15 citations · 35 across the 19 of their papers we have counts for
24 papers
Best Memory Architecture Exploration under Parameters Variations accelerated with Machine Learning
Antonios Tragoudaras, Charalampos Antoniadis, Yehia Massoud
The design of effective memory architecture is of utmost importance in modern computing systems. However, the design of memory subsystems is even more difficult today because proce…
Chance-Aware Lane Change with High-Level Model Predictive Control Through Curriculum Reinforcement Learning
Yubin Wang, Yulin Li, Zengqi Peng +2
Lane change in dense traffic typically requires the recognition of an appropriate opportunity for maneuvers, which remains a challenging problem in self-driving. In this work, we p…
Dissolving Is Amplifying: Towards Fine-Grained Anomaly Detection
Jian Shi, Pengyi Zhang, Ni Zhang +2
Medical imaging often contains critical fine-grained features, such as tumors or hemorrhages, crucial for diagnosis yet potentially too subtle for detection with conventional metho…
Service Discovery in Social Internet of Things using Graph Neural Networks
Aymen Hamrouni, Hakim Ghazzai, Yehia Massoud
Internet-of-Things (IoT) networks intelligently connect thousands of physical entities to provide various services for the community. It is witnessing an exponential expansion, whi…
A Hybrid Artificial Neural Network for Task Offloading in Mobile Edge Computing
Raby Hamadi, Abdullah Khanfor, Hakim Ghazzai +1
Edge Computing (EC) is about remodeling the way data is handled, processed, and delivered within a vast heterogeneous network. One of the fundamental concepts of EC is to push the…
A Machine Learning Smartphone-based Sensing for Driver Behavior Classification
Sarra Ben Brahim, Hakim Ghazzai, Hichem Besbes +1
Driver behavior profiling is one of the main issues in the insurance industries and fleet management, thus being able to classify the driver behavior with low-cost mobile applicati…
Low Complexity Recruitment for Collaborative Mobile Crowdsourcing Using Graph Neural Networks
Aymen Hamrouni, Hakim Ghazzai, Turki Alelyani +1
Collaborative Mobile crowdsourcing (CMCS) allows entities, e.g., local authorities or individuals, to hire a team of workers from the crowd of connected people, to execute complex…
Topic Modeling and Progression of American Digital News Media During the Onset of the COVID-19 Pandemic
Xiangpeng Wan, Michael C. Lucic, Hakim Ghazzai +1
Currently, the world is in the midst of a severe global pandemic, which has affected all aspects of people's lives. As a result, there is a deluge of COVID-related digital media ar…
Towards Collaborative Mobile Crowdsourcing
Aymen Hamrouni, Hakim Ghazzai, Turki Alelyani +1
Mobile Crowdsourcing (MC) is an effective way of engaging large groups of smart devices to perform tasks remotely while exploiting their built-in features. It has drawn great atten…
A Social IoT-driven Pedestrian Routing Approach during Epidemic Time
Abdullah Khanfor, Hamdi Friji, Hakim Ghazzai +1
The unprecedented worldwide spread of coronavirus disease has significantly sped up the development of technology-based solutions to prevent, combat, monitor, or predict pandemics…
Elevated LiDAR Placement under Energy and Throughput Capacity Constraints
Michael C. Lucic, Hakim Ghazzai, Yehia Massoud
Elevated LiDAR (ELiD) has the potential to hasten the deployment of Autonomous Vehicles (AV), as ELiD can reduce energy expenditures associated with AVs, and can also be utilized f…
A Generative Graph Method to Solve the Travelling Salesman Problem
Amal Nammouchi, Hakim Ghazzai, Yehia Massoud
The Travelling Salesman Problem (TSP) is a challenging graph task in combinatorial optimization that requires reasoning about both local node neighborhoods and global graph structu…
Computational Resource Allocation for Edge Computing in Social Internet-of-Things
Abdullah Khanfor, Raby Hamadi, Hakim Ghazzai +3
The heterogeneity of the Internet-of-things (IoT) network can be exploited as a dynamic computational resource environment for many devices lacking computational capabilities. A sm…
Graph Neural Networks-based Clustering for Social Internet of Things
Abdullah Khanfor, Amal Nammouchi, Hakim Ghazzai +3
In this paper, we propose a machine learning process for clustering large-scale social Internet-of-things (SIoT) devices into several groups of related devices sharing strong relat…
A Photo-Based Mobile Crowdsourcing Framework for Event Reporting
Aymen Hamrouni, Hakim Ghazzai, Mounir Frikha +1
Mobile Crowdsourcing (MCS) photo-based is an arising field of interest and a trending topic in the domain of ubiquitous computing. It has recently drawn substantial attention of th…
A Stochastic Team Formation Approach for Collaborative Mobile Crowdsourcing
Aymen Hamrouni, Hakim Ghazzai, Turki Alelyani +1
Mobile Crowdsourcing (MCS) is the generalized act of outsourcing sensing tasks, traditionally performed by employees or contractors, to a large group of smart-phone users by means…
Optimal Team Recruitment Strategies for Collaborative Mobile Crowdsourcing Systems
Aymen Hamrouni, Hakim Ghazzai, Turki Alelyani +1
The wide spread of mobile devices has enabled a new paradigm of innovation called Mobile Crowdsourcing (MCS) where the concept is to allow entities, e.g., individuals or local auth…
Leveraging Personal Navigation Assistant Systems Using Automated Social Media Traffic Reporting
Xiangpeng Wan, Hakim Ghazzai, Yehia Massoud
Modern urbanization is demanding smarter technologies to improve a variety of applications in intelligent transportation systems to relieve the increasing amount of vehicular traff…
Word Embedding-based Text Processing for Comprehensive Summarization and Distinct Information Extraction
Xiangpeng Wan, Hakim Ghazzai, Yehia Massoud
In this paper, we propose two automated text processing frameworks specifically designed to analyze online reviews. The objective of the first framework is to summarize the reviews…
Scalable and Secure Architecture for Distributed IoT Systems
Najmeddine Dhieb, Hakim Ghazzai, Hichem Besbes +1
Internet-of-things (IoT) is perpetually revolutionizing our daily life and rapidly transforming physical objects into an ubiquitous connected ecosystem. Due to their massive deploy…
A Trustworthy Recruitment Process for Spatial Mobile Crowdsourcing in Large-scale Social IoT
Abdullah Khanfor, Aymen Hamrouni, Hakim Ghazzai +2
Spatial Mobile Crowdsourcing (SMCS) can be leveraged by exploiting the capabilities of the Social Internet-of-Things (SIoT) to execute spatial tasks. Typically, in SMCS, a task req…
Automated Service Discovery for Social Internet-of-Things Systems
Abdullah Khanfor, Hakim Ghazzai, Ye Yang +2
In this paper, we propose to design an automated service discovery process to allow mobile crowdsourcing task requesters select a small set of devices out of a large-scale Internet…
Autonomous UAV Navigation: A DDPG-based Deep Reinforcement Learning Approach
Omar Bouhamed, Hakim Ghazzai, Hichem Besbes +1
In this paper, we propose an autonomous UAV path planning framework using deep reinforcement learning approach. The objective is to employ a self-trained UAV as a flying mobile uni…
A Latency-Aware Task Offloading in Mobile Edge Computing Network for Distributed Elevated LiDAR
Michael C. Lucic, Hakim Ghazzai, Ahmad Alsharoa +1
Recently, elevated LiDAR (ELiD) has been proposed as an alternative to local LiDAR sensors in autonomous vehicles (AV) because of the ability to reduce costs and computational requ…