HOME / PUBLICATIONS /

Publications

2018
DEMAGH Y. De l'idee novatrice a la concretisation theorique: developpement d'un nouvel absorbeur d’energie pour capteurs solaires a concentrations lineaires. seminaire national sur les energies renouvelables et le devetoppement durable snerdd-18, LE 25 & 26 JUIN . 2018.
Benamar S. Deciphering epidemiological link between healthcare-associated infections involving multi drug-resistant Enterococcus faecium vanA in Algeria underlines the need to reinforce infection control program in developing countries. Infection Prevention AnnualConference. 2018.
Ouarlent Y. Deficiency acquired in factor X Revealing an AL.Amyloidosis. 64 th Annual SSC Meeting of the ISTH. 2018.
Ouarlent Y. Déficit en facteur VII asymptomatique chez l’enfant. Congres des sociétés de pédiatrie . 2018.
Tebbal S. Dermohypodermites aiguës bactériennes en milieu hospitalier. ème conférence internationale d’infectiologie . 2018.
Mokrani K. Dermohypodermites aiguës bactériennes en milieu hospitalier.; 2018.
Nabila KALLA. Dermohypodermites aiguës bactériennes en milieu hospitalier. 3ème conférence internationale d’infectiologie. 2018.
Hamid HA. Dermohypodermites aiguës bactériennes en milieu hospitalier. 3ème conférence internationale d’infectiologie . 2018.
Mokrani K. Description des deux cas familiaux de FBM. 3ème Conférence Internationale d’Infectiologie . 2018.
Hadj Aissa H. Description des deux cas familiaux de FBM. 3ème conférence internationale d’infectiologie . 2018.
Tebbal S. Description des deux cas familiaux de FBM. 3ème conférence internationale d’infectiologie . 2018.
Kouda S, Abdelghani D, Barra S, Bendib T. Design of a Selective Smart Gas Sensor Based on ANN-FL Hybrid Modeling, ISSN e-ISSN 2077-6772 / 2306-4277. Journal of Nano- and Electronic PhysicsJournal of Nano- and Electronic Physics. 2018;volume 10 :pp 06011-06016.Abstract
The selectivity is one of the main challenges to develop a gas sensor, the good chemical species detection in a gaseous mixture decreasing the missed detections. The present paper proposes a new solution for gas sensor selectivity based on artificial neural networks (ANNs) and fuzzy logic (FL) algorithm. We first use ANNs to develop a gas sensor model in order to accurately express its behavior. In a second step, the FL and Matlab environment are used to create a database for a selective model, where the response of this one only depends on one chemical species. Analytical models for the gas sensor and its selective model are implemented into a Performance Simulation Program with Integrated Circuit Emphasis (PSPICE) simulator as an electrical circuit in order to prove the similarity of the analytical model output with that of the MQ-9 gas sensor where the output of the selective model only depends on one gas. Our results indicate the capability of the ANN-FL hybrid modeling for an accurate sensing analysis.
Kouda S, Abdelghani D, Barra S, Bendib T. Design of a Selective Smart Gas Sensor Based on ANN-FL Hybrid Modeling, ISSN e-ISSN 2077-6772 / 2306-4277. Journal of Nano- and Electronic PhysicsJournal of Nano- and Electronic Physics. 2018;volume 10 :pp 06011-06016.Abstract
The selectivity is one of the main challenges to develop a gas sensor, the good chemical species detection in a gaseous mixture decreasing the missed detections. The present paper proposes a new solution for gas sensor selectivity based on artificial neural networks (ANNs) and fuzzy logic (FL) algorithm. We first use ANNs to develop a gas sensor model in order to accurately express its behavior. In a second step, the FL and Matlab environment are used to create a database for a selective model, where the response of this one only depends on one chemical species. Analytical models for the gas sensor and its selective model are implemented into a Performance Simulation Program with Integrated Circuit Emphasis (PSPICE) simulator as an electrical circuit in order to prove the similarity of the analytical model output with that of the MQ-9 gas sensor where the output of the selective model only depends on one gas. Our results indicate the capability of the ANN-FL hybrid modeling for an accurate sensing analysis.
Kouda S, Abdelghani D, Barra S, Bendib T. Design of a Selective Smart Gas Sensor Based on ANN-FL Hybrid Modeling, ISSN e-ISSN 2077-6772 / 2306-4277. Journal of Nano- and Electronic PhysicsJournal of Nano- and Electronic Physics. 2018;volume 10 :pp 06011-06016.Abstract
The selectivity is one of the main challenges to develop a gas sensor, the good chemical species detection in a gaseous mixture decreasing the missed detections. The present paper proposes a new solution for gas sensor selectivity based on artificial neural networks (ANNs) and fuzzy logic (FL) algorithm. We first use ANNs to develop a gas sensor model in order to accurately express its behavior. In a second step, the FL and Matlab environment are used to create a database for a selective model, where the response of this one only depends on one chemical species. Analytical models for the gas sensor and its selective model are implemented into a Performance Simulation Program with Integrated Circuit Emphasis (PSPICE) simulator as an electrical circuit in order to prove the similarity of the analytical model output with that of the MQ-9 gas sensor where the output of the selective model only depends on one gas. Our results indicate the capability of the ANN-FL hybrid modeling for an accurate sensing analysis.
Kouda S, Abdelghani D, Barra S, Bendib T. Design of a Selective Smart Gas Sensor Based on ANN-FL Hybrid Modeling, ISSN e-ISSN 2077-6772 / 2306-4277. Journal of Nano- and Electronic PhysicsJournal of Nano- and Electronic Physics. 2018;volume 10 :pp 06011-06016.Abstract
The selectivity is one of the main challenges to develop a gas sensor, the good chemical species detection in a gaseous mixture decreasing the missed detections. The present paper proposes a new solution for gas sensor selectivity based on artificial neural networks (ANNs) and fuzzy logic (FL) algorithm. We first use ANNs to develop a gas sensor model in order to accurately express its behavior. In a second step, the FL and Matlab environment are used to create a database for a selective model, where the response of this one only depends on one chemical species. Analytical models for the gas sensor and its selective model are implemented into a Performance Simulation Program with Integrated Circuit Emphasis (PSPICE) simulator as an electrical circuit in order to prove the similarity of the analytical model output with that of the MQ-9 gas sensor where the output of the selective model only depends on one gas. Our results indicate the capability of the ANN-FL hybrid modeling for an accurate sensing analysis.
Youb L, Belkacem S, Naceri F, Cernat M, Pesquer LG. Design of an Adaptive Fuzzy Control System for Dual Star Induction Motor Drives. Advances in Electrical and Computer EngineeringAdvances in Electrical and Computer Engineering. 2018;18.
Youb L, Belkacem S, Naceri F, Cernat M, Pesquer LG. Design of an Adaptive Fuzzy Control System for Dual Star Induction Motor Drives. Advances in Electrical and Computer EngineeringAdvances in Electrical and Computer Engineering. 2018;18.
Youb L, Belkacem S, Naceri F, Cernat M, Pesquer LG. Design of an Adaptive Fuzzy Control System for Dual Star Induction Motor Drives. Advances in Electrical and Computer EngineeringAdvances in Electrical and Computer Engineering. 2018;18.
Youb L, Belkacem S, Naceri F, Cernat M, Pesquer LG. Design of an Adaptive Fuzzy Control System for Dual Star Induction Motor Drives. Advances in Electrical and Computer EngineeringAdvances in Electrical and Computer Engineering. 2018;18.
Youb L, Belkacem S, Naceri F, Cernat M, Pesquer LG. Design of an Adaptive Fuzzy Control System for Dual Star Induction Motor Drives. Advances in Electrical and Computer EngineeringAdvances in Electrical and Computer Engineering. 2018;18.

Pages