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Hidden Multidimensional Modulation Side Channels in Quantum Protocols

Physical Review Letters 2025年第13期134卷 130802-130802页

作者： Amita Gnanapandithan Li Qian Hoi-Kwong Lo Department of Electrical and Computer Engineering University of Toronto Toronto Canada Center for Quantum Information and Quantum Control University of Toronto Toronto Canada Quantum Bridge Technologies Inc. 108 College Street Toronto Canada

Quantum protocols including quantum key distribution and blind quantum computing often require the preparation of quantum states of known dimensions. Here, we show that, rather surprisingly, hidden multidimensional modulation is often performed by practical devices. This violates the dimensional assumption in quantum protocols, thus creating side channels and security loopholes. Our work has important impacts on the security of quantum cryptographic protocols.

关键词： Quantum cryptography

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Multiview Integration Network for Multitask Robotic Surgical Scene Analysis

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IEEE Transactions on Instrumentation and Measurement 2025年

作者： Shen, Wenting Wang, Yaonan Liu, Min Wang, Jiazheng Ding, Renjie Zhang, Zhe Meijering, Erik Hunan University College of Electrical and Information Engineering National Engineering Research Center of Robot Visual Perception and Control Technology International Scientific and Technological Innovation Cooperation Base for Biomedical Image Processing Hunan Changsha410082 China University of New South Wales School of Computer Science and Engineering SydneyNSW2052 Australia

Surgical scene analysis holds a pivotal role in robot-assisted surgery. However, existing methods often suffer from single or little views, leading to erroneous scene analysis conclusions. To address these issues, a novel Multiview Integration Network (MVINet) is proposed, which comprehensively analyzes the surgical scene by integrating effective information from multiple views, including global, local, dynamic, and static views. As a multitask scene analysis network, MVINet could simultaneously perform semantic segmentation of surgical instruments and detection of instrument-tissue interaction. By designing a unique Global-Local Spatial Feature Memory module (G-LSFM), the joint information from globally and locally analyzed views following graph analysis simultaneously enhances the accuracy of multitask scene analysis. The Dynamic-Static Visual Feature Memory module (D-SVFM) introduces an innovative approach by simultaneously incorporating temporal feature from consecutive frames and static feature from single frame into the node features of the interaction reasoning network. The multiscale perspective of both features further enhances the ability of the module to analyze the complex scenes. Experimental results on a public and a private dataset demonstrate that our method achieves superior performance compared to other state-of-the-art methods for two crucial tasks in surgical scene analysis. In the instrument segmentation task, MVINet outperforms the second-best method by 1.73% and 0.55% in terms of mIoU scores. For the interaction detection task, MVINet surpasses the second-best method by 10.14% and 5.47% in mAP scores. © 1963-2012 IEEE.

关键词： Semantic Segmentation

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Enhanced Voltage Stability for DC Microgrids Integrating Hybrid Electric Vehicles with Virtual Inertia and Damping control

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Transportation Research Procedia 2025年 84卷 571-578页

作者： Hossam Ali Mohamed Zaery Syed Muhammad Amrr S.M. Suhail Hussain Vijay Vital Mohammad A. Abido Department of Electrical Engineering Faculty of Energy Engineering Aswan University 81528 Aswan Egypt School of Electrical Computer and Energy Engineering Arizona State University Tempe AZ 85281 USA K.A.CARE Energy Research & Innovation Center King Fahd University of Petroleum and Minerals (KFUPM) Dhahran 31261 Saudi Arabia Control & Instrumentation Engineering Department KFUPM Dhahran 31261 Saudi Arabia Interdisciplinary Research Center for Sustainable Energy Systems KFUPM Dhahran 31261 Saudi Arabia Electrical Engineering Department King Fahd University of Petroleum and Minerals Dhahran 31261 Saudi Arabia SDAIA-KFUPM Joint Research Center for Artificial Intelligence KFUPM Dhahran 31261 Saudi Arabia

DC microgrids (MGs) have experienced swift growth, driven by the expanding integration of energy storage devices(ESD), renewable energy sources (RESs), and localized loads. However, it suffers from insufficient inertia owing to less rotating mass sources, which can lead to poor voltage stability. This paper introduces a control method that emulates both inertia and damping to mitigate fluctuations in DC voltage, enhance system stability, and address the low inertia concern. The proposed virtual inertia and damping (VID) control system is adopted through using hybrid electric vehicle (HEV). The suggested HEV comprises three power sources: a battery, a fuel cell (FC), and a supercapacitor (SC). In this setup, both the battery and the FC are employed to supply virtual damping owing to their high-energy density, and the SC is utilized to support virtual inertial characteristics due to its high-power density. Through this approach, enhancements in the DC voltage stability of an islanded DC MG can be achieved. Simulations demonstrate that the proposed control system significantly outperforms existing works utilizing virtual inertia (VI) based on an EV’s battery only, as well as over systems lacking VI. The proposed control system effectively reduces voltage fluctuations and improves system stability, specifically in terms of the rate of change of voltage (ROCOV) and accelerated settling time.

关键词： Voltage Stability DC Microgrids Virtual Inertia Damping Hybrid Electric Vehicle Renewable Energy Sources

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Adaptive Extensive Cancellation Algorithm and Harmonic Enhanced Heart Rate Estimation based on MMWave Radar

arXiv

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arXiv 2025年

作者： Tang, Hui Yang, Zhan Rong, Yu Chai, Li Engineering Research Center of Metallurgical Automation and Measurement Technology Wuhan University of Science and Technology Wuhan430081 China The School of Electrical Computer and Energy Engineering Arizona State University TempeAZ85281 United States College of Control Science and Engineering Zhejiang University Hangzhou310027 China

Heart rate (HR) monitoring is crucial for assessing physical fitness, cardiovascular health, and stress management. Millimeter-wave radar offers a promising non-contact solution for long-term monitoring. However, accurate HR estimation remains challenging in low signal-to-noise ratio (SNR) conditions. To deal with both respiration harmonics and intermodulation interference, this paper proposes a cancellation-before-estimation strategy. Firstly, we present the adaptive extensive cancellation algorithm (ECA) to suppress respiratory and its low-order harmonics. Then, we propose an adaptive harmonic enhanced trace (AHET) method to avoid intermodulation interference by refining the HR search region. Various experimental results validate the effectiveness of the proposed methods, demonstrating improvements in accuracy, robustness, and computational efficiency compared to conventional approaches based on the FMCW (Frequency Modulated Continuous Wave) system. © 2025, CC BY-NC-ND.

关键词： Intermodulation

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Frequency stabilization of a sophisticated multi-area interconnected hybrid power system considering non-inertia sources

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International Journal of electrical Power and Energy Systems 2025年 169卷

作者： Gawad, Diaa M. Magdy, Gaber Ebrahim, M.A. Petlenkov, Eduard Electrical Engineering Department Faculty of Engineering at Shoubra Benha University Cairo Egypt National Energy Control Center Ministry of Electricity and Renewable Energy Cairo Egypt Department of Electrical Engineering Faculty of Energy Engineering Aswan University Aswan81528 Egypt Faculty of Engineering King Salman International University El-Tor46511 Egypt Centre for Intelligent Systems Department of Computer Systems Tallinn University of Technology Tallinn19086 Estonia

This study introduces a novel interconnected power system model, which combines four real areas, integrating conventional power plants with renewable energy sources (RESs). This comprehensive system model aims to address the load frequency control (LFC) challenges that such systems face. Where the integration of RESs into power systems poses significant challenges, particularly in maintaining frequency stability. The LFC approach utilizes a proportional-integral-derivative (PID) controller, meticulously optimized through the Runge-Kutta (RUN) optimizer based on its mathematical principles. Dealing with the uncertainties of RESs and system nonlinearities poses a significant challenge for this controller. The efficacy of the proposed PID controller based on the RUN algorithm is examined by analyzing the frequency stability of the Egyptian power system (EPS), which stays interconnected with neighboring grids in Jordan, Libya, and Sudan. This study accounts for various loading scenarios and system nonlinearities to validate the algorithm's effectiveness. Furthermore, the superior performance of the RUN optimizer is verified by contrasting its results with other widely recognized optimization techniques, such as the Ant Lion optimizer (ALO) and Chernobyl disaster optimizer (CDO). Additionally, the PID controller based on the RUN optimizer is also evaluated against literature that employed a moth swarm algorithm (MSA) to design the PID controller-based LFC in the EPS. Simulation results in the MATLAB environment demonstrate the effectiveness and robustness of the proposed PID controller based on the RUN algorithm. The RUN-based PID controller outperforms other PID controllers optimized using algorithms from the literature (e.g., ALO, CDO, and MSA), achieving superior performance across various contingencies, including load variations, RES uncertainties, and system nonlinearities. The results highlight the effectiveness of the proposed controller compared to those in the l

关键词： Electric power system interconnection

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Explainable Application Intent for Zero-Touch Networking: An Incorporation of Hypergraph and Transformer

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IEEE Transactions on Communications 2025年

作者： Wu, Bing Zou, Sai Liwang, Minghui Ni, Wei Wang, Xianbin Guizhou University College of Big Data and Information Engineering China National Key Laboratory of Autonomous Intelligent Unmanned Systems Department of Control Science and Engineering China Tongji University Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Shanghai China Data61 CSIRO Australia Department of Electrical and Computer Engineering Western University Canada

The autonomous interpretation of application intent (APPI) represents the primary step towards achieving closed-loop autonomy in zero-touch networking (ZTN) and also a prerequisite for intent-based networking (IBN). However, understanding APPIs and invoking the corresponding network resources require network professionals with extensive technical expertise to customize network service requests (NSRs), which presents significant challenges for the large-scale deployment of ZTN. This paper investigates an interesting problem of autonomous interpretation of APPIs for ZTN, where a novel mechanism integrating hypergraph and transformer with completeness assurance (HyperTrans-CA) is proposed. In particular, we first involve the Bayesian theory to model APPIs interpretability as maximizing the correct transition probability, where hypergraph is used to describe the complex relationship between application characteristics (e.g., scenario function, and performance) and NSRs, including network devices, virtual network functions (VNFs), and resources. Then, the hypergraph is integrated into the encoder, decoder, and attention mechanisms of Transformer, and a completeness assurance mechanism is designed to improve the prediction accuracy. The convergence of HyperTrans-CA and the corresponding convergence speed of the hypergraph-boosted Transformer in the graph search process are also analyzed. Comprehensive simulations and empirical measurements regarding industrial internet demonstrate that HyperTrans-CA can effectively explain/understand APPIs. Compared to the state-of-the-art Transformer and ChatGPT3.5 models, HyperTrans-CA improves the prediction accuracy of APPIs mapped to VNFs by 23% and 46%, respectively, while raising the prediction accuracy of VNF locations by 8.6 and 17.3 times. © 2025 IEEE.

关键词： Bayesian networks

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Dual-beam photothermal material trace detection method based on self-mixing interference

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Applied Optics 2025年第16期64卷 4549-4558页

作者： Yan Zhao Yunlong Zhi Hui Zhao Daming Dong Jigang Tong Chunling Tu School of Electrical Engineering and Automation Tianjin University of Technology Tianjin 300384 China Tianjin Key Laboratory for Control Theory and Applications in Complicated Systems Tianjin 300384 China National Engineering Research Center for Intelligent Agricultural Equipment Beijing Academy of Agriculture and Forestry Sciences Beijing 100097 China Department of Computer Systems Engineering Faculty of ICT Tshwane University of Technology Pretoria 0188 South Africa

In this paper, a dual-beam photothermal self-mixing substance trace detection system is proposed. The crystal violet (CV) solution of the sample undergoes a thermal lens effect under the action of pump photoperiod excitation, and the refractive index changes cause the deviation of the probe beam, and the self-mixing interference (SMI) effect occurs when the modulated light returns to the cavity. By combining theoretical and experimental results, the power fluctuation of the SMI signal caused by the thermo-optic effect is linearly related to CV concentration and other parameters. At an excitation power of 24 mW, the detection limit can reach $8.0 \times {10^{- 8}}\;{\rm mol/L}$ . This method does not require labeling or complex CV pretreatment and has high sensitivity and flexibility, providing a guide for CV characterization in biological, environmental, and pharmaceutical research.

关键词： Gaussian beams Laser beams Optical fields Phase shift Refractive index Spatial resolution

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PCA: Semi-Supervised Segmentation with Patch Confidence Adversarial Training

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IEEE Transactions on Network Science and engineering 2025年

作者： Xu, Zhenghua Yang, Runhe Xu, Zihang Zhang, Shuo Yang, Yuchen Liu, Weipeng Xu, Weichao Chen, Junyang Lukasiewicz, Thomas Leung, Victor C. M. Hebei University of Technology State Key Laboratory of Reliability and Intelligence of Electrical Equipment School of Health Sciences and Biomedical Engineering Tianjin China The University of Hong Kong Department of Electrical and Electronic Engineering Hong Kong The Johns Hopkins University Department of Applied Mathematics and Statistic Baltimore United States Hebei University of Technology School of Artificial Intelligence Tianjin China Hebei Provincial Hospital of Traditional Chinese Medicine Digestive Disease Center Shijiazhuang China Shenzhen University College of Computer Science and Software Engineering Shenzhen China University of Oxford Department of Computer Science University of Oxford United Kingdom Department of Computer Science United Kingdom Vienna University of Technology institute of Logic and Computation nstitute of Logic and Computation Vienna Austria

Deep-learning-based semi-supervised learning (SSL) methods have achieved a strong performance in medical image segmentation, which can alleviate doctors' expensive annotation by utilizing a large amount of unlabeled data. Unlike most existing semi-supervised learning methods, adversarial training methods distinguish samples from different sources by learning the data distribution of the segmentation map, leading the segmenter to generate more accurate predictions. We argue that the current performance restrictions for such approaches are the problems of feature extraction and learning preferences. In this paper, we propose a new semi-supervised adversarial method called Patch Confidence Adversarial Training (PCA) for medical image segmentation. The PCA method's discriminator penalizes patch-level structures, guiding the generator to optimize different patch areas, by leveraging pixel context, the generator is driven to focus on high-frequency features, making it harder to deceive the discriminator and easy to converge to an ideal state, which more effectively guides the segmenter to generate high-quality pseudo-labels. Furthermore, at the discriminator's input, we supplement image information constraints, making it simpler to fit the expected data distribution. Extensive experiments on the Automated Cardiac Diagnosis Challenge (ACDC) 2017 dataset and the Brain Tumor Segmentation (BraTS) 2019 challenge dataset show that our method outperforms the state-of-the-art semi-supervised methods, which demonstrates its effectiveness for medical image segmentation. © 2025 IEEE. All rights reserved.

关键词： Adversarial machine learning

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GLOBAL INTERNAL STABILIZABILITY DOES NOT IMPLY GLOBAL EXTERNAL STABILIZABILITY FOR SMALL SENSOR DISTURBANCES

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IEEE TRANSACTIONS ON AUTOMATIC control 1995年第12期40卷 2119-2122页

作者： FREEMAN, R Center for Control Engineering and Computation Department of Electrical and Computer Engineering University of California Santa Barbara CA USA

It was shown in [1] that for control-affine nonlinear systems, global asymptotic stabilizability via continuous state feedback implies global input-to-state stabilizability with respect to actuator disturbances. We show that the analogous result for sensor disturbances does not hold: we construct a second-order system which admits a continuous memoryless globally asymptotically stabilizing state feedback controller but for which no such controller can prevent finite escape times from every initial condition in the presence of small sensor disturbances.

关键词： Asymptotic stability Actuators Sensor systems control systems Nonlinear systems Nonlinear control systems State feedback Robust stability control theory Working environment noise

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Pinching Antennas: Principles, Applications and Challenges

arXiv

引用

arXiv 2025年

作者： Yang, Zheng Wang, Ning Sun, Yanshi Ding, Zhiguo Schober, Robert Karagiannidis, George K. Wong, Vincent W.S. Dobre, Octavia A. Fujian Provincial Engineering Technology Research Center of Photoelectric Sensing Application Fujian Normal University Fuzhou350117 China School of Information and Control Engineering China University of Mining and Technology Xuzhou221116 China School of Computer Science and Information Engineering Hefei University of Technology Hefei230009 China Khalifa University Abu Dhabi United Arab Emirates University of Manchester ManchesterM1 9BB United Kingdom Germany Group Electrical & Computer Engineering Dept. Aristotle University of Thessaloniki Thessaloniki54 124 Greece Department of Electrical and Computer Engineering The University of British Columbia Vancouver Canada Department of Electrical and Computer Engineering Memorial University St. John’sNL Canada

Flexible-antenna systems, such as fluid antennas and movable antennas, have been recognized as key enabling technologies for sixth-generation (6G) wireless networks, as they can intelligently reconfigure the effective channel gains of the users and hence significantly improve their data transmission capabilities. However, existing flexible-antenna systems have been designed to combat small-scale fading in non-line-of-sight (NLoS) conditions. As a result, they lack the ability to establish line-of-sight links, which are typically 100 times stronger than NLoS links. In addition, existing flexible-antenna systems have limited flexibility, where adding/removing an antenna is not straightforward. This article introduces an innovative flexible-antenna system called pinching antennas, which are realized by applying small dielectric particles to waveguides. We first describe the basics of pinching-antenna systems and their ability to provide strong LoS links by deploying pinching antennas close to the users as well as their capability to scale up/down the antenna system. We then focus on communication scenarios with different numbers of waveguides and pinching antennas, where innovative approaches to implement multiple-input multiple-output and non-orthogonal multiple access are discussed. In addition, promising 6G-related applications of pinching antennas, including integrated sensing and communication and next-generation multiple access, are presented. Finally, important directions for future research, such as waveguide deployment and channel estimation, are highlighted. Copyright © 2025, The Authors. All rights reserved.

关键词： Channel estimation

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