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A Proton Exchange Membrane Fuel Cell (PEMFC) powered Hybrid Electric System (HES) is one of an appreciating research issue for the future due to its high efficiency and capability to use hydrogen as a fuel. The PEMFC cannot sufficiently meet sustained load demands in some cases. For that, to compensate this problem incorporating the slow transient response of the PEMFC, Ultra-capacitors (UCaps) are potential candidates for a solution in this aspect. An adequate Energy management System (EMS) is one essential objective of the researches in this area. Hence, this paper proposed an efficient dynamic model using an energy storage system with the sufficient power capacity to keep the smooth operation of the system. To satisfy the load requirements and optimize the active power flow between hybrid power sources for different modes, the EMS was proposed. This latter was appreciated for its capacity to serve the required power through effective utilization of the PEMFC and UCap. To maximize the system efficiency, the functioning of the system is depending on the decision making and the control of all the system component states. The HES and the control approach are made using Matlab/Simulink environment, from which, the obtained results indicate the reliability and the effectiveness desirability of the HES and its proposed energy management strategy.

Real-time simulation test beds for new zero-emission hybrid electric vehicles are considered as an attractive challenge for future transport applications that are fully recommended in the laboratory environment. In contrast, new zero-emission hybrid electric vehicles have a more complicated charging procedure. For this reason, an efficient simulation tools development for hydrogen consumption control becomes critical. In this vein, a New Zero Emission Hybrid Electric Vehicle Simulation (NZE-HEVSim) tool for the dynamic Fuel Cell Hybrid-Electric System is proposed to smartly control multisource activities. The designed system consists of a proton-exchange membrane fuel cell used to provide the required energy demand and a Supercapacitor system for energy recovery assistance in load peak or in fast transient. To regulate the supplied power, an efficient Real-Time Embedded Intelligent Energy Management (RT-EM-IEM) is implemented and tested through various constraints. The proposed intelligent energy management system aims to act quickly against sudden circumstances related to hydrogen depletion in the basis required fuel consumption prediction using multi-agent system (MAS). The proposed MAS strategy aims to define the proper operating agent according to energy demand and supply. The obtained results prove that the designed system meets the objectives set for RT-EM-IEM by referring to an experimental velocity database.

Nowadays, the diseases of the voice increase because of bad social habits and the misuse of voice. These pathologies should be treated from the beginning. Indeed, it is no longer necessary that the diseases of the voice lead to affect the quality of the voice as heard by a listener. The most useful tool for diagnosing such diseases is the Acoustic analysis. We present in this work, new expression parameters in order to clarify the description of the vocal signal. These parameters help to classify the unhealthy voices. They describes essentially the fundamental frequency F0, the Harmonics-to-Noise report HNR, the report Noise to Harmonics Ratio NHR and Detrended Fluctuation Analysis (DFA). The classification is performed on two Saarbruecken Voice and MEEI pathological databases using HTK classifiers. We can classify them into two different type: the first classification is binary which is used for the normal and pathological voices, the second one is called a four-category classification used in spasmodic, polyp, nodule and normal female voices and male speakers. And we studied the effects of these new parameters when combined with the MFCC, Delta, Delta second and Energy coefficients.

Hybrid Electrical System (HES), combined various promising devices like a Fuel Cell, a battery and a supercapacitor, is an attractive issue. This system was qualified by its high efficiency for electrical vehicle applications. For that, this article aims to analyze and to evaluate the system performance. A Multi-Input-Multi-Output state space model for PEMFC, Supercapacitor and battery have been established and detailed. To control the load demand and to investigate sources of supply, a precise power management unit (PMU) was discussed and evaluated for the hydrogen fuel consumption and the Battery / Super-capacitor state fluctuations. The simulation results can greatly confirm the system performance using Matlab/Simulink environment.

Renewable Energy system (such as: Wind Turbine (WT)) provides a dispatching power and large-scale energy recovery. This latter is a suitable technology in Grid power systems due to its high variability and high levels of renewable generation. A variable Speed WT is one essential objective of the researches in this area. Hence, this paper proposed and discusses an efficient design based on a Higher Order Sliding Mode Control (HOSMC) applied to Permanent Magnet Synchronous Generator (PMSG). The HOSMC can provide a feedback linearization controller utilizes the torque estimate to ensure a torque reference. The HOSMC feedback provides the relationship between the turbine speed and an additional input. To achieve a stable error dynamics and speed tracking, a linear control theory is proposed. The applied speed reference is selected according to a classical MPPT algorithm. The reliability and the effectiveness of the proposed design is given by the Matlab / Simulink environment, from which, the obtained results have been treated and discussed in details.

Effective data transmission in sensor networksis a crucial problematic on routing researches. Hence, thispaper proposes an adaptive routing algorithm called Multi-KG based on clustering. The main contributions consist in theintegration of an improved unsupervised algorithm of the Kmeanson clusters and the use of the Gaussian eliminationalgorithm for choosing Cluster Heads (CH). To route datato the base station, a multi-hop communication Inter-CHs isadopted. In this manner, balanced-energy clusters are createdand distributed energy consumption is guaranteed. Simulationsin a wireless sensor network show that the new approachgreatly reduces computation time thanks to K-means andminimizes energy consumption thanks to Gauss. It shouldbe mentioned that 'Multi-KG' gives better results becauseit prolongs the lifetime of CHs nodes and consequently thenetwork lifetime by adopting an inter-cluster communicationand intra-cluster in a multi-Hop.

This paper proposes a new adaptive speech compression system based on discrete wave atoms transform. First, the signal is decomposed on wave atoms, then wave atom coefficients are truncated using a new adaptive thresholding which depends on the SNR estimation. The thresholded coefficients are quantized using Max Lloyd scalar quantizer. Besides, they are encoded using zero run length encoding followed by Huffman coding. Numerous simulations are performed to prove the robustness of our approach. The results of current work are compared with wavelet based compression by using objective criteria, namely CR, SNR, PSNR and NRMSE. This study shows that the wave atoms transform is more appropriate than wavelets transform since it offers a higher compression ratio and a better speech quality.