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343 results on '"Chabchoub, Habib"'

3. TinySiamese Network for Biometric Analysis

Author

Jarraya, Islem, Hamdani, Tarek M., Chabchoub, Habib, and Alimi, Adel M.

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Biometric recognition is the process of verifying or classifying human characteristics in images or videos. It is a complex task that requires machine learning algorithms, including convolutional neural networks (CNNs) and Siamese networks. Besides, there are several limitations to consider when using these algorithms for image verification and classification tasks. In fact, training may be computationally intensive, requiring specialized hardware and significant computational resources to train and deploy. Moreover, it necessitates a large amount of labeled data, which can be time-consuming and costly to obtain. The main advantage of the proposed TinySiamese compared to the standard Siamese is that it does not require the whole CNN for training. In fact, using a pre-trained CNN as a feature extractor and the TinySiamese to learn the extracted features gave almost the same performance and efficiency as the standard Siamese for biometric verification. In this way, the TinySiamese solves the problems of memory and computational time with a small number of layers which did not exceed 7. It can be run under low-power machines which possess a normal GPU and cannot allocate a large RAM space. Using TinySiamese with only 8 GO of memory, the matching time decreased by 76.78% on the B2F (Biometric images of Fingerprints and Faces), FVC2000, FVC2002 and FVC2004 while the training time for 10 epochs went down by approximately 93.14% on the B2F, FVC2002, THDD-part1 and CASIA-B datasets. The accuracy of the fingerprint, gait (NM-angle 180 degree) and face verification tasks was better than the accuracy of a standard Siamese by 0.87%, 20.24% and 3.85% respectively. TinySiamese achieved comparable accuracy with related works for the fingerprint and gait classification tasks.

Published
2023

7. A Hybrid Approach Using 2D CNN and Attention-Based LSTM for Parkinson’s Disease Detection from Video

Author

Krichene, Emna, Jarraya, Islem, Dhieb, Thameur, Mahfouf, Zohra, Neji, Mohamed, Farhat, Nouha, Smaoui, Emna, Hamdani, Tarek M., Damak, Mariem, Mhiri, Chokri, Chabchoub, Habib, Ouahada, Khmaies, Alimi, Adel M., Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Nguyen, Ngoc Thanh, editor, Franczyk, Bogdan, editor, Ludwig, André, editor, Núñez, Manuel, editor, Treur, Jan, editor, Vossen, Gottfried, editor, and Kozierkiewicz, Adrianna, editor

Published
2024
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9. Time to Revisit Existing Student's Performance Evaluation Approach in Higher Education Sector in a New Era of ChatGPT -- A Case Study

Author

Chaudhry, Iffat Sabir, Sarwary, Sayed Ahmad M., El Refae, Ghaleb A., and Chabchoub, Habib

Abstract

Artificial intelligence-based tools are rapidly revolutionizing the field of higher education, yet to be explored in terms of their impact on existing higher education institutions' (HEIs) practices adopted for continuous learning improvement, given the sparsity of the literature and empirical experiments in undergraduate degree programs. After the entry of ChatGPT--a conversational artificial intelligence (AI) tool that uses a deep learning model to generate human-like text response based on provided input--it has become crucial for HEIs to be exposed to the implications of AI-based tools on students' learning outcomes, commonly measured using an assessment-based approach to improve program quality, teaching effectiveness, and other learning support. An empirical study has been conducted to test the ChatGPT capability of solving a variety of assignments (from different level courses of undergraduate degree programs) to compare its performance with the highest scored student(s). Further, the ChatGPT-generated assignments were tested using the best-known tools for plagiarism detection to determine whether they could pass the academic integrity tests, including Turnitin, GPTZero, and Copyleaks. The study reported the limitations of the Bot and highlighted the implications of the newly launched AI-based ChatGPT in academia, which calls for HEIs' managers and regulators to revisit their existing practices used to monitor students' learning progress and improve their educational programs.

Published
2023
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10. Voronoi Diagram-Based Approach to Identify Maritime Corridors

Author

Masmoudi, Mariem, Chakhar, Salem, Chabchoub, Habib, 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, Troiano, Luigi, editor, Vaccaro, Alfredo, editor, Kesswani, Nishtha, editor, Díaz Rodriguez, Irene, editor, Brigui, Imene, editor, and Pastor-Escuredo, David, editor

Published
2023
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14. Taylor-based Optimized Recursive Extended Exponential Smoothed Neural Networks Forecasting Method

Author

Krichene, Emna, Ouarda, Wael, Chabchoub, Habib, and Alimi, Adel M.

Subjects
Computer Science - Neural and Evolutionary Computing, Computer Science - Artificial Intelligence
Abstract

A newly introduced method called Taylor-based Optimized Recursive Extended Exponential Smoothed Neural Networks Forecasting method is applied and extended in this study to forecast numerical values. Unlike traditional forecasting techniques which forecast only future values, our proposed method provides a new extension to correct the predicted values which is done by forecasting the estimated error. Experimental results demonstrated that the proposed method has a high accuracy both in training and testing data and outperform the state-of-the-art RNN models on Mackey-Glass, NARMA, Lorenz and Henon map datasets.

Published
2018

15. Testing the Success of Real-Time Online Delivery Channel Adopted by Higher Education Institutions in the United Arab Emirates during the COVID-19 Pandemic

Author

Chaudhry, Iffat Sabir, Paquibut, Rene, Islam, AbuReza, and Chabchoub, Habib

Abstract

E-learning was mandated for all the higher education institutions (HEI) in the United Arab Emirates (UAE) to encounter the pandemic and practice social distancing in year 2020. This led education institutions to shift from face-to-face traditional classroom settings to online education channels for delivering education to their students despite being less familiar with the real-time remote learning. The current study attempts to measure the success of e-learning systems adopted by the HEIs in UAE. An e-learning system success measuring the framework based on DeLone and McLean (J Manage Inf Syst 19(4):9-30, 2003) was developed including the measures of quality, system use, perceptual benefits and future outcomes from students' perspective. A survey was conducted from more than 1200 students studying at different higher education institutions of the UAE region. The findings have implications for educators and policy-makers recommending the success factors of e-learning delivery channels in this region.

Published
2021
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16. A Medical Image Classification Model based on Quantum-Inspired Genetic Algorithm.

Author

Ibrahim, Hussain K., Rokbani, Nizar, Wali, Ali, Ouahada, Khmaies, Chabchoub, Habib, and Alimi, Adel M.

Subjects
MACHINE learning, IMAGE recognition (Computer vision), FEATURE selection, GENETIC algorithms, QUANTUM computing
Abstract

This study used a Quantum-Inspired Genetic Algorithm (QIGA) to select the proper functionality and reduce the dimensions, classification time, and computational cost of a learning dataset. QIGA reduces the complexity of solutions and improves the selection of the best features. The application of quantum principles, in particular the unpredictability of quantum chromosomes, which are represented by qubits, can help in investigating a significantly more extensive solution space. QIGA offers a novel approach to feature selection in optimization problems. Using principles from quantum computing, this algorithm aims to enhance the efficiency and effectiveness of the feature selection process to increase performance. This indicates that features of both exploration and exploitation are embodied by QIGA without requiring massive amounts of data. Considerable gains in classification accuracy were achieved compared to traditional methods. The dynamic design of the models through the evolutionary mechanism in QIGA enables the optimization process to adapt to varying probabilities produced from the qubit overlay via the quantum rotation gate. This is contrary to traditional methods. The model using QIGA offered a more precise classification than the model optimized by Genetic Algorithms (GA). The proposed method achieved superior performance in terms of classification accuracy, with a score of more than 98%, compared to GA, which achieved a classification accuracy of 94%. [ABSTRACT FROM AUTHOR]

Published
2024
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20. The VESP Model

Author

Lahmar, Arij, primary, Chabchoub, Habib, additional, Galasso, François, additional, and Lamothe, Jacques, additional

Published
2020
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21. A Supply Chain Risk Index Estimation Methodological Framework Using Exposure Assessment

Author

Lahmar, Arij, Galasso, François, Chabchoub, Habib, Lamothe, Jacques, Rannenberg, Kai, Editor-in-chief, Sakarovitch, Jacques, Series editor, Goedicke, Michael, Series editor, Tatnall, Arthur, Series editor, Neuhold, Erich J., Series editor, Pras, Aiko, Series editor, Tröltzsch, Fredi, Series editor, Pries-Heje, Jan, Series editor, Whitehouse, Diane, Series editor, Reis, Ricardo, Series editor, Furnell, Steven, Series editor, Furbach, Ulrich, Series editor, Winckler, Marco, Series editor, Rauterberg, Matthias, Series editor, Camarinha-Matos, Luis M., editor, Afsarmanesh, Hamideh, editor, and Fornasiero, Rosanna, editor

Published
2017
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23. Integration of Case Based Reasoning in Multi-agent System for the Real-Time Container Stacking in Seaport Terminals

Author

Rekik, Ines, Elkosantini, Sabeur, Chabchoub, Habib, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Martínez de Pisón, Francisco Javier, editor, Urraca, Rubén, editor, Quintián, Héctor, editor, and Corchado, Emilio, editor

Published
2017
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29. Toward a Knowledge Based Multi-agent Architecture for the Reactive Container Stacking in Seaport Terminals

Author

Rekik, Ines, Elkosantini, Sabeur, Chabchoub, Habib, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Rutkowski, Leszek, editor, Korytkowski, Marcin, editor, Scherer, Rafał, editor, Tadeusiewicz, Ryszard, editor, Zadeh, Lotfi A., editor, and Zurada, Jacek M., editor

Published
2016
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31. Towards an Integrated Model of Supply Chain Risks: An Alignment Between Supply Chain Characteristics and Risk Dimensions

Author

Lahmar, Arij, Galasso, François, Chabchoub, Habib, Lamothe, Jacques, Rannenberg, Kai, Editor-in-chief, Sakarovitch, Jacques, Series editor, Goedicke, Michael, Series editor, Tatnall, Arthur, Series editor, Neuhold, Erich J., Series editor, Pras, Aiko, Series editor, Tröltzsch, Fredi, Series editor, Pries-Heje, Jan, Series editor, Whitehouse, Diane, Series editor, Reis, Ricardo, Series editor, Murayama, Yuko, Series editor, Furbach, Ulrich, Series editor, Gulliksen, Jan, Series editor, Rauterberg, Matthias, Series editor, Camarinha-Matos, Luis M., editor, Bénaben, Frédérick, editor, and Picard, Willy, editor

Published
2015
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35. Analysis of municipal solid waste collection using GIS and multi-criteria decision aid

Author

Amal, Louati, Son, Le Hoang, Chabchoub, Habib, and Lahiani, Hanene

Abstract

Global average temperature increases and causes extreme weather events, killing millions of people and affecting economic stability. Municipal solid waste (MSW) is one of the primary factors that contribute to climate change that is the main concern of various municipalities in the world. In this paper, a two-step systematic approach is proposed to analyze municipal solid waste collection (MSWC) in Sfax, the second most populated city in Tunisia. In the first step, three feasible waste collection scenarios were suggested and have gained the consensus of decision makers and stakeholders. In the second, a geographic information system–based multi-criteria decision aid approach is proposed to identify the most appropriate scenario. Firstly, the Network Analyst function in ArcGIS is used to determine the optimal routes with the traveling distances and operational time of vehicles associated to each scenario. Secondly, a ranking of scenarios is produced by ELECTRE III method. Six pseudo criteria such as fuel consumption cost, gas emission, reliability, road length, and compatibility with the national energy policy were taken into account. The results suggest a relatively efficient and environment-friendly scenario where all vehicles start their trips from the depot, collect garbage from the gather sites, and unload waste at a transfer station then travel back to the depot. The methodology can be adopted into similar contexts to improve the effectiveness of MSW collection through the systematic use of GIS.

Published
2024
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37. Genetic Algorithm for Patients Scheduling in Emergency Department: A Case Study.

Author

Jlassi, Jihène, Rekik, Ines, Elloumi, Sonda, and Chabchoub, Habib

Subjects
MEDICAL care wait times, HOSPITAL emergency services, GENETIC algorithms, INTEGER programming
Abstract

Emergency Departments (EDs) in hospitals typically aim to deliver accurate and rapid treatment to patients. The scheduling of patients in EDs is a challenging task that depends not only on the triage process but also on the availability of both human (staff) and material resources. In this paper, a real case study is conducted to tackle the issues coming from crowding and long waiting times for patients processing at the largest hospital in the region of Sfax (Tunisia). An integer programming formulation is proposed to minimize total patient waiting times (PWT) in EDs subject to procedural and staff availability constraints. Due to the large scale of the treated problem, a Genetic Algorithm (GA) is developed as a solution method. The efficiency of the presented approach is evaluated based on diverse sets of theoretically and randomly generated instances in a first way and on the actual data obtained from the real case study hospital in a second way. Results show significant improvements compared to the First Come First Served (FCFS) real case study's rule. The decrease in patient waiting time ranges between 18.84 % to 27.45%. [ABSTRACT FROM AUTHOR]

Published
2023
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45. A Decision Support System Based on Metaheuristic Model for Aircrafts Landing Problems

Author

Hbaieb, Sonda, Dhouib, Souhail, Chabchoub, Habib, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Meersman, Robert, editor, Dillon, Tharam, editor, and Herrero, Pilar, editor

Published
2011
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49. The First Belief Dominance: A New Approach in Evidence Theory for Comparing Basic Belief Assignments

Author

Boujelben, Mohamed Ayman, De Smet, Yves, Frikha, Ahmed, Chabchoub, Habib, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Rossi, Francesca, editor, and Tsoukias, Alexis, editor

Published
2009
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