Outputs (330)

Dual-blockchain based multi-layer grouping federated learning scheme for heterogeneous data in industrial IoT (2024)
Journal Article
Wang, X., Zhang, H., Wu, H., & Yu, H. (2024). Dual-blockchain based multi-layer grouping federated learning scheme for heterogeneous data in industrial IoT. Blockchain: Research and Applications, 5(3), Article 100195. https://doi.org/10.1016/j.bcra.2024.100195

Federated Learning (FL) allows data owners to train neural networks together without sharing local data, allowing the Industrial Internet of Things (IIoT) to share a variety of data. However, traditional federated learning frameworks suffer from data... Read More about Dual-blockchain based multi-layer grouping federated learning scheme for heterogeneous data in industrial IoT.

Considering Environmental Effects on Porous Concrete Applications: An Experimental Investigation (2024)
Journal Article
Marinelli, A., & Rasheed, L. P. H. (2024). Considering Environmental Effects on Porous Concrete Applications: An Experimental Investigation. Procedia Structural Integrity, 54, 332-339. https://doi.org/10.1016/j.prostr.2024.01.091

Urban areas worldwide grapple with ecological disruption due to overpopulation, exacerbated by impermeable concrete surfaces that hinder rainwater absorption, curb plant growth and foster urban heat islands. Innovative porous concrete applications we... Read More about Considering Environmental Effects on Porous Concrete Applications: An Experimental Investigation.

Very Accurate Time-Frequency Representation of Induction Motors Harmonics for Fault Diagnosis Under Load Variations (2024)
Journal Article
Bonet-Jara, J., Fernandez-Cavero, V., Vedreno-Santos, F., Morinigo-Sotelo, D., & Pons-Llinares, J. (2024). Very Accurate Time-Frequency Representation of Induction Motors Harmonics for Fault Diagnosis Under Load Variations. IEEE Transactions on Industry Applications, 60(3), 3903-3911. https://doi.org/10.1109/tia.2024.3371393

Induction motors work under steady-state in many applications. Nevertheless, in some cases they experience periodic load fluctuations, which generate constant frequency harmonics close to variable frequency bar breakage harmonics. In these cases, tim... Read More about Very Accurate Time-Frequency Representation of Induction Motors Harmonics for Fault Diagnosis Under Load Variations.

Data Matters- Storytelling with technologies (2024)
Digital Artefact
Lechelt, S., Panneels, I., Kaye, R., & Disley, M. Data Matters- Storytelling with technologies. [Video]

Watch Dr Susan Lechelt, Dr Inge Panneels, Rebecca Kaye (ploterre) and Martin Disley from Creative Informatics, Edinburgh, present their practice and research.

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/10.1016/j.eswa.2023.121378

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).

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. (2024). Hate speech detection: A comprehensive review of recent works. Expert Systems, 41(8), Article e13562. 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 Communication Networks, 2024, Article 6651584. https://doi.org/10.1155/2024/6651584

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.