Abstract: This paper presents a hybrid algorithm employed to reduce the weight of an elec-tric motor, designed for electric vehicle (EV) propulsion. The approach uses a hybridization between Cuckoo Search and CMAES to generate an initial popula-tion. Then, the population is transferred to a new procedure which adaptively switches between two search strategies, i.e. one for exploration and one for ex-ploitation. Besides the electric motor optimization, the proposed algorithm per-formance is also evaluated using the 15 functions of the CEC 2015 competition benchmark. The results reveal that the proposed approach can show a very com-petitive performance when compared with different state-of-the-art algorithms.

Abstract: Nowadays, mobile cloud applications are growing progressively. It supports both compute and data intensive application integrates with the mobile device. Many attempts have been proposed to boost the application performance and to reduce the energy power of the mobile device by offloading computational components to the cloud server. However, current research only focused on mobile run time offloading cost. On the other hand, the cloud platform offloading cost has been ignored by the literature research. In this paper, we are studying the response time minimization problem of a real time applications (i.e., augmented reality, 3D gaming, mathematical tools) by considering offloading cost from both ends such as mobile run time and cloud run time with delay constraints (transmission cost and process cost). To minimize the total offloading cost, we have developed novel hybrid run time platform framework which will improve the offloading performance. However, the real time applications must be executed within a given deadline. To solve the above problem we have proposed the Latency Aware Task Assignment (LATA) algorithm which always executes real time application within a given deadline. Performance evaluation shows our proposed framework and algorithm are improving the response time and offloading cost as compared to baseline and conventional method.

Abstract: This work presents computations of electric current distributions inside an industrial submerged arc furnace. A 3D model has been developed in ANSYS Fluent that solves Maxwell’s equations based on scalar and vector potentials approach that are treated as transport equations. In this paper, the approach is described in detail and numerical simulations are performed on an industrial three-phase sub-merged arc furnace. The current distributions within electrodes due to skin and proximity effects are presented. The results show that the proposed method adequately models these phenomena