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Annual North-American Power Symposium

作者： Sarangan Rajendrane Amirthagunaraj Yogarathnam Tianqiao Zhao Satoshi Endo Visvakumar Aravinthan Al Tamimi Charles R. Yokley Meng Yue Interdisciplinary Science Department Brookhaven National Laboratory Upton NY USA Department of Electrical and Computer Engineering Wichita State University Wichita KS USA Environmental and Climate Sciences Department Brookhaven National Laboratory Upton NY USA Transmission Planning and Policy Sunflower Electric Power Corporation Wichita KS USA

ISBN: (数字)9798331521035

ISBN: (纸本)9798331521042

Expanding electric transmission capacity for renewable energy sources such as wind and solar is essential for decarbonization efforts and meeting increased load demand. This typically requires significant investments in new transmission lines or upgrades to existing ones. However, enhancing the efficiency of current infrastructure can also be highly beneficial. Recently, the use of Dynamic Line Ratings (DLR) has gained significant attention from utilities. DLR allows operators to use lines at their true capacities by considering weather conditions, which can be much higher than the conservative static line ratings. This paper presents a methodology for identifying and implementing DLR on selected lines to enhance capacity and reduce upgrade costs. Line identification is performed using power flow tracing algorithms, where lines carrying more wind power are chosen as candidates for DLR implementation. A criticality score, which is a function of the average wind power flow in the line and the worst-case loading level, is then defined to prioritize the lines that need DLR implementation. The proposed method is tested on a modified system based on the Western Kansas area, with estimated cost savings evaluated. The criticality of these transmission lines during $(n-1)$ contingencies is also evaluated. Additionally, alternative reinvestment strategies for these savings are explored, which show their potential benefits for system security and reliability.

关键词： Wind Renewable energy sources Power transmission lines Costs Wind power generation Low carbon economy Planning Security Reliability North America

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Beyond the Horizon: Decoupling UAVs Multi-View Action Recognition via Partial Order Transfer

arXiv

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arXiv 2025年

作者： Liu, Wenxuan Zhong, Xian Zhou, Zhuo Yang, Siyuan Lin, Chia-Wen Kot, Alex Chichung School of Computer Science Peking University Beijing100871 China Hubei Key Laboratory of Transportation Internet of Things School of Computer Science and Artificial Intelligence Wuhan University of Technology Wuhan430070 China Rapid-Rich Object Search Lab School of Electrical and Electronic Engineering Nanyang Technological University Singapore639798 Singapore School of Computer Science Wuhan University Wuhan430072 China Department of Electrical Engineering National Tsing Hua University Hsinchu30013 Taiwan

Action recognition in unmanned aerial vehicles (UAVs) poses unique challenges due to significant view variations along the vertical spatial axis. Unlike traditional ground-based settings, UAVs capture actions from a wide range of altitudes, resulting in considerable appearance discrepancies. We introduce a multi-view formulation tailored to varying UAV altitudes and empirically observe a partial order among views, where recognition accuracy consistently decreases as the altitude increases. This motivates a novel approach that explicitly models the hierarchical structure of UAV views to improve recognition performance across altitudes. To this end, we propose the Partial Order Guided Multi-View Network (POG-MVNet), designed to address drastic view variations by effectively leveraging view-dependent information across different altitude levels. The framework comprises three key components: a View Partition (VP) module, which uses the head-to-body ratio to group views by altitude;an Order-aware Feature Decoupling (OFD) module, which disentangles action-relevant and view-specific features under partial order guidance;and an Action Partial Order Guide (APOG), which leverages the partial order to transfer informative knowledge from easier views to support learning in more challenging ones. We conduct experiments on DRONE-ACTION, MOD20, and UAV datasets, demonstrating that POG-MVNet significantly outperforms competing methods. For example, POG-MVNet achieves a 4.7% improvement on DRONE-ACTION dataset and a 3.5% improvement on UAV dataset compared to state-of-the-art methods ASAT and FAR. The code for POG-MVNet will be made available soon. Copyright © 2025, The Authors. All rights reserved.

关键词： Drones

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MetaGCD: Learning to Continually Learn in Generalized Category Discovery

MetaGCD: Learning to Continually Learn in Generalized Catego...

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International Conference on computer Vision (ICCV)

作者： Yanan Wu Zhixiang Chi Yang Wang Songhe Feng Key Laboratory of Big Data & Artificial Intelligence in Transportation Ministry of Education Beijing Jiaotong University Beijing China School of Computer and Information Technology Beijing Jiaotong University Beijing China Department of Electrical and Computer Engineering University of Toronto Toronto Canada Department of Computer Science and Software Engineering Concordia University Montreal Canada

In this paper, we consider a real-world scenario where a model that is trained on pre-defined classes continually encounters unlabeled data that contains both known and novel classes. The goal is to continually discover novel classes while maintaining the performance in known classes. We name the setting Continual Generalized Category Discovery (C-GCD). Existing methods for novel class discovery cannot directly handle the C-GCD setting due to some unrealistic assumptions, such as the unlabeled data only containing novel classes. Furthermore, they fail to discover novel classes in a continual fashion. In this work, we lift all these assumptions and propose an approach, called MetaGCD, to learn how to incrementally discover with less forgetting. Our proposed method uses a meta-learning framework and leverages the offline labeled data to simulate the testing incremental learning process. A meta-objective is defined to revolve around two conflicting learning objectives to achieve novel class discovery without forgetting. Furthermore, a soft neighborhood-based contrastive network is proposed to discriminate uncorrelated images while attracting correlated images. We build strong baselines and conduct extensive experiments on three widely used benchmarks to demonstrate the superiority of our method.

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Nonreciprocal Control of the Speed of Light Using Cavity Magnonics

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Physical Review Letters 2025年第19期134卷 196904-196904页

作者： Jiguang Yao Chenyang Lu Xiaolong Fan Desheng Xue Greg E. Bridges C.-M. Hu Department of Physics and Astronomy University of Manitoba Winnipeg Manitoba R3T 2N2 Canada The Key Laboratory for Magnetism and Magnetic Materials of the Ministry of Education Lanzhou University Lanzhou 730000 China Department of Electrical and Computer Engineering University of Manitoba Winnipeg Manitoba R3T 5V6 Canada

We demonstrate nonreciprocal control of the speed of light by sending a microwave pulse through a cavity magnonics device. In contrast to reciprocal group velocity controlled by conventional electromagnetically induced transparency (EIT) effects, incorporating a dissipative magnon-photon coupling establishes a nonreciprocal EIT effect, allowing slow and fast light propagation in opposite directions at the same frequency with comparable amplitude. Remarkably, reversing the magnetic field enables a directional switch between nonreciprocal fast and slow light. This discovery may offer new possibilities for pulse time regulation in microwave signal communications, neuromorphic computing, and quantum signal processing.

关键词： Light velocity

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Fast Calculations of Bands of Vector Electromagnetic Waves in 3D Periodic Structures Using Broadband Green's Function-Multiple Scattering Theory (BBGF-MST)

Fast Calculations of Bands of Vector Electromagnetic Waves i...

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Progress in Electromagnetic Research Symposium (PIERS)

作者： Tien-Hao Liao Leung Tsang Shurun Tan Xiaolan Xu Xuyang Bai Department of Electrical Engineering National Taipei University of Technology Taipei Taiwan Department of Electrical Engineering and Computer Science Radiation Laboratory University of Michigan Ann Arbor MI USA Zhejiang University/University of Illinois at Urbana-Champaign Institute Zhejiang University Haining Zhejiang China Jet Propulsion Laboratory California Institute of Technology Pasadena CA USA

We have extended the Fast method of BBGF_MST to the vector 3D case of 3D periodic structures for band diagrams and band field calculations. In the BBGF-MST approach, the broadband transformation to vector spherical waves for 3D is derived using the Broadband Green's function, and the band eigenvalue problem is expressed in terms of the single scatterer $T$ matrix. For the first five bands, we use six vector spherical waves to calculate the Korringa-Kohn-Rostoker matrix equation. The BBGF-MST method can calculate the band eigenvalues in vector 3D problems with only 0.309 seconds for the first 5 bands on a standard laptop. The method outperforms commercial software COMSOL which requires 34 secs that ran on a latest desktop/server for 110 times. The memory usage of the software is 2GB during the simulation. Taking account that the desktop server is 10 times faster than the standard laptop, this means that the Fast MST-BBGF method is several hundred times faster than COMSOL. In band field calculation, we use an extended coefficients approach to use the low order eigenvector of 6 to extend to 30 coefficients without the need of recalculating the eigen solution. The extended coefficients approach gives accurate band field results.

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Experiments in Underwater Feature Tracking with Performance Guarantees Using a Small AUV

Experiments in Underwater Feature Tracking with Performance ...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Benjamin Biggs Hans He James McMahon Daniel J. Stilwell Virginia Tech the Bradley Department of Electrical and Computer Engineering Virginia Tech Blacksburg VA USA Acoustics Division US Naval Research Laboratory the US Naval Research Laboratory Washington D.C. USA

We present the results of experiments performed using a small autonomous underwater vehicle to determine the location of an isobath within a bounded area. The primary contribution of this work is to implement and integrate several recent developments real-time planning for environmental map-ping, and to demonstrate their utility in a challenging practical example. We model the bathymetry within the operational area using a Gaussian process and propose a reward function that represents the task of mapping a desired isobath. As is common in applications where plans must be continually updated based on real-time sensor measurements, we adopt a receding horizon framework where the vehicle continually computes near-optimal paths. The sequence of paths does not, in general, inherit the optimality properties of each individual path. Our real-time planning implementation incorporates recent results that lead to performance guarantees for receding-horizon planning.

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CNN-Based Forensic Method on Contrast Enhancement with JPEG Post-Processing

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computers, Materials & Continua 2021年第12期69卷 3205-3216页

作者： Ziqing Yan Pengpeng Yang Rongrong Ni Yao Zhao Hairong Qi Institute of Information Science Beijing Jiaotong UniversityBeijing100044China Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing Jiaotong UniversityBeijing100044China Electrical Engineering and Computer Science Department University of Tennessee KnoxvilleKnoxville37996TNUSA

As one of the most popular digital image manipulations,contrast enhancement(CE)is frequently applied to improve the visual quality of the forged images and conceal traces of forgery,therefore it can provide evidence of tampering when verifying the authenticity of digital *** enhancement forensics techniques have always drawn significant attention for image forensics community,although most approaches have obtained effective detection results,existing CE forensic methods exhibit poor performance when detecting enhanced images stored in the JPEG *** detection of forgery on contrast adjustments in the presence of JPEG post processing is still a challenging *** this paper,we propose a new CE forensic method based on convolutional neural network(CNN),which is robust to JPEG *** proposed network relies on a Xception-based CNN with two preprocessing ***,unlike the conventional CNNs which accepts the original image as its input,we feed the CNN with the gray-level co-occurrence matrix(GLCM)of image which contains CE fingerprints,then the constrained convolutional layer is used to extract high-frequency details in GLCMs under JPEG compression,finally the output of the constrained convolutional layer becomes the input of Xception to extract multiple features for further *** results show that the proposed detector achieves the best performance for CE forensics under JPEG post-processing compared with the existing methods.

关键词： Contrast enhancement forensics convolutional neural networks robust forensics JPEG compression

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Fluid Antenna Systems Enabling 6G:Principles, Applications, and Research Directions

arXiv

引用

arXiv 2024年

作者： Wu, Tuo Zhi, Kangda Yao, Junteng Lai, Xiazhi Zheng, Jianchao Niu, Hong Elkashlan, Maged Wong, Kai-Kit Chae, Chan-Byoung Ding, Zhiguo Karagiannidis, George K. Debbah, Mérouane Yuen, Chau The School of Electrical and Electronic Engineering Nanyang Technological University 639798 Singapore The School of Electrical Engineering and Computer Science Technical University of Berlin Berlin10623 Germany The Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo315211 China The School of Computer Science Guangdong University of Education Guangdong Guangzhou China The School of Computer Science and Engineering Huizhou University Huizhou516000 China The School of Electronic Engineering and Computer Science Queen Mary University of London LondonE1 4NS United Kingdom The Department of Electronic and Electrical Engineering University College London LondonWC1E 6BT United Kingdom The Yonsei Frontier Laboratory Yonsei University Seoul03722 Korea Republic of The School of Integrated Technology Yonsei University Seoul03722 Korea Republic of The Department of Electrical Engineering and Computer Science Khalifa University Abu Dhabi127788 United Arab Emirates The Department of Electrical and Computer Engineering Aristotle University of Thessaloniki Thessaloniki54124 Greece Lebanon Lebanon The Center for 6G Technology Khalifa University of Science and Technology P. O. Box 127788 Abu Dhabi United Arab Emirates

Fluid antenna system (FAS), a novel advancement in reconfigurable antenna technologies, offers unprecedented shape and position flexibility. This innovative approach is emerging as an exciting and potentially transformative technology for wireless communication systems. FAS encompasses any software-controlled fluidic, conductive, or dielectric structure capable of dynamically altering an antenna’s shape and position to modify critical parameters such as gain, radiation pattern, operating frequency, and other key characteristics. Given its unique capabilities, FAS is highly anticipated to play a significant role in shaping the upcoming sixth-generation (6G) wireless networks. This article explores this potential by addressing four major questions: 1) Is FAS crucial to 6G? 2) How can FAS be characterized? 3) What are the applications of FAS? 4) What challenges and future research directions are associated with FAS? In particular, five promising research directions that highlight FAS’s potential are examined. Finally, we conclude by demonstrating the impressive performance of FAS, reinforcing its relevance and promise in future networks. © 2024, CC BY.

关键词： Liquefied gases

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Designing of a Solar MPPT Controller with the Technique of Differentiation Between Uniform Irradiance and Partial Shading Conditions 9

Designing of a Solar MPPT Controller with the Technique of D...

引用

9th IEEE International Conference on Power and Energy, PECon 2022

作者： Ahmed, Sajib Mekhilef, Saad Mubin, Marizan Tey, Kok Soon Rawa, Muhyaddin University of Malaya Power Electronics and Renewable Energy Research Laboratory Faculty of Engineering Department of Electrical Engineering Kuala Lumpur50603 Malaysia School of Science Computing and Engineering Technologies Swinburne University of Technology HawthornVIC3122 Australia University of Malaya Faculty of Computer Science and Information Technology Department of Computer System and Technology Kuala Lumpur50603 Malaysia King Abdulaziz University Center of Research Excellence in Renewable Energy and Power Systems Jeddah21589 Saudi Arabia

ISBN: (数字)9781665409902

ISBN: (纸本)9781665409902

Solar energy is considered one of the best essential energy sources to solve the present power crisis. The solar photovoltaic system has a low conversion efficiency that inflicts maximum power extractions. The non-linear relationship between the voltage and current insists on using a maximum power point tracking (MPPT) controller. Perturb and observe (P&O) MPPT controller is popular because of its simple design and cost-effectiveness features;nonetheless, it has drawbacks while operating under partial shading conditions (PSC). The maximum power trapezium (MPT) method modified the P&O algorithm by incorporating an appropriate scanning mechanism for PSC. Despite having good PSC performance, this method's tracking time is much longer than the conventional algorithm in both uniform irradiance conditions (UIC) and PSC. The algorithm proposed in this paper modifies the MPT method with an extra strategy to distinguish between the UIC and PSC. If the pattern is recognized as UIC, the proposed method utilizes the conventional P&O algorithm to track the MPP;otherwise, scanning techniques are being used. The proposed algorithm's operation was tested on simulation using distinct UIC and PSC patterns and worked effectively. © 2022 IEEE.

关键词： Cost effectiveness

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Interactive Learning Through the Metaverse and its Impact on Primary Education

Interactive Learning Through the Metaverse and its Impact on...

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International Conference on electrical engineering/Electronics, computer, Telecommunications and Information Technology, ECTI-CON

作者： Cheilsi Sharma Basant Agarwal Lunchakorn Wuttisittikulkij Daksh Joshi Akshat Bhatnagar Sushank Chaudhary Pruk Sasithong Dept. of Computer Science Rajasthan University Jaipur India Department of Computer Science and Engineering Central University of Rajasthan Kishangarh India Telecommunication System Research Laboratory Chulalongkorn University Bangkok Thailand Bangkok Thailand Department of CSE Indian Institute of Information Technology Kota (IIIT Kota) Kota India Department of Electrical Engineering Chulalongkorn University Bangkok Thailand Bangkok Thailand

ISBN: (数字)9798350381559

ISBN: (纸本)9798350381566

The rise of the Metaverse, an immersive, three-dimensional digital environment, has been gradually transforming human-computer interaction. This paper focuses on exploring the potential of the Metaverse to improve learning through interactive games. The Metaverse serves as a dynamic platform for students to collaborate, explore and engage with. It enables educators to create interactive learning environments that amalgamate both physical and virtual spaces through technologies such as virtual reality, augmented reality, and artificial intelligence. These interactive games within the Metaverse foster critical thinking and problem-solving on top of making learning enjoyable. This paper discusses the development of educational environments within the metaverse, the integration of interactive games as well as their impact on learning outcomes and student engagement. The Metaverse poses a novel route towards effective education with this gamified approach. This study highlights the potential for the Metaverse to prepare students for the challenges inherent in this digital age by transforming traditional educational methods.

关键词： Metaverse Space technology Education Mixed reality Games Learning (artificial intelligence) Telecommunications

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