The purpose of this paper is to ensure power efficiency in wireless sensor networks (WSNs) through a new framework-oriented middleware, based on a biologically inspired mechanism that uses an evolutionary multi-objective optimization algorithm. The authors call this middleware framework multi-objective optimization for wireless sensor networks (MONet).

Motion detection is a live issue. Moving objects are an important clue for smart video surveillance systems. In this work we try to detect the motion in video surveillance systems. The aim of our work is to propose solutions for the automatic detection of moving objects in real time with a surveillance camera. We are interested by objects that have some geometric shape (circle, ellipse, square, and rectangle). Proposed approaches are based on background subtraction and edge detection. Proposed algorithms mainly consist of three steps: edge detection, extracting objects with some geometric shapes and motion detection of extracted objects.

Reduction of the Total Harmonic Distortion (THD) in multilevel inverters requires resolution of complex nonlinear transcendental equations; in this paper we propose a combination of one of the best existing optimized hardware structures with the recent firefly algorithm, which was used to optimize the THD, through finding the best switching angles and guaranteeing the minimization of harmonics within a user defined bandwidth. The obtained THD through the simulation of the thirteen-level symmetric inverter has been reduced down to 5% (FFT of 60 harmonics). In order to validate the simulation results, a thirteen-level symmetric inverter prototype has been made, and practically experimented and tested with different loads. Consequently, the measured THD with resistive load was 4.7% on a bandwidth of 3 kHz. The main advantage of the achieved work is the reduction of the THD.

In this paper, Multi-depot Fleet Size Mix Vehicle Routing Problem with time window (MD-FSMVRP-TW) is presented as a multi-criteria optimization problem. For this purpose, we propose in this study a decision support system which aims to discover a set of satisfying solutions (routes) minimizing total travel distance, total tardiness time and the total number of vehicles. These routes satisfy transportation requests without contravening any of the instance specific constraints: schedules requests from clients, the heterogeneous capacity of vehicles. The new encoding and structure algorithm on which this contribution is based uses a genetic algorithm, a selection process using ranking with several Pareto fronts and an elitist selection strategy for replacement. Computational experiments with the benchmark test instances confirm that our approach produces acceptable quality solutions compared with previous results in similar problems in terms of generated solutions and processing time. Experimental results prove that the method of genetic algorithm heuristics is effective in solving the MD-FSMVRP-TW problem and hence has a great potential.

Providing quality of service (QoS) for real-time multimedia applications such as video streaming in mobile ad hoc networks (MANETs) is an important challenge. MANETs are characterized by lack of fixed infrastructure, dynamic topology, and limited resources that make more difficult multimedia applications transport and run on this networks. To overcome this challenge, video coding techniques combined to multiple routing paths (multipath) is a promising technique for supporting transmission of multiple video streams with appropriate QoS over mobile ad hoc networks. In this paper, firstly, many issues and different techniques for video streaming over MANET have been reviewed and secondly two multi paths routing protocols (M-AODV and MDSDV) have been evaluated in order to improve QoS for real-time multimedia applications. Results show that none of these two protocols is better than the other. In certain situations (throughput and load network with high mobility) is M-AODV but in others (network load and reliability for large-scale network) is MDSDV protocol which displays good performance. It is also noted that these two protocols provide between acceptable and good quality and a small jitter regardless of nodes number in medium mobility.

Modeling and design of rectangular microstrip patch printed on isotropic or anisotropic substrate are accomplished in this paper. The use of spectral domain method in conjunction with artificial neural networks (ANNs) to compute the resonant characteristics of rectangular microstrip patch printed on isotropic or anisotropic substrates. The moment method implemented in the spectral domain offers good accurateness, but its computational cost is high owing to the evaluation of the slowly decaying integrals and the iterative nature of the solution process. The paper introduces the electromagnetic knowledge combined with ANN in the analysis of rectangular microstrip antenna on uniaxially anisotropic substrate to reduce the complexity of the spectral domain method and to minimize the CPU time necessary to obtain the numerical results. The numerical comparison between neurospectral and conventional moment methods shows significant improvements in time convergence and computational cost. Hence, the use of neurospectral approach presented here as a promising fast technique in the design of microstrip antennas.    

During the last years, in industrial process control, requirements for Continuous Emission Monitoring (CEM) have increased significantly. Most plants are investing in CEM systems in order to burn waste, obtain ISO 14000 and 18001 certification to protect operator’s life. In this work, our approach describes development of a novel internet and fuzzy-based CEM system(IFCEMS). This system contains operator’s stations for the bag filter’s automation system and monitored using Internet. The object of the present installation consists of a suction ventilator, a bag filter and a system for collecting and evacuating the dust. To optimize the running of the bag filter workshop and ensure continuous control, the process based on one of the most powerful Artificial Intelligence techniques which is fuzzy logic involves the removal or filtration of smoke from the kiln and/or cement mill with control of temperature and pressure of the fumes