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Ya Laghouaouta, Nassar, Mb, Anwar, Ac, et Bruel, J. - Md, « On the use of graph transformations for model composition traceability », in Proceedings - International Conference on Research Challenges in Information Science, 2014.
Y. Laghouaouta, Anwar, A., et Nassar, M., « A Traceability Approach for Model Composition », in 2013 ACS INTERNATIONAL CONFERENCE ON COMPUTER SYSTEMS AND APPLICATIONS (AICCSA), 2013.
Y. Laghouaouta, Anwar, A., Nassar, M., et Coulette, B., « A dedicated approach for model composition traceability », Information and Software Technology, vol. 91, p. 142-159, 2017.
Ya Laghouaouta, Anwar, Ab, et Nassar, Ma, « A traceability approach for model composition », in Proceedings of IEEE/ACS International Conference on Computer Systems and Applications, AICCSA, 2013.
Y. Laghouaouta, Anwar, A., Nassar, M., et Coulette, B., « A Graph Based Approach to Trace Models Composition. », Journal of Software (1796217X), vol. 9, p. 2813 - 2822, 2014.
H. Laghridat, Essadki, A., et Nasser, T., « Coordinated control by ADRC strategy for a wind farm based on SCIG considering low voltage ride-through capability », Protection and Control of Modern Power Systems, vol. 7, 2022.
H. Laghridat, Essadki, A., Annoukoubi, M., et Nasser, T., « A Novel Adaptive Active Disturbance Rejection Control Strategy to Improve the Stability and Robustness for a Wind Turbine Using a Doubly Fed Induction Generator », Journal of Electrical and Computer Engineering, vol. 2020, 2020.
H. Laghridat, Essadki, A., et Nasser, T., « Comparative Analysis between PI and Linear-ADRC Control of a Grid Connected Variable Speed Wind Energy Conversion System Based on a Squirrel Cage Induction Generator », Mathematical Problems in Engineering, vol. 2019, 2019.
H. Lahdili et Ismaili, Z. A. A., « New approach for self-parking management system », International Journal of Engineering and Technology(UAE), vol. 7, p. 2765-2772, 2018.
F. Zahra Lahlou, Benbrahimand, H., Mountassir, A., et Kassou, I., « Context Extraction from Reviews for Context Aware Recommendation Using Text Classification Techniques », in 2013 ACS INTERNATIONAL CONFERENCE ON COMPUTER SYSTEMS AND APPLICATIONS (AICCSA), 2013.
F. Z. Lahlou, Benbrahim, H., et Kassou, I., « Improving recommendations using context from users' reviews », in Proceedings of the 27th International Business Information Management Association Conference - Innovation Management and Education Excellence Vision 2020: From Regional Development Sustainability to Global Economic Growth, IBIMA 2016, 2016, p. 3312-3315.
F. Z. Lahlou, Benbrahim, H., et Kassou, I., « Textual context aware factorization machines: Improving recommendation by leveraging users' reviews », in ACM International Conference Proceeding Series, 2018, p. 64-69.
F. Zahra Lahlou, Benbrahim, H., et Kassou, I., « Improving Recommendations Using Context from Users' Reviews », in INNOVATION MANAGEMENT AND EDUCATION EXCELLENCE VISION 2020: FROM REGIONAL DEVELOPMENT SUSTAINABILITY TO GLOBAL ECONOMIC GROWTH, VOLS I - VI, 2016, p. 3312-3315.
F. Z. Lahlou, Mountassir, A., Benbrahim, H., et Kassou, I., « A Text Classification based method for context extraction from online reviews », in 2013 8th International Conference on Intelligent Systems: Theories and Applications, SITA 2013, 2013.
Y. Lahlou, Fkihi, S. E., et Faizi, R., « Automatic Detection of Fake News on Twitter by Using a New Feature: User Credibility », Lecture Notes in Networks and Systems, vol. 489 LNNS, p. 568-580, 2022.
F. Zahra Lahlou, Mountassir, A., Benbrahim, H., et Kassou, I., « A Text Classification Based Method for Context Extraction from Online Reviews », in 2013 8TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS: THEORIES AND APPLICATIONS (SITA), 2013.
F. Z. Lahlou, Benbrahimand, H., Mountassir, A., et Kassou, I., « Context extraction from reviews for Context Aware Recommendation using Text Classification techniques », in Proceedings of IEEE/ACS International Conference on Computer Systems and Applications, AICCSA, 2013.
C. Lahmar et Idri, A., « Deep hybrid architectures for diabetic retinopathy classification », Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization, 2022.
C. Lahmar et Idri, A., « On the value of deep learning for diagnosing diabetic retinopathy », Health and Technology, vol. 12, p. 89-105, 2022.
M. Lahmer, Belkasmi, M., et Ayoub, F., « Iterative threshold decoding of one step majority logic decodable block codes », in 2007 IEEE INTERNATIONAL SYMPOSIUM ON SIGNAL PROCESSING AND INFORMATION TECHNOLOGY, VOLS 1-3, 2007, p. 1059+.
S. Lahrichi, Rhanoui, M., Mikram, M., et Asri, B. E., « Toward a multimodal multitask model for neurodegenerative diseases diagnosis and progression prediction », in Proceedings of the 10th International Conference on Data Science, Technology and Applications, DATA 2021, 2021, p. 322-328.
M. Lakhdissi et Bounabat, B., « Toward a Novel Methodology for IT Strategic Planning. », Proceedings of the European Conference on Information Management & Evaluation, p. 263 - 273, 2011.
Z. Lakhili, A. Alami, E., Mesbah, A., Berrahou, A., et Qjidaa, H., « Deformable 3D Shape Classification Using 3D Racah Moments and Deep Neural Networks », in Procedia Computer Science, 2019, vol. 148, p. 12-20.
J. Lakhrouit, Baina, K., et Benali, K., « Model and Application Architecture Indicators of Evaluation the Enterprise Architecture », in NEW PERSPECTIVES IN INFORMATION SYSTEMS AND TECHNOLOGIES, VOL 2, 2014, vol. 276, p. 63-71.
J. Lakhrouit et Baina, K., « Evaluating enterprise architecture complexity using fuzzy AHP approach », in Proceedings of 2015 IEEE World Conference on Complex Systems, WCCS 2015, 2015.

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