M’Sila, Algeria
M’Sila, Algeria

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Daliento S.,University of Naples Federico II | Chouder A.,University of ila | Guerriero P.,University of Naples Federico II | Pavan A.M.,University of Trieste | And 3 more authors.
International Journal of Photoenergy | Year: 2017

A wide literature review of recent advance on monitoring, diagnosis, and power forecasting for photovoltaic systems is presented in this paper. Research contributions are classified into the following five macroareas: (i) electrical methods, covering monitoring/diagnosis techniques based on the direct measurement of electrical parameters, carried out, respectively, at array level, single string level, and single panel level with special consideration to data transmission methods; (ii) data analysis based on artificial intelligence; (iii) power forecasting, intended as the ability to evaluate the producible power of solar systems, with emphasis on temporal horizons of specific applications; (iv) thermal analysis, mostly with reference to thermal images captured by means of unmanned aerial vehicles; (v) power converter reliability especially focused on residual lifetime estimation. The literature survey has been limited, with some exceptions, to papers published during the last five years to focus mainly on recent developments. © 2017 S. Daliento et al.


Benmehdi S.,University of Bourdj Bouarreridj | Makarava N.,University of Potsdam | Benhamidouche N.,University of ila | Holschneider M.,University of Potsdam
Nonlinear Processes in Geophysics | Year: 2011

The aim of this paper is to estimate the Hurst parameter of Fractional Gaussian Noise (FGN) using Bayesian inference. We propose an estimation technique that takes into account the full correlation structure of this process. Instead of using the integrated time series and then applying an estimator for its Hurst exponent, we propose to use the noise signal directly. As an application we analyze the time series of the Nile River, where we find a posterior distribution which is compatible with previous findings. In addition, our technique provides natural error bars for the Hurst exponent. © 2011 Author(s).


A direct adaptive control algorithm, based on neural networks (NN) is presented for a class of single input single output (SISO) nonlinear systems. The proposed controller is implemented without a priori knowledge of the nonlinear systems; and only the output of the system is considered available for measurement. Contrary to the approaches available in the literature, in the proposed controller, the updating signal used in the adaptive laws is an estimate of the control error, which is directly related to the NN weights instead of the tracking error. A fuzzy inference system (FIS) is introduced to get an estimate of the control error. Without any additional control term to the NN adaptive controller, all the signals involved in the closed loop are proven to be exponentially bounded and hence the stability of the system. Simulation results demonstrate the effectiveness of the proposed approach. © 2012 Elsevier Ltd.


Si Abdallah M.,University of ila | Zeghmati B.,University of Perpignan
Fluid Dynamics and Materials Processing | Year: 2014

In the present work, a numerical analysis is performed of the combined effects of (opposing) thermal and solutal buoyancy in the presence of a wavy (vertical) surface. The boundary layer equations and related boundary conditions are discretized using a finite volume scheme and solved numerically using a Gauss-Seidel algorithm. The influence of the wavy geometry (in terms of related wavelength L and amplitude a) and the buoyancy ratio N on the local Nusselt and Sherwood numbers and on the skin-friction coefficient are studied in detail. Results show that when PrSc, the flow is completely perturbed; the thickness of the mass boundary layer is larger than that of the thermal boundary layer. © 2014 Tech Science Press.


Barra S.,University of Batna | Dendouga A.,Center for Development of Advanced Technologies | Kouda S.,University of ila | Bouguechal N.-E.,University of Batna
Journal of Circuits, Systems and Computers | Year: 2013

The present work analyses the non-ideal effects of pipelined analog-to-digital converters (ADCs), also sometimes referred to as pipeline ADCs, including the non-ideal effects in operational amplifiers (op-amps or OAs), switches and sampling circuits. We study these nonlinear effects in pipelined ADCs built using CMOS technology and switched-capacitor (SC) techniques. The proposed improved model of a pipelined ADC includes most of the non-idealities which affect its performance. This model, simulated using MATLAB, can determine the basic blocks specifications that allow the designer to meet given data converter requirements. © 2013 World Scientific Publishing Company.


Kahoul A.,University of Bordj Bou Arréridj | Kahoul A.,Ferhat Abbas University Setif | Kahoul A.,University of ila | Aylikci V.,Karadeniz Technical University | And 3 more authors.
Radiation Physics and Chemistry | Year: 2012

The measured K-shell fluorescence yield values that were reported in the literature from 1994 to 2011 were reviewed and presented in a table form (about 341 new measurements). The Weighted-mean values of experimental data were fitted by the analytical function to deduce new empirical K-shell fluorescence yields for a broad range of elements. The results were compared with the other theoretical, experimental and semi-empirical values reported in the literature. Reasonable agreement was typically obtained between our result and other works. © 2012 Elsevier Ltd.


Chemachema M.,University of ila | Belarbi K.,University of Mentouri Constantine
International Journal of Systems Science | Year: 2011

A new approach of direct adaptive control of single input single output nonlinear systems in affine form using single-hidden layer neural network (NN) is introduced. In contrast to the algorithms in the literature, the weights adaptation laws are based on the control error and not on the tracking error or its filtered version. Since the control error is being expressed in terms of the NN controller, hence its weights updating laws are obtained via back-propagation concept. A fuzzy inference system (FIS) with heuristically defined rules is introduced to provide an estimate of this error based on the past history of the system behaviour. The stability of the closed loop is studied using Lyapunov theory. A fixed structure is then proposed for the FIS and the design parameters reduce to the parameters of the NN. The method is reproducible and does not require any pre-training of the network weights. © 2011 Taylor & Francis.


Chemachema M.,University of ila
Control and Intelligent Systems | Year: 2010

Based on state feedback linearization technique, a direct adaptive neural network (NN) control is presented for a class of SISO nonlinear systems. An additional sliding mode control (SMC) term is added to the basic NN adaptive controller to deal with approximation errors without persistent chattering phenomenon usually found in SMC control. Thus, contrary to the SMC approaches available in the literature, the implementation of the proposed control law doesn't need any smoothening procedure. Furthermore, the updating signal used in the adaptation laws is an estimate of the control error instead of the tracking error. Lyapunov direct method is then used to prove the global boundedness of all the signals involved in the closed loop and the asymptotic convergence of the tracking error to zero. Simulation results demonstrate the effectiveness of the proposed approach.


Fedias M.,University Mohamed Khider of Biskra | Saigaa D.,University of ila
International Review on Computers and Software | Year: 2010

Face authentication is a significant problem in pattern recognition. The face is not rigid it can undergo a large variety of changes in illumination, facial expression and aging. Principal Component Analysis (PCA) is a typical and successful face based technique which considers face as global feature. In this paper, we developed a new simple method to extract the global feature vector based in the Mean and the Standard deviation (MS) of the image of face. Once the feature vector is extracted, the next stage consists of comparing it with the feature vector of face which is authenticated, and then we calculated the error rates in the two sets of evauation and test for the data base XM2VTS according to the protocol of Lausanne. The experimental results indicated that the extraction of image features is more efficient and faster using MS method than PCA. © 2010 Praise Worthy Prize S.r.l. - All rights reserved.


Bakhti F.Z.,University of ila | Si-Ameur M.,University of ila | Si-Ameur M.,University of Batna
Journal of Engineering Science and Technology Review | Year: 2011

In this work, a numerical study of a laminar mixed convection in a inclined thick duct is considered. A uniform heat flux is applied over the entire circumference of the tube. The governing differential equations were solved by a finite volume method. The SIMPLE algorithm for pressure- velocity coupling was adopted. A parametric study is carried out to analyze the effect of the Grashof number, the angle of the duct inclination and the wall conductivity on the thermal-fluid fields. Several numbers of Grashof (4. 104, 4. 106, 4. 107) are considered for an angle of inclination equal: 0°, 30° and 60°. For material of the wall, we chose Report/ratio of conductivity (K=kp/kf) of the copper (K=19000), iron (K=3600) and aluminium (K=11500). The results are analyzed by examining the velocity, pressure and temperature fields§. The axial evolution of the Nusselt number and that of the parietal constraints are examined for various studied cases. © 2011 Kavala Institute of Technology.

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