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arXiv 2022年

作者： Madurasinghe, Dulip Venayagamoorthy, Ganesh K. Real-Time Power and Intelligent Systems Laboratory Holcombe Department of Electrical and Computer Engineering Clemson University ClemsonSC29634 United States

Power system transmission network topology is utilized in energy management system applications. Substation configurations are fundamental to transmission network topology processing. Modern power systems consisting of renewable energy sources require reliable and fast network topology processing due to the variable nature of wind and solar power plants. Currently used transmission network topology processing, which is based on the relay signals communicated through SCADA is not highly reliable or highly accurate. Substation configuration identification (SCI) for different substation arrangements including main and transfer bus arrangement (MTBA), ring bus arrangement (RBA), and single bus arrangement (SBA) is investigated. Synchrophasor measurement based SCI for functional arrangements (FA) using artificial intelligence (AI) approaches is proposed in this paper. This method improves monitoring FA. Typical results for MTBA, RBA and SBA substation configuration identification is presented. A modified two-area four-machine power system model with two grid connected solar PV plants consisting of MTBA, RBA and SBA is simulated on real-time digital simulator. AI based SCI is shown to accurately identify all possible FAs for the three substation arrangements under any operating condition. © 2022, CC BY.

关键词： Network topology

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Metamaterial-induced-transparency engineering through quasi-bound states in the continuum by using dielectric cross-shaped trimers

arXiv

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arXiv 2024年

作者： Ghahremani, Maryam Zapata-Rodríguez, Carlos J. Photonics Research Laboratory Center of Excellence on Applied Electromagnetic Systems School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Department of Optics and Optometry and Vision Sciences Faculty of Physics University of Valencia Dr. Moliner 50 Burjassot46100 Spain

This study presents a novel approach to activate a narrowband transparency line within a reflecting broadband window in all-dielectric metasurfaces, in analogy to the electromagnetically-induced transparency effect, by means of a quasi-bound state in the continuum (qBIC). We demonstrate that the resonance overlapping of a bright mode and a qBIC-based nearly-dark mode with distinct Q-factor can be fully governed by a silicon trimer-based unit cell with broken-inversion-symmetry cross shape, thus providing the required response under normal incidence of a linearly-polarized light. Our analysis that is derived from the far-field multipolar decomposition and near-field electromagnetic distributions uncovers the main contributions of different multipoles on the qBIC resonance, with governing magnetic dipole and electric quadrupole terms supplied by distinct parts of the dielectric "molecule." The findings extracted from this research open up new avenues for the development of polarization-dependent technologies, with particular interest in its capabilities for sensing and biosensing. © 2024, CC BY-NC-ND.

关键词： Transparency

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GINN-LP: A Growing Interpretable Neural Network for Discovering Multivariate Laurent Polynomial Equations

arXiv

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arXiv 2023年

作者： Ranasinghe, Nisal Senanayake, Damith Seneviratne, Sachith Premaratne, Malin Halgamuge, Saman AI Optimization and Pattern Recognition Research Group Dept. of Mechanical Eng. University of Melbourne Australia Melbourne School of Design University of Melbourne Australia Department of Electrical and Computer Systems Engineering Monash University Australia

Traditional machine learning is generally treated as a black-box optimization problem and does not typically produce interpretable functions that connect inputs and outputs. However, the ability to discover such interpretable functions is desirable. In this work, we propose GINN-LP, an interpretable neural network to discover the form and coefficients of the underlying equation of a dataset, when the equation is assumed to take the form of a multivariate Laurent Polynomial. This is facilitated by a new type of interpretable neural network block, named the "power-term approximator block", consisting of logarithmic and exponential activation functions. GINN-LP is end-to-end differentiable, making it possible to use backpropagation for training. We propose a neural network growth strategy that will enable finding the suitable number of terms in the Laurent polynomial that represents the data, along with sparsity regularization to promote the discovery of concise equations. To the best of our knowledge, this is the first model that can discover arbitrary multivariate Laurent polynomial terms without any prior information on the order. Our approach is first evaluated on a subset of data used in SRBench, a benchmark for symbolic regression. We first show that GINN-LP outperforms the state-of-the-art symbolic regression methods on datasets generated using 48 real-world equations in the form of multivariate Laurent polynomials. Next, we propose an ensemble method that combines our method with a high-performing symbolic regression method, enabling us to discover non-Laurent polynomial equations. We achieve state-of-the-art results in equation discovery, showing an absolute improvement of 7.1% over the best contender, by applying this ensemble method to 113 datasets within SRBench with known ground-truth equations. © 2023, CC BY-NC-ND.

关键词： Polynomials

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Near-field communications:characteristics,technologies,and engineering

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Frontiers of Information Technology & Electronic engineering 2024年第12期25卷 1580-1626页

作者： Yajun ZHAO Linglong DAI Jianhua ZHANG Ran JI Mengnan JIAN Hao XUE Hongkang YU Yunqi SUN Yu LU Zidong WU Zhuo XU Jinke LI Haiyang MIAO Zhiqiang YUAN Pan TANG Jiayu SHEN Tierui GONG Haixia LIU Jiaqi HAN Qiang FENG Zhi CHEN Lingxiang LI Gang YANG Yong ZENG Cunhua PAN Wang LIU Kangda ZHI Weidong HU Yuanwei LIU Xidong MU Chau YUEN Mérouane DEBBAH Chongwen HUANG Long LI Ping ZHANG State Key Laboratory of Mobile Network and Mobile Multimedia Technology Shenzhen 518055China ZTE Corporation Beijing 100192China Department of Electronic Engineering Tsinghua UniversityBeijing 100084China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China College of Information Science and Electronic Engineering Zhejiang UniversityHangzhou 310007China Key Laboratory of High Speed Circuit Design and EMC of Ministry of Education School of Electronic EngineeringXidian UniversityXi’an 710071China Collaborative Innovation Center of Information Sensing and Understanding Xidian UniversityXi’an 710071China National Key Laboratory of Wireless Communications University of Electronic Science and Technology of ChinaChengdu 611731China National Mobile Communications Research Laboratory Southeast UniversityNanjing 210096China Purple Mountain Laboratories Nanjing 211111China School of Electrical Engineering and Computer Science Technical University of BerlinBerlin 10623Germany School of Integrated Circuits and Electronics Beijing Institute of TechnologyBeijing 100081China Department of Electrical and Electronic Engineering The University of Hong KongHong KongChina Centre for Wireless Innovation(CWI) School of ElectronicsElectrical Engineering and Computer ScienceQueen’s University BelfastBelfast BT39DTUK School of Electrical and Electronic Engineering Nanyang Technological UniversitySingapore 639798Singapore KU 6G Research Center Khalifa University of Science and TechnologyAbu DhabiUnited Arab Emirates

Near-field technology is increasingly recognized due to its transformative potential in communication systems,establishing it as a critical enabler for sixth-generation(6G)telecommunication *** paper presents a comprehensive survey of recent advancements in near-field technology ***,we explore the near-field propagation fundamentals by detailing definitions,transmission characteristics,and performance ***,we investigate various near-field channel models—deterministic,stochastic,and electromagnetic information theory based models,and review the latest progress in near-field channel testing,highlighting practical performance and *** evolving channel models,traditional mechanisms such as channel estimation,beamtraining,and codebook design require redesign and optimization to align with near-field propagation *** then introduce innovative beam designs enabled by near-field technologies,focusing on non-diffractive beams(such as Bessel and Airy)and orbital angular momentum(OAM)beams,addressing both hardware architectures and signal processing frameworks,showcasing their revolutionary potential in near-field communication ***,we highlight progress in both engineering and standardization,covering the primary 6G spectrum allocation,enabling technologies for near-field propagation,and network deployment ***,we conclude by identifying promising future research directions for near-field technology development that could significantly impact system *** comprehensive review provides a detailed understanding of the current state and potential of near-field technologies.

关键词： 6G Near-field technology Channel model Codebook Non-diffractive beams Orbital angular momentum engineering and standardization

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A Multi-Player Potential Game Approach for Sensor Network Localization with Noisy Measurements

A Multi-Player Potential Game Approach for Sensor Network Lo...

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IEEE Conference on Decision and Control

作者： Gehui Xu Guanpu Chen Baris Fidan Yiguang Hong Hongsheng Qi Thomas Parisini Karl H. Johansson Department of Electrical and Electronic Engineering Imperial College London London UK Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Department of Mechanical and Mechatronics Engineering University of Waterloo Waterloo ON Canada Department of Control Science and Engineering Tongji University shanghai China Shanghai Research Institute for Intelligent Autonomous Systems Shanghai China Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Beijing China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing China Department of Electronic Systems Aalborg University Denmark Department of Engineering and Architecture University of Trieste Italy

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

Sensor network localization (SNL) is a challenging problem due to its inherent non-convexity and the effects of noise in inter-node ranging measurements and anchor node position. We formulate a non-convex SNL problem as a multiplayer non-convex potential game and investigate the existence and uniqueness of a Nash equilibrium (NE) in both the ideal setting without measurement noise and the practical setting with measurement noise. We first show that the NE exists and is unique in the noiseless case, and corresponds to the precise network localization. Then, we study the SNL for the case with errors affecting the anchor node position and the inter-node distance measurements. Specifically, we establish that in case these errors are sufficiently small, the NE exists and is unique. It is shown that the NE is an approximate solution to the SNL problem, and that the position errors can be quantified accordingly. Based on these findings, we apply the results to case studies involving only inter-node distance measurement errors and only anchor position information inaccuracies.

关键词： Location awareness Noise Games Position measurement Nash equilibrium Distance measurement Noise measurement

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Bilateral Teleoperation Control Using Unified Interactive Model for Manipulation in Contact Environment*

Bilateral Teleoperation Control Using Unified Interactive Mo...

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IEEE International Conference on Robotics and Biomimetics

作者： Xiao Yang Fanghao Huang Jason Gu Zheng Chen State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang University Hangzhou China Ocean College Zhejiang University Zhoushan China Department of Electrical and Computer Engineering Dalhousie University Halifax Canada Zhejiang Laboratory Hangzhou China

In this paper, a novel bilateral teleoperation control is designed specifically for manipulation in contact environment. Firstly, serval interaction conditions (e.g., free motion and rigid interaction) are defined and unified into one equation as the designed unified interactive model, which can also be utilized as a control objective. Based on this model, a remote hybrid motion/force controller is designed for remote robot, which achieves the good position and force tracking, and ensures the precise and safe contact force that helps reduce the workload of operator. Subsequently, the contact force is reconstructed in the local side by estimating and transmitting the non-power environment coefficient from remote side, which provides the operator with accurate force feedback. Since the coefficient replaces the direct transmission of force signal in the communication channel, the traditional power-cycle problem is essentially avoided, which guarantees the stability of teleoperation system under communication time delays. Comparative experiments are implemented to verify the effectiveness of proposed method for teleoperated manipulation.

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Effects of Multimodal Alarms on the Performance of Mental Available Resources in Complex Monitoring Task

SSRN

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SSRN 2024年

作者： Cun, Wenzhe Yu, Suihuai Chu, Jianjie Jianhua, Sun Jiang, Ao Fan, Hao Key Laboratory of Industrial Design and Ergonomics Ministry of Industry and Information Technology Northwestern Polytechnical University China School of Mechanical and Electrical Engineering Nanjing University of Aeronautics and Astronautics China Department of Design Southeast University China College of Computer Science and Technology Zhejiang University China Northwestern Polytechnical University China

Due to the extensive information presented in complex monitoring task, visual and auditory channels may become overwhelmed and incapable of efficiently conveying the necessary information for response tasks to alarms. This overload can lead to a significant rise in the operators' mental workload. This study aims to investigate the performance of multimodal alarms under different levels of mental available resources (MARs) in complex monitoring task. The effectiveness of three multimodal alarms—VA (Visual and Auditory) mode, VT (Visual and Tactile) mode, and VAT (Visual, Auditory, and Tactile) mode—across three levels of MAR (MAR-L1, MAR-L2, and MAR-L3) were investigated while operators engaged in complex monitoring tasks. Specifically, simulated experiments of flight take-offs in a civil aircraft cockpit during emergency scenarios were conducted in this investigation. The results showed that the VAT alarm was superior to the VA and VT alarm under MAR-L1 and MAR-L3 conditions, whereas the performance of VA and VAT alarm had no significant difference. As operators who are engaged in complex monitoring task are generally under heavy workload and lower MAR conditions, the VAT alarm is considered to hold significant potential for practical engineering applications. © 2024, The Authors. All rights reserved.

关键词： Cockpits (aircraft)

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QuerySOD: A Small Object Detection Algorithm Based on Sparse Convolutional Network and Query Mechanism

QuerySOD: A Small Object Detection Algorithm Based on Sparse...

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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Zhengcai Cao Junnian Li Jie Niu MengChu Zhou State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin China College of Information Science and Technology Beijing University of Chemical Technology Beijing China Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Although remarkable advances have been achieved in generic object detection, small object detection (SOD) remains challenging owing to small objects’ information loss and noisy representation caused by their non-uniform distribution. Their limited width and height, scale variations, and redundant computation make SOD hard. To overcome them, this work proposes a new SOD method based on sparse convolutional network (SCNet) and Query Mechanism called QuerySOD. First, an extended feature pyramid network is constructed for extracting feature maps of small objects with more regional details. Then, a Sparse Head is neatly designed by using SCNet for accelerating the interfering speed and obtaining weights of each layer. After that, a Query Mechanism is innovatively introduced for harvesting the benefit of sparse value feature maps from the Sparse Head. QuerySOD is evaluated on public benchmarks including COCO and VisDrone. Finally, we apply it on ‘Jinghai’ unmanned survey vehicles and receive excellent SOD performance from this real-world application.

关键词： Surveys Accuracy Object detection Seaports Lakes Feature extraction Prediction algorithms Convolutional neural networks Security Noise measurement

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Reconfigurable intelligent surfaces for wireless communications:Overview of hardware designs,channel models,and estimation techniques

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Intelligent and Converged Networks 2022年第1期3卷 1-32页

作者： Mengnan Jian George C.Alexandropoulos Ertugrul Basar Chongwen Huang Ruiqi Liu Yuanwei Liu Chau Yuen the Wireless Research Institute ZTE CorporationBeijing 100029China the State Key Laboratory of Mobile Network and Mobile Multimedia Technology Shenzhen 518055China Department of Informatics and Telecommunications National and Kapodistrian University of AthensAthens 15784Greece Communications Research and Innovation Laboratory(CoreLab) Department of Electrical and Electronics EngineeringKoçUniversityIstanbul 34450Turkey College of Information Science and Electronic Engineering Zhejiang UniversityHangzhou 310027China School of Electronic Engineering and Computer Science Queen Mary University of LondonLondonE14NSUK. the Engineering Product Development(EPD)Pillar Singapore University of Technology and DesignSingapore 487372Singapore

The demanding objectives for the future sixth generation(6G)of wireless communication networks have spurred recent research efforts on novel materials and radio-frequency front-end architectures for wireless connectivity,as well as revolutionary communication and computing *** the pioneering candidate technologies for 6G belong the reconfigurable intelligent surfaces(RISs),which are artificial planar structures with integrated electronic circuits that can be programmed to manipulate the incoming electromagnetic field in a wide variety of *** RISs in wireless networks have been recently advocated as a revolutionary means to transform any wireless signal propagation environment to a dynamically programmable one,intended for various networking objectives,such as coverage extension and capacity boosting,spatiotemporal focusing with benefits in energy efficiency and secrecy,and low electromagnetic field *** by the recent increasing interests in the field of RISs and the consequent pioneering concept of the RIS-enabled smart wireless environments,in this paper,we overview and taxonomize the latest advances in RIS hardware architectures as well as the most recent developments in the modeling of RIS unit elements and RIS-empowered wireless signal *** also present a thorough overview of the channel estimation approaches for RIS-empowered communications systems,which constitute a prerequisite step for the optimized incorporation of RISs in future wireless ***,we discuss the relevance of the RIS technology in the latest wireless communication standards,and highlight the current and future standardization activities for the RIS technology and the consequent RIS-empowered wireless networking approaches.

关键词： reconfigurable intelligent surfaces beyond 5G 6G channel modeling hardware architecture channel estimation smart wireless environment standardization

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Pneumonia Classification using deep learning: a comparative study

Pneumonia Classification using deep learning: a comparative ...

引用

International Conference on Image and Signal Processing and their Applications (ISPA)

作者： Mohamed Lakhdar Tiar Nadjiba Terki Juan Jose Dominguez-Jimenez IL3CUB Laboratory University of Mohamed Khider Biskra Algeria Electrical Engineering Department University of Mohamed Khider Biskra Algeria Dept. Computer Languages and Systems University of Cadiz Escuela Superior de Ingenieria Cadiz Spain

ISBN: (数字)9798350309249

ISBN: (纸本)9798350309256

Pneumonia is an infectious disease of the lungs, caused by viruses, bacteria or fungi. Pneumonia is distinguished by acute inflammation of the lung tissue, causing the consolidation of the terminal bronchioles and alveoli. According to the WHO (the World Health Organization), this disease causes about 4 million deaths. Among the methods of diagnosing pneumonia uses a chest X-ray. This is widely used to visualize pulmonary abnormalities. This work aims at the detection and characterization of pneumonia by the development of computer-assisted diagnosis systems (DAOC). We use deep learning algorithms and chest X-ray images from a pneumonia database to examine the classification of pneumonia. To improve the accuracy, we compare several deep learning models. This research contributes to meeting the growing demand for medical personnel by addressing the global incidence of chest disorders.

关键词： Deep learning Visualization Pneumonia Lung Signal processing algorithms Medical services Signal processing

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