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The energy consumption is considered to be the major challenge in wireless sensor networks. In this paper, we shed light on a new approach to overcome the energy consumption problems. The objective of this work is to integrate an improved algorithm which is the K-means to create a balanced energy on clusters and to use the Gaussian elimination algorithm during the election of cluster head that will guarantee the distribution of energy consumption. To address the problem of the optimal number of groups, we use Davies Bouldin index to increase the network lifetime. The simulation result shows that the proposed protocol extends the network lifetime compared to Leach, iMod-Leach, leach-C, and CELRP. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs) are used to retrieve information in hostile environments that are not always accessible to human beings. Once they are deployed, the sensors are considered autonomous. Their lifetime is equivalent to the lifetime of their battery. The energy factor is the center of all the concerns of the sensors: economic routing protocols, adapted wireless technology, etc. Energy costs must be minimized because energy is a key constraint in sensor networks. This paper is part of the study of the routing problem in WSNs. Indeed, the problem consists of the nodes located around the base station (BS), which transmit data to other nodes, their energy is depleted more quickly. This causes energy holes and areas called hot spot. To address this problem, we used the unequal clustering mechanism in order to solve the network hot spot problem. Clusters closer to the BS have smaller sizes than those farther from the BS to overcome the energy over-consumption around the BS. The evaluation of our solution will be carried out using the platform Omnet++/Castalia. The simulation results obtained allow a glimpse of the energy gained by the proposed protocol compared to the protocol Eeuc. Energy efficiency is achieved thanks to the use of a network management policy which enables to balance the energy levels of different nodes, consequently, extends the lifetime of the network. • The hierarchical architecture in Wireless Sensor Networks (WSN) has been widely adopted. • A new routing algorithm Multi Hop based Competition Radius is developed aiming to increase the WSN's life time. • Simulation results show that the proposed algorithm presents efficient results in terms of network lifetime, Latency and energy consumption. [ABSTRACT FROM AUTHOR]

In this paper, a speech enhancement algorithm for dual-microphone mobile phones is improved. The proposed method is based on the exploitation of the coherence function and the quadrature mirror filter banks. This latter is designed by the genetic algorithm as criteria for noise reduction. Thus, the quadrature mirror filter banks are used as a mother wavelet in the speech enhancement algorithm. The adopted algorithm benefits of non-interfering signals statistics prediction. Hence, it can be applied with two closely microphones in small cellular mobile phones. Finally, referred to the objective measures and the time domain waveforms, the proposed method proves its effectiveness in term of speech quality and intelligibility compared with other algorithms when the speech is corrupted by different noise types. [ABSTRACT FROM AUTHOR]

In this paper, a dual-microphone speech enhancement algorithm for the mobile phones is proposed. The adopted method exploits the coherence function algorithm and the Kalman filter. This algorithm has a simple implementation that does not need a prediction of interfering signals statistics. In addition, this algorithm can be used in small devices with so closely distance between the two microphones. Moreover, the use of such algorithm allows reducing multiple noise sources at many azimuths positions. Finally, the new algorithm proves its performances referring to the perceptual evaluation of speech quality and the time domain waveforms. [ABSTRACT FROM AUTHOR]

In this paper, we present an autonomous Hybrid Power system (HPS) whose main goal is to ensure the electricity production without interruption in any remote areas. To achieve this goal, the system is composed of two energy sources one, as a renewable energy, serves to primary load feeding while the other, based on hydrogen conversion, works as a backup system. Thus, the system includes two kinds of energy storage devices one is used to chemical form energy storage (H 2 gas) while the second, based on ultracapacitor storage, is dedicated to electricity power saving. The functioning of system depends on a smart energy management that is based on the decision making and the control of all the system components states to achieve a high efficiency and better performance. Hence, the reliability and the effectiveness of the proposed system are tested by Matlab/Simulink environment, from which, the obtained results have been presented and discussed in details. [ABSTRACT FROM AUTHOR]

The aim of this paper is to evaluate a novel control approach for a Hydrogen Consumption System (HCS). A Proton Exchange Membrane Fuel Cell (PEMFC) is considered as a mainly source that supplies a load. An energy flow management approach is detailed in order to satisfy the load requirements despite the absence of any other power source. Finally, an analysis of the simulation results is conducted using Matlab/Simulink software in order to verify the performance of the proposed system. [ABSTRACT FROM AUTHOR]

A dual-microphone noise reduction method is proposed in this paper. It is based on the coherence function and the bionic wavelet transform using Kalman filter. This filter is applied to the Bionic wavelet coefficients obtained through the application of the BWT to the input signal. The adopted method can treat noisy signals using two closely spaced microphones in different noise scenarios and outperforms other dual-channel speech enhancement methods referring to the perceptual evaluation of speech quality, the spectrogram analysis and the time domain waveforms. [ABSTRACT FROM AUTHOR]

In this paper, we present a Stand-alone Power system (SPS). The goal of this system is the ensuring of the electricity production without interruption in remote areas. It consists generally of a five components which are a solar energy, an energy storage that combines a water electrolyze and a storage gas tank, an energy conversion based on a proton exchange membrane fuel cell (PEMFC), an ultra-capacitor storage (UCap) and a suitable energy management unit to manage and to supervise the system operation of the hybrid system. This combination can ensure the optimal behavior of the load with the respect of the slow dynamics of the PEMFC. The integration UCap ensures the elimination of the slow dynamics of the PEMFC during the transient event. A Novel supervisory command is proposed. The modeling of the overall system is given and the obtained results are presented and discussed. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a theoretical and practical study of a single phase photovoltaic conversion system. It consists of a step down converter to charge a battery with the maximum power available from photovoltaic generator (PVG) and a single phase voltage source inverter (VSI) to produce a stable AC voltage (220V/50Hz) with lower total harmonic distortion (THD). A new perturb and observe algorithm is designed and implemented in a cheaper microcontroller PIC 16F876 where the duty cycle perturbation and the sampling period are selected to insure the stability of the PV system around the maximum power. The control strategy adopted for the inverter is the Selective Harmonic Eliminated Pulse Width Modulation (SHE PWM). The pulses are calculated and transferred on the PIC 16F876 memory. With this technique, inverter losses are decreased and the output voltage is easily filtered with a simple low pass filter producing a perfectly sine wave form voltage. The battery is sized to supply loads in non-sunny times. With optimization of its various components, the conventional single phase PV system has a low cost, high efficiency but also good power quality which represents a good opportunity to use it in many stand alone photovoltaic applications such as houses lighting. An experimental system has been made to demonstrate the efficiency of the photovoltaic system and to validate simulations done by Matlab–Simulink environment. [Copyright &y& Elsevier]

Within the medical environment, diverse techniques exist to assess the state of the voice of the patient. The inspection technique is inconvenient for a number of reasons, such as its high cost, the duration of the inspection, and above all, the fact that it is an invasive technique. This study focuses on a robust, rapid and accurate system for automatic identification of pathological voices. This system employs non-invasive, non-expensive and fully automated method based on hybrid approach: wavelet transform analysis and neural network classifier. First, we present the results obtained in our previous study while using classic feature parameters. These results allow visual identification of pathological voices. Second, quantified parameters drifting from the wavelet analysis are proposed to characterise the speech sample. On the other hand, a system of multilayer neural networks (MNNs) has been developed which carries out the automatic detection of pathological voices. The developed method was evaluated using voice database composed of recorded voice samples (continuous speech) from normophonic or dysphonic speakers. The dysphonic speakers were patients of a National Hospital 'RABTA' of Tunis Tunisia and a University Hospital in Brussels, Belgium. Experimental results indicate a success rate ranging between 75% and 98.61% for discrimination of normal and pathological voices using the proposed parameters and neural network classifier. We also compared the average classification rate based on the MNN, Gaussian mixture model and support vector machines. [ABSTRACT FROM AUTHOR]

This paper proposes an enhanced energy management system (EEMS) for a residential AC microgrid. The renewable energy-based AC microgrid with hybrid energy storage is broken down into three distinct parts: a photovoltaic (PV) array as a green energy source, a battery (BT) and a supercapacitor (SC) as a hybrid energy storage system (HESS), and apartments and electric vehicles, given that the system is for residential areas. The developed EEMS ensures the optimal use of the PV arrays' production, aiming to decrease electricity bills while reducing fast power changes in the battery, which increases the reliability of the system, since the battery undergoes fewer charging/discharging cycles. The proposed EEMS is a hybrid control strategy, which is composed of two stages: a state machine (SM) control to ensure the optimal operation of the battery, and an operating mode (OM) for the best operation of the SC. The obtained results show that the EEMS successfully involves SC during fast load and PV generation changes by decreasing the number of BT charging/discharging cycles, which significantly increases the system's life span. Moreover, power loss is decreased during passing clouds phases by decreasing the power error between the extracted power by the sources and the required equivalent; the improvement in efficiency reaches 9.5%. [ABSTRACT FROM AUTHOR]