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Chaaben A.B.,Research Unit RME | Andoulsi R.,LaNSE | Sellami A.,ESSTT
Journal of Applied Fluid Mechanics | Year: 2011

The most widely used desalination processes are based on membrane separation via reverse osmosis (RO) which has become an important process for desalting seawater and cleaning brackish water. The use of these processes requires an efficient control system. Consequently, it is necessary to establish a dynamic model of the system with experimental validation. This paper deals with a new modelling approach of a small photovoltaic reverse osmosis (PV-RO) desalination unit. The proposed model considers the unit as a Multi Input Multi Output (MIMO) process. The relations between the output variables and the input variables are given by the use of empirical transfer matrix. A state model of the unit is also given. Some experimental results are presented to validate the proposed model. As result, the obtained unit model can be easily used for a process control loop implementation in order to assure an optimum operating condition and to reduce the water product cost.

Boubaker K.,ESSTT | Petkova P.,University of Shumen
Journal of Molecular Structure | Year: 2013

In this study, we try to give an explanation to Ruthenium-doped (BSO) Bi12SiO20:Ru single crystals stability issues in two states of the material (untreated and UV-illuminated). Lattice scale analyses have been carried out in the framework of the Lattice Compatibility Theory (LCT). Disparities between Ruthenium ions doping behaviors have been discussed in terms of Urbach Tailing and surface energy along with doping agent intrinsic lattice patterns. © 2013 Elsevier Ltd. All rights reserved.

Kombass L.,National Engineering School of Tunis | Ayari F.,IPEI EL Manar | Soula M.,ESSTT
Lecture Notes in Mechanical Engineering | Year: 2013

The objective of this work is to characterize a composite material (Al-Fe3O4) using micro-indentation test. A numerical method is developed via the ABAQUS software to simulate the micro-indentation test of this composite material and calculate the equivalent Young's modulus and the material hardness. Effects of the volume fraction, the inclusion size, and the load conditions during the simulation of a micro indentation test are performed Please write down your abstract here. © Springer-Verlag Berlin Heidelberg 2013.

Trad D.,ESSTT | Al-Ani T.,UVSQ | Al-Ani T.,School of Engineering in Information and Communication Science and Technology | Jemni M.,ESSTT
2015 5th International Conference on Information and Communication Technology and Accessibility, ICTA 2015 | Year: 2015

The aim of this paper is to investigate a nonlinear approach for feature extraction of Electroencephalogram (EEG) signals in order to classify motor imagery for Brain Computer Interface (BCI). This approach consists of combining the Empirical Mode Decomposition (EMD) and band power (BP). Considering the non-stationary and nonlinear characteristics of the motor imagery EEG, the EMD method is proposed to decompose the EEG signal into set of stationary time series called Intrinsic Mode Functions (IMF). These IMFs are analyzed with the bandpower (BP) to detect the caracteristics of sensorimotor rhythms (mu and beta). Finally, the data were reconstructed with only with the specific IMFs and then the band power is employed on the new database. Once the new feature vector is reconstructed, the classification of motor imagery is applied using Hidden Markov Models (HMMs). The results obtained show that the EMD method allows the most reliable features to be extracted from EEG and that the classification rate obtained is higher and better than using only the direct BP approach. Such a system appears as a particularly promising communication channel for people suffering from severe paralysis, for instance for persons with myopatic diseases or muscular dystrophy (MD) to move a joystick to a desired direction corresponding to the specific motor imagery. © 2015 IEEE.

Seddik H.,ESSTT | Ben Braiek E.,ESSTT
2013 International Conference on Electrical Engineering and Software Applications, ICEESA 2013 | Year: 2013

Applying cryptographic techniques in the field of 2D signal processing is an attractive approach in the recent years. Different methods are proposed to ensure prior data protection. Symmetric block encryption schemes, designed on two-dimensional chaotic maps, are efficient and secure for real-time image encryption. In the case of numeric data, the encrypted signal can be easily viewed and then intercepted in order to be revealed. This creates a need to offer a posterior protection to improve protection for confidential data. In this paper a method combining chaotic encryption system with frequency watermarking is presented. The proposed technique is divided in two steps. The first step, consists in applying a modified Tao algorithm based chaotic map with higher complexity and applicable for all images sizes. To avoid revealing that the transmitted data is encrypted, this data is then hidden by coding it in the frequencies DCT coefficients of a transformed second image. The proposed approach presents more security and reliability for any kind of image data. © 2013 IEEE.

Awojoyogbe O.B.,Minna Federal University Of Technology | Faromika O.P.,Federal University of Technology Akurre | Moses F.O.,P.O. Box 9352 | Dada M.,Minna Federal University Of Technology | And 2 more authors.
Current Applied Physics | Year: 2010

In this study, the Bloch NMR flow equations are modelled into diffusion equation with constant transport coefficient in terms of the NMR transverse magnetization. Mathematical conditions are established for the diffusion coefficients to be constant or spatially varied with direction. When these conditions are met, the diffusion coefficients can then be easily evaluated in terms of Boubaker polynomials for the study of flow in restricted geometries. © 2009 Elsevier B.V. All rights reserved.

Boubaker K.,ESSTT
Renewable and Sustainable Energy Reviews | Year: 2012

In this review, general features of the renewable energy sources in the North African upper zone have been studied. The primal renewable sources of energy have been identified in Algeria, Morocco and Tunisia. Taking into account concordances and divergences of the different actors in the region, a polynomial optimization scheme has been performed in order to predict future potentials and perspectives. © 2012 Elsevier Ltd. All right reserved.

Nasri W.,ESSTT
International Journal of Parallel, Emergent and Distributed Systems | Year: 2010

Today, due to many reasons, such as the inherent heterogeneity, the diversity and the continuous evolution of actual computational supports, writing efficient parallel applications on such systems represents a great challenge. To achieve good performances in these execution environments, the impact of communications on the global performances of parallel applications should not be neglected. Our objective within this work is to design an analytical model able to predict accurately the performance of communication operations on computational systems characterised by both heterogeneity and hierarchical structure. We principally aim to guarantee the accuracy of the predicted performances with a neglected additional overhead. The proposed model was applied on point-to-point and collective communication operations and showed by achieving experiments on a hierarchical cluster-based system with heterogeneous resources that the predicted performances are close to measured ones. © 2010 Taylor & Francis.

Anissa S.,ESSTT | Hassene S.,ESSTT | Zouhair M.,ESSTT
2013 International Conference on Electrical Engineering and Software Applications, ICEESA 2013 | Year: 2013

In this paper, we investigated the enhancement of speech by applying an optimal adaptive low-pass filter supervised by neural network. The corruption of speech due to the presence of additive noise causes its degradation in quality and intelligibility. To filter this distorted signal in its spatial representation is a hard task. This task is more difficult to realize if the distortion are caused by colored noise. In addition using a static filter is not efficient due to the speech signal variability. In the same sentence a phoneme can change in shape and amplitude. For these constraints, we propose to apply a low-pass filter with Gaussian core supervised by neural networks. Filtering strength changes continuously with the phoneme variation to generate a variable filter that change over the whole sentence. © 2013 IEEE.

In this study, achievements, potentials and perspectives for renewable energy sources in the North African upper zone have been investigated. The renewable sources of energy, mainly solar, wind, biomass and geothermal, have been identified. Renewable energies were shown to have a promising future in the context of a connected network with the European Union, despite divergences of individual national targets and policies. Assuming a competitive, regional and stable energy framework in the region, a probabilistic optimization scheme has been proposed for a 2025 horizon within a Data Envelopment Analysis (DEA) framework. © 2011 Elsevier Ltd.

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