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arXiv 2024年

作者： Cultice, Tyler Onim, Md. Saif Hassan Giani, Annarita Thapliyal, Himanshu Department of Electrical Engineering and Computer Science University of Tennessee KnoxvilleTN37996 United States GE Vernova Advanced Research Center United States

Cyber-physical control systems are critical infrastructures designed around highly responsive feedback loops that are measured and manipulated by hundreds of sensors and controllers. Anomalous data, such as from cyber-attacks, greatly risk the safety of the infrastructure and human operators. With recent advances in the quantum computing paradigm, the application of quantum in anomaly detection can greatly improve identification of cyber-attacks in physical sensor data. In this paper, we explore the use of strong pre-processing methods and a quantum-hybrid Support Vector Machine (SVM) that takes advantage of fidelity in parameterized quantum circuits to efficiently and effectively flatten extremely high dimensional data. Our results show an F-1 Score of 0.86 and accuracy of 87% on the HAI CPS dataset using an 8-qubit, 16-feature quantum kernel, performing equally to existing work and 14% better than its classical counterpart. © 2024, CC BY.

关键词： Quantum computers

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Enabling Cognitive Radio in NOMA-Assisted Reconfigurable Intelligent Surfaces: Outage Performance Analysis 5th

Enabling Cognitive Radio in NOMA-Assisted Reconfigurable Int...

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5th International Conference on Communication, Device and Networking, ICCDN 2021

作者： Pogaku, Arjun Chakravarthi Nguyen, Nhan Duc Le, Anh-Tu Do, Dinh-Thuan Department of Computer Science and Information Engineering College of Information and Electrical Engineering Asia University Taichung41354 Taiwan Innovation Center Van Lang University Ho Chi Minh City Viet Nam International Cooperation and Scientific Research Department Van Lang University Ho Chi Minh City Viet Nam

ISBN: (纸本)9789811920035

Non-orthogonal multiple access (NOMA) proves to be a prominent solution for huge device connectivity and enhances spectral efficacy. NOMA can handle several users in a single time and frequency slot. The superimposed signal transmitted from the transmitter to the receiver will be applied to successive interference cancelation (SIC) technique at the user to extract the desired user’s signal. However in cognitive radio (CR) networks, the users in the secondary network will only be assigned with the unused spectrum not being used by the primary network users. Though the secondary users utilize the idle spectrum, there is a minimum probability of primary users being affected by interference from secondary users. On the other hand, reconfigurable intelligent surfaces (RIS) can control the propagation of electromagnetic waves in the radio environment, according to the position of the user. In this paper, we suggest a simple CR-enabled NOMA-assisted RIS system to examine the performance of the users in the secondary network, consisting of a base station, RIS device, and two NOMA users. We have derived the closed-form expressions for outage probability (OP) at both the users and compared their performance in the presence of CR networks. The results show that, in the presence of CR, the number of meta-surfaces in RIS can significantly enhance the outage performance of the users. The comparison of both users’ performance has manifested that near users will have better outage performance compared to the far users. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Cognitive radio

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Facilitating Safe Automated Navigation in Ice with Cooperating Autonomous Vehicles

Facilitating Safe Automated Navigation in Ice with Cooperati...

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OCEANS

作者： Onoise G. Kio Faruq Afolabi Alexander McGregor Matthew Garvin Robert Gash Robert S. Allison Department of Electrical Engineering and Computer Science York University Toronto Canada Ocean Coastal and River Engineering Research Center National Research Council Canada St. John's Canada

ISBN: (数字)9798331540081

ISBN: (纸本)9798331540098

Autonomous shipping has gained much interest in the last decade stemming from several desirable safety and environmental benefits. A significant boost to Canada's autonomous shipping drive would be adequately monitoring ice conditions in shipping environments with unmanned assets and calculating safe navigation routes for autonomous ships. A workflow was created to simulate an unmanned aerial vehicle (UAV) cooperating with a maritime autonomous surface ship (MASS) to facilitate the MASS's safe navigation through an icy waterway. Both vehicles were modeled as MATLAB Simulink's Sim3D objects operating in an icy shipping environment representing a section of Canada's St Lawrence Seaway and built with Unreal Game Engine version 4.26.2. The UAV performed regular ice-condition-monitoring flights over the shipping environment with its vision and LiDAR sensors. Maps of Ice Numerals (IN) pertaining to the MASS's class were developed from processed data from the UAV's sensors. They served as inputs to a Rapidly Exploring Random Tree (RRT) algorithm that estimated safe obstacle free routes for the MASS through the shipping environment. Colour-coded hazard maps specifying safe and hazardous waterway regimes were also developed from IN maps. Hazard maps could serve as navigational aids to operators monitoring MASS operations in hazardous environments. Results obtained from testing the workflow on the MA TLAB Simulink + Unreal Engine simulation environment produced the desired INs and hazard maps with safe navigation routes for the MASS. These results show the possibility of having autonomous assets corporate to facilitate safe autonomous navigation in ice.

关键词： Sea surface Navigation Software packages Autonomous aerial vehicles Ice Hazards Sensors Marine vehicles Engines Monitoring

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Polychromatic full-polarization control in mid-infrared light

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Light(science & Applications) 2023年第5期12卷 894-904页

作者： Jin Chen Feilong Yu Xingsi Liu Yanjun Bao Rongsheng Chen Zengyue Zhao Jiuxu Wang Xiuxia Wang Wen Liu Yuzhi Shi Cheng-Wei Qiu Xiaoshuang Chen Wei Lu Guanhai Li State Key Laboratory of Infrared Physics Shanghai Institute of Technical PhysicsChinese Academy of Sciences500 Yu Tian RoadShanghai 200083China Hangzhou Institute for Advanced Study University of Chinese Academy of SciencesNo.1 SubLane XiangshanHangzhou 310024China Shanghai Research Center for Quantum Sciences 99 Xiupu RoadShanghai 201315China University of Chinese Academy of Science No.19 Yuquan RoadBeijing 100049China Department of Electrical and Computer Engineering National University of Singapore4 Engineering Drive 3Singapore 117583Singapore Institute of Nanophotonics Jinan UniversityGuangzhou 511443China Center for Micro-and Nanoscale Research and Fabrication University of Science and Technology of ChinaHefei 230026China Institute of Precision Optical Engineering School of Physics Science and EngineeringTongji UniversityShanghai 200092China National University of Singapore Suzhou Research Institute No.377 Linquan StreetSuzhouJiangsu 215123China

Objects with different shapes,materials and temperatures can emit distinct polarizations and spectral information in mid-infrared band,which provides a unique signature in the transparent window for object ***,the crosstalk among various polarization and wavelength channels prevents from accurate mid-infrared detections at high signal-to-noise ***,we report full-polarization metasurfaces to break the inherent eigen-polarization constraint over the wavelengths in *** recipe enables to select arbitrary orthogonal polarization basis at individual wavelength independently,therefore alleviating the crosstalk and efficiency degradation.A six-channel all-silicon metasurface is specifically presented to project focused mid-infrared light to distinct positions at three wavelengths,each with a pair of arbitrarily chosen orthogonal *** isolation ratio of 117 between neighboring polarization channels is experimentally recorded,exhibiting detection sensitivity one order of magnitude higher than existing infrared ***,the high aspect ratio~30 of our meta-structures manufactured by deep silicon etching technology at temperature−150℃ guarantees the large and precise phase dispersion control over a broadband from 3 to 4.5μ*** believe our results would benefit the noise-immune mid-infrared detections in remote sensing and space-to-ground communications.

关键词： polarization light noise

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Exploring Contextual Representation and Multi-modality for End-to-end Autonomous Driving

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engineering Applications of Artificial Intelligence 2024年 135卷

作者： Azam, Shoaib Munir, Farzeen Kyrki, Ville Kucner, Tomasz Piotr Jeon, Moongu Pedrycz, Witold Department of Electrical Engineering and Automation Aalto University Espoo Finland Finnish Center for Artificial Intelligence Finland School of Electrical Engineering and Computer Science Gwangju Institute of Science and Technology Gwangju61005 Korea Republic of Department of Electrical and Computer Engineering University of Alberta EdmontonABT6R 2V4 Canada Department of Electrical and Computer Engineering Faculty of Engineering King Abdulaziz University Jeddah21589 Saudi Arabia Systems Research Institute Polish Academy of Sciences Warsaw01-447 Poland

Learning contextual and spatial environmental representations enhances autonomous vehicle's hazard anticipation and decision-making in complex scenarios. Recent perception systems enhance spatial understanding with sensor fusion but often lack global environmental context. Humans, when driving, naturally employ neural maps that integrate various factors such as historical data, situational subtleties, and behavioral predictions of other road users to form a rich contextual understanding of their surroundings. This neural map-based comprehension is integral to making informed decisions on the road. In contrast, even with their significant advancements, autonomous systems have yet to fully harness this depth of human-like contextual understanding. Motivated by this, our work draws inspiration from human driving patterns and seeks to formalize the sensor fusion approach within an end-to-end autonomous driving framework. We introduce a framework that integrates three cameras (left, right, and center) to emulate the human field of view, coupled with top-down bird-eye-view semantic data to enhance contextual representation. The sensor data is fused and encoded using a self-attention mechanism, leading to an auto-regressive waypoint prediction module. We treat feature representation as a sequential problem, employing a vision transformer to distill the contextual interplay between sensor modalities. The efficacy of the proposed method is experimentally evaluated in both open and closed-loop settings. Our method achieves displacement error by 0.67m in open-loop settings, surpassing current methods by 6.9% on the nuScenes dataset. In closed-loop evaluations on CARLA's Town05 Long and Longest6 benchmarks, the proposed method enhances driving performance, route completion, and reduces infractions. © 2024 The Authors

关键词： Autonomous vehicles

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RADIOMICS-GUIDED MULTIMODAL SELF-ATTENTION NETWORK FOR PREDICTING PATHOLOGICAL COMPLETE RESPONSE IN BREAST MRI

arXiv

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arXiv 2024年

作者： Kim, Jonghun Park, Hyunjin Department of Electrical and Computer Engineering Sungkyunkwan University Suwon Korea Republic of Center for Neuroscience Imaging Research Institute for Basic Science Suwon Korea Republic of

Breast cancer is the most prevalent cancer among women and predicting pathologic complete response (pCR) after anticancer treatment is crucial for patient prognosis and treatment customization. Deep learning has shown promise in medical imaging diagnosis, particularly when utilizing multiple imaging modalities to enhance accuracy. This study presents a model that predicts pCR in breast cancer patients using dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) and apparent diffusion coefficient (ADC) maps. Radiomics features are established hand-crafted features of the tumor region and thus could be useful in medical image analysis. Our approach extracts features from both DCE MRI and ADC using an encoder with a self-attention mechanism, leveraging radiomics to guide feature extraction from tumor-related regions. Our experimental results demonstrate the superior performance of our model in predicting pCR compared to other baseline methods. © 2024, CC BY-NC-SA.

关键词： Tumors

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The applied principles of EEG analysis methods in neuroscience and clinical neurology

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Military Medical research 2024年第6期11卷 907-941页

作者： Hao Zhang Qing-Qi Zhou He Chen Xiao-Qing Hu Wei-Guang Li Yang Bai Jun-Xia Han Yao Wang Zhen-Hu Liang Dan Chen Feng-Yu Cong Jia-Qing Yan Xiao-Li Li School of Systems Science Beijing Normal UniversityBeijing 100875China College of Electrical and Control Engineering North China University of TechnologyBeijing 100041China School of Automation Science and Engineering South China University of TechnologyGuangzhou 510641China Department of Psychology the State Key Laboratory of Brain and Cognitive Sciencesthe University of Hong KongHong Kong SAR 999077China HKU-Shenzhen Institute of Research and Innovation Shenzhen 518057GuangdongChina Department of Health Technology and Informatics the Hong Kong Polytechnic UniversityHong Kong SAR 999077China Department of Rehabilitation Medicine the First Afliated Hospital of Nanchang UniversityNanchang 330006China Rehabilitation Medicine Clinical Research Center of Jiangxi Province Nanchang 330006China Beijing Key Laboratory of Learning and Cognition School of PsychologyCapital Normal UniversityBeijing 100048China School of Communication Science Beijing Language and Culture UniversityBeijing 100083China Institute of Electrical Engineering Yanshan UniversityQinhuangdao 066004HebeiChina School of Computer Science Wuhan UniversityWuhan 430072China School of Biomedical Engineering Faculty of Electronic Information and Electrical EngineeringDalian University of TechnologyDalian 116081LiaoningChina Guangdong Artifcial Intelligence and Digital Economy Laboratory(Guangzhou) Guangzhou 510335China.

Electroencephalography(EEG)is a non-invasive measurement method for brain *** to its safety,high resolution,and hypersensitivity to dynamic changes in brain neural signals,EEG has aroused much interest in scientific research and medical *** article reviews the types of EEG signals,multiple EEG signal analysis methods,and the application of relevant methods in the neuroscience feld and for diagnosing neurological ***,3 types of EEG signals,including time-invariant EEG,accurate event-related EEG,and random event-related EEG,are ***,5 main directions for the methods of EEG analysis,including power spectrum analysis,time-frequency analysis,connectivity analysis,source localization methods,and machine learning methods,are described in the main section,along with diferent sub-methods and effect evaluations for solving the same ***,the application scenarios of different EEG analysis methods are emphasized,and the advantages and disadvantages of similar methods are *** article is expected to assist researchers in selecting suitable EEG analysis methods based on their research objectives,provide references for subsequent research,and summarize current issues and prospects for the future.

关键词： Electroencephalogram analysis methods Applied principles Neuroscience Diagnosis Neurological diseases

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PriRoAgg: Achieving Robust Model Aggregation with Minimum Privacy Leakage for Federated Learning

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IEEE Transactions on Information Forensics and Security 2025年 20卷 5690-5704页

作者： Hou, Sizai Li, Songze Jahani-Nezhad, Tayyebeh Caire, Giuseppe Hong Kong University of Science and Technology Hong Kong Southeast University School of Cyber Science and Engineering Nanjing China Supervision and Management (Southeast University) Ministry of Education Engineering Research Center of Blockchain Application China Technische Universität Berlin Department of Electrical Engineering and Computer Science Berlin 10587 Germany

Federated learning (FL), as a promising machine learning paradigm for large-scale distributed data, faces two security challenges of privacy and robustness: the transmitted model updates potentially leak sensitive user information, and the lack of central control over local model updates leaves the global model susceptible to malicious attacks. Current solutions attempting to address both problems under the one-server FL setting fall short in the following aspects: 1) design for simple validity checks that are insufficient against advanced attacks (e.g., checking norm of individual update);and 2) have partial privacy leakage for more complicated robust aggregation algorithms (e.g., distances between model updates are leaked for multi-Krum). In this work, we formalize a novel security notion of aggregated privacy that characterizes the minimum amount of user information, in the form of aggregated statistics of users’ updates, that is necessary to be revealed to accomplish more advanced robust aggregation. We develop a general framework PriRoAgg, utilizing Lagrange coded computing and distributed zero-knowledge proof, to execute a wide range of robust aggregation algorithms while satisfying aggregated privacy. As concrete instantiations of PriRoAgg, we construct two secure and robust protocols based on state-of-the-art robust algorithms, for which we provide full theoretical analyses on security and complexity. Extensive experiments are conducted for these protocols, demonstrating their robustness against various model integrity attacks, and their efficiency advantages over baselines. © 2005-2012 IEEE.

关键词： Byzantine Resilience Federated Learning Privacy Preservation Secure and Robust Aggregation

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Set Stabilization of Large-Scale Stochastic Boolean Networks:A Distributed Control Strategy

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IEEE/CAA Journal of Automatica Sinica 2024年第3期11卷 806-808页

作者： Lin Lin Jinde Cao Jianquan Lu Leszek Rutkowski the Department of Mechanical Engineering the University of Hong KongHong Kong China the School of Mathematics Southeast UniversityNanjing 210096China IEEE the School of Mathematics and the Frontiers Science Center for Mobile Information Communication and Security Southeast UniversityNanjing 210096China the School of Mathematics the Southeast UniversityNanjing 210096 the School of Electronic Information and Electrical Engineering Chengdu UniversityChengdu 610106China the Systems Research Institute of the Polish Academy of Sciences Warsaw 01-447 the Institute of Computer Science AGH University of Science and TechnologyKraków 30-059 the Information Technology Institute University of Social SciencesŁódź90-113Poland

Dear Editor,This letter deals with the set stabilization of stochastic Boolean control networks(SBCNs)by the pinning control strategy,which is to realize the full control for systems by imposing control inputs on a fr... 详细信息

关键词： Boolean stabilization letter

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General and Offset-Resistant Physical-Layer Acknowledgement Approach for Cross-Technology Communication

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IEEE Transactions on Communications 2025年

作者： Yao, Shumin Zhao, Qinglin Zhou, MengChu Feng, Li Zhang, Peiyun Albeshri, Aiiad Macau University of Science and Technology School of Computer Science and Engineering Avenida Wei Long Taipa China Pengcheng Laboratory Department of Broadband Communication Shenzhen518066 China New Jersey Institute of Technology Department of Electrical and Computer Engineering NewarkNJ07102 United States Nanjing University of Information Science & Technology Engineering Research Center of Digital Forensics of Ministry of Education School of Computer Science Nanjing210044 China King Abdulaziz University Department of Computer Science Jeddah21481 Saudi Arabia

Cross-technology communication (CTC) enables direct communications among devices with heterogeneous wireless technologies (e.g., Bluetooth, WiFi, ZigBee, etc.), thereby reducing the cost and complexity of their interconnections. However, CTC is essentially unreliable due to the technology heterogeneity, and most existing CTC designs do not provide acknowledgment (ACK) feedback to ensure reliable data transmission. Few ACK designs are only applicable to feedback for ZigBee-WiFi pair and are vulnerable to sampling offsets that inherently exist in CTC. In this work, we propose a General and Offset-resistant Physical-layer ACK approach, called GOP-ACK, to support reliable feedback with practical considerations. Its core idea lies in encoding ACK messages with offset-resistant signal that has two benefits: 1) it can be adapted to a wide range of CTC scenarios with minimal adjustment, and 2) it can be effortlessly and robustly detected even in the presence of sampling offsets. We offer practical guidelines to tackle key deployment challenges related to signal construction, efficient and robust transmission, and effective firmware module reuse, enabling the application of GOP-ACK to specific CTC scenarios. Based on these guidelines, we implement two design cases: ZigBee-to-BLE and ZigBee-to-WiFi feedback, and propose a theoretical model to analyze their performance. We then conduct real-world experiments and extensive simulations to verify its feasibility and superiority over the state of the art, thereby enhancing the practicality of CTC greatly. © 1972-2012 IEEE.

关键词： Firmware

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