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138 results on '"Mohamed Lahby"'

1. Modeling and Mathematical Analysis of Liquidity Risk Contagion in the Banking System

Author

Hamza Mourad, Said Fahim, Adriana Burlea-Schiopoiu, Mohamed Lahby, and Abdelbaki Attioui

Subjects
Mathematics, QA1-939
Abstract

In recent times, all world banks have been threatened by the liquidity risk problem. This phenomenon represents a devastating financial threat to banks and may lead to irrecoverable consequences in case of negligence or underestimation. In this article, we study a mathematical model that describes the contagion of liquidity risk in the banking system based on the SIR epidemic model simulation. The model consists of three ordinary differential equations illustrating the interaction between banks susceptible or affected by liquidity risk and tending towards bankruptcy. We have demonstrated the bornness and positivity of the solutions, and we have mathematically analyzed this system to demonstrate how to control the banking system’s stability. Numerical simulations have been illustrated by using real data to support the analytical results and prove the effects of different system parameters studied on the contagion of liquidity risk.

Published
2022
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2. A Bagged Ensemble Convolutional Neural Networks Approach to Recognize Insurance Claim Frauds

Author

Youness Abakarim, Mohamed Lahby, and Abdelbaki Attioui

Subjects
automobile insurance, ensemble learning, fraud claims, parallel learning, DCNN, Technology, Applied mathematics. Quantitative methods, T57-57.97
Abstract

Fighting fraudulent insurance claims is a vital task for insurance companies as it costs them billions of dollars each year. Fraudulent insurance claims happen in all areas of insurance, with auto insurance claims being the most widely reported and prominent type of fraud. Traditional methods for identifying fraudulent claims, such as statistical techniques for predictive modeling, can be both costly and inaccurate. In this research, we propose a new way to detect fraudulent insurance claims using a data-driven approach. We clean and augment the data using analysis-based techniques to deal with an imbalanced dataset. Three pre-trained Convolutional Neural Network (CNN) models, AlexNet, InceptionV3 and Resnet101, are selected and minimized by reducing the redundant blocks of layers. These CNN models are stacked in parallel with a proposed 1D CNN model using Bagged Ensemble Learning, where an SVM classifier is used to extract the results separately for the CNN models, which is later combined using the majority polling technique. The proposed method was tested on a public dataset and produced an accuracy of 98%, with a 2% Brier score loss. The numerical experiments demonstrate that the proposed approach achieves promising results for detecting fake accident claims.

Published
2023
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3. A novel modeling approach for vertical handover based on dynamic k-partite graph in heterogeneous networks

Author

Mohamed Lahby, Ayoub Essouiri, and Abderrahim Sekkaki

Subjects
Information technology, T58.5-58.64
Abstract

The future network world will be embedded with different generations of wireless technologies, such as 3G, 4G and 5G. At the same time, the development of new devices equipped with multiple interfaces is growing rapidly in recent years. As a consequence, the vertical handover protocol is developed in order to provide ubiquitous connectivity in the heterogeneous wireless environment. Indeed, by using this protocol, the users have opportunities to be connected to the Internet through a variety of wireless technologies at any time and anywhere. The main challenge of this protocol is how to select the best access network in terms of Quality of Service (QoS) for users. For that, many algorithms have been proposed and developed to deal with the issue in recent studies. However, all existing algorithms permit only the selection of one access network from the available networks during the vertical handover process. To cope with this problem, in this paper we propose a new approach based on k-partite graph. Firstly, we introduce k-partite graph theory to model the vertical handover problem. Secondly, the selection of the best path is performed by a robust and lightweight mechanism based on cost function and Dijkstra’s algorithm. The experimental results show that the proposed approach can achieve better performance of QoS than the existing algorithms for FTP traffic and video streaming. Keywords: Heterogeneous wireless networks, Vertical handover, K-partite graph, Cost function, QoS, Mininet

Published
2019
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34. Modeling and Mathematical Analysis of Liquidity Risk Contagionin the Banking System an optimal control

Author

SAID FAHIM, Hamza MOURAD, and Mohamed LAHBY

Abstract

Modeling the spread of contagiousness is well known in epidemiology. However, theapplication of spread modeling to the banking system is quite recent.Optimal control theory analyzes the properties of controlled systems, ie systems on which one canact by means of a command.In this work, we present a liquidity risk problem in the banking system with an optimal controlterm is formulated in order to study the impact of a possible central bank measure in the economy,simulating data from the largest European banks.Then, the proposed approach allows qualitative specifications of contagion in obtaining bankingand adequate analysis and prognosis within the development of the financial and macroeconomicsector as a whole. We show that our model de-reflects the reality of the largest European banks.The simulations were done with optimal control python, and the main results are taken for threedistinct scenarios.

Published
2022
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43. A novel modeling approach for vertical handover based on dynamic k-partite graph in heterogeneous networks

Author

Ayoub Essouiri, Mohamed Lahby, and Abderrahim Sekkaki

Subjects
Vertical handover, Access network, lcsh:T58.5-58.64, lcsh:Information technology, Computer Networks and Communications, business.industry, Computer science, Quality of service, ComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS, 020206 networking & telecommunications, Graph theory, 02 engineering and technology, 020210 optoelectronics & photonics, Hardware and Architecture, 0202 electrical engineering, electronic engineering, information engineering, Graph (abstract data type), The Internet, business, Dijkstra's algorithm, Heterogeneous network, Computer network
Abstract

The future network world will be embedded with different generations of wireless technologies, such as 3G, 4G and 5G. At the same time, the development of new devices equipped with multiple interfaces is growing rapidly in recent years. As a consequence, the vertical handover protocol is developed in order to provide ubiquitous connectivity in the heterogeneous wireless environment. Indeed, by using this protocol, the users have opportunities to be connected to the Internet through a variety of wireless technologies at any time and anywhere. The main challenge of this protocol is how to select the best access network in terms of Quality of Service (QoS) for users. For that, many algorithms have been proposed and developed to deal with the issue in recent studies. However, all existing algorithms permit only the selection of one access network from the available networks during the vertical handover process. To cope with this problem, in this paper we propose a new approach based on k-partite graph. Firstly, we introduce k-partite graph theory to model the vertical handover problem. Secondly, the selection of the best path is performed by a robust and lightweight mechanism based on cost function and Dijkstra’s algorithm. The experimental results show that the proposed approach can achieve better performance of QoS than the existing algorithms for FTP traffic and video streaming. Keywords: Heterogeneous wireless networks, Vertical handover, K-partite graph, Cost function, QoS, Mininet

Published
2019
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44. Empowering Digital Education with ChatGPT : From Theoretical to Practical Applications

Author

Mohamed Lahby and Mohamed Lahby

Subjects
ChatGPT, Artificial intelligence--Educational application, Web-based instruction, Language and languages--Study and teaching
Abstract

Recently, there has been a significant increase in the development and interest in applying generative AI across various domains, including education. The emergence of large language models (LLMs), such as the ChatGPT tool, fueled by advancements in generative AI, is profoundly reshaping education. The use of the ChatGPT tool offers personalized support, improves accessibility, and introduces innovative methods for students and educators to engage with information and learning materials. Furthermore, ChatGPT facilitates a wide range of language learning services, including language instruction, speech recognition, pronunciation feedback, and immersive virtual simulations for hands-on learning experiences.This book explores the transformative potential of the ChatGPT tool within education, shedding light on the opportunities that arise through the integration of the ChatGPT tool into various aspects of the learning process. It serves as a platform for the community to share cutting-edge research ideas concerning the use of the ChatGPT tool in digital education. Readers will discover how the ChatGPT tool can enhance student engagement, foster personalized learning experiences, facilitate intelligent tutoring systems, support virtual classroom interactions, and revolutionize assessment and feedback mechanisms.

Published
2024

45. General Aspects of Applying Generative AI in Higher Education : Opportunities and Challenges

Author

Mohamed Lahby, Yassine Maleh, Antonio Bucchiarone, Satu Elisa Schaeffer, Mohamed Lahby, Yassine Maleh, Antonio Bucchiarone, and Satu Elisa Schaeffer

Subjects
Artificial intelligence--Educational applications, Education, Higher--Data processing
Abstract

This book explores the transformative impact of generative artificial intelligence (GenAI) on teaching and learning, examining how recent advancements in GenAI are revolutionizing educational practices across disciplines. The book is organized into three parts: an overview of GenAI in education, its application in diverse educational contexts, and future perspectives on how educators and GenAI can interface. The first part addresses the pressing concerns within the educational landscape, both the bridges GenAI allows us to build and the remaining as well as the emerging gaps. The middle part explores specific academic disciplines, such as history, sports medicine, mathematics, engineering, and the humanities, dissecting the influence of GenAI on each. The final part looks ahead, discussing the ethical implications, the evolving role of prompting, and innovative frameworks for personalized learning. By presenting a balanced view of the opportunities that are now within reach through GenAI and the challenges such leaps pose to the way we learn and teach, this book allows interested educators to learn from the early-adopting contributors to fruitfully and responsibly integrate such technologies into their pedagogical practices. It serves as a resource for anyone interested in the future of educational practices and research of education, offering insights that can spark further exploration and discussion within the academic community and educational policy makers.

Published
2024

46. Enhancing Modeling for Network Selection Using Graph Theory in Beyond 4G Networks

Author

Mohamed Lahby

Subjects
0202 electrical engineering, electronic engineering, information engineering, 020206 networking & telecommunications, 020201 artificial intelligence & image processing, 02 engineering and technology
Abstract

In recent years, the development and the deployment of different generation systems such as 3G (UMTS, Wi-Fi), 4G (LTE, WIMAX), and 5G have become a reality for different telecommunication operators. At the same time, the development of new mobile devices with multiple interfaces have shifted the behavior of users concerning the utilization of the internet. Additionally, several streaming servers are available to provide real time applications such as e-commerce transactions, video streaming, online gaming, etc. As a result, the users have the privilege to use different multimedia applications at anytime and anywhere. The major trend in Beyond 4G networks is determining the best access network for the end user in terms of quality of service (QoS) during the network selection decision. Thus, in this article, the authors investigate graph theory and the AHP approach to deal with the network selection issue. The experimental results show that the proposed policy can achieve a significant performance in terms of QoS metrics for real-time streaming than conventional algorithms.

Published
2021
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50. Internet of Unmanned Things (IoUT) and Mission-based Networking

Author

Chaker Abdelaziz Kerrache, Carlos Calafate, Abderrahmane Lakas, Mohamed Lahby, Chaker Abdelaziz Kerrache, Carlos Calafate, Abderrahmane Lakas, and Mohamed Lahby

Subjects
Cooperating objects (Computer systems), Automotive engineering, Transportation engineering, Traffic engineering, Telecommunication
Abstract

This book discusses the potential of the Internet of Unmanned Things (IoUT), which is considered a promising paradigm resulting in numerous applications including shipment of goods, home package delivery, crop monitoring, agricultural surveillance, and rescue operations. The authors discuss how IoUT nodes collaborate with each other in ad hoc manner through a Line-of-Sight (LoS) link to exchange data packets. Also discussed is how Unmanned Arial Vehicles (UAVs) can communicate with fixed ground stations, with an air traffic controller, or through a Non-Line-of-Sight (NLoS) link with a satellite-aided controller, generally based on preloaded missions. The authors go on to cover how to tackle issues that arise with dissimilar communication technologies. They cover how various problems can appear in inter-UAV and UAV-to-X communications including energy management, lack of security and the unreliability of wireless communication links, and handover from LoS to NLoS, and vice versa. In this book, the editors invited front-line researchers and authors to submit research exploring emerging technologies for IoUT and mission-based networking and how to overcome challenges.

Published
2023

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