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arXiv 2025年

作者： Gao, Chengrui Yang, Ziyuan Jia, Wei Leng, Lu Zhang, Bob Teoh, Andrew Beng Jin College of Computer Science Sichuan University Chengdu610065 China Singapore School of Computer and Information Hefei University of Technology Hefei China Jiangxi Provincial Key Laboratory of Image Processing and Pattern Recognition Nanchang Hangkong University Nanchang China Pattern Analysis and Machine Intelligence Group Department of Computer and Information Science University of Macau Taipa China School of Electrical and Electronic Engineering College of Engineering Yonsei University Seoul Korea Republic of

Palmprint recognition has emerged as a prominent biometric technology, widely applied in diverse scenarios. Traditional handcrafted methods for palmprint recognition often fall short in representation capability, as they heavily depend on researchers' prior knowledge. Deep learning (DL) has been introduced to address this limitation, leveraging its remarkable successes across various domains. While existing surveys focus narrowly on specific tasks within palmprint recognition-often grounded in traditional methodologies-there remains a significant gap in comprehensive research exploring DL-based approaches across all facets of palmprint recognition. This paper bridges that gap by thoroughly reviewing recent advancements in DL-powered palmprint recognition. The paper systematically examines progress across key tasks, including region-of-interest segmentation, feature extraction, and security/privacy-oriented challenges. Beyond highlighting these advancements, the paper identifies current challenges and uncovers promising opportunities for future research. By consolidating state-of-the-art progress, this review serves as a valuable resource for researchers, enabling them to stay abreast of cutting-edge technologies and drive innovation in palmprint recognition. Copyright © 2025, The Authors. All rights reserved.

关键词： Biometrics

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Signal Detection and Spectrum Sensing Using Random Matrix Theory in Massive MIMO Systems

Signal Detection and Spectrum Sensing Using Random Matrix Th...

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IEEE International Conference on Communications Workshops, ICC

作者： Lily Li ZhiQiang Wu Adam L. Anderson Department of Veterans Affairs Integrated Veteran Care Veterans Health Administration Denver CO USA Department of Electrical Engineering Wright State University Dayton OH USA Department of Electrical and Computer Engineering Oak Ridge National Laboratory Tennessee Technological University Cookeville TN USA

ISBN: (数字)9798350304053

ISBN: (纸本)9798350304060

Spectrum sensing plays a key role in modern communication systems where higher congested bands require more intelligent radio access. Additionally, next generation wireless, such as 5G, will use a large number of antennas and increased carrier frequency ranges. Unfortunately, due to high frequency carriers resulting in greater path loss, in low signal-noise-ratio (SNR) environments many spectrum sensing approaches do not work effectively. A random matrix theory (RMT) generalized likelihood ratio test (RGLRT) algorithm is introduced in this paper for massive multiple-input multiple-output (MIMO) antenna systems. We successfully demonstrate the eigenvalue distribution of the covariance matrix of the MIMO system signal is the same as a spiked central Wishart matrix. The spike dimension of this central Wishart matrix is associated to the number of users. Using this result, the highly recognized (linear) generalized likelihood ratio test (GLRT) is implemented for hypothesis testing. Compared with other well-known spectrum sensing methods, this new algorithm gives impressive detection performance in low SNR environments when the number of antennas is large. Simulations further confirm the theoretical results.

关键词： Wireless communication Wireless sensor networks Conferences Massive MIMO Sensors Covariance matrices Signal detection

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Defect Recognition based on Radon Transform in Pentacene organic thin-film Archimedean interdigitated spirals transistor

Defect Recognition based on Radon Transform in Pentacene org...

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International Conference on Clean electrical Power (ICCEP)

作者： Grazia Lo Sciuto Sivan Linde Rafi Shikler Paweł Kowol Salvo Coco Giacomo Capizzi Department of Mechatronics Silesian University of Technology Gliwice Poland Department of Electrical Electronics and Informatics Engineering University of Catania Catania Italy Department of Electrical and Computer Engineering School of Electrical and Computer Engineering Optoelectronic Organic Semiconductor Devices Laboratory Ben-Gurion University of the Negev Beer-Sheva Israel Ilse Katz Institute for Nanoscale Science and Technology Ben-Gurion University of the Negev Beer-Sheva Israel

In this paper the problem of automatic defects detection in thin film transistor is considered in order to increase the efficiency of electronic devices. An effective approach based on defect pattern recognition in organic transistor is developed using the Radon transform. The adopted design and technology in Pentacene organic thin-film transistor exhibits two interdigitated Archimedean spirals pattern. In the conducted experiments, the images acquisition is performed with a microscope camera to capture the various defects of surface morphology on the top of the examined transistors. The defects detection is obtained by using the Radon transform on each channel (R,G,B) of these images.

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Online Demand Peak Shaving with Machine-Learned Advice in Cyber-Physical Energy Systems

Online Demand Peak Shaving with Machine-Learned Advice in Cy...

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IEEE International Symposium on Dependable, Autonomic and Secure Computing (DASC)

作者： Minxi Fengl Wei Li Boyu Qin Albert Y. Zomaya Centre for Distributed and High Performance Computing School of Computer Science The University of Sydney Australia Department of Electrical Engineering State Key Laboratory of Electrical Insulation and Power Equipment Xi'an Jiaotong University China

With the deep integration of cyber tools, control algorithms are increasingly employed in cyber-physical energy systems to enhance management, cost efficiency, and robustness. Effective demand load management is crucial in cyber-physical energy systems as it directly impacts operational costs. Failure to adequately manage spiky or seasonal demand loads can lead to significant expenses on monthly utility bills. In this study, we propose AMPAMOD, a randomized online algorithm with machine-learned advice, to optimize battery operations and mitigate highly dynamic peak loads. AMPAMOD utilizes limited advice from machine learning algorithms to guide our online algorithm and ensure cost-effective peak load management. The theoretical analysis shows that our solution has minimal advice complexity, a linear computational cost, and an improved competitive ratio. Finally, we conduct extensive trace-driven experiments on real-world datasets. AMPAMOD achieves a peak shaving success rate of over 90%, outperforming baselines by at least 50%. These experimental results confirm theoretical findings and demonstrate the potential of AMPAMOD.

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DSTrack: Diffusion-based sequence learning for visual object tracking

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Pattern Recognition 2025年 168卷

作者： Wang, Zhixing Wang, Kai Tang, Chuanming Li, Xiang Zhang, Jianlin Gao, Lianli Institute of Optics and Electronics Chinese Academy of Sciences Chengdu610207 China School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu611731 China Key Laboratory of Optical Engineering Chinese Academy of Sciences Chengdu610207 China School of Electronic Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing100049 China National Key Laboratory of Optical Field Manipulation Science and Technology Chinese Academy of Sciences Chengdu610209 China Computer Vision Center Universitat Antonoma de Barcelona Barcelona08193 Spain School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu611731 China

Visual object tracking (VOT) is vital in pattern recognition. Traditional methods often use classification and regression heads. Recent autoregressive methods in visual tracking, treating tracking as bounding-box sequence generation, have shown better performance by framing tracking as discrete sequence generation. These approaches convert bounding box coordinates to discrete tokens in a shared vocabulary for sequential regression. However, this shift from a continuous to a discrete representation introduces quantization and positional biases, adversely affecting performance with larger vocabularies. To overcome this constraint, we propose a diffusion-based sequence learning tracking approach, named DSTrack. In this method, we employ the diffusion model to predict bounding-box coordinates in a parallel manner and transform the discrete variable distribution estimation into continuous probability distribution estimation. Furthermore, to enhance the representational prowess of the vision Transformer (ViT) backbones, we amplify the pre-trained ViT model by integrating additional Ladder modules. This strategic enhancement is designed to effectively bridge the gaps between different dataset domains. This novel diffusion-based sequence learning paradigm theoretically circumvents the constraints of the discrete token vocabulary and improves tracking performance. With fair comparison in our experiments, the proposed DSTrack achieves state-of-the-art results on benchmark datasets such as LaSOT and TrackingNet. © 2025

关键词： Normal distribution

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Design of a Flexible Robot Arm for Safe Aerial Physical Interaction

arXiv

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arXiv 2024年

作者： Mellet, Julien Berra, Andrea Seisa, Achilleas Santi Sankaranarayanan, Viswa Gamage, Udayanga G.W.K.N. Soto, Miguel Ángel Trujillo Heredia, Guillermo Nikolakopoulos, George Lippiello, Vincenzo Ruggiero, Fabio PRISMA Lab Department of Electrical Engineering and Information Technology University of Naples Federico II Naples Italy CATEC Advanced Center for Aerospace Technologies Seville Spain Robotics and AI Team Department of Computer Electrical and Space Engineering LuleåUniversity of Technology Luleå Sweden Automation and Control Group Department of Electrical Engineering and Photonics Technical University of Denmark Denmark Robotics Vision and Control Group School of Engineering University of Seville Seville Spain

This paper introduces a novel compliant mechanism combining lightweight and energy dissipation for aerial physical interaction. Weighting 400 g at take-off, the mechanism is actuated in the forward body direction, enabling precise position control for force interaction and various other aerial manipulation tasks. The robotic arm, structured as a closed-loop kinematic chain, employs two deported servomotors. Each joint is actuated with a single tendon for active motion control in compression of the arm at the end-effector. Its elasto-mechanical design reduces weight and provides flexibility, allowing passive-compliant interactions without impacting the motors’ integrity. Notably, the arm’s damping can be adjusted based on the proposed inner frictional bulges. Experimental applications showcase the aerial system performance in both free-flight and physical interaction. The presented work may open safer applications for Micro Aerial Vehicle (MAV) in real environments subject to perturbations during interaction. © 2024, CC BY.

关键词： End effectors

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Accurate Parameter Estimation for PMSMs using electrical and Mechanical Models Considering Temperature Effect and Inverter Distortion

Accurate Parameter Estimation for PMSMs using Electrical and...

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2022 Chinese Automation Congress, CAC 2022

作者： Tong, Zhe Meng, Bo Ding, Beichen Feng, Guodong Lai, Chunyan Sun Yat-sen University School of Intelligent Systems Engineering Shenzhen China Sun Yat-sen University School of Intelligent Systems Engineering Guangdong Provincial Key Laboratory of Fire Science and Intelligent Emergency Technology Guangzhou510006 China Concordia University Department of Electrical and Computer Engineering Montreal Canada

ISBN: (纸本)9781665465335

This paper presents a decoupled parameter estimation method for PMSM considering temperature rise and inverter distortion. Both electrical and mechanical models are explored to derive the estimation model to achieve better parameter estimation accuracy. Specifically, the proposed approach firstly performs the initial estimation of the PM flux, winding resistance and friction coefficient by considering the temperature effect, and then derives the decoupled model for inductance estimation using both the electrical and mechanical measurements. Compared with other approaches, our decoupled approach employs the mechanical model and considers the temperature effect, which can make the parameter identification more accurate. The experiment is performed on a test PMSM to verify the estimation performance of the proposed approach. © 2022 IEEE.

关键词： Parameter estimation

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Mathematical Modeling of an Anion Exchange Membrane Electrolyzer for Integration in a Novel Solar Photovoltaic-Battery-Green Hydrogen Nanogrid

Mathematical Modeling of an Anion Exchange Membrane Electrol...

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International Conference on Energy Transition in the Mediterranean Area (SyNERGY MED)

作者： Alexandros Arsalis Panos Papanastasiou George E. Georghiou Department of Electrical and Computer Engineering PV Technology Laboratory University of Cyprus Nicosia Cyprus PHAETHON Centre of Excellence for Intelligent Efficient and Sustainable Energy Solutions Nicosia Cyprus Department of Civil and Environmental Engineering University of Cyprus Nicosia Cyprus

ISBN: (数字)9798350375923

ISBN: (纸本)9798350375930

The Mediterranean area is an ideal location for harnessing solar energy due to the high solar irradiation availability. Utilization of innovative solutions address renewable energy instabilities and optimize the utilization of local clean energy resources. A promising technology is the utilization of green hydrogen subsystem to these solar systems. Such an integration could add significant capabilities, namely, provision of seasonal energy storage, increase of solar photovoltaic capacity, and export of the generated green hydrogen for other uses, such as fueling of hydrogen electric vehicles. A detailed model is developed in this work to assess the performance of the proposed green hydrogen subsystem configuration with a view to utilizing it as part of a future, larger, wholistic energy system. At full-load the model performs at an efficiency of 62.4%, while performance at a 10% part-load is 82.3%. These performance results suggest a very promising potential for this technology which can be harnessed in the future multi-scale energy systems, provided that the economic performance is also promising.

关键词： Photovoltaic systems Green energy Radiation effects Electric potential Solar energy Green hydrogen Electric vehicles Mathematical models Solar system Energy storage

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Antihyperbolic surface waves on hyperbolic metasurfaces

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Physical Review A 2025年第3期111卷 033522-033522页

作者： Chenxu Bian Xinyan Zhang Wenbo Ma Xuhuinan Chen Hongsheng Chen Tony Low Xiao Lin Interdisciplinary Center for Quantum Information State Key Laboratory of Extreme Photonics and Instrumentation College of Information Science and Electronic Engineering Zhejiang University Hangzhou 310027 China International Joint Innovation Center The Electromagnetics Academy at Zhejiang University Zhejiang University Haining 314400 China Department of Electrical and Computer Engineering University of Minnesota Minneapolis Minnesota 55455 USA

Hyperbolic metasurfaces exhibit the ability to support surface waves with hyperbolic isofrequency contours (i.e., hyperbolic eigenmodes), offering an exceptional platform for enhancing light-matter interactions. In addition to hyperbolic eigenmodes, hyperbolic metasurfaces can also support the propagation of surface-wave eigenmodes with an antihyperbolic isofrequency contour (i.e., antihyperbolic eigenmodes). In this work, we explore the lesser-known antihyperbolic eigenmodes, highlighting their unique polarization properties compared to hyperbolic eigenmodes. We find that the antihyperbolic eigenmodes at the vertices of the antihyperbolic isofrequency contour and the hyperbolic eigenmodes at the vertices of the hyperbolic isofrequency contour could have purely linear but opposite polarizations. Moreover, we reveal that the manipulation of metasurface's surface conductivity can provide a feasible route to realize the polarization conversion between these linearly polarized antihyperbolic and hyperbolic eigenmodes. That is, the s-polarized antihyperbolic eigenmodes would be changed to p-polarized ones, while the p-polarized hyperbolic eigenmodes are changed to s-polarized ones. These findings offer a pathway to selectively excite either hyperbolic or antihyperbolic eigenmodes, enabling control over subwavelength light propagation. Our results provide insights into polarization manipulation and potential applications in nano-optics and photonic devices.

关键词： Surface waves

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Optimal Routing and Link Configuration for Covert Heterogeneous Wireless Networks

arXiv

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arXiv 2024年

作者： Gillani, Amna Lorenzo, Beatriz Ghaderi, Majid Dagefu, Fikadu Goeckel, Dennis Department of Electrical and Computer Engineering University of Massachusetts Amherst AmherstMA01003 United States Department of Computer Science University of Calgary CalgaryABT2N 1N4 Canada Army Research Laboratory AdelphiMD20783 United States

Nodes in contemporary radio networks often have multiple interfaces available for communication: WiFi, cellular, LoRa, Zigbee, etc. This motivates understanding both link and network configuration when multiple communication modalities with vastly different capabilities are available to each node. In conjunction, covertness or the hiding of radio communications is often a significant concern in both commercial and military wireless networks. We consider the optimal routing problem in wireless networks when nodes have multiple interfaces available and intend to hide the presence of the transmission from attentive and capable adversaries. We first consider the maximization of the route capacity given an end-to-end covertness constraint against a single adversary, and we find a polynomial-time algorithm for optimal route selection and link configuration. We further provide optimal polynomial-time algorithms for two important extensions: (i) statistical uncertainty during optimization about the channel state information for channels from system nodes to the adversary;and, (ii) maintaining covertness against multiple adversaries. Numerical results are included to demonstrate the gains of employing heterogeneous radio resources and to compare the performance of the proposed approach versus alternatives. Copyright © 2024, The Authors. All rights reserved.

关键词： Zigbee

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