Outputs (10791)

ASB-CS: Adaptive sparse basis compressive sensing model and its application to medical image encryption (2024)
Journal Article
Jiang, D., Tsafack, N., Boulila, W., Ahmad, J., & Barba-Franco, J. (in press). ASB-CS: Adaptive sparse basis compressive sensing model and its application to medical image encryption. Expert Systems with Applications, 236, Article 121378. https://doi.org/

Recent advances in intelligent wearable devices have brought tremendous chances for the development of healthcare monitoring system. However, the data collected by various sensors in it are user-privacy-related information. Once the individuals’ priv... Read More about ASB-CS: Adaptive sparse basis compressive sensing model and its application to medical image encryption.

The retailer perspective on the potential for using urban consolidation centres (UCCs) (2024)
Journal Article
Akgün, E. Z., Monios, J., Cowie, J., & Fonzone, A. (2024). The retailer perspective on the potential for using urban consolidation centres (UCCs). Research in Transportation Economics, 103, Article 101413. https://doi.org/10.1016/j.retrec.2024.101413

This paper examines the role of supportive policies and value-added services which may incentivise retailers to use an urban consolidation centre (UCC). The methodology is a case study of the city of Edinburgh, Scotland, based on semi-structured inte... Read More about The retailer perspective on the potential for using urban consolidation centres (UCCs).

Deep Learning-Based Receiver Design for IoT Multi-User Uplink 5G-NR System (2024)
Presentation / Conference Contribution
Gupta, A., Bishnu, A., Ratnarajah, T., Adeel, A., Hussain, A., & Sellathurai, M. (2024). Deep Learning-Based Receiver Design for IoT Multi-User Uplink 5G-NR System. In GLOBECOM 2023 - 2023 IEEE Global Communications Conference (4110-4115). https://doi.or

Designing an efficient receiver for multiple users transmitting orthogonal frequency-division multiplexing signals to the base station remain a challenging interference-limited problem in 5G-new radio (5G-NR) system. This can lead to stagnation of de... Read More about Deep Learning-Based Receiver Design for IoT Multi-User Uplink 5G-NR System.

A Deep Transfer Learning-Powered EDoS Detection Mechanism for 5G and Beyond Network Slicing (2024)
Presentation / Conference Contribution
Benzaïd, C., Taleb, T., Sami, A., & Hireche, O. (2024). A Deep Transfer Learning-Powered EDoS Detection Mechanism for 5G and Beyond Network Slicing. In GLOBECOM 2023 - 2023 IEEE Global Communications Conference (4747-4753). https://doi.org/10.1109/globe

Network slicing is recognized as a key enabler for 5G and beyond (B5G) services. However, its dynamic nature and the growing sophistication of DDoS attacks put it at risk of Economical Denial of Sustainability (EDoS) attack, causing economic losses t... Read More about A Deep Transfer Learning-Powered EDoS Detection Mechanism for 5G and Beyond Network Slicing.

Hate speech detection: A comprehensive review of recent works (2024)
Journal Article
Gandhi, A., Ahir, P., Adhvaryu, K., Shah, P., Lohiya, R., Cambria, E., Poria, S., & Hussain, A. (online). Hate speech detection: A comprehensive review of recent works. Expert Systems, https://doi.org/10.1111/exsy.13562

There has been surge in the usage of Internet as well as social media platforms which has led to rise in online hate speech targeted on individual or group. In the recent years, hate speech has resulted in one of the challenging problems that can unf... Read More about Hate speech detection: A comprehensive review of recent works.

Event-Triggered Relearning Modeling Method for Stochastic System with Non-Stationary Variable Operating Conditions (2024)
Journal Article
Liu, J., Zhang, Y., Zhou, Y., & Chen, J. (2024). Event-Triggered Relearning Modeling Method for Stochastic System with Non-Stationary Variable Operating Conditions. Mathematics, 12(5), Article 667. https://doi.org/10.3390/math12050667

This study presents a novel event-triggered relearning framework for neural network modeling, designed to improve prediction precision in dynamic stochastic complex industrial systems under non-stationary and variable conditions. Firstly, a sliding w... Read More about Event-Triggered Relearning Modeling Method for Stochastic System with Non-Stationary Variable Operating Conditions.

Solar Wall Technology and Its Impact on Building Performance (2024)
Journal Article
Ghamari, M., & Sundaram, S. (2024). Solar Wall Technology and Its Impact on Building Performance. Energies, 17(5), Article 1075. https://doi.org/10.3390/en17051075

Solar walls provide transformative solutions by harnessing solar energy to generate electricity, improve thermal comfort, and reduce energy consumption and emissions, contributing to zero-energy buildings and mitigating climate change. In hot and hum... Read More about Solar Wall Technology and Its Impact on Building Performance.

Toward a Real-Time TCP SYN Flood DDoS Mitigation Using Adaptive Neuro-Fuzzy Classifier and SDN Assistance in Fog Computing (2024)
Journal Article
Bensaid, R., Labraoui, N., Abba Ari, A. A., Maglaras, L., Saidi, H., Abdu Lwahhab, A. M., & Benfriha, S. (2024). Toward a Real-Time TCP SYN Flood DDoS Mitigation Using Adaptive Neuro-Fuzzy Classifier and SDN Assistance in Fog Computing. Security and Commu

The growth of the Internet of Things (IoT) has recently impacted our daily lives in many ways. As a result, a massive volume of data are generated and need to be processed in a short period of time. Therefore, a combination of computing models such a... Read More about Toward a Real-Time TCP SYN Flood DDoS Mitigation Using Adaptive Neuro-Fuzzy Classifier and SDN Assistance in Fog Computing.

BBox-Free SAR Ship Instance Segmentation Method Based on Gaussian Heatmap (2024)
Journal Article
Gao, F., Zhong, F., Sun, J., Hussain, A., & Zhou, H. (2024). BBox-Free SAR Ship Instance Segmentation Method Based on Gaussian Heatmap. IEEE Transactions on Geoscience and Remote Sensing, 62, Article 5206218. https://doi.org/10.1109/tgrs.2024.3369614

Recently, deep learning methods have been widely adopted for ship detection in synthetic aperture radar (SAR) images. However, many of the existing methods miss adjacent ship instances when detecting densely arranged ship targets in inshore scenes. B... Read More about BBox-Free SAR Ship Instance Segmentation Method Based on Gaussian Heatmap.

A QOBL-SAO and its variant: An open source software for optimizing PV/wind/battery system and CEC2020 real world problems (2024)
Journal Article
Mas’ud, A. A., Salawudeen, A. T., Umar, A. A., Shaaban, Y. A., Muhammad-Sukki, F., Musa, U., & Alshammari, S. J. (2024). A QOBL-SAO and its variant: An open source software for optimizing PV/wind/battery system and CEC2020 real world problems. Software

The Quasi oppositional smell agent optimization (QOBL-SAO) and its levy flight variant (LFQOBL-SAO) are two cutting-edge software tools for optimizing PV/wind/battery power systems. They can also be used to solve real-world CEC2020 optimization probl... Read More about A QOBL-SAO and its variant: An open source software for optimizing PV/wind/battery system and CEC2020 real world problems.