All Outputs (4670)

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.

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.

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. (online). Dual-blockchain based multi-layer grouping federated learning scheme for heterogeneous data in industrial IoT. Blockchain: Research and Applications, 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.

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.

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.

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.

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 Impacts, 19, Article 100630. https://doi.org/10.1016/j.simpa.2024.100630

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.

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.

Performance Analysis of Multiport Antennas in Vehicle-to-Vehicle Communication Channels (2024)
Journal Article
Pour Sohrab, A., Huang, Y., & Karadimas, P. (2024). Performance Analysis of Multiport Antennas in Vehicle-to-Vehicle Communication Channels. Wireless Personal Communications, 134, 1231–1257. https://doi.org/10.1007/s11277-024-10875-0

A holistic performance analysis and classification of multiport antennas (MPAs) is conducted in this paper. We focus on 5.9 GHz vehicle-to-vehicle communications suited to the emerging technology of intelligent transportation systems. Three-dimension... Read More about Performance Analysis of Multiport Antennas in Vehicle-to-Vehicle Communication Channels.

Temporal analysis and predictive modeling of ambient air quality in Hulu Langat District, Selangor, Malaysia: A chemometric approach (2024)
Journal Article
Abdullah, A., Mohd Saudi, A. S., Shafii, N. Z., Kamarudin, M. K. A., & Muhammad-Sukki, F. (2024). Temporal analysis and predictive modeling of ambient air quality in Hulu Langat District, Selangor, Malaysia: A chemometric approach. Planning Malaysia Journal, 22(1), https://doi.org/10.21837/pm.v22i30.1448

One of the most important environmental problems facing the globe today is air pollution. The centre area for the local populace is the Hulu Langat district, which borders Kuala Lumpur, the capital. The purpose of this study is to look at how the amb... Read More about Temporal analysis and predictive modeling of ambient air quality in Hulu Langat District, Selangor, Malaysia: A chemometric approach.

Use of buffer treatment to utilize local non-alkali tolerant bacteria in microbial induced calcium carbonate sedimentation in concrete crack repair (2024)
Journal Article
Pianfuengfoo, S., Kongtunjanphuk, S., Zhang, H., & Sukontasukkul, P. (2024). Use of buffer treatment to utilize local non-alkali tolerant bacteria in microbial induced calcium carbonate sedimentation in concrete crack repair. Heliyon, 10(4), Article e26776. https://doi.org/10.1016/j.heliyon.2024.e26776

Concrete often suffers cracks due to its low tensile strength. The repair process can vary ranging from surface coating, grouting, and strengthening. Microbial induced calcium carbonate sedimentation process (MICP) is a process of utilizing non-patho... Read More about Use of buffer treatment to utilize local non-alkali tolerant bacteria in microbial induced calcium carbonate sedimentation in concrete crack repair.

A novel generative adversarial network‐based super‐resolution approach for face recognition (2024)
Journal Article
Chougule, A., Kolte, S., Chamola, V., & Hussain, A. (2024). A novel generative adversarial network‐based super‐resolution approach for face recognition. Expert Systems, 41(8), Article e13564. https://doi.org/10.1111/exsy.13564

Face recognition is an essential feature required for a range of computer vision applications such as security, attendance systems, emotion detection, airport check-in, and many others. The super-resolution of subject images is an important and chall... Read More about A novel generative adversarial network‐based super‐resolution approach for face recognition.

Improved bounds on number fields of small degree (2024)
Journal Article
Anderson, T. C., Gafni, A., Hughes, K., Lemke Oliver, R. J., Lowry-Duda, D., Thorne, F., Wang, J., & Zhang, R. (in press). Improved bounds on number fields of small degree. Discrete Analysis,

We study the number of degree n number fields with discriminant bounded by X. In this article, we improve an upper bound due to Schmidt on the number of such fields that was previously the best known upper bound for 6 ≤ n ≤ 94.

Implementing Virtualization on Single-Board Computers: A Case Study on Edge Computing (2024)
Journal Article
Lambropoulos, G., Mitropoulos, S., Douligeris, C., & Maglaras, L. (2024). Implementing Virtualization on Single-Board Computers: A Case Study on Edge Computing. Computers, 13(2), Article 54. https://doi.org/10.3390/computers13020054

The widespread adoption of cloud computing has resulted in centralized datacenter structures; however, there is a requirement for smaller-scale distributed infrastructures to meet the demands for speed, responsiveness, and security for critical appli... Read More about Implementing Virtualization on Single-Board Computers: A Case Study on Edge Computing.

Data-based bipartite formation control for multi-agent systems with communication constraints (2024)
Journal Article
Wang, J., Zhao, H., Yu, H., Yang, R., & Li, J. (2024). Data-based bipartite formation control for multi-agent systems with communication constraints. Science Progress, 107(1), https://doi.org/10.1177/00368504241227620

This article investigates data-driven distributed bipartite formation issues for discrete-time multi-agent systems with communication constraints. We propose a quantized data-driven distributed bipartite formation control approach based on the plant’... Read More about Data-based bipartite formation control for multi-agent systems with communication constraints.

Robust Real-time Audio-Visual Speech Enhancement based on DNN and GAN (2024)
Journal Article
Gogate, M., Dashtipour, K., & Hussain, A. (in press). Robust Real-time Audio-Visual Speech Enhancement based on DNN and GAN. IEEE Transactions on Artificial Intelligence, https://doi.org/10.1109/tai.2024.3366141

The human auditory cortex contextually integrates audio-visual (AV) cues to better understand speech in a cocktail party situation. Recent studies have shown that AV speech enhancement (SE) models can significantly improve speech quality and intellig... Read More about Robust Real-time Audio-Visual Speech Enhancement based on DNN and GAN.

British Sign Language Detection Using Ultra-Wideband Radar Sensing and Residual Neural Network (2024)
Journal Article
Saeed, U., Shah, S. A., Ghadi, Y. Y., Hameed, H., Shah, S. I., Ahmad, J., & Abbasi, Q. H. (2024). British Sign Language Detection Using Ultra-Wideband Radar Sensing and Residual Neural Network. IEEE Sensors Journal, 24(7), 11144-11151. https://doi.org/10.1109/jsen.2024.3364389

This study represents a significant advancement in Sign Language Detection (SLD), a crucial tool for enhancing communication and fostering inclusivity among the hearing-impaired community. It innovatively combines radar technology with deep learning... Read More about British Sign Language Detection Using Ultra-Wideband Radar Sensing and Residual Neural Network.