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76 results on '"Benghabrit, Asmaa"'

1. A Multi-Agent System for the Optimization of Medical Waste Management

Author

Chtioui, Ahmed, Bouhaddou, Imane, Benabdella, Abla Chaouni, Benghabrit, Asmaa, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Masrour, Tawfik, editor, Ramchoun, Hassan, editor, Hajji, Tarik, editor, and Hosni, Mohamed, editor

Published
2023
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5. Industry 4.0 for PLM in Pandemics: Towards a Smart Digital Agile PLM

Author

Moufaddal, Mariam, Benghabrit, Asmaa, Bouhaddou, Imane, Rannenberg, Kai, Editor-in-Chief, Soares Barbosa, Luís, Editorial Board Member, Goedicke, Michael, Editorial Board Member, Tatnall, Arthur, Editorial Board Member, Neuhold, Erich J., Editorial Board Member, Stiller, Burkhard, Editorial Board Member, Tröltzsch, Fredi, Editorial Board Member, Pries-Heje, Jan, Editorial Board Member, Kreps, David, Editorial Board Member, Reis, Ricardo, Editorial Board Member, Furnell, Steven, Editorial Board Member, Mercier-Laurent, Eunika, Editorial Board Member, Winckler, Marco, Editorial Board Member, Malaka, Rainer, Editorial Board Member, Canciglieri Junior, Osiris, editor, Noël, Frédéric, editor, Rivest, Louis, editor, and Bouras, Abdelaziz, editor

Published
2022
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6. Analysis and Modeling the Intersection of Design for X Techniques, Business Strategies and Product Life-Cycle Management

Author

Chaouni Benabdellah, Abla, Zekhnini, Kamar, Bouhaddou, Imane, Benghabrit, Asmaa, Rannenberg, Kai, Editor-in-Chief, Soares Barbosa, Luís, Editorial Board Member, Goedicke, Michael, Editorial Board Member, Tatnall, Arthur, Editorial Board Member, Neuhold, Erich J., Editorial Board Member, Stiller, Burkhard, Editorial Board Member, Tröltzsch, Fredi, Editorial Board Member, Pries-Heje, Jan, Editorial Board Member, Kreps, David, Editorial Board Member, Reis, Ricardo, Editorial Board Member, Furnell, Steven, Editorial Board Member, Mercier-Laurent, Eunika, Editorial Board Member, Winckler, Marco, Editorial Board Member, Malaka, Rainer, Editorial Board Member, Canciglieri Junior, Osiris, editor, Noël, Frédéric, editor, Rivest, Louis, editor, and Bouras, Abdelaziz, editor

Published
2022
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8. Theme Identification for Linked Medical Data

Author

Eddamiri, Siham, Zemmouri, Elmoukhtar, Benghabrit, Asmaa, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Masrour, Tawfik, editor, El Hassani, Ibtissam, editor, and Cherrafi, Anass, editor

Published
2021
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9. Theme Identification for RDF Graphs Based on LSTM Neural Reccurent Network

Author

Eddamiri, Siham, Zemmouri, Elmoukhtar, Benghabrit, Asmaa, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Hassanien, Aboul Ella, editor, Haqiq, Abdelkrim, editor, Tonellato, Peter J., editor, Bellatreche, Ladjel, editor, Goundar, Sam, editor, Azar, Ahmad Taher, editor, Sabir, Essaid, editor, and Bouzidi, Driss, editor

Published
2021
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10. A Cyber-Physical Warehouse Management System Architecture in an Industry 4.0 Context

Author

Moufaddal, Mariam, Benghabrit, Asmaa, Bouhaddou, Imane, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Masrour, Tawfik, editor, Cherrafi, Anass, editor, and El Hassani, Ibtissam, editor

Published
2021
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11. SmartDFRelevance: A Holonic Agent Based System for Engineering Industrial Projects in Concurrent Engineering Context

Author

Benabdellah, Abla Chaouni, Bouhaddou, Imane, Benghabrit, Asmaa, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Masrour, Tawfik, editor, Cherrafi, Anass, editor, and El Hassani, Ibtissam, editor

Published
2021
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23. The adoption of I4.0 technologies for a sustainable and circular supply chain: an industry‐based SEM analysis from the textile sector.

Author

Hmamed, Hala, Cherrafi, Anass, Benghabrit, Asmaa, Tiwari, Sunil, and Sharma, Pankaj

Subjects
TEXTILE industry, SUPPLY chains, SUSTAINABILITY, TEXTILE chemistry, STRUCTURAL equation modeling, TECHNICAL textiles, TECHNOLOGY transfer
Abstract

Currently, researchers have been particularly interested in Industry 4.0 (I4.0) as a combination of novel revolutionary digital technologies. This evolution is transforming how organizations operate to promote sustainable and circular practices. Consequently, this research empirically investigates the capabilities of I4.0 adoption to establish a sustainable and circular supply chain. The study investigates the impact of organizational factors on the deployment of I4.0 technologies to achieve sustainability objectives. Furthermore, this approach combines empirical and qualitative analyses within a methodological framework to investigate the relationship between organizational factors, I4.0 adoption, sustainable, and circular practices. In this context, survey responses have been collected from 323 supply chain professionals in the textile sector in Morocco. Consequently, employing structural equation modeling, our results reveal a strong link between I4.0 adoption and the promotion of circular and sustainable approaches. The study finds a positive association between I4.0 adoption, technological readiness, and environmental responsiveness while highlighting the challenges posed by organizational practices on I4.0 implementation in developing countries. This research contributes to the theoretical foundations of the potential influence of I4.0 technologies, and it provides practical contributions for stakeholders to effectively embrace I4.0 technologies and thereby drive more sustainable and efficient practices. [ABSTRACT FROM AUTHOR]

Published
2024
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32. Is Supply Chain a complex system?

Author

Raaidi Safaa, Bouhaddou Imane, and Benghabrit Asmaa

Subjects
Engineering (General). Civil engineering (General), TA1-2040
Abstract

Nowadays, industries are continually looking to implement new subsidiaries in different continents, in order to better fulfill their customers’ needs, generate the best products in the shortest time and cheaper than their competitors. Achieving these goals is no longer related to the company itself, but to all partners in the supply chain. This justifies the need for efficient and judicious management of the whole supply chain, through the collective intervention of all its actors. Needless to say, a supply chain is a system made up of a set of suppliers, producers, subcontractors, retailers, wholesalers and customers, between whom material, information and financial flows are exchanged. Management of these flows is becoming increasingly difficult and constitutes the main source of the supply chain complexity. In order to alleviate this problem and improve supply chain performance, it is necessary to model it, taking into consideration its characteristics, which make it a complex system. Hence, the scoop of this paper is to prove that supply chain is a complex system, by highlighting its most relevant characteristics that make it such a system. Complex means what is braided together or woven together. If we separate the elements, we get acquaintance elements, but we lose their interactions. Within this trend, our contribution subscribes with its ultimate purpose modelling supply chain as complex system.

Published
2018
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36. COMPLEXITE DE LA CHAINE LOGISTIQUE HOSPITALIERE ET DU COVID-19 : VERS UNE MODELISATION MULTI-AGENTS

Author

Chtioui, Ahmed, bouhaddou, imane, Chaouni Benabdellah, Abla, Benghabrit, Asmaa, Ecole Nationale Supérieure d'Arts et Métiers de Meknès, and MAFAYOUX, Jenny

Subjects
[SPI.AUTO] Engineering Sciences [physics]/Automatic, Systèmes Multi-Agents, Chaîne logistique hospitalière, Complexité, [SPI.MECA]Engineering Sciences [physics]/Mechanics [physics.med-ph], [SPI.MECA] Engineering Sciences [physics]/Mechanics [physics.med-ph], Covid-19, Systèmes complexes, [SPI.AUTO]Engineering Sciences [physics]/Automatic
Abstract

International audience; La crise sanitaire du Covid-19 a frappé de plein fouet toutes les sphères de l'activité humaine. Les secteurs de soins de par le monde, censés contrecarrer la propagation de la maladie et d'en limiter l'étendue sont à bout de souffle suite au manque cruel de moyens et de ressources notamment au pic de la pandémie. Les Chaînes Logistiques Hospitalières (CLH), dont la mission est de mettre à disposition des services de soins ce dont ils ont besoin pour assurer la prise en charge médicale des patients, se sont vues à leurs tours bouleversées par la crise, ce qui mettrait à coup sur le processus de soin en péril. Par ailleurs, la complexité de la CLH conjuguée à la propagation aléatoire et imprévisible du Covid-19 est à même de générer un système très complexe [CLH & Covid-19], et par conséquent compliquer davantage sa compréhension et par la suite sa maîtrise. Dans ce contexte, le présent papier se propose d'abord, de présenter la CLH et de montrer sa complexité, ensuite de prouver via un matching que la propagation du Covid-19 présente des caractéristiques similaires à celles des systèmes complexes, avant de mettre en évidence l'intérêt des Systèmes Multi-Agents (SMA) en tant que paradigme spécifique aux systèmes complexes pour la modélisation du système étudié.

Published
2020

37. Recommendation using a clustering algorithm based on a hybrid features selection method

Author

Hdioud Ferdaous, Benghabrit Asmaa, Mountasser Imad-eddine, Frikh Bouchra, and Ouhbi Brahim

Subjects
Exploit, Computer Networks and Communications, Computer science, media_common.quotation_subject, RSS, 02 engineering and technology, Recommender system, Machine learning, computer.software_genre, Artificial Intelligence, 020204 information systems, 0202 electrical engineering, electronic engineering, information engineering, Collaborative filtering, Cluster analysis, media_common, business.industry, 05 social sciences, Ambiguity, computer.file_format, Missing data, Hardware and Architecture, Artificial intelligence, 0509 other social sciences, 050904 information & library sciences, business, computer, Software, Natural language, Information Systems
Abstract

The cold start problem is a potentiel problem in Recommender Systems (RSs). It concerns the inability of the system to infer recommendaation for new users or new items about wich it has not enough iformation. Specifically, when an item is new, the system may fail to perform well due to the insufficiency of available information for this item. The most common solution addressed in the literature consists in combining the content and collaborative information under a single RS. However these hybrid solutions inherit the classical problems of natural language ambiguity and don’t exploit semantic knowledge in their items representations. In this paper, we propose a hybrid RS composed of three modules to surpass those weaknesses. The first one is rested on a powerful content clustering algorithm; which uses a Hybrid Features Selection Method (HFSM). It combines statistical and semantic relevant features to get the maximum profit from the content of items. The second module is the Collaborative Filtering (CF) one, which depends only on users’ ratings. The third one combines the previous modules to solve the problem of missing values in CF approach and to handle new-item issue. The proposed hybrid Recommender is evaluated against traditional item-based CF in different settings: no cold-start situation and a simulation of a new-item scenario (an item with few/ no ratings). The conducted experiments show the ability of the proposed hybrid recommender to deliver more accurate predictions for any item and its outperformance on the classical CF approach, which fails in cold-start situations.

Published
2018

49. Feature selection methods for document clustering: a comparative study and a hybrid solution

Author

Benghabrit, Asmaa, Ouhbi, Brahim, Frikh, Bouchra, Zemmouri, El Moukhtar, and Behja, Hicham

Abstract

The web proliferation makes the exploration and the use of the huge amount of available unstructured text documents challenged, which drives the need of document clustering. Hence, improving the performances of this mechanism by using feature selection seems worth investigation. Therefore, this paper proposes an efficient way to highly benefit from feature selection for document clustering. We first present a review and comparative studies of feature selection methods in order to extract efficient ones. Then we propose a sequential and hybrid combination modes of statistical and semantic techniques in order to benefit from crucial information that each of them provides for document clustering. Extensive experiments prove the benefit of the proposed combination approaches. The performance of document clustering is highest when the measures based on Chi-square statistic and the mutual information are linearly combined. Doing so, it avoids the unwanted correlation that the sequential approach creates between the two treatments.

Published
2019
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