The compressed sensing (CS)

In this paper, a new genetic approach based on arithmetic crossover for solving the economic dispatch problem is proposed. Elitism, arithmetic crossover and mutation are used in the genetic algorithm to generate successive sets of possible operating policies. The proposed technique improves the quality of the solution. The new genetic approach is compared with an improved Hopfield NN approach (1") [I], a fuzzy logic controlled genetic algorithm (FLCGA) [ 21, an advance engineered-conditioning genetic approach (AECGA) [3] and an advance Hopfield NN approach (AHNN) [4].

Abstract-M-learning has enhanced the e-learning by making the learning process learner-centered. However, enforcing exam security in open environments where each student has his/her own mobile/tablet device connected to a Wi-Fi network through which it is further connected to the Internet can be one of the most challenging tasks. In such environments, students can easily exchange information over the network during exam time. This paper aims to identify various vulnerabilities that may violate exam security in mlearning environments and to design the appropriate security services and countermeasures that can be put in place to ensure exam security. It also aims to integrate the resulting secure exam system with an existing, open-source, and widely accepted Learning Management System (LMS) and its service extension to the m-learning environment, namely "the Moodbile Project".

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