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Advancements and Challenges in Antenna Design and Rectifying Circuits for Radio Frequency Energy Harvesting (2024)
Journal Article
Odiamenhi, M., Jahanbakhsh Basherlou, H., Hwang See, C., Ojaroudi Parchin, N., Goh, K., & Yu, H. (2024). Advancements and Challenges in Antenna Design and Rectifying Circuits for Radio Frequency Energy Harvesting. Sensors, 24(21), Article 6804. https://doi.org/10.3390/s24216804

The proliferation of smart devices increases the demand for energy-efficient, battery-free technologies essential for sustaining IoT devices in Industry 4.0 and 5G networks, which require zero maintenance and sustainable operation. Integrating radio... Read More about Advancements and Challenges in Antenna Design and Rectifying Circuits for Radio Frequency Energy Harvesting.

Valorization of diverse waste-derived nanocellulose for multifaceted applications: A review (2024)
Journal Article
Ghamari, M., Sun, D., Dai, Y., See, C. H., Yu, H., Edirisinghe, M., & Sundaram, S. (2024). Valorization of diverse waste-derived nanocellulose for multifaceted applications: A review. International Journal of Biological Macromolecules, 280(3), Article 136130. https://doi.org/10.1016/j.ijbiomac.2024.136130

The study underscores the urgent need for sustainable waste management by focusing on circular economy principles, government regulations, and public awareness to combat ecological threats, pollution, and climate change effects. It explores extractin... Read More about Valorization of diverse waste-derived nanocellulose for multifaceted applications: A review.

Enhancing Human Activity Recognition with FedPA: Focusing on Non-IID Data Challenges in Federated Learning (2024)
Journal Article
Wen, X., Wang, Y., Yuan, M., Geng, Y., Yu, H., & Zheng, G. (2024). Enhancing Human Activity Recognition with FedPA: Focusing on Non-IID Data Challenges in Federated Learning. IEEE Sensors Journal, 24(23), 39230 - 39242. https://doi.org/10.1109/jsen.2024.3465593

Federated Learning (FL) revolutionizes distributed learning in Human Activity Recognition (HAR) by allowing clients to train models locally and share only model parameters, thus optimizing data usage and mitigating privacy concerns. However, the pres... Read More about Enhancing Human Activity Recognition with FedPA: Focusing on Non-IID Data Challenges in Federated Learning.

Active Disturbance Rejection Control of Wrist Tremor Suppression System With Additional High-Order Repetitive Control Component (2024)
Journal Article
Zhang, Z., Huo, B., Liu, Y., Dong, A., & Yu, H. (online). Active Disturbance Rejection Control of Wrist Tremor Suppression System With Additional High-Order Repetitive Control Component. IEEE/ASME Transactions on Mechatronics, https://doi.org/10.1109/tmech.2024.3450599

Intention tremor is an involuntary and rhythmic muscle contraction that occurs during purposeful limb movements. Functional electrical stimulation based repetitive control (RC) has proven to be an effective approach to reject periodic tremor disturba... Read More about Active Disturbance Rejection Control of Wrist Tremor Suppression System With Additional High-Order Repetitive Control Component.

H∞ High-Order Repetitive Control for Functional Electrical Stimulation in Intention Tremor Suppression (2024)
Journal Article
Zhang, Z., Huo, B., Liu, Y., Dong, A., & Yu, H. (online). H∞ High-Order Repetitive Control for Functional Electrical Stimulation in Intention Tremor Suppression. IEEE Transactions on Automation Science and Engineering, https://doi.org/10.1109/tase.2024.3427638

Intention tremor is a rhythmic and involuntary limb swing movement that causes significant inconvenience to the daily life of patients. Repetitive control is suitable for functional-electrical-stimulation-based intention tremor suppression because it... Read More about H∞ High-Order Repetitive Control for Functional Electrical Stimulation in Intention Tremor Suppression.

A Transformer-Based Network With Feature Complementary Fusion for Crack Defect Detection (2024)
Journal Article
Ma, M., Yang, L., Liu, Y., & Yu, H. (2024). A Transformer-Based Network With Feature Complementary Fusion for Crack Defect Detection. IEEE Transactions on Intelligent Transportation Systems, 25(11), 16989-17006. https://doi.org/10.1109/tits.2024.3421331

Pavement crack detection poses a formidable challenge due to the intricate texture structures of cracks and the complex environmental settings in which they are situated. In recent years, the advancement of deep learning techniques has prompted a sur... Read More about A Transformer-Based Network With Feature Complementary Fusion for Crack Defect Detection.

Enhancing Human Activity Recognition in Wrist-Worn Sensor Data Through Compensation Strategies for Sensor Displacement (2024)
Journal Article
Wang, H., Wang, X., Lu, C., Yuan, M., Wang, Y., Yu, H., & Li, H. (2024). Enhancing Human Activity Recognition in Wrist-Worn Sensor Data Through Compensation Strategies for Sensor Displacement. IEEE Access, 12, 95058 - 95070. https://doi.org/10.1109/access.2024.3422256

Human Activity Recognition (HAR) using wearable sensors, particularly wrist-worn devices, has garnered significant research interest. However, challenges such as sensor displacement and variations in wearing habits can affect the accuracy of HAR syst... Read More about Enhancing Human Activity Recognition in Wrist-Worn Sensor Data Through Compensation Strategies for Sensor Displacement.

Res-BiLSTMs model based on multi-task attention for real-time measurement of the free calcium oxide content (2024)
Journal Article
Zhao, Y., Wang, Y., Zhang, S., Wang, X., & Yu, H. (2024). Res-BiLSTMs model based on multi-task attention for real-time measurement of the free calcium oxide content. Measurement Science and Technology, 35(9), Article 095107. https://doi.org/10.1088/1361-6501/ad5612

The content of free calcium oxide (f-CaO) is the primary economic index to evaluate the quality of cement. A residual bidirectional long short-term memory network model (Res-BiLSTMs) based on a multi-task attention mechanism was proposed for the char... Read More about Res-BiLSTMs model based on multi-task attention for real-time measurement of the free calcium oxide content.

ESO-Based Antisaturation Motion Control for Cable-Driven Continuum Robots (2024)
Journal Article
Zhang, K., Liu, Y., Huo, B., Wu, Z., Yang, L., & Yu, H. (online). ESO-Based Antisaturation Motion Control for Cable-Driven Continuum Robots. IEEE/ASME Transactions on Mechatronics, https://doi.org/10.1109/tmech.2024.3402369

High precision motion control is the key to complete the refined operation tasks for cable-driven continuum robots. However, the existence of model inaccuracy and actuator saturation pose great challenges to the high precision motion control of cable... Read More about ESO-Based Antisaturation Motion Control for Cable-Driven Continuum Robots.

Power Consumption Analysis For Smarter Robotics Via Industry 4.0 Methods And Technologies RS HYu V2 (2024)
Presentation / Conference Contribution
Samson, R., Goh, K., Sankarraj, A., Gkanatsios, A., & Yu, H. (2023, September). Power Consumption Analysis For Smarter Robotics Via Industry 4.0 Methods And Technologies RS HYu V2. Presented at 2023 International Conference on Innovation of Communication and Information Technology (ICIEICT 2023), Madrid, Spain

This paper examines the opportunities to apply industry 4.0 technology to practical applications, with a specific focus on sustainability and resource efficiency in industrial environments. The main objective of this paper is to design and implement... Read More about Power Consumption Analysis For Smarter Robotics Via Industry 4.0 Methods And Technologies RS HYu V2.

Data-based adaptive predictive bipartite consensus for nonlinear multiagent systems against DoS attacks (2024)
Journal Article
Halimu, Y., Zhao, H., Yu, H., Ding, S., & Qiao, S. (2024). Data-based adaptive predictive bipartite consensus for nonlinear multiagent systems against DoS attacks. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 238(7), 1231 - 1241. https://doi.org/10.1177/09596518241236928

This article investigates a Denial-of-Service (DoS) attack problem for nonlinear unknown discrete-time multiagent systems (MASs) to implement bipartite consensus tracking tasks with fixed and switching topologies. Firstly, an equivalent linearization... Read More about Data-based adaptive predictive bipartite consensus for nonlinear multiagent systems against DoS attacks.

DIBNN: A Dual-Improved-BNN Based Algorithm for Multi-Robot Cooperative Area Search in Complex Obstacle Environments (2024)
Journal Article
Chen, B., Zhang, H., Zhang, F., Jiang, Y., Miao, Z., Yu, H., & Wang, Y. (online). DIBNN: A Dual-Improved-BNN Based Algorithm for Multi-Robot Cooperative Area Search in Complex Obstacle Environments. IEEE Transactions on Automation Science and Engineering, https://doi.org/10.1109/tase.2024.3379166

Aiming at the area search task of a multi-robot system in an unknown complex obstacle environment, we propose a cooperative area search algorithm based on a dual improved bio-inspired neural network (DIBNN). First, we improve the BNN model to reduce... Read More about DIBNN: A Dual-Improved-BNN Based Algorithm for Multi-Robot Cooperative Area Search in Complex Obstacle Environments.

DBMA-Net: A Dual-Branch Multi-Attention Network for Polyp Segmentation (2024)
Journal Article
Zhai, C., Yang, L., Liu, Y., & Yu, H. (2024). DBMA-Net: A Dual-Branch Multi-Attention Network for Polyp Segmentation. IEEE Transactions on Instrumentation and Measurement, 73, Article 2512316. https://doi.org/10.1109/tim.2024.3379418

In the early prevention stage of colorectal cancer, the utilization of automatic polyp segmentation techniques from colonoscopy images has demonstrated efficacy in mitigating the misdiagnosis rate. Nonetheless, accurate polyp segmentation is always a... Read More about DBMA-Net: A Dual-Branch Multi-Attention Network for Polyp Segmentation.

A Transformer-based Gesture Prediction Model via sEMG Sensor for Human-robot Interaction (2024)
Journal Article
Liu, Y., Li, X., Yang, L., & Yu, H. (2024). A Transformer-based Gesture Prediction Model via sEMG Sensor for Human-robot Interaction. IEEE Transactions on Instrumentation and Measurement, 73, Article 2510615. https://doi.org/10.1109/tim.2024.3373045

As one of the most direct and pivotal modes of human-computer interaction (HCI), the application of surface electromyography (sEMG) signals in the domain of gesture prediction has emerged as a prominent area of research. To enhance the performance of... Read More about A Transformer-based Gesture Prediction Model via sEMG Sensor for Human-robot Interaction.

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.

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.

A Multiple-stage Uniform Transmission Line Matching Technique for Triple-Band RF to-DC Rectifier with Harmonic Suppression for Wireless Power Transfer Applications. (2024)
Presentation / Conference Contribution
Odiamenhi, M., See, C. H., Ojaroudi Parchin, N., Yu, H., & Goh, K. (2024, February). A Multiple-stage Uniform Transmission Line Matching Technique for Triple-Band RF to-DC Rectifier with Harmonic Suppression for Wireless Power Transfer Applications. Presented at URSI UK Symposium, National Physics Laboratory, Teddington

Dynamic Event-Triggered Resilient Heading Control for Unmanned Surface Vehicle With Encrypted Data (2024)
Journal Article
Zhao, H., Xu, D., Zhou, Z., & Yu, H. (online). Dynamic Event-Triggered Resilient Heading Control for Unmanned Surface Vehicle With Encrypted Data. IEEE Transactions on Intelligent Vehicles, https://doi.org/10.1109/tiv.2024.3358789

This paper studies data-driven dynamic event-triggered heading control issues for an unmanned surface vehicle (USV) with enciphered data and aperiodic denial of service (DoS) attacks. First, we establish a compact form dynamic linearization model for... Read More about Dynamic Event-Triggered Resilient Heading Control for Unmanned Surface Vehicle With Encrypted Data.

DMF-Net: A Dual-Encoding Multi-Scale Fusion Network for Pavement Crack Detection (2023)
Journal Article
Bai, S., Yang, L., Liu, Y., & Yu, H. (2024). DMF-Net: A Dual-Encoding Multi-Scale Fusion Network for Pavement Crack Detection. IEEE Transactions on Intelligent Transportation Systems, 25(6), 5981 - 5996. https://doi.org/10.1109/tits.2023.3331769

Currently, cracks are the most common defect in pavement diseases. Long-term non-maintenance can lead to crack lengthening and expansion, causing serious traffic accidents, as well as shortening the service life of pavement cracks. Therefore, it is o... Read More about DMF-Net: A Dual-Encoding Multi-Scale Fusion Network for Pavement Crack Detection.