Mohammed Ouadi Bensalah

Mohammed V University

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Abou el kacem Qaiss

Moroccan Foundation for Advanced Science, Innovation and Research

Rachid Bouhfid

Moroccan Foundation for Advanced Science, Innovation and Research

Hamid Essabir

Moroccan Foundation for Advanced Science, Innovation and Research

Marya Raji

Moroccan Foundation for Advanced Science, Innovation and Research

Denis Rodrigue

Université Laval

Souad Nekhlaoui

Mohammed V University

Mohamed Youssfi

Université Hassan II Mohammedia

Omar Bouattane

Université Hassan II Mohammedia

Wafa Ouarhim

Mohammed V University

Hamid Essabir

Moroccan Foundation for Advanced Science, Innovation and Research

Cooperative Institutions

Mohammed V University

Moroccan Foundation for Advanced Science, Innovation and Research

Universiti Putra Malaysia

Université Mohammed VI Polytechnique

Centre National de la Recherche Scientifique

Technical University of Malaysia Malacca

University of Hassan II Casablanca

Université Hassan II Mohammedia

King Abdulaziz University

École Normale Supérieure de l'Enseignement Technique de Mohammedia

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A computational model based on cooperative mobile agents for big data image segmentation

Fatéma Zahra Benchara Mohamed Youssfi Omar Bouattane Hassan Ouajji Mohammed Ouadi Bensalah

The aim of this paper is to present interesting results obtained by implementing big data classification algorithm using a cooperative mobile agents model. In this work we focused on the application of this classification for Magnetic Resonance Images (MRI) segmentation which is presented based on parallel fine grained c-means algorithm. This algorithm is converged to distributed classification c-means algorithm in order to be implemented on a parallel and distributed virtual machine based on mobile agents. The big data MRI image to be processed is split into small elementary images by the host agent. The obtained list of item images is distributed to mobile agents deployed on each node of the distributed system. Each agent is asked to perform the execution of the c-means algorithm using its assigned image item and return its elementary results to the host agent which computes the current global class centers and newly distributes them. This process is repeated until the convergence of the distributed algorithm. The experimental results show that the distributed classification method can improve the big data segmentation.

Mobile agent

Market Segmentation

10.1109/icocs.2014.7061007

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A fine grained parallel fuzzy segmentation algorithm on reconfigurable mesh computer

Advanced Studies in Theoretical Physics (2015)

Mohamed Youssfi Omar Bouattane Mohammed Ouadi Bensalah

10.12988/astp.2015.5111

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The micromechanics modeling piezoelectric composite materials by method of homogenization Mori Tanaka: study of piezo-composite SiO2/BaTiO3

Advanced Studies in Theoretical Physics (2013)

Zouhair Sadoune I. Elguesse Mohammed Ouadi Bensalah

In this work, the behavior of piezoelectric composite has been studied in terms of prediction, in order to contribute to understanding the piezoelectricity, perroelectricity phenomenon of these materials. The materials with the piezoelectric intrinsic properties have been added fillers to matrix to obtain the piezoelectric composites materials. The Mori-Tanaka model has been used to predict the mechanical behavior, which is part of the electromechanical formulation. The use of Mori-Tanaka model is based on its compatibility with the composites at high fiber volume content. The results from the Mori-Tanaka model have been compared to Voigt and Reuss models. The models have been simulated using programming language to determine stress-strain behavior.

Micromechanics

Homogenization

10.12988/astp.2013.3550

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Citations (1)

Mechanical and thermal properties of natural fibers reinforced polymer composites: Doum/low density polyethylene

Materials & Design (1980-2015) (2012)

F.Z. Arrakhiz Mounir El Achaby Mustapha Malha Mohammed Ouadi Bensalah O. Fassi‐Fehri

Low-density polyethylene

Flexural modulus

Natural fiber

10.1016/j.matdes.2012.06.056

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Citations (287)

Hygroscopic Behaviour Modelling of Syntactic Foams in the Presence of Trapping and Diffuse Interfaces

Composite Interfaces (2010)

Lahsen Ouissaden Ahmed Lekhder Hélène Dumontet Abelwahed Benhamida Mohammed Ouadi Bensalah

In order to determine the role of reinforcement–matrix interfaces in the infiltration of water molecules within a composite material, we introduced a very thin layer that was highly diffusive and trapping between reinforcements and matrix. A finite element discretization of such an extremely thin surface layer poses numerical difficulties. To resolve this problem, we sought to substitute this interfacial surface, whose thickness is very low, with a thicknessless interface which has equivalent diffusion behaviour. Using asymptotic development techniques, we also established a minimum interface limit which is asymptotically equivalent to the problem of moisture transmission through a very thin highly diffusive and trapping layer. Using the method of homogenization environments periodicals and model Langmuir, we determined hygroscopic behaviour equivalent to the syntactic foams while taking account of interface law proposed. Determination of the diffusion coefficients and trapping is then compared with the experimental results.

Homogenization

Syntactic foam

Tortuosity

Thin layers

10.1163/092764409x12580201111629

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Citations (2)

List of Contributors

Elsevier eBooks (2019)

M.Z. Akop Abdullah M. Asiri Aftab Aslam Parwaz Khan Indrani Banerjee Sunita Barik

10.1016/b978-0-12-814548-7.01002-3

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Injection molding of short coir fiber polypropylene biocomposites: Prediction of the mold filling phase

Polymer Composites (2019)

Fatima‐Zahra Semlali Aouragh Hassani Wafa Ouarhim Nadia Zari Mohammed Ouadi Bensalah Denis Rodrigue

The mold‐filling phase in injection molding is the most important one because the material flow behavior controls the final part structure. In this work, the effect of melt rheology on the flow front progression of coir fiber (2.5, 5, 10, and 15 wt%) filled polypropylene is investigated. The flow behavior is predicted using the incompressible Navier–Stokes equations to determine the flow front shape and position and the model proposed is in good agreement with the experimental results for the range of conditions studied. Finally, to provide a better understanding of the effect of different processing conditions (pressure, melt, and mold temperature) on the flow front evolution, several simulations were performed using Autodesk Moldflow Insight. POLYM. COMPOS., 40:4042–4055, 2019. © 2019 Society of Plastics Engineers

Polypropylene

Molding (decorative)

Melt flow index

10.1002/pc.25265

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Citations (19)

Parallel c-means algorithm for image segmentation on a reconfigurable mesh computer

Zenodo (CERN European Organization for Nuclear Research) (2011)

Omar Bouattane Bouchaib Cherradi Mohamed Youssfi Mohammed Ouadi Bensalah

10.5281/zenodo.34874

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Citations (2)

7. Hygrothermoelastic behaviour Natural fibers based composites: Mechanisms and formalism

De Gruyter eBooks (2019)

Wafa Ouarhim Mohammed Ouadi Bensalah Abou el kacem Qaiss Rachid Bouhfid

Natural fibers have shown their applications grow strongly in recent years, both in construction and in transport and leisure. This chapter discusses the hygrothermoelastic behavior of composites reinforced with natural fibers. Different behaviors have been proved, including hygroscopic, thermal, hygrothermal, hygroelastic, thermoelastic, and hygrothermoelastic behaviors. The mechanisms and formalisms of each behavior are reported concurrently. Finally, the focus is on the application of equations governing the hygrothermoelastic effect in the case of the laminated composite structure.

Thermoelastic damping

Formalism (music)

10.1515/9783110603699-007

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Compatibilization of PA6/ABS blend by SEBS-g-MA: morphological, mechanical, thermal, and rheological properties

The International Journal of Advanced Manufacturing Technology (2020)

Hamid Essabir Fatima Zahra El Mechtali Souad Nekhlaoui Marya Raji Mohammed Ouadi Bensalah

Compatibilization

Maleic anhydride

Molding (decorative)

10.1007/s00170-020-05888-5

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Citations (36)