All Outputs (348)

MAGRU-IDS: A Multi-Head Attention-based Gated Recurrent Unit for Intrusion Detection in IIoT Networks (2023)
Journal Article
Ullah, S., Boulila, W., Koubaa, A., & Ahmad, J. (2023). MAGRU-IDS: A Multi-Head Attention-based Gated Recurrent Unit for Intrusion Detection in IIoT Networks. IEEE Access, 11, 114590-114601. https://doi.org/10.1109/access.2023.3324657

The increasing prevalence of the Industrial Internet of Things (IIoT) in industrial environments amplifies the potential for security breaches and compromises. To monitor IIoT networks, intrusion detection systems (IDS) have been introduced to detect... Read More about MAGRU-IDS: A Multi-Head Attention-based Gated Recurrent Unit for Intrusion Detection in IIoT Networks.

Embodied carbon quantification of luminaires using life cycle assessment and CIBSE TM65 methodologies: A comparison case study (2023)
Journal Article
Mazzei, I., Saint, R., Kay, A., & Pomponi, F. (2024). Embodied carbon quantification of luminaires using life cycle assessment and CIBSE TM65 methodologies: A comparison case study. Journal of Industrial Ecology, 28(1), 59-73. https://doi.org/10.1111/jiec

The European legislative landscape on sustainability is steadily growing to meet objectives to reach net zero targets by mid‐century. In this context, companies and manufacturers may soon be legally required to provide quantification of the environme... Read More about Embodied carbon quantification of luminaires using life cycle assessment and CIBSE TM65 methodologies: A comparison case study.

Deep Vision in Analysis and Recognition of Radar Data: Achievements, Advancements, and Challenges (2023)
Journal Article
Liu, Q., Yang, Z., Ji, R., Zhang, Y., Bilal, M., Liu, X., Vimal, S., & Xu, X. (2023). Deep Vision in Analysis and Recognition of Radar Data: Achievements, Advancements, and Challenges. IEEE Systems, Man, and Cybernetics Magazine, 9(4), 4-12. https://doi.o

Radars are widely used to obtain echo information for effective prediction, such as precipitation nowcasting. In this article, recent relevant scientific investigation and practical efforts using deep learning (DL) models for weather radar data analy... Read More about Deep Vision in Analysis and Recognition of Radar Data: Achievements, Advancements, and Challenges.

An empirical analysis of the factors influencing Scottish residents’ compliance with COVID-19 travel restrictions (2023)
Journal Article
Semple, T., Fonzone, A., Fountas, G., & Downey, L. (2023). An empirical analysis of the factors influencing Scottish residents’ compliance with COVID-19 travel restrictions. Transportation Research Part A: Policy and Practice, 178, Article 103842. https

This study uses survey data to investigate the factors affecting compliance with the Scottish Government’s COVID-19 travel restrictions. The survey contained self-reported data (n=819) regarding various aspects of Scottish residents’ COVID-19 travel... Read More about An empirical analysis of the factors influencing Scottish residents’ compliance with COVID-19 travel restrictions.

DenMerD: A Feature Propagation Enhanced Approach to Beam Blockage Correction in Weather Radar (2023)
Journal Article
Liu, Q., Sun, J., & Liu, X. (in press). DenMerD: A Feature Propagation Enhanced Approach to Beam Blockage Correction in Weather Radar. Journal on Artificial Intelligence,

In the realm of meteorological research, extensive global radar networks serve to detect and provide early warnings for a diverse array of weather phenomena. However, the inherently discontinuous nature of radar observations often results in the pres... Read More about DenMerD: A Feature Propagation Enhanced Approach to Beam Blockage Correction in Weather Radar.

A high-performance pH-sensitive electrode integrated with a multi-sensing probe for online water quality monitoring (2023)
Journal Article
Uppuluri, K., Szwagierczak, D., Fernandes, L., Zaraska, K., Lange, I., Synkiewicz-Musialska, B., & Manjakkal, L. (2023). A high-performance pH-sensitive electrode integrated with a multi-sensing probe for online water quality monitoring. Journal of Materi

Water quality monitoring is an essential tool in effective environmental and public health protection. This study presents a new screen-printed Co2O3–RuO2-based electrode for electrochemical pH sensing and its comprehensive morphological, composition... Read More about A high-performance pH-sensitive electrode integrated with a multi-sensing probe for online water quality monitoring.

Information Fusion for 5G IoT: An Improved 3D Localisation Approach Using K-DNN and Multi-Layered Hybrid Radiomap (2023)
Journal Article
El Boudani, B., Dagiuklas, T., Kanaris, L., Iqbal, M., & Chrysoulas, C. (2023). Information Fusion for 5G IoT: An Improved 3D Localisation Approach Using K-DNN and Multi-Layered Hybrid Radiomap. Electronics, 12(19), Article 4150. https://doi.org/10.3390/e

Indoor positioning is a core enabler for various 5G identity and context-aware applications requiring precise and real-time simultaneous localisation and mapping (SLAM). In this work, we propose a K-nearest neighbours and deep neural network (K-DNN)... Read More about Information Fusion for 5G IoT: An Improved 3D Localisation Approach Using K-DNN and Multi-Layered Hybrid Radiomap.

The Extent to Which Hemp Insulation Materials Can Be Used in Canadian Residential Buildings (2023)
Journal Article
Liu, C. H. J., Pomponi, F., & D'Amico, B. (2023). The Extent to Which Hemp Insulation Materials Can Be Used in Canadian Residential Buildings. Sustainability, 15(19), Article 14471. https://doi.org/10.3390/su151914471

The embodied carbon of building materials is a significant contributor to greenhouse gas (GHG) emissions. Hemp is widely acknowledged as the most used vegetal insulation in building and construction due to its comparable thermal properties and better... Read More about The Extent to Which Hemp Insulation Materials Can Be Used in Canadian Residential Buildings.

VLC-Assisted Safety Message Dissemination in Roadside Infrastructure-Less IoV Systems: Modeling and Analysis (2023)
Journal Article
Xie, Y., Xu, D., Zhang, T., Yu, K., Hussain, A., & Guizani, M. (2024). VLC-Assisted Safety Message Dissemination in Roadside Infrastructure-Less IoV Systems: Modeling and Analysis. IEEE Internet of Things, 11(5), 8185-8198. https://doi.org/10.1109/jiot.20

Internet of Vehicles (IoV) is an emerging paradigm with significant potential to improve traffic efficiency and driving safety. Here, we focus on the design of a novel visible light communication (VLC)-assisted scheme to enable driving safety-related... Read More about VLC-Assisted Safety Message Dissemination in Roadside Infrastructure-Less IoV Systems: Modeling and Analysis.

Privacy-Enhanced Pneumonia Diagnosis: IoT-Enabled Federated Multi-Party Computation in Industry 5.0 (2023)
Journal Article
Siddique, A. A., Boulila, W., Alshehri, M. S., Ahmed, F., Gadekallu, T. R., Victor, N., …Ahmad, J. (2023). Privacy-Enhanced Pneumonia Diagnosis: IoT-Enabled Federated Multi-Party Computation in Industry 5.0. IEEE Transactions on Consumer Electronics, ht

Pneumonia is a significant global health concern that can lead to severe and sometimes fatal consequences. Timely identification and classification of pneumonia can substantially improve patient outcomes. However, the disclosure of sensitive medical... Read More about Privacy-Enhanced Pneumonia Diagnosis: IoT-Enabled Federated Multi-Party Computation in Industry 5.0.

AI-Enabled Traffic Control Prioritization in Software-Defined IoT Networks for Smart Agriculture (2023)
Journal Article
Masood, F., Khan, W. U., Jan, S. U., & Ahmad, J. (2023). AI-Enabled Traffic Control Prioritization in Software-Defined IoT Networks for Smart Agriculture. Sensors, 23(19), Article 8218. https://doi.org/10.3390/s23198218

Smart agricultural systems have received a great deal of interest in recent years because of their potential for improving the efficiency and productivity of farming practices. These systems gather and analyze environmental data such as temperature,... Read More about AI-Enabled Traffic Control Prioritization in Software-Defined IoT Networks for Smart Agriculture.

A Low-Cost Platform for Real Time Data Acquisition and Fractional Control with Application to a DC motor (2023)
Journal Article
Abdel Fettah Berkani, H., Keziz, B., Lashab, M., Djouambi, A., & Kerrouche, A. (2023). A Low-Cost Platform for Real Time Data Acquisition and Fractional Control with Application to a DC motor. International Journal of Power Electronics and Drive Systems,

This paper presents a low-cost experimental platform for real time data acquisition, identification and fractional order control of some low dynamic systems via Arduino-Simulink interface. As a demonstrative example, a DC motor is considered and mode... Read More about A Low-Cost Platform for Real Time Data Acquisition and Fractional Control with Application to a DC motor.

CoDeS: A Deep Learning Framework for Identifying COVID-Caused Depression Symptoms (2023)
Journal Article
Wani, M. A., ELAffendi, M., Bours, P., Imran, A. S., Hussain, A., & Abd El-Latif, A. A. (2024). CoDeS: A Deep Learning Framework for Identifying COVID-Caused Depression Symptoms. Cognitive Computation, 16(1), 305-325. https://doi.org/10.1007/s12559-023-10

Depression is a serious mental health condition that affects a person’s ability to feel happy and engaged in activities. The COVID-19 pandemic has led to an increase in depression due to factors such as isolation, financial stress, and uncertainty ab... Read More about CoDeS: A Deep Learning Framework for Identifying COVID-Caused Depression Symptoms.

Rapidrift: Elementary Techniques to Improve Machine Learning-Based Malware Detection (2023)
Journal Article
Manikandaraja, A., Aaby, P., & Pitropakis, N. (2023). Rapidrift: Elementary Techniques to Improve Machine Learning-Based Malware Detection. Computers, 12(10), Article 195. https://doi.org/10.3390/computers12100195

Artificial intelligence and machine learning have become a necessary part of modern living along with the increased adoption of new computational devices. Because machine learning and artificial intelligence can detect malware better than traditional... Read More about Rapidrift: Elementary Techniques to Improve Machine Learning-Based Malware Detection.

The Influence of ENSO on the Long‐Term Water Storage Anomalies in the Middle‐Lower Reaches of the Yangtze River Basin: Evaluation and Analysis (2023)
Journal Article
Li, X., Jin, T., Liu, B., Chao, N., Li, F., & Cai, Z. (2023). The Influence of ENSO on the Long‐Term Water Storage Anomalies in the Middle‐Lower Reaches of the Yangtze River Basin: Evaluation and Analysis. Earth and Space Science, 10(10), Article e202

Recent extreme events in the Middle‐Lower reaches of the Yangtze River basin (MLYRB) are proven to be possibly linked to the El Niño‐Southern Oscillation (ENSO) events as indicated by terrestrial water storage anomaly (TWSA). But the relatively short... Read More about The Influence of ENSO on the Long‐Term Water Storage Anomalies in the Middle‐Lower Reaches of the Yangtze River Basin: Evaluation and Analysis.

Orchestration in the Cloud-to-Things compute continuum: taxonomy, survey and future directions (2023)
Journal Article
Ullah, A., Kiss, T., Kovács, J., Tusa, F., Deslauriers, J., Dagdeviren, H., …Hamzeh, H. (in press). Orchestration in the Cloud-to-Things compute continuum: taxonomy, survey and future directions. Journal of cloud computing: advances, systems and applic

IoT systems are becoming an essential part of our environment. Smart cities, smart manufacturing, augmented reality, and self-driving cars are just some examples of the wide range of domains, where the applicability of such systems have been increasi... Read More about Orchestration in the Cloud-to-Things compute continuum: taxonomy, survey and future directions.

Cascaded ESO based multi-task priority tracking and null-space compliance control for redundant robots (2023)
Journal Article
Fan, K., Liu, Y., Huo, B., Yang, L., Wu, Z., & Yu, H. (2023). Cascaded ESO based multi-task priority tracking and null-space compliance control for redundant robots. Control Engineering Practice, 141, Article 105710. https://doi.org/10.1016/j.conengprac.2

This paper investigates multi-task priority trajectory tracking and null-space compliance control of redundant robots without joint velocity and joint torque sensors. A novel multi-task priority controller is proposed to improve the dynamic performan... Read More about Cascaded ESO based multi-task priority tracking and null-space compliance control for redundant robots.

Advancing the Understanding of Clinical Sepsis Using Gene Expression-Driven Machine Learning to Improve Patient Outcomes (2023)
Journal Article
Rashid, A., Al-Obeida, F., Hafez, W., Benakatti, G., Malik, R. A., Koutentis, C., …Hussain, A. (2024). Advancing the Understanding of Clinical Sepsis Using Gene Expression-Driven Machine Learning to Improve Patient Outcomes. Shock, 61(1), 4-18. https://

Sepsis remains a major challenge that necessitates improved approaches to enhance patient outcomes. This study explored the potential of Machine Learning (ML) techniques to bridge the gap between clinical data and gene expression information to bette... Read More about Advancing the Understanding of Clinical Sepsis Using Gene Expression-Driven Machine Learning to Improve Patient Outcomes.

Force monitoring of Galfan cables in a long-span cable-truss string-support system based on the magnetic flux method (2023)
Journal Article
Zhang, Y., Tian, X., Xia, J., & Zhang, H. (2023). Force monitoring of Galfan cables in a long-span cable-truss string-support system based on the magnetic flux method. Structural Monitoring and Maintenance, 10(3), 261-281. https://doi.org/10.12989/smm.202

Magnetic flux sensors are commonly used in monitoring the cable force, but the application of the sensors in large diameter non-closed Galfan cables, as those adopted in Yueqing Gymnasium which is located in Yueqing City, Zhejiang Province, China and... Read More about Force monitoring of Galfan cables in a long-span cable-truss string-support system based on the magnetic flux method.

Phases study for AgNb(Ta,W)O3 lead-free antiferroelectric ceramics (2023)
Journal Article
Lu, Z., Zhu, Y., Sun, D., Wang, B., Wang, D., Day, S., & Wang, G. (2023). Phases study for AgNb(Ta,W)O3 lead-free antiferroelectric ceramics. Results in Engineering, 20, Article 101447. https://doi.org/10.1016/j.rineng.2023.101447

Uncovering lead-free materials with an exceptionally high recoverable energy density is vital for the creation of future pulse power capacitors. This study determined that introducing Tungsten (W) and Tantalum (Ta) into the Nb-site of AgNbO3 lead-fre... Read More about Phases study for AgNb(Ta,W)O3 lead-free antiferroelectric ceramics.