paper we present an enhancement to the GRPW algorithm for wireless sensor networks. Performance of GRPW algorithm algorithm depends heavily on single sink position , we propose a protocol called GRPW-MuS( Geographic Routing to Multiple Sinks in connected wireless sensor networks) based on Multiple Static Sinks, we modified the existing sink location privacy protection scheme by dividing nodes in the network containing multiple sink into different levels in which real packets are forwarded to sink belong to corresponding logical levels and the intermediate node generating fake packets and sending it to fake sinks. Using OMNET++ simulation and the MiXiM framework, it is shown that proposed protocol significantly improves the robustness and adapts to rapid topological changes with multiple mobile sinks, while efficiently reducing the communication overhead and the energy consumption.