Publications

Alzahrani, A, Gay, V, Alturki, R & Alanazi, F 2025, 'Conducting Usability Testing for Artificial Intelligence-Enabled Mobile Wireless Applications for Self-care Management in Saudi Arabia, the Sehhaty Wa Daghty App' in Communications in Computer and Information Science, Springer Nature Switzerland, pp. 44-67.
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Candra, H, Chai, R, Nguyen, HT & Su, S 2025, 'Optimizing electroencephalography-emotion classification through strategic window selection methodology' in Digital Technology in Public Health and Rehabilitation Care, Elsevier, pp. 261-280.
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Jiang, K, Huang, J, Xie, W, Lei, J, Li, Y, Shao, L & Lu, S 2025, 'DA-BEV: Unsupervised Domain Adaptation for Bird’s Eye View Perception' in Lecture Notes in Computer Science, Springer Nature Switzerland, pp. 322-341.
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Ni, Z & Zhang, JA 2025, 'Communication-centric multi-metric ISAC waveform optimization' in Integrated Sensing and Communications for Future Wireless Networks, Elsevier, pp. 151-170.
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Sali, S, Chai, R & Ganesan, B 2025, 'Recent trends and digital technology applications in lower limb injury rehabilitation' in Digital Technology in Public Health and Rehabilitation Care, Elsevier, pp. 99-124.
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Wang, X, Ma, B, Liu, RP & Oppermann, I 2025, 'DPAC: A New Data-Centric Privacy-Preserving Access Control Model' in Lecture Notes in Computer Science, Springer Nature Singapore, pp. 267-276.
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Xu, W, Wu, Y, Jiang, H, Wang, Y, Wu, Q & Zhang, J 2025, 'Task Consistent Prototype Learning for Incremental Few-Shot Semantic Segmentation' in Lecture Notes in Computer Science, Springer Nature Switzerland, pp. 147-162.
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Zhang, Z, Yin, H, Wang, Y, Yu, G, Wang, X, Ni, W & Liu, RP 2025, 'Enabling Efficient Cross-Shard Smart Contract Calling via Overlapping' in Lecture Notes in Computer Science, Springer Nature Singapore, pp. 164-178.
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Akter, K, Rahman, MA, Islam, MR, Sheikh, MRI & Hossain, MJ 2025, 'Attack-resilient framework for wind power forecasting against civil and adversarial attacks', Electric Power Systems Research, vol. 238, pp. 111065-111065.
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Alam, MM, Hossain, MJ, Zamee, MA & Al-Durra, A 2025, 'Design and operation of future low-voltage community microgrids: An AI-based approach with real case study', Applied Energy, vol. 377, pp. 124523-124523.
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Alhelou, HH, Bahrani, B & Ma, J 2025, 'An Affordable Sophisticated Frequency Control Ancillary Services for Australian National Electricity Market System Considering Industry and Infrastructure Challenges', IEEE Transactions on Energy Markets, Policy and Regulation, vol. 3, no. 1, pp. 72-82.
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Alsenwi, M, Abolhasan, M & Lipman, J 2025, 'RIS-UAV Integration for Enhanced Coverage and Energy-Efficient 6G Wireless Networks', IEEE Transactions on Green Communications and Networking, pp. 1-1.
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Amiri, M, Abolhasan, M, Shariati, N & Lipman, J 2025, 'Development of a polarization-neutral metamaterial absorber for efficient low-power EM energy harvesting', Sensors and Actuators A: Physical, vol. 381, pp. 116055-116055.
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Asif Raja, MJA, Masood, Z, Hussain, I, Zameer, A, Mehmood, A & Raja, MAZ 2025, 'Design of Nonlinear Delay Differential System for Analyzing Vulnerabilities in Nanoscale Hardware Implants: A Deep Dive into Intelligent Computing Networks', Nano, vol. 20, no. 03.
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In the annals of contemporary innovation, the study of miniature marvels nanoscale hardware implants emerged as a pivotal instrument, scarcely perceptible to the naked eye, embodies a prowess of cutting-edge technologies and clandestine intrigue. The objective of this research is to introduce a time delay nonlinear system for nanoscale hardware implants vulnerabilities that portray the exploitation of a system by utilizing the stupendous knacks of advanced deep bidirectional long short-term memory (LSTM) networks for time series predictions. Firmware-level bugs present the potential for escalating privileges and executing of code remotely beneath the operating system, allowing for infiltration or complete intervention within a computer system. The designed deep bidirectional LSTM is configured to precisely predict and forecast the dynamic states of time delay differential system, offering a robust framework for mimicking delays that commonly manifest in the real cyber-physical systems. To orchestrate the system compromises in real scenarios through the activation of bugged hardware, time delay factors [Formula: see text] and [Formula: see text] are introduced to account the time delays necessary for exploiting the bugged and patched nodes, respectively. Synthetic data is generated to train the LSTM network for all scenarios of the model for the dynamics of bugged, compromised, patched nodes and these acquired information is used for training, testing and validation purposes regarding exploitation of the bugged hardware. Comparative analysis on exhaustive simulations revealed a minimal difference between the LSTM’s predictions and those from the numerical outcomes with MSE in the range of [Formula: see text], underscoring the network’s effectiveness, robustness and stability in modeling complex system dynamics of hardware vulnerabilities.

Aung, HW, Jiao Li, J, An, Y & Su, SW 2025, 'A Real-Time Framework for EEG Signal Decoding With Graph Neural Networks and Reinforcement Learning', IEEE Transactions on Neural Networks and Learning Systems, pp. 1-12.
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Aung, HW, Li, JJ, Shi, B, An, Y & Su, SW 2025, 'EEG_GLT-Net: Optimising EEG graphs for real-time motor imagery signals classification', Biomedical Signal Processing and Control, vol. 104, pp. 107458-107458.
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Bibi, H, Abolhasan, M, Lipman, J, Abdollahi, M & Ni, W 2025, 'A comprehensive survey on privacy-preserving technologies for Smart Grids', Computers and Electrical Engineering, vol. 124, pp. 110371-110371.
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Bryant, L, Stubbs, P, Bailey, B, Nguyen, V, Bluff, A & Hemsley, B 2025, 'Interacting with virtual characters, objects and environments: investigating immersive virtual reality in rehabilitation', Disability and Rehabilitation: Assistive Technology, vol. 20, no. 1, pp. 107-117.
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PURPOSE: This pilot study aimed to (a) investigate opportunities for immersive Virtual Reality (VR) technology in communication, physical, and visual rehabilitation by examining the interaction of people without disabilities in a range of structured virtual environments; and (b) validate research protocols that might be used to evaluate the physical, visual, and verbal interaction of users in virtual worlds, and their safety while using the technology. METHODS: Thirteen adults identifying as people without disability were exposed to VR via a head-mounted display. A video-review method was used to qualitatively code and analyse each participant's communication, movement, orientation, and support needs. RESULTS: All participants oriented to their virtual environments sufficiently to use applications. Their spoken language was effective for interaction, although unconventional social behaviours were also observed. Two participants reported minor adverse reactions consistent with mild cybersickness. CONCLUSION: The results provide insight into the types of environments and characters that support the greatest communicative, physical, and visual interaction in immersive VR. The tested protocols are useful to assess safety when using VR, and to observe communicative, physical, and visual interaction with virtual environments and characters. Implications for future research and use of VR with people with communication, physical and visual disability are discussed.

Chen, J, Wu, K, Niu, J, Li, Y, Xu, P & Andrew Zhang, J 2025, 'Spectral and Energy Efficient Waveform Design for RIS-Assisted ISAC', IEEE Transactions on Communications, vol. 73, no. 1, pp. 158-172.
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Chen, Y-N, Ding, C, Zhu, H, Huang, X, Jia, Y, Liu, Y & Guo, YJ 2025, 'A Four-Port Shared-Aperture In-Band Full-Duplex Antenna Array Based on A Novel Common-Mode and Differential-Mode Combination Method', IEEE Transactions on Antennas and Propagation, pp. 1-1.
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Chu, NH, Hieu, NQ, Nguyen, DN, Hoang, DT, Phan, KT, Dutkiewicz, E, Niyato, D & Shu, T 2025, 'Dynamic Multi-Tier Resource Allocation Framework for Metaverse', IEEE Network, vol. 39, no. 1, pp. 197-204.
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Cuzmar, RH, Mora, A, Montenegro, A, Pereda, J, Gajardo, J & Aguilera, RP 2025, 'Optimal Fault-Tolerant Reference Generator for Circulating Currents in Modular Multilevel Matrix Converters', IEEE Transactions on Industrial Electronics, pp. 1-11.
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Cuzmar, RH, Mora, A, Pereda, J & Aguilera, RP 2025, 'An Improved Reference Generator Based on MPC of Circulating Currents and Common-Mode Voltage for Modular Multilevel Matrix Converters', IEEE Transactions on Industrial Electronics, vol. 72, no. 2, pp. 1958-1968.
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Dinh, TQ, Dau, SH, Lagunas, E, Chatzinotas, S, Nguyen, DN & Hoang, DT 2025, 'Quantum Annealing for Complex Optimization in Satellite Communication Systems', IEEE Internet of Things Journal, vol. 12, no. 4, pp. 3771-3784.
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Dong, S, Xie, W, Yang, D, Li, Y, Zhang, J, Tian, J & Lei, J 2025, 'SeaDATE: Remedy Dual-Attention Transformer With Semantic Alignment via Contrast Learning for Multimodal Object Detection', IEEE Transactions on Circuits and Systems for Video Technology, vol. 35, no. 5, pp. 4713-4726.
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Du, G, Cui, C, Li, L, Li, N, Lei, G & Zhu, J 2025, 'Comprehensive Performance Analysis of High-Speed PM Motors With Layered Rotor Structures', IEEE Transactions on Industrial Electronics, vol. 72, no. 4, pp. 3460-3470.
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Du, L, Chen, Z, Hu, H, Liu, X & Guo, Y 2025, 'An improved uncooperative space target de-tumbling method using electromagnetic de-tumbling devices with AC excitation', Advances in Space Research, vol. 75, no. 1, pp. 1264-1276.
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Duc Manh, B, Nguyen, C-H, Thai Hoang, D, Nguyen, DN, Zeng, M & Pham, Q-V 2025, 'Privacy-Preserving Cyberattack Detection in Blockchain-Based IoT Systems Using AI and Homomorphic Encryption', IEEE Internet of Things Journal, vol. 12, no. 11, pp. 16478-16492.
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Esfandiari, M, Lv, X, Chamani, S & Yang, Y 2025, 'Graphene metasurfaces: Advances in lens applications, design strategies, and fabrication techniques', Materials Today Electronics, vol. 11, pp. 100140-100140.
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Farah, N, Lei, G, Zhu, J & Guo, Y 2025, 'Robust Model-Free Reinforcement Learning Based Current Control of PMSM Drives', IEEE Transactions on Transportation Electrification, vol. 11, no. 1, pp. 1061-1076.
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Gajardo, J, Pereda, J, Aguilera, RP, Mora, A, Cuzmar, RH & Poblete, P 2025, 'Optimization-Based Control of Modular Multilevel Matrix Converters With Integrated Energy Storage for Simultaneous Variable-Speed Drive and Grid-Feeding', IEEE Transactions on Industrial Electronics, pp. 1-11.
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Ghanbari Motlagh, S, Oladigbolu, J & Li, L 2025, 'A review on electric vehicle charging station operation considering market dynamics and grid interaction', Applied Energy, vol. 392, pp. 126058-126058.
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Gu, Z, Jia, W, Piccardi, M & Yu, P 2025, 'Empowering large language models for automated clinical assessment with generation-augmented retrieval and hierarchical chain-of-thought', Artificial Intelligence in Medicine, vol. 162, pp. 103078-103078.
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Guo, K, Guo, Y, Fang, S, Wu, W & Gao, X 2025, 'Design Optimization and Performance Evaluation of a Novel Linear-Rotary Motor with Moving Coils', IEEE Transactions on Energy Conversion, pp. 1-16.
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Guo, W, Liu, D, Xie, W, Li, Y, Ning, X, Meng, Z, Zeng, S, Lei, J, Fang, Z & Wang, Y 2025, 'ShiftQuant: Towards Accurate and Efficient Sub-8-Bit Integer Training', IEEE Transactions on Circuits and Systems for Video Technology, pp. 1-1.
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Guo, X & Yang, Y 2025, 'Low-Profile Full-Space Transmission-Reflection- Integrated Multiple Focused and OAM Beams Metasurface for Indoor Communication', IEEE Transactions on Microwave Theory and Techniques, vol. 73, no. 6, pp. 3644-3654.
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Guo, X, Guo, Y, Luo, Y & Yang, Y 2025, 'Full-Space Transmission–Reflection-Integrated Metasurface for Multibeam Generation on Orthogonal Planes', IEEE Transactions on Microwave Theory and Techniques, pp. 1-11.
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Guo, Y, Xu, X, Jin, P, Zhou, T, Lei, G & Zhu, J 2025, 'Design and Analysis of a Novel Simultaneous Wireless Power and Data Transfer System with a High-Frequency Tank-Type Ferrite Core Loosely-Coupled Transformer', IEEE Transactions on Energy Conversion, pp. 1-12.
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Hassan, MA, Jamshidi, MB, Manh, BD, Chu, NH, Nguyen, C-H, Hieu, NQ, Nguyen, CT, Hoang, DT, Nguyen, DN, Van Huynh, N, Alsheikh, MA & Dutkiewicz, E 2025, 'Enabling technologies for Web 3.0: A comprehensive survey', Computer Networks, vol. 264, pp. 111242-111242.
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He, Y, Wang, S, Wei, G, Ding, C & Jay Guo, Y 2025, 'A New Buffering Scheme for Shared-Aperture Dual-Band Base Station Antenna Array Utilizing Tight-Coupling Concept', IEEE Transactions on Antennas and Propagation, vol. 73, no. 6, pp. 3492-3502.
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He, Y, Yu, G, Wang, X, Wang, Q, Niu, Z, Ni, W & Liu, RP 2025, 'Accountability and Reliability in 6G O-RAN: Who is Responsible When it Fails?', IEEE Wireless Communications, vol. 32, no. 2, pp. 52-59.
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He, Z, Xu, Y, Wang, B, Tian, G & Zhang, H 2025, 'Fabrication and mechanical properties of the NiAl sheet with a 3-dimensional network structure prepared by Ni nets and Al foils', Journal of Materials Processing Technology, vol. 336, pp. 118680-118680.
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Hiep Dinh, T, Kumar Singh, A, Manh Doan, Q, Linh Trung, N, Nguyen, DN & Lin, C-T 2025, 'An EEG signal smoothing algorithm using upscale and downscale representation^*', Journal of Neural Engineering, vol. 22, no. 3, pp. 036012-036012.
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Abstract Objective. Effective smoothing of electroencephalogram (EEG) signals while maintaining the original signal’s features is important in EEG signal analysis and brain–computer interface. This paper proposes a novel EEG signal-smoothing algorithm and its potential application in cognitive conflict (CC) processing. Approach. Instead of being processed in the time domain, the input signal is visualized in increasing line width, the representation frame of which is converted into a binary image. An effective thinning algorithm is employed to obtain a unit-width skeleton as the smoothed signal. Main results. Experimental results on data fitting have verified the effectiveness of the proposed approach on different levels of signal-to-noise (SNR) ratio, especially on high noise levels (SNR ⩽ 5 dB), where our fitting error is only 86.4%–90.4% compared to that of its best counterpart. The potential application of the proposed algorithm in EEG-based CC processing is comprehensively evaluated in a classification and a visual inspection task. The employment of the proposed approach in pre-processing the input data has significantly boosted the F 1 score of state-of-the-art models by more than 1%. The robustness of our algorithm is also evaluated via a visual inspection task, where specific CC peaks, i.e. the prediction error negativity and error-related positive potential (Pe), can be easily observed at ...

Hill, M, Stapleton, S, Nguyen, PT, Sais, D, Deutsch, F, Gay, VC, Marsh, DJ & Tran, N 2025, 'The potential regulation of the miR-17–92a cluster by miR-21', The International Journal of Biochemistry & Cell Biology, vol. 178, pp. 106705-106705.
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Hoang, LM, Nguyen, DN, Zhang, JA & Hoang, DT 2025, 'Adaptive Nullification of Multiple Correlated Jammers Using Deep Reinforcement Learning', IEEE Transactions on Vehicular Technology, pp. 1-14.
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Hoang, T-D, Huang, X & Qin, P 2025, 'Low-Complexity Direction-of-Arrival Estimation With Orthogonal Matching Pursuit for Large-Scale Lens Antenna Array', IEEE Transactions on Communications, vol. 73, no. 6, pp. 3924-3939.
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Hu, Y, Andrew Zhang, J, Wu, K, Deng, W & Jay Guo, Y 2025, 'Anchor Points Assisted Uplink Sensing in Perceptive Mobile Networks', IEEE Transactions on Communications, vol. 73, no. 2, pp. 904-920.
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Huang, S, Zheng, J, Qin, P, Zhan, Q & Chen, X 2025, 'Corrigendum to “Improved planar near-field measurement based on data assimilation” [Measurement 227 (2024) 114265]', Measurement, vol. 242, pp. 116168-116168.
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Huang, Y, Huang, Y, Zhang, Z, Wu, Q, Zhong, Y & Wang, L 2025, 'CSFRNet: Integrating Clothing Status Awareness for Long-Term Person Re-identification', International Journal of Computer Vision, vol. 133, no. 6, pp. 3180-3202.
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Hussain, M, Keshavarz, R & Shariati, N 2025, 'Advancements in Agricultural Microwave Remote Sensing: An Overview From Indoor to Space-Borne Platforms', IEEE Transactions on Instrumentation and Measurement, vol. 74, pp. 1-22.
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Jafaryahya, J, Keshavarz, R, Abolhasan, M, Lipman, J & Shariati, N 2025, 'Integrating Electrical Features for Simultaneous Prediction of Soil Moisture and Potassium Levels Based on Neural Network Prediction Model', IEEE Transactions on Instrumentation and Measurement, vol. 74, pp. 1-12.
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Jafaryahya, J, Keshavarz, R, Nikkhah, N, Nagatani, A & Shariati, N 2025, 'Soil Salinity Frequency-Dependent Prediction Model Using Permittivity Spectroscopy', IEEE Transactions on AgriFood Electronics, pp. 1-12.
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Jamshidi, MB, Hoang, DT, Nguyen, DN, Niyato, D & Warkiani, ME 2025, 'Revolutionizing biological digital twins: Integrating internet of bio-nano things, convolutional neural networks, and federated learning', Computers in Biology and Medicine, vol. 189, pp. 109970-109970.
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Jay Guo, Y, Guo, CA, Li, M & Latva-aho, M 2025, 'Antenna Technologies for 6G – Advances and Challenges', IEEE Transactions on Antennas and Propagation, pp. 1-1.
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Jin, P, Hu, Y, Liu, J, Guo, Y, Lei, G & Zhu, J 2025, 'A Flexible Compensation Control Strategy for High-Frequency Link Matrix Converters', IEEE Transactions on Industrial Electronics, pp. 1-9.
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Jin, P, Wang, H, Xu, H, Cao, C, Guo, Y, Lei, G & Zhu, J 2025, 'Stability Analysis for Three-Stage Serial PMSM Drive System Based on Bidirectional WPT', IEEE Transactions on Industrial Electronics, vol. 72, no. 5, pp. 4526-4534.
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Ju, M, He, C, Ding, C, Ren, W, Zhang, L & Ma, K-K 2025, 'All-Inclusive Image Enhancement for Degraded Images Exhibiting Low-Frequency Corruption', IEEE Transactions on Circuits and Systems for Video Technology, vol. 35, no. 1, pp. 838-856.
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Karami, H, Thurn, B, de Boer, NK, Ramos, J, Covington, JA, Lozano, J, Liu, T, Zhang, W, Su, S & Ueland, M 2025, 'Application of gas sensor technology to locate victims in mass disasters – a review', Natural Hazards, vol. 121, no. 1, pp. 31-60.
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Abstract The occurrence of mass disasters are increasing as a result of changing climates and the growing threat of terrorist activities/conflicts. When these tragedies strike, it is critical to locate victims. While search and rescue dogs are trained to locate the living, cadaver detection dogs are trained to locate the deceased. These dogs rely on the volatile organic compounds (VOCs) emitted from the victims to do so. Knowing which dog unit to deploy can be challenging, and the victims’ makeup is likely to change following disasters in densely inhabited places, where commingling is likely to occur. The use of electronic nose technologies in forensic science is a recent breakthrough. Due to their ability to detect differing VOCs, this technology can be used to assist in the recovery of victims in disaster events. The most popular types of accessible gas sensor technologies are briefly introduced and compared in this article for their potential use to locate missing persons, both living and deceased. The current and future market needs are articulated, and the lack of enrichment of these needs is examined in relation to the capabilities of existing gas sensors. This will inform further research areas of preference to increase victim detection capabilities.

Kathiresan, AC, Jeyaraj, PR, Albert, BK, Thanikanti, SB, Nallapaneni, MK & Alhelou, HH 2025, 'A versatile control of solar DVR for enhanced utilization and power quality improvement in a series‐connected wind‐solar farm', IET Renewable Power Generation, vol. 19, no. 1.
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AbstractThis paper presents a solar dynamic voltage restorer for hybrid series‐connected solar‐wind farms to mitigate the power quality problems. The operating region of the proposed hybrid system is derived and studied through graphical analysis. Upon examination of the system's operation under various grid conditions, the feasibility of solar PV power injected into the grid is verified. It is further proved that the series injection of voltage is also capable of mitigating the effects of voltage sag/swell, and unbalance, which have adverse effects on wind‐connected induction generators. Further, the effectiveness of Solar DVR to mitigate the fault ride‐through capability of the wind farm is analyzed. The non‐requirement for an energy storage device such as a battery is also validated. A control system for the series PV inverter is proposed and the computer simulations are performed to confirm the efficacy and ride‐through capability of the system.

Kielly, M, Chacon, A, Caracciolo, A, Bolst, D, Rosenfeld, A, Carminati, M, Fiorini, C, Franklin, DR, Guatelli, S & Safavi-Naeini, M 2025, 'An exploratory study of shielding strategies for boron neutron capture discrimination in 10B Neutron Capture Enhanced Particle Therapy', Physica Medica, vol. 129, pp. 104866-104866.
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Kumar Dalai, S, Prasad Panda, K, Siwakoti, YP & Panda, G 2025, 'Three‐Phase Neutral‐Point‐Clamped Multilevel Inverter Interfacing Grid Interactive Renewable Energy System', International Journal of Circuit Theory and Applications, vol. 53, no. 6, pp. 3450-3461.
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ABSTRACTThe potentiality of DC microgrid to incorporate renewable energy sources and improve power distribution efficiency has garnered considerable interest, especially in light of the ever‐increasing demand for efficient and clean energy systems. Multilevel inverters (MLIs) play a crucial role in interfacing these grid‐tied microgrids with various loads and energy sources. To improve the efficiency and dependability of such systems, this paper presents a three‐phase MLI interfacing solar photovoltaic (PV)‐battery‐based grid‐tied system. The system comprises of MLI with features such as (a) neutral point clamped input, (b) reduced number of switches to produce 7‐level output per phase, (c) self‐balanced capacitors, and (d) inherent voltage boosting ability. A novel power management control algorithm is designed to enhance the dynamic response and efficiency of the developed system. The effectiveness of the proposed system and its workability is validated through extensive experiments demonstrating enhanced power quality and efficient energy utilization.

Lai, J, Lv, X, Rahman, MM, Oni, MAI, Dey, S & Yang, Y 2025, 'An Angle-Multiplexed Multifocal Method for D-Band 2-D Beam-Scanning Transmitarray Leveraging 3-D Transmission Line Component', IEEE Antennas and Wireless Propagation Letters, vol. 24, no. 3, pp. 731-735.
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Le, TH, Nguyen, HAD, Ha, QP, Ahmed, M, Barthelemy, X, Jiang, N, Duc, H, Azzi, M & Riley, M 2025, 'Dependable Dempster-Shafer Inference Framework for Urban Air Quality Monitoring', IEEE Sensors Journal, pp. 1-1.
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Li, H, Teng, F, Guo, Q, Zhang, JA, Huang, X & Cheng, Z 2025, 'Efficient Asynchronous Uplink Sensing in Perceptive Mobile Networks via Accurate Delay Estimation', IEEE Transactions on Cognitive Communications and Networking, pp. 1-1.
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Li, H, Xiang, Y, Guo, Q, Liu, L, Huang, X, Cheng, Z & Pang, Y 2025, 'An Efficient Direct Downlink Sensing Method Using 5G NR SSB Signals in Perceptive Mobile Networks', IEEE Internet of Things Journal, vol. 12, no. 11, pp. 15360-15369.
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Li, H, Yu, B, Wei, Y, Wang, K, Xu, RYD & Wang, B 2025, 'KERMIT: Knowledge graph completion of enhanced relation modeling with inverse transformation', Knowledge-Based Systems, vol. 324, pp. 113500-113500.
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Li, K, Ding, J, Sun, X, Lei, G, Dianov, A, Demidova, G & Prakht, V 2025, 'Compensation Control of PMSMs Based on a High-order Sliding Mode Observer with Inertia Identification', IEEE Journal of Emerging and Selected Topics in Power Electronics, pp. 1-1.
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Li, K, Zha, X, Sun, X & Lei, G 2025, 'Model Predictive Control With Series Structure for Five-Phase PMSHM Based on Discrete Space Virtual Voltage Modulation', IEEE Transactions on Transportation Electrification, vol. 11, no. 1, pp. 1313-1323.
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Li, M, Cai, J, Deng, L, Li, X, Iacopi, F & Yang, Y 2025, 'Additively manufactured conductive and dielectric 3D metasurfaces for independent manipulation of broadband orbital angular momentum', Materials & Design, vol. 249, pp. 113500-113500.
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Li, M, Guo, YJ & Chen, S-L 2025, 'Enable Continuous Beam Scanning for Joint Communication and Sensing Employing the Generalized Joined Coupler Matrix', IEEE Transactions on Vehicular Technology, pp. 1-13.
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Li, T, Sun, X, Yang, Z & Lei, G 2025, 'Simplified Two-Step Model Predictive Control With Fast Voltage Vector Search', IEEE Transactions on Industrial Electronics, vol. 72, no. 4, pp. 3303-3312.
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Li, T, Zhao, S, Huang, Y, Lu, J & Burnett, IS 2025, 'A distributed adaptive wave field synthesis system', The Journal of the Acoustical Society of America, vol. 157, no. 3, pp. 2221-2235.
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The conventional wave field synthesis (WFS) theory is based on the free field assumption and the performance of systems based on it deteriorates significantly in reverberant environments. By introducing an error microphone array to monitor reproduction errors, the adaptive WFS (AWFS) system adjusts the loudspeaker signals to correct the sound field in reverberant environments. The AWFS system utilizes a centralized control strategy with a single processor, which imposes a high computational burden on the processor due to global error estimation, limiting the application scale. To address this issue, this paper proposes a distributed AWFS (DAWFS) system for an acoustic sensor and actuator network using a distributed signal processing strategy. Simulation results in a rectangular room demonstrate that the proposed DAWFS system can achieve comparable sound reproduction performance to the conventional AWFS system, both at the near-field error microphone array and in the target listening area. A global computational complexity analysis shows that the proposed DAWFS system exhibits significantly lower computational complexity than existing AWFS systems in various application scenarios, especially for massive channel systems. The results further demonstrate the potential applicability of the proposed DAWFS system in realistic reverberant environments.

Lin, X, Ma, B, Wang, X, Yu, G, He, Y, Ni, W & Liu, RP 2025, 'CAN-Trace Attack: Exploit CAN Messages to Uncover Driving Trajectories', IEEE Transactions on Intelligent Transportation Systems, vol. 26, no. 3, pp. 3223-3236.
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Liu, B, Ni, W, Liu, RP, Guo, YJ & Zhu, H 2025, 'Delay-Sensitive Goods Delivery and In-Situ Sensing Using A Multi-Task Drone', IEEE Transactions on Mobile Computing, pp. 1-14.
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Liu, C, Du, H, Lei, G, Wang, Y & Zhu, J 2025, 'Design and Analysis of Modular Permanent Magnet Claw Pole Machines With Hybrid Cores for Electric Vehicles', IEEE Transactions on Energy Conversion, vol. 40, no. 2, pp. 1047-1061.
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Liu, C, Du, H, Lei, G, Wang, Y & Zhu, J 2025, 'Multi-Physics Coupling Analysis of Permanent Magnet Claw Pole Machine with Hybrid Cores by Inverter Power Supply', Diangong Jishu Xuebao Transactions of China Electrotechnical Society, vol. 40, no. 6, pp. 1758-1770.
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The stator core of the permanent magnet claw pole machine (PMCPM) is typically made of soft magnetic composite material (SMC). SMC has defects such as high eddy current loss at low frequency, low magnetic permeability, and poor mechanical strength. In addition, because of the high cost of manufacturing large-sized SMC cores, previous designs for PMCPM were often based on low-power motors. If SMC is combined with other materials, using hybrid cores can improve PMCPM Performance and reduce manufacturing costs. However, research on PMCPM with hybrid cores is limited to electromagnetic fields. Various physical fields inside the motor are coupled, and a multi-physics coupling analysis should be used to comprehensively study the impact of hybrid cores.Compared with traditional PMCPM with SMC cores, the paper studies the impact of inverter power supply on the Performance of PMCPM with hybrid cores and summarizes the advantages of hybrid cores. Firstly, the electromagnetic Performance of PMCPM with hybrid cores is analyzed using the field-circuit coupling method. The temperature distribution of PMCPM with hybrid cores under different power supply modes is obtained, and the influence of the power supply mode is studied. Then, a comparison is made between PMCPM with hybrid cores and PMCPM with SMC cores from the perspectives of electromagnetic field, temperature field, and stress field. Finally, the Simulation results are validated through prototype experiments.The multi-physics coupling Simulation analysis shows that under rated conditions, the torque ripple of the motor is 22.5% when powered by the inverter and only 10% when powered by the current source. The inverter power supply greatly increases the torque ripple, increasing the iron and permanent magnet eddy current losses by 22.2% and 44%, respectively. Compared with the PMCPM with SMC cores, hybrid cores reduce the maximum compressive stress on the SMC part of the stator core by 34.1% and the material cos...

Liu, C, Yang, G, Wang, Y & Lei, G 2025, 'Shape Optimization Design of Claw Pole Permanent Magnet Wind Generator with Hybrid Core', Journal of Electrical Engineering & Technology, vol. 20, no. 5, pp. 3135-3146.
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Liu, C, Yang, G, Wang, Y, Lei, G & Zhu, J 2025, 'Comparative Study of Radial, Axial and Transverse Flux Generators with Hybrid Cores for 5 kW Wind Generator', Journal of Electrical Engineering & Technology, vol. 20, no. 5, pp. 3123-3134.
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Liu, F, Wang, M, Liu, Y, Ni, W & Jamalipour, A 2025, 'Hybrid NOMA Offloading for Delay-Sensitive Applications in MEC-Based NB-IoT Networks', IEEE Internet of Things Journal, vol. 12, no. 5, pp. 5245-5259.
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Liu, F, Yuan, Z, Guo, Q, Zhang, Y, Wang, Z & Zhang, JA 2025, 'Joint Near Field Uplink Communication and Localization Using Message Passing-Based Sparse Bayesian Learning', IEEE Transactions on Vehicular Technology, vol. 74, no. 5, pp. 7666-7675.
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Liu, L, Guo, Y, Yin, W, Lei, G, Sun, X & Zhu, J 2025, 'Efficient Design Optimization of PMSM Drive Systems Using Improved Equivalent-Circuit-Based Loss Minimization Control', IEEE Transactions on Industrial Electronics, vol. 72, no. 4, pp. 3280-3291.
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Liu, P, Fei, Z, Wang, X, Huang, J, Hu, J & Andrew Zhang, J 2025, 'Joint Offloading and Beamforming Design in Integrating Sensing, Communication, and Computing Systems: A Distributed Approach', IEEE Transactions on Communications, pp. 1-1.
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Liu, X, Li, M, Yu, G, Wang, X, Ni, W, Li, L, Peng, H & Liu, RP 2025, 'BlockFUL: Enabling Unlearning in Blockchained Federated Learning', IEEE Transactions on Information Forensics and Security, pp. 1-1.
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Liu, Y, Zhang, Y, Zhang, M, Xu, W, Shao, S & Guo, Y 2025, 'Minimum Torque Ripple Control for Brushless Doubly-Fed Induction Generator-DC System Under Power Winding Open-Phase Fault', IEEE Transactions on Power Electronics, vol. 40, no. 4, pp. 5743-5755.
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Luo, Z, Yang, L, Su, T, Zhu, X & Gómez-García, R 2025, 'Single-Ended and Balanced Flat-Group-Delay RF Low-Pass Filters With Input-Quasi-Reflectionless Behavior for Digital-Communication Systems', IEEE Transactions on Microwave Theory and Techniques, vol. 73, no. 1, pp. 321-334.
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Lv, X, Yang, Y, Luo, Z & Tyo, JS 2025, 'Multimaterial 3-D-Printed FSSs for Ultrawide and Dual Passbands in the K-Ka Spectra', IEEE Transactions on Microwave Theory and Techniques, vol. 73, no. 1, pp. 75-86.
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Ma, B, Li, Y, Zheng, J, Zhang, J, Huang, S, Zhu, J & Lei, G 2025, 'Multiphysics Topology Optimization of SynRMs Considering Control Performance and Machinability', IEEE Transactions on Transportation Electrification, vol. 11, no. 1, pp. 1287-1297.
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Ma, B, Xing, J, Huang, S, Wang, K, Zhang, J, Lei, G & Zhu, J 2025, 'Cooling System Design for High-Power-Density Permanent Magnet Synchronous Motor Based on Micro Heat Pipe Array', IEEE Transactions on Transportation Electrification, vol. 11, no. 2, pp. 6719-6730.
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Minh Tuan, B, Nguyen, DN, Linh Trung, N, Nguyen, V-D, Van Huynh, N, Thai Hoang, D, Krunz, M & Dutkiewicz, E 2025, 'Securing MIMO Wiretap Channel With Learning-Based Friendly Jamming Under Imperfect CSI', IEEE Internet of Things Journal, vol. 12, no. 11, pp. 16009-16022.
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Mirazur Rahman, M, Yang, Y & Dey, S 2025, 'Application of Metamaterials in Antennas for Gain Improvement: A Study on Integration Techniques and Performance', IEEE Access, vol. 13, pp. 49489-49503.
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Moazzen, F & Hossain, MJ 2025, 'A two-layer strategy for sustainable energy management of microgrid clusters with embedded energy storage system and demand-side flexibility provision', Applied Energy, vol. 377, pp. 124659-124659.
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Moradian, M, Lie, TT & Gunawardane, K 2025, 'Design and performance evaluation of low-voltage solid-state DCCB using capacitor-based surge mitigation techniques', Power Electronic Devices and Components, vol. 11, pp. 100095-100095.
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Moradian, M, Lie, TT & Gunawardane, K 2025, 'Enhanced LV solid-state DC circuit breaker design with divided surge absorption technique', Electric Power Systems Research, vol. 241, pp. 111280-111280.
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Moradian, M, Peykarporsan, R, Lie, TT & Gunawardane, K 2025, 'Bidirectional Solid State Circuit Breaker with Passive Surge Absorber for LV Applications', IEEE Journal of Emerging and Selected Topics in Power Electronics, pp. 1-1.
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Moradian, M, Peykarporsan, R, Lie, TT & Gunawardane, K 2025, 'Low-Voltage Solid State DCCB Design Based on Bypassed Bidirectional Thyristor-Capacitor Suppressor', IEEE Transactions on Power Electronics, vol. 40, no. 1, pp. 516-525.
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Nabeel, MI, Afzal, MU, Singh, K, Thalakotuna, DN & Esselle, KP 2025, 'Waveguide-Based All-Metal Near-Field Metasurfaces for Linearly and Circularly Polarized Beam Steering Antennas', IEEE Access, vol. 13, pp. 10857-10869.
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Nanda, P, Srivastava, S, Verma, VK & Vyas, P 2025, 'Preface', Smart Innovation Systems and Technologies, vol. 398, pp. v-vi.

Ngo, QT, He, Y, Jayawickrama, B & Dutkiewicz, E 2025, 'A Fast Fuzzy DRL-Based Joint Beam Design and Power Allocation for Multi-Beam GEO-LEO Coexisting Satellite Networks', IEEE Transactions on Wireless Communications, pp. 1-1.
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Ngo, QT, Jayawickrama, B, He, Y & Dutkiewicz, E 2025, 'A Novel Satellite-Based REM Construction in Cognitive GEO-LEO Satellite IoT Networks', IEEE Internet of Things Journal, vol. 12, no. 6, pp. 7532-7548.
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Ngo, QT, Jayawickrama, BA, He, Y, Dutkiewicz, E, Weththasinghe, K, Clark, N, Arbon, E & Bowyer, M 2025, 'Optimizing Spectrum Sensing in Cognitive GEO-LEO Satellite Networks: Overcoming Challenges for Effective Spectrum Utilization', IEEE Vehicular Technology Magazine, pp. 2-11.
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Nguyen, CT, Liu, Y, Du, H, Hoang, DT, Niyato, D, Nguyen, DN & Mao, S 2025, 'Generative AI-Enabled Blockchain Networks: Fundamentals, Applications, and Case Study', IEEE Network, vol. 39, no. 2, pp. 232-241.
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Nguyen, DV, Tran, TL, Nguyen, H, Chen, G, Lai, TK, Song, P, Tran, TT, Tran, C-D, Bell, J & Dinh, T 2025, 'The Concept of Pressure-Induced Conduction Band Mismatch in Soft–Hard Semiconductors for Self-Powered Phototronic Pressure Sensing', ACS Applied Materials & Interfaces, vol. 17, no. 22, pp. 32827-32837.
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Nguyen, HAD, Le, HT, Barthelemy, X, Azzi, M, Duc, H, Jiang, N, Riley, M & Ha, QP 2025, 'A Deep-Learning-Based Visualization Tool for Air Pollution Forecasting', IEEE Software, vol. 42, no. 2, pp. 47-56.
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Nguyen, X-B, Phan, X-H & Piccardi, M 2025, 'Fine-tuning text-to-SQL models with reinforcement-learning training objectives', Natural Language Processing Journal, vol. 10, pp. 100135-100135.
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Nikkhah, N, Keshavarz, R & Shariati, N 2025, 'Highly Sensitive Differential 3D Oblique-Gap Rectangular Sensor for Non-Invasive Glucose Level Monitoring', IEEE Sensors Journal, pp. 1-1.
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Noh, M-S, Kim, D-H, Guo, Y & Lee, H-J 2025, 'A Study on the Performance of Bearingless PMSM Based on Rotor Permanent Magnet Arrangement', The transactions of The Korean Institute of Electrical Engineers, vol. 74, no. 4, pp. 739-746.
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Oladigbolu, JO, Bilal, M, Gupta, S, Mujeeb, A & Li, L 2025, 'A novel approach for optimal deployment of plug-in electric vehicles with integrated renewable energy sources', Electrical Engineering, vol. 107, no. 4, pp. 3847-3881.
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Park, H-M, Lee, H-W, Park, C-B, Guo, Y & Lee, J-B 2025, 'Solution to Mitigate the Disadvantages in the Design of LLC Resonant Converters for Electric Vehicle Fast Chargers with High Output Power and Wide Output Voltage Range', The transactions of The Korean Institute of Electrical Engineers, vol. 74, no. 2, pp. 316-325.
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Parnell, J, Unanue, IJ, Matthews, S & Piccardi, M 2025, 'APG: Automatic Prompt Generation for Improved Document Summarization', IEEE Transactions on Audio, Speech and Language Processing, pp. 1-15.
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Pfeffer, MA, Nguyen, AHP, Kim, K, Wong, JKW & Ling, SH 2025, 'Evolving optimized transformer-hybrid systems for robust BCI signal processing using genetic algorithms', Biomedical Signal Processing and Control, vol. 108, pp. 107883-107883.
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Picano, B, Hoang, DT & Nguyen, DN 2025, 'A Matching Game for LLM Layer Deployment in Heterogeneous Edge Networks', IEEE Open Journal of the Communications Society, vol. 6, pp. 3795-3805.
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Pichot, C, Huff, GH, Yang, Y, Jiang, ZH, Tong, X, Loh, TH, Alemaryeen, A, Wagih, M, Noghanian, S, Paryani, RC, Huang, Y, Sakakibara, K, Vipiana, F, Fear, E, Bakshi, SC, Waterhouse, R, Urbina, J, Meinrath, SD, Shih, BP-J, Sharma, R, Manohar, V, Dagefu, FT & Ito, K 2025, 'New and Emerging Directions in the Fields of Antennas and Propagation', IEEE Transactions on Antennas and Propagation, vol. 73, no. 1, pp. 566-581.
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Poblete, P, Aguilera, RP, Pereda, J, Cuzmar, RH, Alcaide, AM, Lu, DD-C, Siwakoti, YP & Acuna, P 2025, 'Offset-Free Optimal Control of Cascaded H-Bridge Converters Based on a Kalman Filter Harmonic Compensator', IEEE Transactions on Power Electronics, vol. 40, no. 1, pp. 625-637.
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Poblete, P, Cuzmar, RH, Aguilera, RP, Pereda, J, Alcaide, AM, Lu, D, Siwakoti, YP & Konstantinou, G 2025, 'Dual-Stage MPC for SoC Balancing in Second-Life Battery Energy Storage Systems Based on Delta-Connected Cascaded H-Bridge Converters', IEEE Transactions on Power Electronics, vol. 40, no. 1, pp. 500-515.
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Ponrekha A., S, Subathra, MSP, Bharatiraja, C, Manoj Kumar, N & Haes Alhelou, H 2025, 'A topology review and comparative analysis on transformerless grid‐connected photovoltaic inverters and leakage current reduction techniques', IET Renewable Power Generation, vol. 19, no. 1.
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AbstractPhotovoltaic energy source growth is significant in power generation field. Moreover, grid connected inverters strengthen this growth. Development of transformerless inverters with higher efficiency, low cost and size is competitive than the inverters with transformers. However, leakage current generation in transformerless inverters is a challenge to their growth. The research in evolution of new transformerless inverter topologies with higher efficiency, boosting capability, and reduced leakage current is interesting. This paper presents an extensive discussion of transformerless inverters under the categorization of their structures and the subcategorization with leakage current reduction techniques. The components and connections of inverters are differentiated with colours for the effortless understanding of operation. The detailed comparisons of transformerless inverters based on performance and construction are also presented with their strengths and weaknesses. To give deep intuition on characteristics of transformerless inverters, selected inverters are simulated with different operating conditions. Loss contribution of each switch in the selected inverters is analysed, to help the new researchers, designers and engineers to design efficient topologies.

Pradeepkumar, A, Yang, Y, Castañeda, E, Angel, FA & Iacopi, F 2025, 'An ionic polymer route to a stable unpinning of the Fermi level of highly doped graphene', Journal of Applied Physics, vol. 137, no. 22.
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Epitaxial graphene on cubic silicon carbide on silicon could enable unique optical metasurface devices seamlessly integrated with CMOS technologies. However, one of the most promising methods to obtain large-scale epitaxial graphene on this challenging system typically leads to a highly p-type-doped graphene with a Fermi level pinned at ∼0.55 eV below the Dirac point. Hence, the use of conventional gate dielectric materials such as SiO2 and Si3N4 precludes the tuning of the graphene carrier concentration. We demonstrate that this limitation can be overcome with the use of polyethyleneimine (PEI) as a gate dielectric material for graphene field-effect transistors. We achieve significant tuning of the graphene's Fermi level, enabling ambipolar operation exceeding a 3 eV window. In addition, we demonstrate that excellent stability of the PEI-based devices can be achieved, thanks to the addition of a thin protective oxide film. These findings highlight the potential of ionic polymers for advancing reconfigurable graphene-based devices for photonic applications.

Qi, J, Li, L, Hossain, J & Lei, G 2025, 'Optimizing electric vehicle parking lot profitability through vehicle-to-grid incentive decision-making in multiple energy markets', Sustainable Energy, Grids and Networks, vol. 41, pp. 101595-101595.
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Qian, J, Wang, Y, Xue, Y, Begum, H, Fu, Y-Q & Lee, JE-Y 2025, 'Integrated functions of microfluidics and gravimetric sensing enabled by piezoelectric driven microstructures', Applied Physics Reviews, vol. 12, no. 1.
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Micro- and nano-electromechanical systems resonators have been regarded as powerful tools for precision mass detection, and their abilities to measure these in a liquid environment open various opportunities for biosensing, chemical analysis, and environmental monitoring. Apart from overcoming issues of fluidic damping and electrical interfaces, there is a great challenge of bringing microanalytes to these devices with the required precision and scaling for high throughput sensing. Herein, we address the above challenges by proposing a self-excited localized acoustic manipulation methodology based on a piezoelectric micromechanical diaphragm resonator (PMDR). Such a PMDR integrates acoustofluidics and mass sensing functions in tandem on a single device. Particle enrichment is realized within tens of seconds and the limit of detection is enhanced by mitigating common issues such as low capture rate and non-uniform distribution. The developed PMDR is versatile in its applicability to a range of particle sizes and densities for both acoustofluidic actuation and in situ mass sensing. This work addresses long-term technical challenges of inaccurate and inefficient measurement of liquid phase resonance mass sensing with great application potentials in biochemical detection and environmental monitoring.

Ramadan, HS, Haes Alhelou, H & Ahmed, AA 2025, 'Impartial near‐optimal control and sizing for battery hybrid energy system balance via grey wolf optimizers: Lead acid and lithium‐ion technologies', IET Renewable Power Generation, vol. 19, no. 1.
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AbstractThe balance of renewable‐energy‐based power systems has witnessed significant importance particularly with their rapid integration within these systems. The optimal sizing and control of energy storage systems (ESS) in hybrid power systems (HPSs) based on renewable energy becomes of particular interest. In this research, the HPS under study comprises PV, wind, and energy storage system. Two battery technologies, lead acid (LA) and lithium‐Ion (LI)—are conducted to reach a near‐optimal solution via metaheuristic optimization algorithms in HPS. This paper aims at reaching the equilibrium of the generation consumption for HPS through applying a novel technique, grey wolf optimization (GWO) through the optimal battery sizing of the HPS. The optimization is used for reaching the due balance between the production of power and that absorbed by the load, by minimizing the difference between the final and initial state of charge. Based on numerical simulations, the two different battery technologies are considered in the sizing of the ESS using GWO approach. From the simulation results, the proposed GWO leads to more enhanced performance with LI rather than LA by 3.1% with reduced number of parallel/series cells (Np/Ns) of 240/3450 and 270/3500. Accordingly, the GWO provides an adequate dynamic controlled performance.

Raza, A, Keshavarz, R & Shariati, N 2025, 'A Multiband Forward–Backward Nonlinear Metamaterial Network: An Agile Solution for Wireless Power Transfer, Sensing, and Communication', IEEE Transactions on Microwave Theory and Techniques, pp. 1-14.
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Raza, A, Keshavarz, R & Shariati, N 2025, 'In Situ Soil Moisture Monitoring Using Compact Multiband Sensing System for Smart Agriculture', IEEE Transactions on AgriFood Electronics, pp. 1-12.
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Raza, MA, Abolhasan, M, Lipman, J & Ni, W 2025, 'Device-Level Learning-Based Distributed Power Control for Uplink NOMA in IoT Networks', IEEE Transactions on Cognitive Communications and Networking, pp. 1-1.
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Santra, A, Wang, P, Shaker, G, Mysore, BS, Dolmans, G, Chen, Y, Shariati, N & Pandharipande, A 2025, 'Machine Learning-Powered Radio Frequency Sensing: A Review', IEEE Sensors Journal, pp. 1-1.
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Shafei, H, Farhangi, M, Li, L, Aguilera, RP & Alhelou, HH 2025, 'A Novel Cyber-Attack Detection and Mitigation for Coupled Power and Information Networks in Microgrids Using Distributed Sliding Mode Unknown Input Observer', IEEE Transactions on Smart Grid, vol. 16, no. 2, pp. 1667-1681.
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Shang, C, Thai Hoang, D, Yu, J, Hao, M & Niyato, D 2025, 'Constructing the Metaverse With a New Perspective: UAV FoV-Assisted Low-Latency Imaging', IEEE Wireless Communications Letters, vol. 14, no. 1, pp. 158-162.
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Shen, Y, Chen, C, Zou, Z, Li, W, Zhang, Y, Zhang, H, Yu, Z, Zhao, H & Wang, G 2025, 'Room temperature aqueous-phase hydrogenation coupling with green hydrogen: Sustainable technologies innovating by efficient Co-CoO _x @NC catalyst derived from N-induced interfacial electron rearrangement', Nano Research, vol. 18, no. 2, pp. 94907118-94907118.
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Shrestha, S, Huang, X, Saleem, K, Bevinakoppa, S & Jan, T 2025, 'Quantification of Interference Constraint for Small Cells in Low SINR Regime With Steepest Ascent Method', IEEE Access, vol. 13, pp. 2328-2339.
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Song, L-Z, Diao, Y-Z, Qin, P-Y, Ansari, M, von Loesecke, J, Maci, S & Jay Guo, Y 2025, 'A 3-D-Printed Broadband Wide-Angle Multibeam Flat GRIN Lens Aided by Multifocal Ray-Path Analyses', IEEE Transactions on Antennas and Propagation, vol. 73, no. 1, pp. 22-32.
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Song, Y, Liu, Z, Li, G, Xie, J, Wu, Q, Zeng, D, Xu, L, Zhang, T & Wang, J 2025, 'EMS: A Large-Scale Eye Movement Dataset, Benchmark, and New Model for Schizophrenia Recognition', IEEE Transactions on Neural Networks and Learning Systems, vol. 36, no. 5, pp. 9451-9462.
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Stone, G 2025, 'Book Reviews', IEEE Electrical Insulation Magazine, vol. 41, no. 2, pp. 39-39.
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Su, SW, Zhang, Z, Celler, B & Savkin, A 2025, 'Distributed integral controllability for non-square processes: A comprehensive study and numerical analysis', Journal of the Franklin Institute, vol. 362, no. 1, pp. 107338-107338.
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Su, Z, Sun, X, Lei, G & Yao, M 2025, 'Improved Model-Free Predictive Current Control for SPMSM Drives With Adaptive Prediction Horizon Strategy', IEEE Transactions on Industrial Electronics, vol. 72, no. 6, pp. 5705-5715.
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Sun, X, Chen, Z, Pan, M, Cai, Y, Jin, Z, Lei, G & Tian, X 2025, 'Robust Energy Management Optimization for PHEB Considering Driving Uncertainties by Using Sequential Taguchi Method', IEEE Transactions on Transportation Electrification, vol. 11, no. 2, pp. 5191-5200.
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Sun, X, Huang, Z, Yang, Z, Lei, G & Li, T 2025, 'Improved Model-Free Predictive Current Control for Suppressing Inverter Nonlinearity and Parametric Time-Varying of PMSM Drive Systems', IEEE Transactions on Industrial Electronics, pp. 1-10.
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Sun, X, Wang, N, Yao, M & Lei, G 2025, 'Position Sensorless Control of SRMs Based on Improved Sliding Mode Speed Controller and Position Observer', IEEE Transactions on Industrial Electronics, vol. 72, no. 1, pp. 100-110.
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Sun, X, Wen, Y, Han, S & Lei, G 2025, 'Fault Diagnosis of Power Converter for Switched Reluctance Motors Based on Current Reconstruction Scheme', IEEE Transactions on Transportation Electrification, vol. 11, no. 1, pp. 4169-4178.
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Sun, X, Wen, Y, Zhang, L, Yao, M & Lei, G 2025, 'Fault Detection and Fault-Tolerant Control of Switched Reluctance Motor Based on Dual-Sensor Current Detection Scheme', IEEE Transactions on Transportation Electrification, vol. 11, no. 1, pp. 19-28.
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Sun, X, Wen, Y, Zhu, Y, Zhang, L, Yao, M & Lei, G 2025, 'FCS-MPC With Improved Prediction for Suppressing Torque and Current Pulsations of Switched Reluctance Motors', IEEE Transactions on Industrial Electronics, vol. 72, no. 7, pp. 6831-6839.
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Sun, X, Xu, Z, Pan, M, Sun, C & Lei, G 2025, 'Medium-to-High Speed Range Sensorless Control of SRM Drives Based on Unaligned Rotor Position Estimation', IEEE Transactions on Industrial Electronics, pp. 1-10.
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Sun, X, Xu, Z, Pan, M, Sun, C, Pan, W & Lei, G 2025, 'Sensorless Control Strategy for SRM Based on Flux Linkage in Medium to High-Speed Range', IEEE Transactions on Industrial Electronics, pp. 1-9.
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Sun, X, Zhang, S, Yang, Z, Lei, G & Li, T 2025, 'Improved DPCC and Parameter Identification for Permanent Magnet Synchronous Motors With Current Error Compensation', IEEE Transactions on Industrial Electronics, pp. 1-11.
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Sun, Z, Liang, Z, Lv, X, Zhou, Y, Liu, S, Luo, Z & Yang, Y 2025, 'C-/Ka-Band Low-Profile Circularly Polarized Shared-Aperture Antenna for CubeSat Communications', IEEE Transactions on Antennas and Propagation, vol. 73, no. 2, pp. 1221-1226.
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Sun, Z, Lv, X & Yang, Y 2025, 'Wideband Sequential Rotation Dual-Circularly Polarized Magnetoelectric Dipole Array With Polarization Independent Control for Intelligent Vehicle Communications', IEEE Transactions on Antennas and Propagation, vol. 73, no. 4, pp. 2666-2671.
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Sun, Z, Lv, X, Zhu, X, Liang, Z & Yang, Y 2025, 'A Dual-Band Circularly Polarized Antenna With Shared Aperture for Satellite-Assisted Internet of Things Communications', IEEE Internet of Things Journal, vol. 12, no. 7, pp. 8461-8469.
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Tan, X, Yang, R, Chen, S-L, Chan, KF, Chen, BJ, Cui, Z-Q, Qin, P-Y, Guo, YJ & Chan, CH 2025, 'Highly Integrated Full-Space Coding Metasurface for LP and CP Waves Manipulation Spanning Millimeter-Wave and Sub-THz Bands', Journal of Lightwave Technology, vol. 43, no. 1, pp. 288-298.
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Tofigh, F & Lipman, J 2025, 'Human Presence Detection Sensor Using Polarization Insensitive Metamaterial Absorbers', IEEE Access, vol. 13, pp. 81725-81735.
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Tong, M, Huang, X & Andrew Zhang, J 2025, 'Joint Inter-Symbol Interference and I/Q Imbalance Cancellation in FTN Systems', IEEE Transactions on Wireless Communications, vol. 24, no. 4, pp. 2680-2692.
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Tong, M, Huang, X, Andrew Zhang, J & Hanzo, L 2025, 'Adaptive FTN Signaling Over Rapidly-Fading Channels', IEEE Transactions on Communications, pp. 1-1.
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Torres, IJ, Aguilera, RP & Ha, QP 2025, 'Design and Performance Evaluation of Nonlinear Model-Predictive Control for 3-D Ground Target Tracking With Fixed-Wing UAVs', IEEE Open Journal of the Industrial Electronics Society, vol. 6, pp. 76-94.
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Tusher, AS, Islam, MR, Hossain, MA, Ishraque, MF, Maliha, MI, Rahman, MA & Hossain, J 2025, 'FALCON: A Semi-Supervised Framework for Addressing Physical and Cyber Anomalies in DGA-based Transformer Fault Diagnosis', IEEE Transactions on Dielectrics and Electrical Insulation, pp. 1-1.
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Tyler, G, Luo, S, Calderon Hurtado, A & Makki Alamdari, M 2025, 'Semi-supervised bridge indirect structural health monitoring using Isolation Distributional Kernels', Mechanical Systems and Signal Processing, vol. 226, pp. 112296-112296.
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Wang, K, Huang, S, Zhang, J, Ma, B, Xing, J, Lei, G & Zhu, J 2025, 'An Effective Cooling Scheme Using Micro Heat Pipe Array for Electrical Machines With Distributed Windings', IEEE Transactions on Transportation Electrification, vol. 11, no. 2, pp. 5891-5900.
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Wang, L, Wang, S, Zhang, Q, Wu, Q & Xu, M 2025, 'Federated User Preference Modeling for Privacy-Preserving Cross-Domain Recommendation', IEEE Transactions on Multimedia, pp. 1-12.
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Wang, Q, Yu, G, Sai, Y, Sun, C, Nguyen, LD & Chen, S 2025, 'Understanding DAOs: An Empirical Study on Governance Dynamics', IEEE Transactions on Computational Social Systems, pp. 1-19.
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Wang, X, Wu, K, Andrew Zhang, J, Gong, S & Xing, C 2025, 'Bayesian Sensing for Time-Varying Channels in ISAC Systems', IEEE Transactions on Communications, pp. 1-1.
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Wang, X, Zhang, Y, Shen, Y, Liu, J & Zhang, H 2025, 'Efficient improvement strategy for supported iridium-based catalysts in pure water electrolysis', Journal of Alloys and Compounds, vol. 1023, pp. 180071-180071.
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Wang, X-Y, Yang, S, Zhai, H-Y, Masouros, C & Andrew Zhang, J 2025, 'Windowing Optimization for Fingerprint-Spectrum-Based Passive Sensing in Perceptive Mobile Networks', IEEE Transactions on Communications, vol. 73, no. 2, pp. 1367-1382.
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Wang, Y, Xu, M, Wang, Z, Wang, Y & Zhang, JA 2025, 'User Re-Identification Through mmWave Radio Imaging', IEEE Internet of Things Journal, pp. 1-1.
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Wang, Z, Wang, Q, Yu, G & Chen, S 2025, 'TDML—A trustworthy distributed machine learning framework', Future Generation Computer Systems, pp. 107951-107951.
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Wang, Z, Zhang, JA, Zhang, H, Xu, M & Guo, J 2025, 'Passive Human Tracking With WiFi Point Clouds', IEEE Internet of Things Journal, vol. 12, no. 5, pp. 5528-5543.
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Wei, F, Zhou, X-C, Shi, Z-H, Liu, H-Y & Qin, P-Y 2025, 'A Balanced Bandpass Filter With High-Selectivity and Common-Mode Suppression Based on Inverted Microstrip Gap Waveguide', IEEE Microwave and Wireless Technology Letters, vol. 35, no. 2, pp. 181-184.
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Weththasinghe, K, Ngo, QT, He, Y & Jayawickrama, B 2025, 'Optimizing Beam Size in Multibeam LEO Satellite Networks: Addressing Interbeam Interference, Doppler Shift, and Frequency Reuse', IEEE Transactions on Aerospace and Electronic Systems, vol. 61, no. 3, pp. 5871-5884.
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Wu, J, Li, L, Zhang, J & Xiao, B 2025, 'Flexibility estimation of electric vehicles and its impact on the future power grid', International Journal of Electrical Power & Energy Systems, vol. 164, pp. 110435-110435.
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Wu, T, Dai, P, Xue, G, Guo, Y, Lei, G, Zhu, J & Wang, Y 2025, 'A Novel Thermal Analysis Method for Tubular PM Linear Motors Based on Transfer Learning', IEEE Transactions on Transportation Electrification, vol. 11, no. 3, pp. 7379-7388.
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Xia, H, Chen, S-L, Wang, Y, Zhao, Y, Jia, H, Yang, R & Jay Guo, Y 2025, 'Deep-learning-assisted intelligent design of terahertz hybrid-functional metasurfaces with freeform patterns', Optics & Laser Technology, vol. 181, pp. 112041-112041.
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Xiao, Z, Liu, X, Zeng, Y, Zhang, JA, Jin, S & Zhang, R 2025, 'Rethinking Waveform for 6G: Harnessing Delay-Doppler Alignment Modulation', IEEE Communications Magazine, vol. 63, no. 5, pp. 110-117.
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Xie, A, Zhang, J, Chen, C, Zhang, Y, Zhang, H, Zhao, H & Wang, G 2025, 'Enhanced selective hydrogenation of dimethyl oxalate to methyl glycolate through Cu-Ag bimetallic catalysts encapsulated in amino-functionalized mesoporous silica nanospheres', Surfaces and Interfaces, vol. 67, pp. 106612-106612.
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Xie, W, Ma, J, Lu, T, Li, Y, Lei, J, Fang, L & Du, Q 2025, 'Distributed Deep Learning With Gradient Compression for Big Remote Sensing Image Interpretation', IEEE Transactions on Neural Networks and Learning Systems, pp. 1-15.
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Xu, K, Tuyen Le, A, Huang, X & Ryu, H-G 2025, 'Generalized Analog Least Mean Square Loop for Self-Interference Cancellation in In-Band Full-Duplex Communications', IEEE Transactions on Wireless Communications, vol. 24, no. 3, pp. 2022-2035.
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Xu, Y & Guo, YJ 2025, 'Compact generalized joined coupler matrix with orthogonal beams', Electronics Letters, vol. 61, no. 1.
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AbstractAn analogue beamforming network, such as the Butler matrix can produce orthogonal beams, the peak of each beam being aligned with the nulls of all other beams. This is particularly important in scenarios requiring interference resilience in systems like base stations and user equipment. This paper presents a 3 × 5 Nolen‐like generalized joined coupler (GJC) matrix to produce orthogonal beams with both compact size and flexibility. The phase shifters are integrated into couplers while the coupling value range of couplers are extended to achieve the required performance of the GJC matrix. A prototype GJC matrix is designed, simulated, fabricated, and measured. The measured results agree well with the simulation ones.

Xu, Y, Zhu, H & Jay Guo, Y 2025, 'Reconfigurable True-Time-Delay Phase Shifter Using Defected Ground Structure With Loaded Stubs', IEEE Microwave and Wireless Technology Letters, vol. 35, no. 2, pp. 161-164.
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Xuan Tung, N, Van Chien, T, Thai Hoang, D & Hwang, WJ 2025, 'Jointly Optimizing Power Allocation and Device Association for Robust IoT Networks Under Infeasible Circumstances', IEEE Transactions on Network and Service Management, vol. 22, no. 2, pp. 1372-1390.
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Yan, B, Zhao, Q, Zhang, J & Zhang, JA 2025, 'Heuristic solution to joint deployment and beamforming design for STAR-RIS aided networks', Expert Systems with Applications, vol. 267, pp. 126144-126144.
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Yan, H, Du, G, Li, N, Li, L, Chen, Y, Lei, G & Zhu, J 2025, 'Four Rotor Structures for High-Speed Interior Permanent Magnet Motor Considering Mechanical, Electromagnetic, and Thermal Performance', IEEE Transactions on Transportation Electrification, vol. 11, no. 1, pp. 2595-2608.
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Yao, J, Zhang, H, Song, D, Zhang, J & Jiang, Y-P 2025, 'Growth of monolayer 1T′-WTe2 with a nearly complete coverage', Applied Physics Letters, vol. 126, no. 7.
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Monolayer WTe2, known for its intriguing properties as a quantum spin Hall insulator, presents significant challenges for high-quality epitaxial film growth. These difficulties primarily arise from the low mobility of W on the substrate and the reduced reaction rate between W and Te. This study addresses these challenges by employing a low-temperature deposition technique combined with the introduction of a Te buffer layer to mitigate these limitations. High-quality monolayer 1T′-WTe2 with nearly complete coverage has been grown on the SrTiO3 (100) substrate. Furthermore, scanning tunneling microscopy/spectroscopy demonstrates the presence of random domain orientations and variations in gap size within the monolayer WTe2. This approach offers a solution to the primary obstacles in WTe2 epitaxial growth and may be extended to other transition metal dichalcogenides.

Yin, Q, Zhong, L, Song, Y, Bai, L, Wang, Z, Li, C, Xu, Y & Yang, X 2025, 'A decision support system in precision medicine: contrastive multimodal learning for patient stratification', Annals of Operations Research, vol. 348, no. 1, pp. 579-607.
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Abstract Precision medicine aims to provide personalized healthcare for patients by stratifying them into subgroups based on their health conditions, enabling the development of tailored medical management. Various decision support systems (DSSs) are increasingly developed in this field, where the performance is limited to their capability of handling big amounts of heterogeneous and high-dimensional electronic health records (EHRs). In this paper, we focus on developing a deep learning model for patient stratification that can identify and explain patient subgroups from multimodal EHRs. The primary challenge is to effectively align and unify heterogeneous information from various modalities, which includes both unstructured and structured data. Here, we develop a Contrastive Multimodal learning model for EHR (ConMEHR) based on topic modelling. In ConMEHR, modality-level and topic-level contrastive learning (CL) mechanisms are adopted to obtain a unified representation space and diversify patient subgroups, respectively. The performance of ConMEHR will be evaluated on two real-world EHR datasets and the results show that our model outperforms other baseline methods.

Yin, W, Jia, M, Liu, L, Li, M, Guo, Y, Lei, G & Zhu, JG 2025, 'Advanced power curve modeling for wind turbines: A multivariable approach with SGBRT and grey wolf optimization', Energy Conversion and Management, vol. 332, pp. 119680-119680.
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Yin, Z, Zhu, H, Lv, X, Lai, J & Yang, Y 2025, '3-D-Printed Ultracompact Butler Matrix for Wideband Millimeter-Wave Beamforming', IEEE Transactions on Microwave Theory and Techniques, pp. 1-13.
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You, Q, Wu, YF, Yang, Y, Chai, Y & Cheng, YJ 2025, 'Near-Field Phase-Scanning Self-Accelerating Airy–Bessel Beam for Nonline-of-Sight Wireless Communication', IEEE Transactions on Microwave Theory and Techniques, pp. 1-13.
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Yu, G, Wang, X, Sun, C, Wang, Q, Yu, P, Ni, W & Liu, RP 2025, 'IronForge: An Open, Secure, Fair, Decentralized Federated Learning', IEEE Transactions on Neural Networks and Learning Systems, vol. 36, no. 1, pp. 354-368.
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Federated learning (FL) offers an effective learning architecture to protect data privacy in a distributed manner. However, the inevitable network asynchrony, overdependence on a central coordinator, and lack of an open and fair incentive mechanism collectively hinder FL's further development. We propose IronForge, a new generation of FL framework, that features a directed acyclic graph (DAG)-based structure, where nodes represent uploaded models, and referencing relationships between models form the DAG that guides the aggregation process. This design eliminates the need for central coordinators to achieve fully decentralized operations. IronForge runs in a public and open network and launches a fair incentive mechanism by enabling state consistency in the DAG. Hence, the system fits in networks where training resources are unevenly distributed. In addition, dedicated defense strategies against prevalent FL attacks on incentive fairness and data privacy are presented to ensure the security of IronForge. Experimental results based on a newly developed test bed FLSim highlight the superiority of IronForge to the existing prevalent FL frameworks under various specifications in performance, fairness, and security. To the best of our knowledge, IronForge is the first secure and fully decentralized FL (DFL) framework that can be applied in open networks with realistic network and training settings.

Yu, P, Zhang, X, Gong, Y, Zhang, J, Sun, H, Zhang, J, Zhang, X & Yin, Y 2025, 'Enhancing origin–destination flow prediction via bi-directional spatio-temporal inference and interconnected feature evolution', Expert Systems with Applications, vol. 264, pp. 125679-125679.
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Zamee, MA, Hussain, A & Hossain, MJ 2025, 'Fractional-order PI control with Modified Stability Locus for grid connected inverters: Stability enhancement and real-time validation', Electric Power Systems Research, vol. 248, pp. 111854-111854.
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Zamee, MA, Lee, Y & Won, D 2025, 'Corrections to “Self-Supervised Adaptive Learning Algorithm for Multi-Horizon Electricity Price Forecasting”', IEEE Access, vol. 13, pp. 55381-55381.
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Zhang, B, Van Huynh, N, Thai Hoang, D, Nguyen, DN & Pham, Q-V 2025, 'DDPG-E2E: A Novel Policy Gradient Approach for End-to-End Communication Systems', IEEE Transactions on Cognitive Communications and Networking, vol. 11, no. 3, pp. 1738-1751.
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Zhang, C, Zheng, Y, McAviney, J & Ling, SH 2025, 'SSAT-Swin: Deep Learning-Based Spinal Ultrasound Feature Segmentation for Scoliosis Using Self-Supervised Swin Transformer', Ultrasound in Medicine & Biology, vol. 51, no. 6, pp. 999-1007.
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Zhang, H, Huang, X & Zhang, JA 2025, 'Zak-OTFS With Time-Domain Offset Gradient Descent Equalization', IEEE Transactions on Vehicular Technology, pp. 1-10.
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Zhang, H, Lee, C-K & Li, Z 2025, 'Six Degrees of Freedom Tracking and Wireless Charging for Capsule Endoscopy', IEEE Transactions on Industrial Electronics, vol. 72, no. 4, pp. 3643-3652.
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Zhang, H, Liu, W, Li, Z & Lee, C-K 2025, 'Pulse Frequency Modulation of 3D Wireless Power Transfer for Capsule Endoscopy', IEEE Transactions on Industrial Electronics, vol. 72, no. 1, pp. 308-317.
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Zhang, J, Shen, Y, Wu, Z, Zhang, X, Kang, J, Wu, Y, Zhang, S, Chen, S, Wang, G, Zhang, H, Yin, H & Zhao, H 2025, 'Efficient Alkaline‐Free Electrooxidation of 5‐Hydroxymethylfurfural to 2,5‐Furandicarboxylic Acid using Electrochemically‐Charged Ni_xCo_1‐x(OH)₂ as a Redox Mediator', Angewandte Chemie International Edition, vol. 64, no. 13.
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AbstractConverting biomass‐derived molecules like 5‐hydroxymethylfurfural (HMF) into value‐added products alongside hydrogen production using renewable energy offers significant opportunities for sustainable chemical and energy production. Yet, HMF electrooxidation requires strong alkaline conditions and membranes for efficient conversion. These harsh conditions destabilize HMF, leading to humin formation and reduced product purity, meanwhile membranes increase costs. Addressing these challenges, we introduce a two‐step, decoupling system that operates without strong alkaline conditions and eliminates the need of membranes. In this system, nickel‐cobalt hydroxides serve as effective redox mediators, driving HMF oxidation in pure water. The experimental results showed that Ni0.85Co0.15OOH effectively promotes the dehydrogenation of substrate and achieves a highly efficient oxidation of HMF in pure water, with the selectivity of product 2,5‐furandicarboxylic acid (FDCA) approaching 100 %. This system has been expanded to oxidize various substrates, achieving yields exceeding 92 % for the corresponding acids of functionalized compounds such as furfuryl alcohol, furfural, benzyl alcohol, and benzaldehyde. By replacing fixed electrodes with flow electrodes, the scalability of decoupling strategy was evaluated for the harvesting of pure solid FDCA, highlighting the broad prospects in practical applications.

Zhang, J, Zhang, R, Xu, L, Lu, X, Yu, Y, Xu, M & Zhao, H 2025, 'FasterSal: Robust and Real-Time Single-Stream Architecture for RGB-D Salient Object Detection', IEEE Transactions on Multimedia, vol. 27, pp. 2477-2488.
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Zhang, JA, Zhang, H, Wu, K, Huang, X, Yuan, J & Guo, YJ 2025, 'Wireless Communications in Doubly Selective Channels with Domain Adaptivity', IEEE Communications Magazine, vol. 63, no. 5, pp. 102-108.
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Zhang, R, Cao, Z, Huang, Y, Yang, S, Xu, L & Xu, M 2025, 'Visible-Infrared Person Re-Identification With Real-World Label Noise', IEEE Transactions on Circuits and Systems for Video Technology, vol. 35, no. 5, pp. 4857-4869.
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Zhao, S, Gong, S, Gu, B, Li, L, Lyu, B, Thai Hoang, D & Yi, C 2025, 'Exploiting NOMA Transmissions in Multi-UAV-Assisted Wireless Networks: From Aerial-RIS to Mode-Switching UAVs', IEEE Transactions on Wireless Communications, vol. 24, no. 3, pp. 2530-2544.
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Zhao, W, Zhang, H, Li, L, Zhang, J & Chu, L 2025, 'Spinosin enhances non-rapid eye movement sleep and alters c-Fos expression in sleep–wake regulatory brain regions in mice', Sleep and Breathing, vol. 29, no. 1.
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Zhu, H, Xu, Y, Zhang, T, Du, J & Jay Guo, Y 2025, 'Reconfigurable Generalized Joined Coupler Matrices for Independent Control of Multiple Steerable Beams', IEEE Transactions on Antennas and Propagation, vol. 73, no. 3, pp. 1573-1584.
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Zhu, Y, Xu, K, Wan, B, Lei, G & Zhu, J 2025, 'Kolmogorov-Arnold Network for Solving 2-D Magnetostatic Problems', IEEE Transactions on Magnetics, pp. 1-1.
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Abdullah, A, Keshavarz, R & Shariati, N 1970, 'Chiral Metasurface for Asymmetric Transmission and Polarization Conversion in Nonreciprocal Shielding', 2025 6th Australian Microwave Symposium (AMS), 2025 6th Australian Microwave Symposium (AMS), IEEE, pp. 1-2.
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Ahamed, E, Keshavarz, R & Shariati, N 1970, 'Programmable 2-bit Metamaterial for Beamsteering in Smart AgTech Applications', 2025 6th Australian Microwave Symposium (AMS), 2025 6th Australian Microwave Symposium (AMS), IEEE, pp. 1-2.
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Ali, A, Singh, K, Thalakotuna, DN & Esselle, KP 1970, 'A Solar Cell Integrated Antenna for on-the-Move IoT Applications', 2025 19th European Conference on Antennas and Propagation (EuCAP), 2025 19th European Conference on Antennas and Propagation (EuCAP), IEEE, pp. 1-5.
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Ali, A, Singh, K, Thalakotuna, DN & Esselle, KP 1970, 'Improving the Form Factor in the Slot Based Built-in Solar Cell Integrated Antennas', 2025 6th Australian Microwave Symposium (AMS), 2025 6th Australian Microwave Symposium (AMS), IEEE, pp. 1-2.
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Ali, MY, Singh, K, Ahmed, F & Mukhopadhyay, S 1970, 'Miniaturized 3-D Printable Composite Metasurface for 1-D Beam Steering', 2025 6th Australian Microwave Symposium (AMS), 2025 6th Australian Microwave Symposium (AMS), IEEE, pp. 1-2.
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Alqahtani, S, Nanda, P & Mohanty, M 1970, 'Strengthening Cybersecurity: The Influence of Student Behavior, Perceived Factors, and Mitigating Strategies on Phishing Attack Perception', Web Information Systems Engineering, Springer Nature Singapore, Doha, Qatar, pp. 313-329.
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Cao, H, Zhang, Z, Xia, Y, Li, X, Xia, J, Chen, G & Knoll, A 1970, 'Embracing Events and Frames with Hierarchical Feature Refinement Network for Object Detection', Springer Nature Switzerland, pp. 161-177.
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Dang, X, Nanda, P, Xu, H, Mohanty, M & Deng, H 1970, 'A Novel Scheme for Recommendation Unlearning Verification (RUV) Using Non-Influential Trigger Data', 2025 IEEE 22nd Consumer Communications & Networking Conference (CCNC), 2025 IEEE 22nd Consumer Communications & Networking Conference (CCNC), IEEE, Las Vegas, USA, pp. 1-6.
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Haider, W, Batool, S, Milazzo, F & Ha, QP 1970, 'Machine Learning-Based Forecasting Active Power Loss in Distribution Systems', E3S Web of Conferences, EDP Sciences, pp. 04003-04003.
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This paper presents an ensemble learning approach to predict the active power losses during the allocation and sizing of distributed generation (DG) units in power distribution networks. The forecast model incorporates the Gradient Boosting Machine Regression (GBMR) to estimate DG location, bus voltages, DG size, and active losses without conventional power flow calculations. The results demonstrate that the suggested estimations of power losses and DG sizing are effective, practical, and adaptable for power system management. The accuracy of the proposed model has been validated using key performance metrics and tested on the standard IEEE 33 bus system. In the case of fixed load, the GBMR outperforms other machine learning techniques with the R-squared 0.9997, with a very low mean absolute percentage error (MAPE) (0.2216%) and a root mean square error (RMSE) of 1.0673 in predicting active power losses. This approach is promising in enabling grid operators to effectively manage DG unit integration of distributed energy resources from precise and reliable estimates of the power loss.

He, Y, Wei, G, Ziolkowski, RW & Jay Guo, Y 1970, 'Frequency-Reconfigurable Ultra-wideband Phased Array with Enhanced Beam-scanning Performance', 2025 6th Australian Microwave Symposium (AMS), 2025 6th Australian Microwave Symposium (AMS), IEEE, pp. 1-2.
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Huang, Y, Huang, L, Zhu, Y, Lei, G, Wang, A & Zhu, J 1970, 'Application of Large Language Models in Intelligent Preprocessing and Forecasting of Electricity Price', 2025 4th International Conference on Smart Grid and Green Energy (ICSGGE), 2025 4th International Conference on Smart Grid and Green Energy (ICSGGE), IEEE, pp. 246-250.
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Le, TH, Nguyen, HAD, Ha, QP, Tran, MQ, Ahmed, M, Kong, J, Barthelemy, X, Duc, H, Jiang, N, Azzi, M & Riley, M 1970, 'Dempster-Shafer ensemble learning framework for air pollution nowcasting', E3S Web of Conferences, EDP Sciences, pp. 01003-01003.
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Deep-learning has emerged as a powerful approach to significantly improve forecast accuracy for air quality estimation. Several models have been developed, demonstrating their own merits in some scenarios and for certain pollutants. In nowcasting, the prediction of air pollution over a small time period essentially demands accurate and reliable estimates, especially in the event cases. From these, selecting the most suitable model to achieve the required forecast performance remains challenging. This paper presents an ensemble framework based on the Dempster-Shafer theory for data fusion to identify the most accurate and reliable forecasts of air pollution obtained from multiple deep neural network models. Our framework is evaluated against three popular machine learning methods, namely, LightGBM, Random Forest, and XGBoost. Experiments are conducted on two horizons: 6-hour and 12-hour predictions using real-world air quality data collected from state-run monitoring stations and low-cost wireless sensor networks.

Liang, Z, Sun, Z, Lv, X, Thalakotuna, DN, Esselle, KP, Li, X & Yang, Y 1970, 'Antenna Array with Memory Metal for CubeSats Applications', 2025 6th Australian Microwave Symposium (AMS), 2025 6th Australian Microwave Symposium (AMS), IEEE, pp. 1-2.
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Pubill-Font, M, Mesa, F, Algaba-Brazález, A, Ding, C & Quevedo-Teruel, O 1970, '2-D Ray-Tracing Approach for the Design of 3-D Dome Arrays Considering Mutual Coupling', 2025 19th European Conference on Antennas and Propagation (EuCAP), 2025 19th European Conference on Antennas and Propagation (EuCAP), IEEE, pp. 1-5.
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Raza, A, Keshavarz, R & Shariati, N 1970, 'Miniaturized Frequency Reconfigurable Patch Antenna for Wireless Power Transfer', 2025 6th Australian Microwave Symposium (AMS), 2025 6th Australian Microwave Symposium (AMS), IEEE, Australia, pp. 1-2.
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Ren, Q, Wang, Y & Ha, QP 1970, 'Automatic Recognition and Segmentation of Overlapped GPR Target Signatures', E3S Web of Conferences, EDP Sciences, pp. 03003-03003.
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Ground penetrating radar (GPR) has been widely utilized for non-destructive inspection of civil infrastructure systems such as bridges and tunnels. However, the identification of GPR signatures poses significant challenges due to the overlapped multiple objects. To overcome the obstacle, we proposed an innovative Mask R-CNN based network considering spatial relationship between GPR signatures. Firstly, to capture the spatial relationship of overlapping signatures, we introduced an improved intersection over union considering central distance and aspect ratio between GPR signatures. Secondly, we further modified the Non-Maximum Suppression and enhanced the corresponding anchor generative mechanism. To validate the proposed method, we conducted testing on GPR scans obtained from real data from a bridge. The results demonstrate that the proposed method not only accurately detects GPR signatures, but also significantly outperforms existing Mask R-CNN in terms of segmenting overlapped GPR signature. Specially, the proposed method achieved an average accuracy of 46.8% in the segmentation task, marking a substantial advancement in the field.

Singh, K, Nabeel, MI, Saikia, M, Ahmed, F, Thalakotuna, DN & Esselle, KP 1970, 'Investigating Angle Sensitivity of a 1-Bit Unit cell for Reconfigurable Intelligent Surfaces', 2025 6th Australian Microwave Symposium (AMS), 2025 6th Australian Microwave Symposium (AMS), IEEE, pp. 1-2.
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Song, B, Qin, Y, Song, Y-R & Wang, X 1970, 'Cascading Failures Model with Noise Interference in Supply Chain Networks', Springer Nature Switzerland, pp. 165-177.
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Song, L-Z, Squires, A, Du, J & Guo, YJ 1970, 'THz Electrically Tunable Polarization Converter via Graphene-Integrated Metasurface', 2025 6th Australian Microwave Symposium (AMS), 2025 6th Australian Microwave Symposium (AMS), IEEE, pp. 1-2.
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Sun, Z, Yang, Y, Lv, X & Liang, Z 1970, 'A Wideband Circularly Polarized Magneto-Electric Dipole Antenna Array With Sequential Rotated Feeding For Wireless and Satellite Communication', 2025 6th Australian Microwave Symposium (AMS), 2025 6th Australian Microwave Symposium (AMS), IEEE, pp. 1-2.
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Van Huynh, N, Nguycn, DN, Mucchi, L, Caputo, S, Piccardi, M, Hoang, DT & Dutkiewicz, E 1970, 'Defeating Eavesdropping Attacks with Inter-Cell Interference and Deep Reinforcement Learning', 2025 IEEE Wireless Communications and Networking Conference (WCNC), 2025 IEEE Wireless Communications and Networking Conference (WCNC), IEEE, pp. 1-6.
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Xu, Y, Zhu, H & Guo, YJ 1970, 'Reconfigurable Wideband TTD Phase Shifter Based on DGS for Beam Squinting Mitigation', 2025 6th Australian Microwave Symposium (AMS), 2025 6th Australian Microwave Symposium (AMS), IEEE, pp. 1-2.
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Abughalwa, M, Nguyen, DN, Hoang, DT, Nguyen, V-D, Zeng, M, Pham, Q-V & Dutkiewicz, E 2025, ''Security for Everyone' in Finite Blocklength IRS-aided Systems With Perfect and Imperfect CSI'.

Abughalwa, M, Nguyen, DN, Hoang, DT, Vu, TX, Dutkiewicz, E & Chatzinotas, S 2025, 'Secure Communications for All Users in Low-Resolution IRS-aided Systems Under Imperfect and Unknown CSI'.

Deng, S, Yang, Y, Huang, M, Wang, C, Guo, E, Qian, J & Lee, JE-Y 2025, 'Coupling Agents in Acoustofluidics: Mechanisms, Materials, and Applications', MDPI AG.
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Dinh, PV, Nguyen, DN, Hoang, DT, Nguyen, QU & Dutkiewicz, E 2025, 'Multiple-Input Variational Auto-Encoder for Anomaly Detection in Heterogeneous Data'.

Hieu, NQ, Hoang, DT, Nguyen, DN, Alsheikh, MA, Kuhn, CCN, Alem, YF & Radwan, I 2025, 'End-to-End Human Pose Reconstruction from Wearable Sensors for 6G Extended Reality Systems'.

Mai, TNA, Hossain, MS, Nguyen, NM, Chen, Y, Chen, C, Xu, X, Trinh, QT, Dinh, T & Tran, TT 2025, 'Quantum Emitters in Hexagonal Boron Nitride: Principles, Engineering and Applications'.

Nguyen, TL, Hoang, DT, Nguyen, DN & Pham, Q-V 2025, 'Right Reward Right Time for Federated Learning'.

Shang, C, Yu, J & Hoang, DT 2025, 'Energy-Efficient and Intelligent ISAC in V2X Networks with Spiking Neural Networks-Driven DRL'.

Wang, W, Penney, E, Gay, V & Garcia, J 2025, 'A Scoping Review: Exploring the Role of Serious Game for Combating Postnatal Depression in New Parents (Preprint)', JMIR Publications Inc..
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Wang, Z, Zhang, JA, Wu, K & Guo, YJ 2025, 'Water Level Sensing via Communication Signals in a Bi-Static System'.

Xia, J, Xu, M, Huang, W, Zhang, J, Zhang, H & Xiao, C 2025, 'Mitigating Knowledge Discrepancies among Multiple Datasets for Task-agnostic Unified Face Alignment'.

Yang, H, Liu, H, Yuan, X, Wu, K, Ni, W, Zhang, JA & Liu, RP 2025, 'Synergizing Intelligence and Privacy: A Review of Integrating Internet of Things, Large Language Models, and Federated Learning in Advanced Networked Systems', MDPI AG.
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