Publications by Year: 2021

Amina H, Maissa K. Maximization of the Stability Radius of an Infinite Dimensional System Subjected to Stochastic Unbounded Structured Multi-perturbations With Unbounded Input Operator, in International Conference on Recent Advances in Mathematics and Informatics (ICRAMI), 21-22 Sept. Tebessa, Algeria ; 2021 :1-5. Publisher's VersionAbstract

In this paper we consider infinite dimensional systems subjected to stochastic structured multiperturbations. We address the problem of robustness optimization with respect to state feedback but allow both unbounded input and perturbations. Conditions are derived for the existence of a stabilizing controller ensuring that the norm of the closed loop operator below a prespecified bound. Such controllers will be called suboptimal controllers. The suboptimality conditions are obtained in terms of a Riccati equation which satisfies an operator inequality. Finally, we give a lower bound for the supremal achievable stability radius via the Riccati equation.

Amira K, MAISSSA KADA. Robust Stabilization of Infinite Dimensional Systems Subjected to Stochastic and Deterministic Perturbations, in 2021 International Conference on Recent Advances in Mathematics and Informatics (ICRAMI). Tebessa, Algeria ; 2021 :1-4. Publisher's VersionAbstract

This paper deals with the robust stabilization of infinite dimensional systems subjected to stochastic and deterministic perturbations. First, we give conditions providing the stability of the parameterized system. Then, we investigate the maximization of the stability radius by state feedback. We establish conditions for the existence of suboptimal controllers. Using these conditions we characterize the supreme achievable stability radius via an infinite dimensional Riccati equation.

Boussaad L, BOUCETTA ALDJIA. Stacked Auto-Encoders Based Biometrics Recognition, in International Conference on Recent Advances in Mathematics and Informatics (ICRAMI). Tebessa, Algeria ; 2021 :1-6. Publisher's VersionAbstract

Recently deep learning has shown significant achievement in the performance of many tasks, like natural language processing, image and speech recognition. Also, this improvement concerns multiple biometrics recognition systems. In this work, we focus on biometrics recognition, we present a stacked auto-encoder-based approach for various biometrics recognition, including Iris, Ear, palm-print, and face recognition. The proposed method allows training a neural network that includes two hidden layers for biometrics tasks. It runs in two steps, in the first one, each layer is trained individually in an unsupervised manner by auto-encoders, then the layers are stacked and trained in a supervised way. Experimental results on images, obtained from publicly available biometrics databases clearly demonstrate the benefit of using stacked auto-encoders as feature extraction and dimension reduction tools for biometrics recognition, as significant high accuracy rates are obtained over the four databases.

Mekaoussi A, Titaouine M. Simulation Of The Structure FSS Using The WCIP Method For Dual Polarization Applications, in International Conference on Recent Advances in Mathematics and Informatics (ICRAMI). Tebessa, Algeria ; 2021 :1-6. Publisher's VersionAbstract

In this work, we studied an L-shaped frequency selective surface (FSS) by a method called Wave Concept Iterative Procedure (WCIP), this method developed from the Modal Fast Transformation (FMT) is based on the cross- formulation. wave and the solution obtained by an iterative procedure does not use the matrix to ensure convergence and the procedure is stopped when it arrives at convergence, for this geometry the results of a single resonance obtained by the WCIP method have a resonant frequency of 5.35 GHz with a band bandwidth of 2.3 GHz, when the structure is excited in the X direction, a frequency at 10.35 GHz with a bandwidth of 0.44 GHz when the structure is excited in the Y direction. The simulation of the results obtained by the WCIP method is compared with the results of the software HFSS 13.0 (High Frequency Structure Simulator), we find a good agreement.

Mawloud T. Amélioration du processus de capitalisation et de partage des connaissances pour la maximisation de la valeur d’un système de production. Génie Industriel [Internet]. 2021. Publisher's VersionAbstract

Dans cette thèse, nous nous sommes intéressés à un modèle de gestion des connaissances des entreprises industrielles. Certaines tâches manufacturières impliquent un niveau élevé de connaissance tacite des opérateurs qualifiés. L'industrie a besoin des méthodes fiables pour la capture et l'analyse de ces connaissances tacites afin qu'elles puissent être partagées et sans aucune perte. Nous proposons, un modèle de gestion contenant deux processus de gestion, le premier processus est la capitalisation des connaissances basée sur une tâche industrielle. Nous avons utilisé une combinaison de deux méthodologies : une méthodologie d’ingénierie de connaissances CommonKADS et une méthodologie d’élicitation des connaissances MACTAK. Dans la phase de modélisation, nous avons utilisé deux différentes techniques de modélisation, une modélisation basée sur les connaissances d’expert et la deuxième une représentation ontologique. Ce modèle facilite la capture des connaissances d’experts et transforme les connaissances tacites en explicites avec une maximisation des règles de production. Le deuxième processus concerne le partage des connaissances à base d’une ontologie des Tâches Manufacturières MATO en identifiant un ensemble des concepts de fabrication et leurs relations, cette ontologie proposée facilite le partage des connaissances entre les tâches de fabrication et aide à partager et à réutiliser les connaissances durant l'exécution des tâches. Ensuite, une application proposée pour le diagnostic de système d’alarme dans une centrale thermique a été présentée pour démontrer l’importance et l’apport de l’ontologie.

Ameddah H, Mazouz H. 3D Printing Analysis by Powder Bed Printer (PBP) of a Thoracic Aorta Under Simufact Additive. In: Research Anthology on Emerging Technologies and Ethical Implications in Human Enhancement. IGI Global ; 2021. pp. 774-785.Abstract
In recent decades, vascular surgery has seen the arrival of endovascular techniques for the treatment of vascular diseases such as aortic diseases (aneurysms, dissections, and atherosclerosis). The 3D printing process by addition of material gives an effector of choice to the digital chain, opening the way to the manufacture of shapes and complex geometries, impossible to achieve before with conventional methods. This chapter focuses on the bio-design study of the thoracic aorta in adults. A bio-design protocol was established based on medical imaging, extraction of the shape, and finally, the 3D modeling of the aorta; secondly, a bio-printing method based on 3D printing that could serve as regenerative medicine has been proposed. A simulation of the bio-printing process was carried out under the software Simufact Additive whose purpose is to predict the distortion and residual stress of the printed model. The binder injection printing technique in a Powder Bed Printer (PBP) bed is used. The results obtained are very acceptable compared with the results of the error elements found.
Sahraoui H, Mellah H, Drid S, Chrifi-Alaoui L. Adaptive maximum power point tracking using neural networks for a photovoltaic systems according grid. Engineering & Electromechanics,(5)Engineering & Electromechanics,(5). 2021 :57-66.
ZERDOUMI Z, BENMEDDOUR F, ABDOU L, Benatia D. An Adaptive Sigmoidal Activation Function for Training Feed Forward Neural Network Equalizer. The Eurasia Proceedings of Science Technology Engineering and MathematicsThe Eurasia Proceedings of Science Technology Engineering and Mathematics. 2021;14 :1-7.
Arar C, BELAZOUI A, Telli A. Adoption of social robots as pedagogical aids for efficient learning of second language vocabulary to children. Journal of e-Learning and Knowledge SocietyJournal of e-Learning and Knowledge Society. 2021;17 :119-126.
Belkhiri Y, Benbia S, Djaout A. Age related changes in testicular histomorphometry and spermatogenic activity of bulls. Journal of the Hellenic Veterinary Medical SocietyJournal of the Hellenic Veterinary Medical Society. 2021;72 :3139-3146.
Bouatia M. Analyse Numérique du Comportement d’une Conduite sur un Versant Non-Saturé Instable de Grande Hauteur. Cas de la Conduite AEP de Ain Tinn-Mila.(Numerical Analysis of Pipeline Behavior on High Unstable Unsaturated Slope. Case of AEP pipe of Ain Tinn-Mi. 2021.
Youb Y, Kadid A, Lombarkia H. Analysis of the post-mainshock behavior of reinforced concrete bridge pier columns subjected to aftershocks. Jordan Journal of Civil EngineeringJordan Journal of Civil Engineering. 2021;15.
Makhloufi R, Boussaha A, Benbouta R, Baroura L. Anisotropic and Isotropic Elasticity Applied for the Study of Elastic Fields Generated by Interfacial Dislocations in a Heterostructure of InAs/(001) GaAs Semiconductors. Journal of Solid MechanicsJournal of Solid Mechanics. 2021;13 :503-512.
Ghallache L, Mohamed-Cherif A, China B, Mebkhout F, Boilattabi N, Bouchemal A, Rebia A, Ayachi A, Khelef D, Miroud K. Antibiotic Resistance Profile of Escherichia coli Isolated from Bovine Subclinical Mastitis of Dairy Farms in Algeria from 2017 to 2019. WorldWorld. 2021;11 :402-415.
Cheriet T, HANFER M, Mancini I, Benelhadj S, Laouas NE, Ameddah S, Menad A, Seghiri R. Anti-inflammatory and hemostatic effects of Linaria reflexa Desf. Natural Product ResearchNatural Product Research. 2021;35 :2778-2783.
Ghedadba N, Hambaba L, Hachemi M, Bensaad MS. Antioxidant and Anti-inflammatory Activities of Methanolic Extract of Marrubium deserti de Noé Leaves. PSM Biol. Res.PSM Biol. Res. 2021;6 :56-65.
Réggami Y, Benkhaled A, Boudjelal A, Berredjem H, Amamra A, Benyettou H, Larabi N, Senator A, Siracusa L, Ruberto G. Artemisia herba-alba aqueous extract improves insulin sensitivity and hepatic steatosis in rodent model of fructose-induced metabolic syndrome. Archives of physiology and biochemistryArchives of physiology and biochemistry [Internet]. 2021;127 :541-550. Publisher's Version
Boutlikht M, Lahbari N, Hebbache K, Tabchouche S. The assessment of strips arrangement effect on the performance of strengthened reinforced concrete beams. Journal of Adhesion Science and TechnologyJournal of Adhesion Science and Technology. 2021 :1-18.
Guettafi N, Yahiaoui D, Abbeche K, Bouzid T. Author Correction: Numerical Evaluation of Soil-Pile-Structure Interaction Effects in Nonlinear Analysis of Seismic Fragility Curves. Transportation Infrastructure GeotechnologyTransportation Infrastructure Geotechnology. 2021 :1-1.
OULEFKI ADEL, Agaian S, Trongtirakul T, Laouar AK. Automatic COVID-19 lung infected region segmentation and measurement using CT-scans images. Pattern recognitionPattern Recognition [Internet]. 2021;114 :107747. Publisher's VersionAbstract

History shows that the infectious disease (COVID-19) can stun the world quickly, causing massive losses to health, resulting in a profound impact on the lives of billions of people, from both a safety and an economic perspective, for controlling the COVID-19 pandemic. The best strategy is to provide early intervention to stop the spread of the disease. In general, Computer Tomography (CT) is used to detect tumors in pneumonia, lungs, tuberculosis, emphysema, or other pleura (the membrane covering the lungs) diseases. Disadvantages of CT imaging system are: inferior soft tissue contrast compared to MRI as it is X-ray-based Radiation exposure. Lung CT image segmentation is a necessary initial step for lung image analysis. The main challenges of segmentation algorithms exaggerated due to intensity in-homogeneity, presence of artifacts, and closeness in the gray level of different soft tissue. The goal of this paper is to design and evaluate an automatic tool for automatic COVID-19 Lung Infection segmentation and measurement using chest CT images. The extensive computer simulations show better efficiency and flexibility of this end-to-end learning approach on CT image segmentation with image enhancement comparing to the state of the art segmentation approaches, namely GraphCut, Medical Image Segmentation (MIS), and Watershed. Experiments performed on COVID-CT-Dataset containing (275) CT scans that are positive for COVID-19 and new data acquired from the EL-BAYANE center for Radiology and Medical Imaging. The means of statistical measures obtained using the accuracy, sensitivity, F-measure, precision, MCC, Dice, Jacquard, and specificity are 0.98, 0.73, 0.71, 0.73, 0.71, 0.71, 0.57, 0.99 respectively; which is better than methods mentioned above. The achieved results prove that the proposed approach is more robust, accurate, and straightforward.