Browsing by Author "Tourtchine, Victor"

Now showing 1 - 11 of 11

Daily geomagnetic field prediction of intermagnet observatories data using the multilayer perceptron neural network
(Springer, 2014) Ouadfeul, Sid-Ali; Tourtchine, Victor; Aliouane, Leila
Effect of stress-strain conditions on physical precursors and failure stages development in rock samples
(2015) Baddari, Kamel; Frolov, Anatoly D.; Tourtchine, Victor; Rahmoune, Fayçal; Makdeche, Said
Precursory stages of failure development in large rock samples were studied and simultaneous observations of the space-time variation of several physical fields were carried out under different stress-strain states. The failure process was studied in detail. A hierarchical structure of discreet rock medium was obtained after loading. It was found that the moisture reduced the rock strength, increased the microcrack distribution and influenced the shape of the failure physical precursors. The rise in temperature up to 400 °C affected the physical precursors at the intermediate and final stages of the failure. Significant variations were detected in the acoustic and electromagnetic emissions. The coalescence criterion was slightly depending on the rock moisture and temperature effect. The possibility of identifying the precursory stage of failure at different strain conditions by means of a complex parameter derived from the convolution of physical recorded data is shown. The obtained results point out the efficiency of the laboratory modelling of seismic processes
An embedded e-voting machine with smart card
(Inderscience, 2016) Dichou, Karima; Tourtchine, Victor; Rahmoune, Faysal
Finding the best FPGA implementation of the DES algorithm to secure smart cards
(IEEE, 2015) Dichou, Karima; Tourtchine, Victor; Rahmoune, Faycal
Generalized dynamical fuzzy model for identification and prediction
(2014) Saad Saoud, Lyes; Rahmoune, Fayçal; Tourtchine, Victor; Baddari, Kamel
In this paper, the development of an improved Takagi Sugeno (TS) fuzzy model for identification and chaotic time series prediction of nonlinear dynamical systems is proposed. This model combines the advantages of fuzzy systems and Infinite Impulse Response (IIR) filters, which are autoregressive moving average models, to create internal dynamics with just the control input. The structure of Fuzzy Infinite Impulse Response (FIIR) is presented, and its learning algorithm is described. In the proposed model, the Butterworth analogue prototype filters are estimated using the obtained membership functions. Based on the founding orders of the analogue filters, the IIR filters could be constructed. The IIR filters are introduced to each TS fuzzy rule which produces local dynamics. Gustafson-Kessel (GK) clustering algorithm is used to generate the clusters which will be used to find the number of the IIR parameters for each rule. The hybrid genetic algorithm and simplex method are used to identify the consequence parameters. The stability of the obtained model is studied. To demonstrate the performance of this modeling method, three examples have been chosen. Comparative results between the FIIR model on one hand, and the traditional TS fuzzy model, the neural networks and the neuro-fuzzy network on the other hand. The results show that the proposed method provides promising identification results
An improved electronic voting machine using a microcontroller and a smart card
(IEEE, 2015) Dichou, Karima; Tourtchine, Victor; Rahmoune, Faycal
An integrated study of the dynamics of electromagnetic and acoustic regimes during failure of complex macrosystems using rock blocks
(Springer, 2011) Rahmoune, Fayçal; Tourtchine, Victor; Frolov, Anatoly D.; Baddari, Kamel
The development of the failure process in complex macrosystems using large rock samples subjected to biaxial compression has been studied by means of electromagnetic radiation (EMR) and acoustic emission (AE). In order to increase the stage of macrofailure development, a special procedure of rock loading was used to reveal regularities of nucleation and evolution of electromagnetic and acoustic structures. The synchronised measurements of EMR and AE allowed the control of the stress–strain state in the rocks and the structural developments of fracturing. Nonhomogeneous distribution of the rock spatial crystalline structure subject to load leads to a mosaic distribution of EMR and AE characteristics. As a result, the crack scale effect may be observed in the EMR and AE structure behaviours. The EMR and AE following the failure at different levels behave differently according to the difference in the scale and type of cracks. Intense high-frequency EMR pulses were recorded during the initial stage of microcrack generation occurring prior to major failure of material. This was not the case for AE. The nucleation and development of the macroscopic progressive failure evolution caused an alternation in energetic and frequencial properties of electromagnetic and acoustic events. It has been detected that the tensile cracks were more efficient than shear cracks in capacity of EMR generation. The analysis of self potentials allowed reaching the maximum of registered anomalous variations in the stage of microcracking interaction. This stage showed an increase in the EMR activity, which implies the nucleation of microcracks in various regions of rock interfaces. The gradual accumulation of these defects led to weakening some parts of the rock along with a disintegration of electric anomalies, increase of AE and a significant fluctuation in the rate ofEMR. When crack concentration attains its critical value, which results in the formation of dangerous macroscopic failure of higher level, AE shows an intense activity as well as anEMRlower frequency. The hierarchical development of rock failure using the ratio of the average crack size and the mean distance between cracks as a statistical concentration criterion is used to control the boundary of the transition from small dispersed cracks accumulation to gradual crack merger and the formation of the main macrofailure. These results could be transferred into larger scale levels to forecast dynamic events in the earth crust
Ionospheric data prediction of DEMETER Satellite using Levenberg Marquardt neural network model. application to ISL instrument
(2015) Ouadfeul, Sid-Ali; Tourtchine, Victor; Aliouane, Leila
A new modification of LEACH for efficient energy in WSN
(Indonesian Journal of Electrical Engineering and Computer Science, 2020) Lechani, Taous; Tourtchine, Victor; Amari, Said
The limited energy of nodes in wireless sensor networks and the impossibility of replacing their batteries, have lead to protocols development which optimize and balance the energy consumption over the network. LEACH is the most used hierarchical protocol. However, one major weakness of the LEACH protocol lies in both of its random cluster formation and cluster head election. In this paper, we present two new protocols based virtual grid clustering on coverage area. In the first one, sensing area is devided into grids as squares named as VSG-LEACH and in the second one into grids as hexagons named as VHG-LEACH. In each zone, one cluster head is elected according to its residual energy and its distance from the cell center. The simulation results show that the network lifetime is prolonged by 169.67% and the energy consumption is improved by 80.97% compared to LEACH protocol.
Simulation of APDUs exchanged between a microcontroller smart card and a reader
(IEEE, 2015) Dichou, Karima; Tourtchine, Victor; Rahmoune, Faycal
Wavelet-Based multifractal analysis of DEMETER satellite data before the l’Aquila earthquake of 2009
(Springer, 2016) Ouadfeul, Sid-Ali; Tourtchine, Victor; Aliouane, Leila