no code implementations • 20 Jan 2024 • Marwan Dhuheir, Aiman Erbad, Ala Al-Fuqaha
Our simulation results prove that our introduced approach is better than the three state-of-the-art algorithms in providing coverage to strategic locations with fast convergence.
no code implementations • 19 Jan 2024 • Moqbel Hamood, Abdullatif Albaseer, Mohamed Abdallah, Ala Al-Fuqaha
Clustered Federated Multitask Learning (CFL) has gained considerable attention as an effective strategy for overcoming statistical challenges, particularly when dealing with non independent and identically distributed (non IID) data across multiple users.
no code implementations • 5 Oct 2023 • Shawqi Al-Maliki, Adnan Qayyum, Hassan Ali, Mohamed Abdallah, Junaid Qadir, Dinh Thai Hoang, Dusit Niyato, Ala Al-Fuqaha
This paper encompasses a taxonomy that highlights the emergence of AdvML4G, a discussion of the differences and similarities between AdvML4G and AdvML, a taxonomy covering social good-related concepts and aspects, an exploration of the motivations behind the emergence of AdvML4G at the intersection of ML4G and AdvML, and an extensive summary of the works that utilize AdvML4G as an auxiliary tool for innovating pro-social applications.
no code implementations • 11 Aug 2023 • Muhammad Atif Butt, Hassan Ali, Adnan Qayyum, Waqas Sultani, Ala Al-Fuqaha, Junaid Qadir
Semantic understanding of roadways is a key enabling factor for safe autonomous driving.
1 code implementation • 11 Jul 2023 • Hassan Ali, Adnan Qayyum, Ala Al-Fuqaha, Junaid Qadir
Secondly, we utilize the framework to propose two novel attacks: (1) Adversarial Membership Inference Attack (AMIA) efficiently utilizes the membership and the non-membership information of the subjects while adversarially minimizing a novel loss function, achieving 6% TPR on both Fashion-MNIST and MNIST datasets; and (2) Enhanced AMIA (E-AMIA) combines EMIA and AMIA to achieve 8% and 4% TPRs on Fashion-MNIST and MNIST datasets respectively, at 1% FPR.
no code implementations • 15 Jun 2023 • Mohammed Aledhari, Mohamed Rahouti, Junaid Qadir, Basheer Qolomany, Mohsen Guizani, Ala Al-Fuqaha
We also discuss the technical details related to the automatic driving comfort system, the response time of the AV driver, the comfort level of the AV, motion sickness, and related optimization technologies.
no code implementations • 25 Mar 2023 • Adnan Qayyum, Muhammad Bilal, Muhammad Hadi, Paweł Capik, Massimo Caputo, Hunaid Vohra, Ala Al-Fuqaha, Junaid Qadir
Recent advancements in technology, particularly in machine learning (ML), deep learning (DL), and the metaverse, offer great potential for revolutionizing surgical science.
no code implementations • 5 Mar 2023 • Hassan Ali, Muhammad Atif Butt, Fethi Filali, Ala Al-Fuqaha, Junaid Qadir
Although many works have studied these adversarial perturbations in general, the adversarial vulnerabilities of deep crowd-flow prediction models in particular have remained largely unexplored.
no code implementations • 3 Mar 2023 • Aos Mulahuwaish, Matthew Loucks, Basheer Qolomany, Ala Al-Fuqaha
We found differences in language and interest between these two groups regarding Bitcoin and that the opinion leaders of Twitter are not aligned with the majority of users.
1 code implementation • 28 Feb 2023 • Mahmoud Nazzal, Abdallah Khreishah, Joyoung Lee, Shaahin Angizi, Ala Al-Fuqaha, Mohsen Guizani
This approach minimizes inter-cloudlet communication thereby alleviating the communication overhead of the decentralized approach while promoting scalability due to cloudlet-level decentralization.
no code implementations • 2 Nov 2022 • Shawqi Al-Maliki, Faissal El Bouanani, Mohamed Abdallah, Junaid Qadir, Ala Al-Fuqaha
Data distribution shift is a common problem in machine learning-powered smart city applications where the test data differs from the training data.
no code implementations • 24 Oct 2022 • Adnan Qayyum, Muhammad Atif Butt, Hassan Ali, Muhammad Usman, Osama Halabi, Ala Al-Fuqaha, Qammer H. Abbasi, Muhammad Ali Imran, Junaid Qadir
Metaverse is expected to emerge as a new paradigm for the next-generation Internet, providing fully immersive and personalised experiences to socialize, work, and play in self-sustaining and hyper-spatio-temporal virtual world(s).
no code implementations • 29 Apr 2022 • Shadha Tabatabai, Ihab Mohammed, Basheer Qolomany, Abdullatif Albasser, Kashif Ahmad, Mohamed Abdallah, Ala Al-Fuqaha
The remaining cluster with surviving clients is then used for training the best FL model (i. e., remaining FL model).
no code implementations • 9 Feb 2022 • Khubaib Ahmad, Muhammad Asif Ayub, Kashif Ahmad, Jebran Khan, Nasir Ahmad, Ala Al-Fuqaha
We also provide an evaluation of the individual models where the highest F1-score of 0. 81 is obtained with the BERT model.
no code implementations • 30 Nov 2021 • Muhammad Asif Ayub, Khubaib Ahmad, Kashif Ahmad, Nasir Ahmad, Ala Al-Fuqaha
This paper presents our contributions to the MediaEval 2021 task namely "WaterMM: Water Quality in Social Multimedia".
no code implementations • 22 Nov 2021 • Syed Zohaib Hassan, Kashif Ahmad, Michael A. Riegler, Steven Hicks, Nicola Conci, Paal Halvorsen, Ala Al-Fuqaha
The Visual Sentiment Analysis task is being offered for the first time at MediaEval.
no code implementations • 26 Oct 2021 • Izzat Alsmadi, Kashif Ahmad, Mahmoud Nazzal, Firoj Alam, Ala Al-Fuqaha, Abdallah Khreishah, Abdulelah Algosaibi
These vulnerabilities allow adversaries to launch a diversified set of adversarial attacks on these algorithms in different applications of social media text processing.
no code implementations • 2 Oct 2021 • Imran Khan, Kashif Ahmad, Namra Gul, Talhat Khan, Nasir Ahmad, Ala Al-Fuqaha
The results of the study indicate that 78%, 84%, and 78% of the model decisions on natural disasters, sports, and social events datasets, respectively, are based onevent-related objects or regions.
no code implementations • 16 Aug 2021 • Abdullatif Albaseer, Mohamed Abdallah, Ala Al-Fuqaha, Aiman Erbad
Extensive experiments show that the proposed approach lowers the training time and accelerates the convergence rate by up to 50% while imbuing each client with a specialized model that is fit for its local data distribution.
no code implementations • 20 Jun 2021 • Abdullatif Albaseer, Mohamed Abdallah, Ala Al-Fuqaha, Aiman Erbad
Specifically, we consider a problem that aims to find the optimal user's resources, including the fine-grained selection of relevant training samples, bandwidth, transmission power, beamforming weights, and processing speed with the goal of minimizing the total energy consumption given a deadline constraint on the communication rounds of FEEL.
no code implementations • 25 May 2021 • Abdulmalik Alwarafy, Mohamed Abdallah, Bekir Sait Ciftler, Ala Al-Fuqaha, Mounir Hamdi
In this paper, we conduct a systematic in-depth, and comprehensive survey of the applications of DRL techniques in RRAM for next generation wireless networks.
no code implementations • 6 Apr 2021 • Ghezlane Halhoul Merabet, Mohamed Essaaidi, Mohamed Ben Haddou, Basheer Qolomany, Junaid Qadir, Muhammad Anan, Ala Al-Fuqaha, Mohamed Riduan Abid, Driss Benhaddou
Building operations represent a significant percentage of the total primary energy consumed in most countries due to the proliferation of Heating, Ventilation and Air-Conditioning (HVAC) installations in response to the growing demand for improved thermal comfort.
no code implementations • 6 Apr 2021 • Senthil Kumar Jagatheesaperumal, Mohamed Rahouti, Kashif Ahmad, Ala Al-Fuqaha, Mohsen Guizani
In this paper, we provide a comprehensive overview of different aspects of AI and Big Data in Industry 4. 0 with a particular focus on key applications, techniques, the concepts involved, key enabling technologies, challenges, and research perspective towards deployment of Industry 5. 0.
no code implementations • 30 Mar 2021 • Abdullatif Albaseer, Mohamed Abdallah, Ala Al-Fuqaha, Aiman Erbad
Then, the problem is formulated as joint energy minimization and resource allocation optimization problem to obtain the optimal local computation time and the optimal transmission time that minimize the total energy consumption considering the worker's energy budget, available bandwidth, channel states, beamforming, and local CPU speed.
no code implementations • 1 Mar 2021 • Kashif Ahmad, Firoj Alam, Junaid Qadir, Basheer Qolomany, Imran Khan, Talhat Khan, Muhammad Suleman, Naina Said, Syed Zohaib Hassan, Asma Gul, Ala Al-Fuqaha
In this work, we propose a pipeline starting from manual annotation via a crowd-sourcing study and concluding on the development and training of AI models for automatic sentiment analysis of users' reviews.
no code implementations • 19 Jan 2021 • Adnan Qayyum, Kashif Ahmad, Muhammad Ahtazaz Ahsan, Ala Al-Fuqaha, Junaid Qadir
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 security, privacy, and quality of service requirements (such as low latency).
no code implementations • 14 Dec 2020 • Kashif Ahmad, Majdi Maabreh, Mohamed Ghaly, Khalil Khan, Junaid Qadir, Ala Al-Fuqaha
In this paper, we analyze and explore key challenges including security, robustness, interpretability, and ethical (data and algorithmic) challenges to a successful deployment of AI in human-centric applications, with a particular emphasis on the convergence of these concepts/challenges.
no code implementations • 30 Nov 2020 • Naina Said, Kashif Ahmad, Asma Gul, Nasir Ahmad, Ala Al-Fuqaha
The extracted features are then used to train multiple individual classifiers whose scores are then combined in a late fusion manner achieving an F1-score of 0. 75%.
no code implementations • 30 Nov 2020 • Firoj Alam, Zohaib Hassan, Kashif Ahmad, Asma Gul, Michael Reiglar, Nicola Conci, Ala Al-Fuqaha
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 Twitter.
no code implementations • 30 Nov 2020 • Abdullah Hamid, Nasrullah Shiekh, Naina Said, Kashif Ahmad, Asma Gul, Laiq Hassan, Ala Al-Fuqaha
On the binary classification, the BoW and BERT based solutions obtained an average F1-score of . 666% and . 693%, respectively.
no code implementations • 16 Nov 2020 • Ihab Mohammed, Shadha Tabatabai, Ala Al-Fuqaha, Faissal El Bouanani, Junaid Qadir, Basheer Qolomany, Mohsen Guizani
In this work, we solve the problem of optimizing accuracy in stateful FL with a budgeted number of candidate clients by selecting the best candidate clients in terms of test accuracy to participate in the training process.
no code implementations • 5 Sep 2020 • Basheer Qolomany, Kashif Ahmad, Ala Al-Fuqaha, Junaid Qadir
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 matter of performing efficient local training and inference at the edge devices.
no code implementations • 4 Sep 2020 • Syed Zohaib Hassan, Kashif Ahmad, Steven Hicks, Paal Halvorsen, Ala Al-Fuqaha, Nicola Conci, Michael Riegler
While sentiment analysis of text streams has been widely explored in literature, sentiment analysis from images and videos is relatively new.
no code implementations • 11 Aug 2020 • Basheer Qolomany, Ihab Mohammed, Ala Al-Fuqaha, Mohsen Guizan, Junaid Qadir
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.
no code implementations • 22 Jun 2020 • Ghezlane Halhoul Merabet, Mohamed Essaaidi, Mohamed Ben-Haddou, Basheer Qolomany, Junaid Qadir, Muhammad Anan, Ala Al-Fuqaha, Riduan Mohamed Abid, Driss Benhaddou
Recent works have been directed towards more advanced control strategies, based mainly on artificial intelligence which has the ability to imitate human behavior.
no code implementations • 3 Feb 2020 • Kashif Ahmad, Syed Zohaib, Nicola Conci, Ala Al-Fuqaha
Sentiment analysis aims to extract and express a person's perception, opinions and emotions towards an entity, object, product and a service, enabling businesses to obtain feedback from the consumers.
1 code implementation • 27 Jan 2020 • Inaam Ilahi, Muhammad Usama, Junaid Qadir, Muhammad Umar Janjua, Ala Al-Fuqaha, Dinh Thai Hoang, Dusit Niyato
Deep Reinforcement Learning (DRL) has numerous applications in the real world thanks to its outstanding ability in quickly adapting to the surrounding environments.
no code implementations • 21 Jan 2020 • Adnan Qayyum, Junaid Qadir, Muhammad Bilal, Ala Al-Fuqaha
Recent years have witnessed widespread adoption of machine learning (ML)/deep learning (DL) techniques due to their superior performance for a variety of healthcare applications ranging from the prediction of cardiac arrest from one-dimensional heart signals to computer-aided diagnosis (CADx) using multi-dimensional medical images.
no code implementations • 10 Jan 2020 • Abdullatif Albaseer, Bekir Sait Ciftler, Mohamed Abdallah, Ala Al-Fuqaha
The algorithm is divided into two phases where the first phase trains a global model based on the labeled data.
no code implementations • 10 Oct 2019 • Syed Zohaib, Kashif Ahmad, Nicola Conci, Ala Al-Fuqaha
Social media have been widely exploited to detect and gather relevant information about opinions and events.
no code implementations • 7 Oct 2019 • Kashif Ahmad, Konstantin Pogorelov, Mohib Ullah, Michael Riegler, Nicola Conci, Johannes Langguth, Ala Al-Fuqaha
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 Social Media andsatellites.
no code implementations • 27 Sep 2019 • Naina Said, Kashif Ahmad, Nicola Conci, Ala Al-Fuqaha
Disaster analysis in social media content is one of the interesting research domains having abundance of data.
no code implementations • 1 Aug 2019 • Muhammad Usama, Junaid Qadir, Ala Al-Fuqaha
We have evaluated the robustness of two famous such modulation classifiers (based on the techniques of convolutional neural networks and long short term memory) against adversarial machine learning attacks in black-box settings.
no code implementations • 17 Jul 2019 • Abdulaziz Alashaikh, Eisa Alanazi, Ala Al-Fuqaha
With the rapid development of virtualization techniques, cloud data centers allow for cost effective, flexible, and customizable deployments of applications on virtualized infrastructure.
no code implementations • 3 Jun 2019 • Muhammad Usama, Junaid Qadir, Ala Al-Fuqaha, Mounir Hamdi
We also provide some guidelines to design secure ML models for cognitive networks that are robust to adversarial attacks on the ML pipeline of cognitive networks.
no code implementations • 29 May 2019 • Adnan Qayyum, Muhammad Usama, Junaid Qadir, Ala Al-Fuqaha
Connected and autonomous vehicles (CAVs) will form the backbone of future next-generation intelligent transportation systems (ITS) providing travel comfort, road safety, along with a number of value-added services.
no code implementations • 1 Apr 2019 • Basheer Qolomany, Ala Al-Fuqaha, Ajay Gupta, Driss Benhaddou, Safaa Alwajidi, Junaid Qadir, Alvis C. Fong
In this paper, we survey the area of smart building with a special focus on the role of techniques from machine learning and big data analytics.
1 code implementation • 9 Oct 2018 • Mehdi Mohammadi, Ala Al-Fuqaha, Mohsen Guizani, Jun-Seok Oh
In this paper, we propose a semi-supervised deep reinforcement learning model that fits smart city applications as it consumes both labeled and unlabeled data to improve the performance and accuracy of the learning agent.
no code implementations • 9 Oct 2018 • Mehdi Mohammadi, Ala Al-Fuqaha
We argue that semi-supervision is a must for smart city to address this challenge.
no code implementations • 24 Sep 2018 • Ting-Yu Mu, Ala Al-Fuqaha, Khaled Shuaib, Farag M. Sallabi, Junaid Qadir
Modern information technology services largely depend on cloud infrastructures to provide their services.
no code implementations • 23 Apr 2018 • Mehdi Mohammadi, Ala Al-Fuqaha, Jun-Seok Oh
This paper describes and evaluates the use of Generative Adversarial Networks (GANs) for path planning in support of smart mobility applications such as indoor and outdoor navigation applications, individualized wayfinding for people with disabilities (e. g., vision impairments, physical disabilities, etc.
1 code implementation • 9 Dec 2017 • Mehdi Mohammadi, Ala Al-Fuqaha, Sameh Sorour, Mohsen Guizani
The potential of using emerging DL techniques for IoT data analytics are then discussed, and its promises and challenges are introduced.
no code implementations • 28 Nov 2017 • Basheer Qolomany, Ala Al-Fuqaha, Driss Benhaddou, Ajay Gupta
In this paper we propose to replace sensor technology with time series models that can predict the number of occupants at a given location and time.
no code implementations • 28 Nov 2017 • Basheer Qolomany, Majdi Maabreh, Ala Al-Fuqaha, Ajay Gupta, Driss Benhaddou
The number of hidden layers and the number of neurons in each layer of a deep machine learning network are two key parameters, which have main influence on the performance of the algorithm.
no code implementations • 19 Sep 2017 • Muhammad Usama, Junaid Qadir, Aunn Raza, Hunain Arif, Kok-Lim Alvin Yau, Yehia Elkhatib, Amir Hussain, Ala Al-Fuqaha
We provide a comprehensive survey highlighting the recent advancements in unsupervised learning techniques and describe their applications for various learning tasks in the context of networking.