379 citations · 866 across the 40 of their papers we have counts for
43 papers
A Multi-Agent DRL-Based Framework for Optimal Resource Allocation and Twin Migration in the Multi-Tier Vehicular Metaverse
Nahom Abishu Hayla, A. Mohammed Seid, Aiman Erbad +3
Although multi-tier vehicular Metaverse promises to transform vehicles into essential nodes -- within an interconnected digital ecosystem -- using efficient resource allocation and…
Multi-UAV Multi-RIS QoS-Aware Aerial Communication Systems using DRL and PSO
Marwan Dhuheir, Aiman Erbad, Ala Al-Fuqaha +1
Recently, Unmanned Aerial Vehicles (UAVs) have attracted the attention of researchers in academia and industry for providing wireless services to ground users in diverse scenarios…
Fair Selection of Edge Nodes to Participate in Clustered Federated Multitask Learning
Abdullatif Albaseer, Mohamed Abdallah, Ala Al-Fuqaha +3
Clustered federated Multitask learning is introduced as an efficient technique when data is unbalanced and distributed amongst clients in a non-independent and identically distribu…
Semi-decentralized Inference in Heterogeneous Graph Neural Networks for Traffic Demand Forecasting: An Edge-Computing Approach
Mahmoud Nazzal, Abdallah Khreishah, Joyoung Lee +3
Prediction of taxi service demand and supply is essential for improving customer's experience and provider's profit. Recently, graph neural networks (GNNs) have been shown promisin…
Metaverse for Wireless Systems: Architecture, Advances, Standardization, and Open Challenges
Latif U. Khan, Mohsen Guizani, Dusit Niyato +2
The growing landscape of emerging wireless applications is a key driver toward the development of novel wireless system designs. Such a design can be based on the metaverse that us…
Mobile-IRS Assisted Next Generation UAV Communication Networks
Hazim Shakhatreh, Ahmad Sawalmeh, Ali H Alenezi +3
Prior research on intelligent reflection surface (IRS)-assisted unmanned aerial vehicle (UAV) communications has focused on a fixed location for the IRS or mounted on a UAV. The as…
Explainable Event Recognition
Imran Khan, Kashif Ahmad, Namra Gul +3
The literature shows outstanding capabilities for CNNs in event recognition in images. However, fewer attempts are made to analyze the potential causes behind the decisions of the…
Client Selection Approach in Support of Clustered Federated Learning over Wireless Edge Networks
Abdullatif Albaseer, Mohamed Abdallah, Ala Al-Fuqaha +1
Clustered Federated Multitask Learning (CFL) was introduced as an efficient scheme to obtain reliable specialized models when data is imbalanced and distributed in a non-i.i.d. (no…
Fine-Grained Data Selection for Improved Energy Efficiency of Federated Edge Learning
Abdullatif Albaseer, Mohamed Abdallah, Ala Al-Fuqaha +1
In Federated edge learning (FEEL), energy-constrained devices at the network edge consume significant energy when training and uploading their local machine learning models, leadin…
Deep Reinforcement Learning for Radio Resource Allocation and Management in Next Generation Heterogeneous Wireless Networks: A Survey
Abdulmalik Alwarafy, Mohamed Abdallah, Bekir Sait Ciftler +2
Next generation wireless networks are expected to be extremely complex due to their massive heterogeneity in terms of the types of network architectures they incorporate, the types…
Threshold-Based Data Exclusion Approach for Energy-Efficient Federated Edge Learning
Abdullatif Albaseer, Mohamed Abdallah, Ala Al-Fuqaha +1
Federated edge learning (FEEL) is a promising distributed learning technique for next-generation wireless networks. FEEL preserves the user's privacy, reduces the communication cos…
Sentiment Analysis of Users' Reviews on COVID-19 Contact Tracing Apps with a Benchmark Dataset
Kashif Ahmad, Firoj Alam, Junaid Qadir +8
Contact tracing has been globally adopted in the fight to control the infection rate of COVID-19. Thanks to digital technologies, such as smartphones and wearable devices, contacts…
Collaborative Federated Learning For Healthcare: Multi-Modal COVID-19 Diagnosis at the Edge
Adnan Qayyum, Kashif Ahmad, Muhammad Ahtazaz Ahsan +2
Despite significant improvements over the last few years, cloud-based healthcare applications continue to suffer from poor adoption due to their limitations in meeting stringent se…
Fake News Detection in Social Media using Graph Neural Networks and NLP Techniques: A COVID-19 Use-case
Abdullah Hamid, Nasrullah Shiekh, Naina Said +4
The paper presents our solutions for the MediaEval 2020 task namely FakeNews: Corona Virus and 5G Conspiracy Multimedia Twitter-Data-Based Analysis. The task aims to analyze tweets…
Flood Detection via Twitter Streams using Textual and Visual Features
Firoj Alam, Zohaib Hassan, Kashif Ahmad +4
The paper presents our proposed solutions for the MediaEval 2020 Flood-Related Multimedia Task, which aims to analyze and detect flooding events in multimedia content shared over T…
Floods Detection in Twitter Text and Images
Naina Said, Kashif Ahmad, Asma Gul +2
In this paper, we present our methods for the MediaEval 2020 Flood Related Multimedia task, which aims to analyze and combine textual and visual content from social media for the d…
Budgeted Online Selection of Candidate IoT Clients to Participate in Federated Learning
Ihab Mohammed, Shadha Tabatabai, Ala Al-Fuqaha +4
Machine Learning (ML), and Deep Learning (DL) in particular, play a vital role in providing smart services to the industry. These techniques however suffer from privacy and securit…
Particle Swarm Optimized Federated Learning For Industrial IoT and Smart City Services
Basheer Qolomany, Kashif Ahmad, Ala Al-Fuqaha +1
Most of the research on Federated Learning (FL) has focused on analyzing global optimization, privacy, and communication, with limited attention focusing on analyzing the critical…
Visual Sentiment Analysis from Disaster Images in Social Media
Syed Zohaib Hassan, Kashif Ahmad, Steven Hicks +4
The increasing popularity of social networks and users' tendency towards sharing their feelings, expressions, and opinions in text, visual, and audio content, have opened new oppor…
Trust-Based Cloud Machine Learning Model Selection For Industrial IoT and Smart City Services
Basheer Qolomany, Ihab Mohammed, Ala Al-Fuqaha +2
With Machine Learning (ML) services now used in a number of mission-critical human-facing domains, ensuring the integrity and trustworthiness of ML models becomes all-important. In…
Artificial Intelligence-Assisted Energy and Thermal Comfort Control for Sustainable Buildings: An Extended Representation of the Systematic Review
Ghezlane Halhoul Merabet, Mohamed Essaaidi, Mohamed Ben-Haddou +6
Different factors such as thermal comfort, humidity, air quality, and noise have significant combined effects on the acceptability and quality of the activities performed by the bu…
Analysis of Asymmetric Dual-Hop Energy Harvesting-Based Wireless Communication Systems in Mixed Fading Environments
Elmehdi Illi, Faissal El Bouanani, Paschalis C. Sofotasios +4
In this paper, the performance of a dual-hop energy harvesting-based fixed-gain amplify-and-forward (AF) relaying communication system, subject to fading impairments, is investigat…
Sentiment Analysis from Images of Natural Disasters
Syed Zohaib, Kashif Ahmad, Nicola Conci +1
Social media have been widely exploited to detect and gather relevant information about opinions and events. However, the relevance of the information is very subjective and rather…
Multi-Modal Machine Learning for Flood Detection in News, Social Media and Satellite Sequences
Kashif Ahmad, Konstantin Pogorelov, Mohib Ullah +4
In this paper we present our methods for the MediaEval 2019 Mul-timedia Satellite Task, which is aiming to extract complementaryinformation associated with adverse events from Soci…