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On-Line Conference (ONCON), Industrial Electronics Society Annual

作者： Huanfeng Zhao Meibao Yao Xueming Xiao Bo Zheng Tao Cao Tao Hu Intelligent Robotics Lab (IRL) School of Artificial Intelligence Jilin University Changchun China Engineering Research Center of Knowledge-Driven Human-Machine Intelligence Ministry of Education China CVIR Lab Changchun University of Science and Technology Changchun China Key Lab of Opto-Electronic Measurement and Optical Information Transmission Technology Shanghai Aerospace Control Technology Institute Shanghai China

In LiDAR SLAM, data association of sparse LiDAR scan and high computational complexity of point-to-model metrics limit real-time applications of joint optimization module like Bundle Adjustment in Visual SLAM, which leads to cumulative errors deteriorating performance. To address this drawback, in this paper, we propose LPL-SLAM with plane and line optimization for the structural environment. Since plane and line primitives are ubiquitous in man-made environments, we treat the primitives as landmarks to process scans. We introduce line and plane factors relying on line-to-line and plane-to-plane metrics to optimize keyframe poses, planes and lines. With the line and plane factors, our system avoids a large-scale optimization problem and yields accurate and consistent tracking poses. Experimental results demonstrate that LPL-SLAM outperforms the state-of-the-art algorithms and achieves real-time performance.

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NTIRE 2023 Challenge on Efficient Super-Resolution: Methods and Results

NTIRE 2023 Challenge on Efficient Super-Resolution: Methods ...

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2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2023

作者： Li, Yawei Zhang, Yulun Timofte, Radu Van Gool, Luc Yu, Lei Li, Youwei Li, Xinpeng Jiang, Ting Wu, Qi Han, Mingyan Lin, Wenjie Jiang, Chengzhi Luo, Jinting Fan, Haoqiang Liu, Shuaicheng Wang, Yucong Cai, Minjie Li, Mingxi Zhang, Yuhang Fan, Xian-Jun Sheng, Yankai Mao, Yanyu Zhang, Nihao Wang, Qian Zheng, Mingjun Sun, Long Pan, Jinshan Dong, Jiangxin Tang, Jinhui Yang, Zhongbao Wang, Yan Pan, Erlin Cai, Qixuan Dai, Xinan Zhussip, Magauiya Kalyazin, Nikolay Vyal, Dmitry Zou, Xueyi Yan, Youliang Chung, Heaseo Zhang, Jin Yu, Gaocheng Zhang, Feng Wang, Hongbin Liao, Bohao Du, Zhibo Wu, Yu-Liang Shi, Gege Peng, Long Wang, Yang Cao, Yang Zha, Zhengjun Huang, Zhi-Kai Chen, Yi-Chung Chiang, Yuan-Chun Yang, Hao-Hsiang Chen, Wei-Ting Chang, Hua-En Chen, I-Hsiang Hsieh, Chia-Hsuan Kuo, Sy-Yen Liu, Xin Pan, Jiahao Yu, Hongyuan Yu, Weichen Ge, Lin Dong, Jiahua Zou, Yajun Wu, Zhuoyuan Han, Binnan Zhang, Xiaolin Zhang, Heng Yin, Xuanwu Zuo, Kunlong Deng, Weijian Yuan, Hongjie Lu, Zengtong Ouyang, Mingyu Ma, Wenzhuo Liu, Nian Zheng, Hanyou Zhang, Yuantong Zhang, Junxi Chen, Zhenzhong Gendy, Garas Sabor, Nabil Hou, Jingchao He, Guanghui Zhu, Yurui Wang, Xi Fu, Xueyang Zha, Zheng-Jun Yin, Daheng Liu, Mengyang Chen, Baijun Li, Ao Luo, Lei Jin, Kangjun Zhu, Ce Zhang, Xiaoming Xie, Chengxing Li, Linze Meng, Haiteng Zhang, Tianlin Li, Tianrui Zhao, Xiaole Zhang, Zhao Li, Baiang Zheng, Huan Zhao, Suiyi Gao, Yangcheng Ren, Jiahuan Hu, Kang Shi, Jingpeng Wu, Zhijian Huang, Dingjiang Zhu, Jinchen Li, Hui Xv, Qianru Liu, Tianle Weng, Shizhuang Wu, Gang Jiang, Junpeng Liu, Xianming Jiang, Junjun Zhang, Mingjian Hu, Jing Wu, Chengxu Fan, Qinrui Feng, Chengming Luo, Ziwei Hu, Shu Lyu, Siwei Wu, Xi Wang, Xin Computer Vision Lab ETH Zurich Switzerland Computer Vision Lab University of Würzburg Germany Megvii Technology China MicroBT China College of Computer Science and Electronic Engineering Hunan University China Attrsense Xian University of Posts and Telecommunications Xi'an China National Engineering Laboratory for Cyber Event Warning and Control Technologies China Nanjing University of Science and Technology China Nankai University China University of Electronic Science and Technology of China China Tianjin University China Noah's Ark Lab Huawei Technologies McMaster University Canada Espresomedia Korea Republic of AntGroup China University of Science and Technology of China China Department of Electrical Engineering National Taiwan University Taiwan Graduate Institute of Communication Engineering National Taiwan University Taiwan Graduate Institute of Electronics Engineering National Taiwan University Taiwan ServiceNow United States China Mobile Research Institute China Chongqing University of Technology China Multimedia Department Xiaomi Inc. China Institute of Automation Chinese Academy of Sciences China Shenyang Institute of Automation Chinese Academy of Sciences China School of Information and Communication Engineering Communication University of China China Smart Classroom Division Ruijie Networks Co. Ltd. China School of Remote Sensing and Information Engineering Wuhan University China Micro-Nano Electronics Department Shanghai Jiao Tong University Shanghai200240 China Electrical Engineering Department Faculty of Engineering Assiut University Assiut71516 Egypt Southeast University China University of Electronic Science and Technology of China Chengdu China Chongqing University of Posts and Telecommunications Chongqing China Information Technology Co. Ltd Hangzhou China Southwest Jiaotong University China National Space Science Center Chinese Academy of Science China Hefei University of Technology Hefei China Anhui University China Fried Ric

ISBN: (纸本)9798350302493

This paper reviews the NTIRE 2023 challenge on efficient single-image super-resolution with a focus on the proposed solutions and results. The aim of this challenge is to devise a network that reduces one or several aspects such as runtime, parameters, FLOPs, activations, memory footprint, and depth of RFDN while at least maintaining the PSNR of 29.00dB on DIV2K validation datasets. The challenge had 272 registered participants, and 35 teams made valid submissions. They gauge the state-of-the-art for efficient single-image super-resolution. © 2023 IEEE.

关键词： Optical resolving power

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Social Force Embedded Mixed Graph Convolutional Network for Multi-class Trajectory Prediction

arXiv

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arXiv 2024年

作者： Du, Quancheng Wang, Xiao Yin, Shouguo Li, Lingxi Ning, Huansheng The School of Computer and Communication Engineering University of Science and Technology Beijing Beijing100083 China The School of Artificial Intelligence Anhui University Hefei230031 China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China The School of Electrical and Computer Engineering Indiana University Purdue University IndianapolisIN46202 United States

Accurate prediction of agent motion trajectories is crucial for autonomous driving, contributing to the reduction of collision risks in human-vehicle interactions and ensuring ample response time for other traffic participants. Current research predominantly focuses on traditional deep learning methods, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs). These methods leverage relative distances to forecast the motion trajectories of a single class of agents. However, in complex traffic scenarios, the motion patterns of various types of traffic participants exhibit inherent randomness and uncertainty. Relying solely on relative distances may not adequately capture the nuanced interaction patterns between different classes of road users. In this paper, we propose a novel multi-class trajectory prediction method named the social force embedded mixed graph convolutional network (SFEM-GCN). The primary goal is to extract social interactions among agents more accurately. SFEM-GCN comprises three graph topologies: the semantic graph (SG), position graph (PG), and velocity graph (VG). These graphs encode various of social force relationships among different classes of agents in complex scenes. Specifically, SG utilizes one-hot encoding of agent-class information to guide the construction of graph adjacency matrices based on semantic information. PG and VG create adjacency matrices to capture motion interaction relationships between different classes agents. These graph structures are then integrated into a mixed graph, where learning is conducted using a spatio-temporal graph convolutional neural network (ST-GCNN). To further enhance prediction performance, we adopt temporal convolutional networks (TCNs) to generate the predicted trajectory with fewer parameters. Experimental results on publicly available datasets demonstrate that SFEM-GCN surpasses state-of-the-art methods in terms of accuracy and robustness. Copyright © 2024, The Authors.

关键词： Forecasting

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Performance Analysis of OMA/NOMA-aided Satellite communication Networks: A Stochastic Geometry Approach

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IEEE Transactions on communications 2024年

作者： Li, Kecheng Wang, Jun Hou, Tianwei Li, Anna Yue, Xinwei Liu, Yuanwei Chen, Wei School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China School of Electronic Engineering and Computer Science Queen Mary University of London LondonE1 4NS United Kingdom KU Leuven Leuven3001 Belgium School of Computing and Communications Lancaster University LancasterLA1 4WA United Kingdom Key Laboratory of Information and Communication Systems Ministry of Information Industry China Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science and Technology University Beijing100101 China Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong

The increasing quality of service requirements and demand for satellite services necessitate higher data rates, spectral efficiency, and stability in satellite communication networks. Therefore, this paper investigates the non-orthogonal multiple access (NOMA) assisted satellite communication networks, where multiple users are uniformly distributed over a spherical hat according to the homogeneous Poisson point process (HPPP). Based on the characteristics of HPPP, we analyze the distance distributions of users. To evaluate the performance of the proposed networks, we first derive the closed-form expressions and approximated expressions of the outage probability (OP) for paired NOMA users. To obtain more insights into the proposed networks, the ergodic rate and diversity orders for paired NOMA users are also derived. Spectral efficiency is derived for NOMA and orthogonal multiple access (OMA) assisted satellite communication networks. Our analytical results demonstrate that the diversity order of the proposed networks is all one. Numerical results confirm that: 1) compared to OMA, the proposed NOMA-assisted satellite network demonstrates superior outage performance and spectral efficiency, especially in the higher power regimes;2) fading factors have negligible effects on OP and spectral efficiency;and 3) under certain target rates for both near and far users, the outage performance of far users in NOMA-assisted satellite communication networks is superior to that of near users. © 2024 institute of Electrical and Electronics Engineers Inc.. All rights reserved.

关键词： Satellite communication systems

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Simultaneous Generation of Quantum Frequency Combs across Distinct Modal Families in a Single Silicon Nitride Whispering Gallery Mode Resonator

arXiv

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arXiv 2024年

作者： Ji, Bo Yang, Yongjun Wu, Tengfei Li, Nianqin He, Guangqiang State Key Laboratory of Advanced Optical Communication Systems and Networks Department of Electronic Engineering Shanghai Jiao Tong University Shanghai200240 China Science and Technology on Metrology and Calibration Laboratory Changcheng Institute of Metrology Measurement Aviation Industry Corporation of China Beijing100095 China State Key Laboratory of Precision Spectroscopy East China Normal University Shanghai200062 China

Quantum frequency combs (QFCs) are versatile resources for multi-mode entanglement, such as cluster states, crucial for quantum communication and computation. On-chip whispering gallery mode resonators (WGMRs) can generate these states at ultra-low threshold power. This work demonstrates the simultaneous generation of multiple QFCs using a single on-chip silicon nitride WGMR across distinct modal families. It presents a micro-ring resonator with a radius of 240 µm, capable of supporting four modal families within the 130 to 260 THz frequency range for consistency regulation. The results indicate that, by carefully designing the structure of silicon nitride WGMRs, it is possible to generate quantum entangled frequency combs across distinct modal families simultaneously using monochromatic pump light. It is achieved by modulating the pump mode profiles with a spatial light modulator (SLM) or an on-chip inverse-designed mode converter. This approach offers a simple and low-cost method to achieve higher-density entanglement integration on-chip. Copyright © 2024, The Authors. All rights reserved.

关键词： Silicon nitride

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Design of a Remotely Operated Vehicle (ROV) for Biofoul Cleaning and Inspection of Variety of Underwater Structures

Design of a Remotely Operated Vehicle (ROV) for Biofoul Clea...

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RSI/ISM International Conference on Robotics and Mechatronics (ICROM)

作者： Nandha Kizor V Burhanuddin Shirose Mainak Adak Mitesh Kumar Sudarsana Jayandan J Arun Srinivasan Raashid Sheikh Muhammad Electronics and Communication Engineering National Institute of Technology Tiruchirappalli Tamil Nadu India Mechanical Engineering National Institute of Technology Tiruchirappalli Tamil Nadu India Instrumentation and Control Engineering National Institute of Technology Tiruchirappalli Tamil Nadu India

ISBN: (纸本)9781665420952

Biofouling is a thin layer of bacterial formation on surfaces in prolonged contact with water. Biofouling is the primary cause of decay in a lifetime in dams and reduces energy output from reservoirs and ship *** primary aim is to effectively remove biofouling of almost every underwater surface and construction mentioned above. The product will result in less human interference in such dangerous and less efficient aquatic cleaning activities, decreasing the cost and increasing the cleaning operations’ safety and efficiency.

关键词： Surface cleaning Underwater structures Remotely guided vehicles Dams Inspection Robot sensing systems Reservoirs

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Research on fault feature extraction of rotating machinery based on adaptive VMD and optimized CYCBD

Research on fault feature extraction of rotating machinery b...

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Chinese control and Decision Conference, CCDC

作者： Ran Xie Ling Xiong Binbin Dan Zeyu Ren Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education Wuhan Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology Wuhan China Key Laboratory of Metallurgical Equipment and Control of Ministry of Education Wuhan China School of Physics and Electronic Science Hunan Institute of Science and Technology Yueyang China

ISBN: (纸本)9781665478977

To solve the problem that early fault features of rotating machinery are difficult to extract, an adaptive k-value hierarchical variational mode decomposition (H-VMD) combined with optimized maximum second-order cyclostationarity blind deconvolution (CYCBD) fault feature extraction method is proposed in this paper. Mode decomposition of the vibration signal is performed with H-VMD. and then the noise dominant component is denoised by wavelet threshold denoising (WTD). Furthermore, the improved autocorrelation-weighted correlated kurtosis (ACK) when CYCBD enhances the periodic shock component of the denoised signal is the fitness function of ChOA, and the envelope demodulation analysis of the feature-enhanced signal is performed using the teager energy operator (TEO). Simulation analysis and experimental results show that the interference of background noise can be effectively removed and the periodic shock component of the vibration signal be enhanced by the proposed method, which is a new feature extraction method for the fault diagnosis of rotating machinery.

关键词： Vibrations Fault diagnosis Electric shock Noise reduction Interference Feature extraction Linear programming

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Determination of Subscribers Coordinates using Flying Network for Emergencies 24

Determination of Subscribers Coordinates using Flying Networ...

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24th International Conference on Advanced communication technology, ICACT 2022

作者： DInh, Truong Duy Vishnevsky, Vladimir Pham, Van Dai Le, Duc Tran Kirichek, Ruslan Koucheryavy, Andrey Bonch-Bruevich Saint-Petersburg State University of Telecommunications Prospekt Bolshevikov Department of Software Engineering and Computer Technology St. Petersburg Russia V. A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences 65 Profsoyuznaya Street Moscow Russia The University of Danang-University of Science and Technology Information Technology Faculty 54 Nguyen Luong Bang Danang Viet Nam University of Telecommunications Department of Communication Networks and Data Transmission at Bonch-Bruevich Saint-Petersburg State Russia

ISBN: (纸本)9791188428090

In the last decade, unmanned aerial systems have emerged in different fields, such as entertainment, military, Internet of Things, emergencies. In these systems, unmanned aerial vehicles (UAVs) communicate with each other based on a flying network to provide services to customers such as live streaming, high-speed access point, etc. The mobility of UAVs can bring numerous advantages in emergency cases, for example, rescuing and searching victims in areas where the network infrastructure is not available. However, the crucial task needed to be done first is to locate the victims' coordinates. In this paper, we propose a method for detecting the coordinates of subscribers with the Wi-Fi signals generated from victims' phones in the absence of network infrastructure of communication operators using a flying network for emergencies based on UAV-swarms. We develop a new protocol for communication between UAVs and UAV-swarms. A structure of UAV-swarms is considered to optimize the searching time. The results of the proposed method are achieved by simulation. © 2022 Global IT Research institute-GiRI.

关键词： Wi-Fi

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Observer design for 2×2 linear hyperbolic PDEs that are bidirectionally coupled with nonlinear ODEs

Observer design for 2×2 linear hyperbolic PDEs that are bid...

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European control Conference (ECC)

作者： Abdurrahman Irscheid Nicole Gehring Joachim Deutscher Joachim Rudolph Chair of Systems Theory and Control Engineering Saarland University Saarbrücken Germany Institute of Automatic Control and Control Systems Technology Johannes Kepler University Linz Austria Institute for Measurement Control and Microtechnology Ulm University Ulm Germany

A prediction-based observer is designed for systems consisting of 2×2 linear heterodirectional hyperbolic partial differential equations (PDEs) with collocated actuation and measurement at one boundary and bidirectional coupling with nonlinear ordinary differential equations (ODEs) at the other one. Following a preliminary backstepping transformation, a solution-based analysis of the plant allows to draw upon well-known results on the observer design for nonlinear ODEs. For that, the design is split into several steps, with a retarded observer for the ODE state and a prediction thereupon, thus significantly extending existing results for PDE-ODE systems. It is shown that the resulting error system admits a cascaded structure, from which (local) asymptotic convergence follows. Numerical studies underline the performance of the observer.

关键词： Couplings Backstepping Partial differential equations Europe Observers Ordinary differential equations Error correction codes

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Research on Data Integration technology of Large Power Grid Operation Mode for Unconventional Event Analysis

Research on Data Integration Technology of Large Power Grid ...

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IEEE Conference on Energy Internet and Energy System Integration (EI2)

作者： Xuetao Yang Kaixin Liu Dunwen Song Weiwei Miao Facai Xing HaiCheng Tu Power System Department China Electric Power Research Institute(CEPRI) Beijing China Shandong Electric Power Dispatching and Control Center State Grid Shandong Electric Power Company Jinan China Power Grid Technology Center State Grid Shandong Electric Power Research Institute Jinan China School of Communication Engineering Hangzhou Dianzi University Hangzhou China

ISBN: (数字)9798331523527

ISBN: (纸本)9798331523534

The operating laws and characteristics of the new power system have undergone fundamental changes, and are intertwined with the impact of unconventional events such as natural disasters, resulting in a significant increase in safety risks. Firstly, based on the online analysis requirements of unconventional events, a data integration framework for the operation mode of the power grid was constructed, covering both online and offline data generation. Secondly, a standardized integration method for online data to simulation calculation data was proposed, which combines processes such as operational data parsing, topology correlation analysis, and flow convergence adjustment based on reactive power configuration. Finally, based on the characteristics of the impact of unconventional events, a predictive and clustered set of power grid faults is dynamically formed, providing basic data for the study of the evolution law of unconventional event modes. The multi-stage power grid operation mode data integration platform based on the above principles is of great significance for realizing the full cycle analysis of unconventional events and the application of emergency support technology.

关键词： Reactive power Correlation Disasters Data integration Energy Internet System integration Data collection Power grids Topology Load flow

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