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arXiv 2025年

作者： Qian, Yuanbin Ye, Shuhan Wang, Chong Cai, Xiaojie Qian, Jiangbo Wu, Jiafei Faculty of Electrical Engineering and Computer Science Ningbo University China Merchants’ Guild Economics and Cultural Intelligent Computing Laboratory Ningbo University China Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong

Video anomaly detection plays a significant role in intelligent surveillance systems. To enhance model’s anomaly recognition ability, previous works have typically involved RGB, optical flow, and text features. Recently, dynamic vision sensors (DVS) have emerged as a promising technology, which capture visual information as discrete events with a very high dynamic range and temporal resolution. It reduces data redundancy and enhances the capture capacity of moving objects compared to conventional camera. To introduce this rich dynamic information into the surveillance field, we created the first DVS video anomaly detection benchmark, namely UCF-Crime-DVS. To fully utilize this new data modality, a multi-scale spiking fusion network (MSF) is designed based on spiking neural networks (SNNs). This work explores the potential application of dynamic information from event data in video anomaly detection. Our experiments demonstrate the effectiveness of our framework on UCF-Crime-DVS and its superior performance compared to other models, establishing a new baseline for SNN-based weakly supervised video anomaly detection. © 2025, CC BY-NC-SA.

关键词： Optical flows

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Novel Bendable Mnxca(0.90−X)Ni0.10fe2o4 Substrate Based Symmetrical Metamaterial Absorber for Rf Energy Harvesting Application to Achieve Sustainable Development Goals

SSRN

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SSRN 2024年

作者： Hasan, Mohammad Shakibul Islam, Mohammad Tariqul Ouda, Mohammad Alenezi, Abdulmajeed M. Soliman, Mohamed S. Samsuzzaman, Md. Department of Electrical Electronic and Systems Engineering Faculty of Engineering and Built Environment Universiti Kebangsaan Malaysia Selangor Bangi43600 Malaysia Electrical Engineering Technology College of Engineering & Technology University of Doha for Science and Technology Doha24449 Qatar Department of Electrical Engineering Faculty of Engineering Islamic University of Madinah Madinah41411 Saudi Arabia Department of Electrical Engineering College of Engineering Taif University Taif21944 Saudi Arabia Department of Computer and Communication Engineering Faculty of Computer Science and Engineering Patuakhali Science and Technology University Bangladesh

This article presents a bendable substrate MnxCa(0.90−x)Ni0.10Fe2O4 based metamaterial absorber for RF energy harvesting from Wifi frequency of 5 GHz to the achievement of the Sustainable Development Goals. The bendable metamaterial absorber (BMMA) energy harvester unit cell constructed with the physical dimension of 21 × 21 *** proposed unit cell consist of cross sign shaped resonator surrounded by circular ring resonator is located middle portion and boundary split outer ring resonator. Based on the simulation findings, the proposed BMMA energy harvester provides maximum energy harvesting efficiency of 99.42% at 5 GHz. Due to the symmetrical design, the energy harvester unit cell shows excellent angle insensitive up to 90 degrees for incident angle and polarization angle. The proposed BMMA exhibits single negative properties, and it shows excellent harvesting efficiency for various bending conditions. The lightweight, flexibility of the structure indicate that MnxCa(0.90−x)Ni0.10Fe2O4 based bendable metamaterial absorber energy harvester have significant potential for RF energy harvesting application from wifi frequency of 5 GHz and it achieve Sustainable Development Goals (SDGs), specially alignment with SDG 7 (Affordable and Clean Energy), SDG 9 (Industry, Innovation, and Infrastructure), SDG 11 (Sustainable Cities and Communities),and SDG 13 (Climate Action). © 2024, The Authors. All rights reserved.

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MaDEVIoT: Cyberattacks on EV Charging Can Disrupt Power Grid Operation

arXiv

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arXiv 2023年

作者： Acharya, Samrat Khan, Hafiz Anwar Ullah Karri, Ramesh Dvorkin, Yury Pacific Northwest National Laboratory RichlandWA99354 United States Department of Electrical and Computer Engineering New York University BrooklynNY11201 United States Ralph O’Connor Sustainable Energy Institute Department of Electrical and Computer Engineering Department of Civil and Systems Engineering Johns Hopkins University BaltimoreMD21218 United States

This paper examines the feasibility of demand-side cyberattacks on power grids launched via internet-connected high-power EV Charging Stations (EVCSs). By distorting power grid frequency and voltage, these attacks can trigger system-wide outages. Our case study focuses on Manhattan, New York, and reveals that such attacks will become feasible by 2030 with increased EV adoption. With a single EVCS company dominating Manhattan, compromising a single EVCS server raises serious power grid security concerns. These attacks can overload power lines and trip over-frequency (OF) protection relays, resulting in a power grid blackout. This study serves as a crucial resource for planning authorities and power grid operators involved in the EV charging infrastructure roll-out, highlighting potential cyberthreats to power grids stemming from high-power EVCSs. © 2023, CC BY.

关键词： Relay protection

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High-Dimension Bayesian Parameter Estimation for WECC Composite Load Model using Realistic Event Measurements

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IEEE Transactions on Power systems 2025年

作者： Tan, Bendong Zhao, Junbo Chiang, Naiyuan Duan, Nan University of Connecticut Department of Electrical and Computer Engineering StorrsCT06269 United States Lawrence Livermore National Laboratory LivermoreCA94550 United States MISO IN46032 United States

Calibration of the composite load model with distributed generation (CMPLDWG) can be challenging due to its nonlinear and high-dimensional characteristics. To address this issue, this paper proposes a Bayesian load calibration approach for the CMPLDWG model considering realistic measurement errors. The critical parameters that have large sensitivities to the load model are selected through sparse polynomial chaos expansion (SPCE)-based global sensitivity analysis. Subsequently, a deep neural network (DNN)-kernelized vector-valued Gaussian process (VVGP) is developed to learn the relationship between these critical parameters and the load response. Consequently, the DNN-VVGP is utilized to substitute the CMPLDWG model simulator, enabling efficient gradient-based posterior distribution sampling of load parameters via Hamiltonian Monte Carlo (HMC). Numerical results on realistic event measurements verify that the proposed method is more robust to measurement error and achieves higher estimation accuracy than existing state-of-the-art methods. © 1969-2012 IEEE.

关键词： Sensitivity analysis

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Kinematic Optimization and Comparison of Wheelchair-mounted Assistive Robots for Activities of Daily Living 14

Kinematic Optimization and Comparison of Wheelchair-mounted ...

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14th IEEE International Conference on Power Electronics and Drive systems, PEDS 2023

作者： Munoz Montenegro, Elias Jose Haque Sunny, Md Samiul De Caro, Javier Dario Sanjuan Brahmi, Brahim Ghommam, Jawhar Saad, Maarouf Ahmed, Helal Uddin Rahman, Mohammad H University of Wisconsin-Milwaukee Mechanical Engineering MilwaukeeWI United States University of Wisconsin-Milwaukee Computer Science MilwaukeeWI United States Collège Ahuntsic Electrical Engineering MontrealQC9155 Canada Sultan Qaboos University Al-Khod Electrical and Computer Engineering Muscat Oman École de Technologie Supérieure Department of Electrical Engineering MontréalQCH3C 1K3 Canada University of Wisconsin-Milwaukee Biorobotics Laboratory Mechanical Engineering MilwaukeeWI United States University of Wisconsin-Milwaukee Biomedical and Mechanical Engineering MilwaukeeWI United States

ISBN: (纸本)9798350399967

The number of wheelchair users has increased at an alarming rate throughout the last decade due to the increased number of individuals with upper/lower extremity dysfunctions resulting from a stroke, spinal cord injury, trauma, accident, or workplace injuries. Wheelchair-mounted assistive robots have been playing an important role in assisting the activities of daily living (ADLs) of these individuals. This research focuses on the design optimization of wheelchair-mounted assisted robots for essential ADLs. The genetic algorithm (GA) was used to estimate the link length parameters of 5 degrees of freedom (DoFs), 6DoFs, and 7DoFs wheelchair-mounted robots to cover the seven workspaces commonly used in ADLs. The objective function used in the GA includes singularity avoidance, collision avoidance, and ADL coverage. The results show that the proposed optimized 5DoFs robot can cover 25%, 6 DoFs robot can cover 69%, and 7 DoFs robot can cover 71% of essential ADL workspaces. © 2023 IEEE.

关键词： Wheelchairs

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Hidden Convexity-Based Distributed Operation of Integrated Electricity-Gas systems

arXiv

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arXiv 2024年

作者： Liu, Rong-Peng Song, Yue Liu, Junhong Wang, Xiaozhe Guo, Jinpeng Hou, Yunhe The Department of Electrical and Computer Engineering McGill University MontrealQCH3A 0E9 Canada The State Key Laboratory of Intelligent Autonomous Systems Frontiers Science Center for Intelligent Autonomous Systems Tongji University Shanghai China The Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong The Department of Energy and Electrical Engineering Ho-Hai University Jiangsu Nanjing China

This letter proposes a hidden convexity-based method to address distributed optimal energy flow (OEF) problems for transmission-level integrated electricity-gas systems. First, we develop a node-wise decoupling method to decompose an OEF problem into multiple OEF subproblems. Then, we propose a hidden convexity-based method to equivalently reformulate nonconvex OEF subproblems as semi-definite programs. This method differs from any approximation and convexification methods that may incur infeasible solutions. Since all OEF subproblems are originally convex or equivalently convexified, we adopt an ADMM to solve the hidden convexity-based distributed OEF problem with convergence analysis. Test results validate the effectiveness of the proposed method, especially in handling a large number of agents. Copyright © 2024, The Authors. All rights reserved.

关键词： Quadratic programming

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Writable and Erasable Second Harmonic Generation from Crystal-Derived All-Glass Optical Fibers

Writable and Erasable Second Harmonic Generation from Crysta...

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Pietros, Alexander R. Rebeszko, Kacper Hawkins, Thomas Cavillon, Maxime Ballato, John Dragic, Peter D. Laboratory The Department of Electrical and Computer Engineering University of Illinois Urbana-Champaign 208 N Wright St UrbanaIL61801 United States The Department of Materials Science and Engineering Clemson University 91 Technology Drive AndersonSC29625 United States Université Pans-Saclay CNRS Orsay91400 France

All glass optical fibers drawn from crystalline precursors via the molten core method demonstrate instantaneous and greatly enhanced second harmonic generation. Results when pumping in the NIR at relatively low powers... 详细信息

ISBN: (纸本)9781957171258

关键词： Harmonic generation

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Analysis of a Wearable Joint Flexion Sensor Using Anatomical Tissue Models

Analysis of a Wearable Joint Flexion Sensor Using Anatomical...

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2022 United States National Committee of URSI National Radio Science Meeting, USNC-URSI NRSM 2022

作者： Zhu, Keren Kiourti, Asimina Johnson, Michael Reddy, C.J. The Ohio State University ElectroScience Laboratory Department of Electrical and Computer Engineering ColumbusOH43212 United States Altair Engineering Inc. MilwaukeeWI United States Hampton VA United States

ISBN: (数字)9781946815156

ISBN: (纸本)9781946815156

Joint flexion monitoring is critical to applications as diverse as healthcare, sports, gaming, etc. Nevertheless, existing technologies used to monitor joint kinematics are either restricted to contrived lab environments or lack liability and accuracy. We previously reported a wrap-around wearable loop sensor that overcomes these limitations. To date, the design has only been studied using cylindrical models to emulate the limb. In this work, we employ an anatomical arm model to further validate the design. Simulation results confirm that the sensor can reliably detect elbow flexion angles in the typical range of motion (i.e., 0°-130°). In the future, the design can be integrated into garments for seamless, real-world monitoring of joint flexion. © 2022 USNC-URSI.

关键词： Joints (anatomy)

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Pilot Optimization and Channel Estimation Scheme for Semantic Communication: A Framework for Edge Intelligence

Pilot Optimization and Channel Estimation Scheme for Semanti...

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IEEE Symposium on Network Operations and Management

作者： Kitae Kim Yan Kyaw Tun Md. Shirajum Munir Walid Saad Choong Seon Hong Department of Computer Science and Engineering Kyung Hee University Yongin Republic of Korea Department of Electronic Systems Aalborg University København School of Cybersecurity Old Dominion University Norfolk VA USA Bradley Department of Electrical and Computer Engineering Virginia Tech Blacksburg VA USA

ISBN: (数字)9798350327939

ISBN: (纸本)9798350327946

The semantic communication system has become one of the promising communication technologies to support high data-intensive artificial intelligence (AI) applications and services such as meta-verse, 3D maps, and so on for achieving low communication overhead. Unlike traditional communication system, accurate channel estimation is a vital issue in semantic wireless communication since a semantic transmitter is required to send the core meaning of a message rather than an entire bit streams for the receiver. Thus, designing a semantic communication framework is challenging due to the dependencies of the semantic encoder and decoder over the orthogonal frequency division multiplexing (OFDM) setting. Therefore, first, this work designs a holistic semantic communication system model that is composed of a semantic encoder, a 3GPP-defined cluster delay line (CDL) wireless channel model, and a semantic decoder for AI services. Second, this paper proposes a semantic communication framework for AI services, 1) a masked autoencoder (MAE)-based channel estimation, and 2) a hierarchical reinforcement learning (HRL)-based pilot allocation method. Third, the proposed semantic communication framework is trained in an end-to-end manner, combined with OFDM layers, considering the image reconstruction and the performance of vision AI applications. Finally, the proposed MAE-based channel estimation and HRL-based pilot allocation RL agent are integrated into the semantic communication framework. Finally, Experimental results show that the proposed semantic framework demonstrates up to a 21.25% performance improvement in image segmentation tasks. Furthermore, the proposed channel estimator and pilot allocator also show higher channel estimation accuracy compared to existing channel estimators and pilot allocation methods.

关键词： Wireless communication Image segmentation OFDM Semantics Channel estimation Image restoration Decoding

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Organization-wide IOC Monitoring and Security Compliance in Endpoints using Open Source Tools 3

Organization-wide IOC Monitoring and Security Compliance in ...

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3rd IEEE Global Conference for Advancement in Technology, GCAT 2022

作者： Divya, P.J. George, Reenu Sara Madhusudhan, G. Padmasree, S. Jss Science and Technology University Department of Computer Science and Engineering Mysore India Indian Space Research Organization Information Technology Cell Laboratory for Electro-Optics Systems Bengaluru India

ISBN: (数字)9781665468558

ISBN: (纸本)9781665468534

Endpoint Security is an important layer in cyber security and it is one of the first places organizations look to secure their enterprise network. Proactively and iteratively monitoring endpoints for threats and Indicators of Compromise (IOC), helps security analysts to detect malware/attacks and to respond to incidents quickly. An Indicator of Compromise (IOC) refers to data that indicates that a system may have been infiltrated by a cyber-threat. Cyber security agencies send regular cyber-alerts to various organizations nation-wide and provide IOC list in the form of hashes, IPs, URLs, domains, yara rules, etc. for monitoring the presence of IOCs in their respective network. Periodic auditing of endpoints for security compliance is also a challenging and time-consuming task for every organization. To overcome these challenges, a solution based on client-server architecture is proposed in organizational network using open-source tools named Osquery, Fleet, Filebeat and Graylog. Using these tools, endpoints can be monitored for IOCs on demand or on scheduled manner from a central server. Yara based scan can also be performed efficiently in endpoints to monitor for IOCs using this architecture. In addition to IOC monitoring, this paper explains verifying compliance of endpoints with the organization's security policy using the proposed setup. Impact on performance of the endpoints during query execution was also analyzed. This solution will contribute in strengthening the endpoint security which in turn enhances overall cyber-security posture of the organization. © 2022 IEEE.

关键词： Network architecture

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