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Robust tensor decomposition via orientation invariant tubal nuclear norms

Science China(Technological Sciences) 2022年第6期65卷 1300-1317页

作者： WANG AnDong ZHAO QiBin JIN Zhong LI Chao ZHOU GuoXu School of Automation Guangdong University of TechnologyGuangzhou 510006China School of Computer Science and Engineering Nanjing University of Science and TechnologyNanjing 210094China Tensor Learning Team RIKEN Center for Advanced Intelligence ProjectTokyo 103-0027Japan Key Laboratory of Intelligent Perception and System for High-Dimensional Information Ministry of EducationNanjing 210094China Key Laboratory of Intelligent Detection and the Internet of Things in Manufacturing Ministry of EducationGuangzhou 510006China

Aiming at recovering an unknown tensor(i.e.,multi-way array)corrupted by both sparse outliers and dense noises,robust tensor decomposition(RTD)serves as a powerful pre-processing tool for subsequent tasks like classification and target detection in many computer vision and machine learning ***,tubal nuclear norm(TNN)based optimization is proposed with superior performance as compared with other tensorial nuclear norms for tensor ***,one major limitation is its orientation sensitivity due to low-rankness strictly defined along tubal orientation and it cannot simultaneously model spectral low-rankness in multiple *** this end,we introduce two new tensor norms called OITNN-O and OITNN-L to exploit multi-orientational spectral low-rankness for an arbitrary K-way(K≥3)*** further formulate two RTD models via the proposed norms and develop two algorithms as the ***,we establish non-asymptotic error bounds which can predict the scaling behavior of the estimation *** on real-world datasets demonstrate the superiority and effectiveness of the proposed norms.

关键词： tensor recovery t-SVD estimation error tensor completion

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Adaptive Neural Consensus Tracking Control for Nonlinear Multiagent systems with Dead Zone and Sensor Faults 42

Adaptive Neural Consensus Tracking Control for Nonlinear Mul...

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42nd Chinese Control Conference, CCC 2023

作者： Huang, Chengjie Chen, Ci Liu, Zhi Li, Zhenni Guangdong University of Technology Guangzhou510006 China Guangdong Key Laboratory of IoT Information Technology Guangzhou510006 China 111 Center for Intelligent Batch Manufacturing Based on IoT Technology Guangzhou510006 China Guangdong-HongKong-Macao Joint Laboratory for Smart Discrete Manufacturing Guangzhou510006 China Key Laboratory of Intelligent Information Processing and System Integration of IoT Ministry of Education Guangzhou510006 China Key Laboratory of Intelligent Detection and the Internet of Things in Manufacturing Ministry of Education Guangzhou510006 China

ISBN: (纸本)9789887581543

In this paper, an adaptive neural tracking control design is investigated for uncertain multiagent systems (MASs) with actuator dead zone and sensor faults. The adaptive control technique based on neural networks is employed to handle the uncertainty in the systems, which, however, results in a bounded tracking error from most existing works. To achieve the asymptotic tracking performance, we proposed a direct adaptive strategy via the tuning function method. Technically, a Lyapunov function with a series of smooth functions is designed, which benefits proposing of an asymptotic controller. Then, under the framework of direct adaptive control, an inverse compensation scheme, as well as a fault-tolerant mechanism, are considered for disposing of the actuator dead zone and sensor failures. As a result, user-preset tracking performance is achieved and the system error in the MASs converges to a predefined range. An example in the simulation section illustrates the effectiveness of the proposed method. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Multi agent systems

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A Topic-Aware Graph-Based Neural Network for User Interest Summarization and Item Recommendation in Social Media 28th

A Topic-Aware Graph-Based Neural Network for User Interest ...

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28th International Conference on Database systems for Advanced Applications, DASFAA 2023

作者： Chen, Junyang Fan, Ge Gong, Zhiguo Li, Xueliang Leung, Victor C. M. Wang, Mengzhu Yang, Ming College of Computer Science and Software Engineering Shenzhen University Shenzhen China Shenzhen China Tencent Inc. Shenzhen China State Key Laboratory of Internet of Things for Smart City Department of Computer Information Science University of Macau China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen China

ISBN: (纸本)9783031306716

User-generated content is daily produced in social media, as such user interest summarization is critical to distill salient information from massive information. While the interested messages (e.g., tags or posts) from a single user are usually sparse becoming a bottleneck for existing methods, we propose a topic-aware graph-based neural interest summarization method (UGraphNet), enhancing user semantic mining by unearthing potential user relations and jointly learning the latent topic representations of posts that facilitates user interest learning. Experiments on two datasets collected from well-known social media platforms demonstrate the superior performance of our model in the tasks of user interest summarization and item recommendation. Further discussions also show that exploiting the latent topic representations and user relations are conductive to the user automatic language understanding. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Graphic methods

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Facile assembly of flexible,stretchable and attachable symmetric microsupercapacitors with wide working voltage windows and favorable durability

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Microsystems & Nanoengineering 2024年第4期10卷 297-304页

作者： Xiangguang Han Xiaoyu Wu Libo Zhao Min Li Chen Jia Zhikang Li Jiaqi Xie Guoxi Luo Ping Yang Rabah Boukherroub Yurdanur Türker Mert UmutÖzkaynak Koray Bahadır Dönmez State Key Laboratory for Manufacturing Systems Engineering International Joint Laboratory for Micro/Nano Manufacturing and Measurement TechnologiesXi’an Jiaotong University(Yantai)Research Institute for Intelligent Sensing Technology and SystemXi’an Jiaotong UniversityXi’an 710049China School of Instrument Science and Technology Xi’an Jiaotong UniversityXi’an 710049China Shandong Laboratory of Advanced Materials and Green Manufacturing at Yantai Yantai 264000China School of Mechanical Engineering Xi’an Jiaotong UniversityXi’anShaanxi 710049China Chongqing Key Laboratory of Micro-Nano Systems and Intelligent Sensing Chongqing Academician WorkstationChongqing 2011 Collaborative Innovation Center of Micro/Nano Sensing and Intelligent Ecological Internet of ThingsChongqing Technology and Business UniversityNan’an DistrictChongqing 400067China Univ.Lille CNRSUniv.Polytechnique Hauts-de-FranceUMR 8520-IEMNF-59000 LilleFrance Sabanci University Nanotechnology Research and Application Center(SUNUM) IstanbulTurkey Department of Materials Science and Engineering Istanbul Technical UniversityIstanbulTurkey

With the increasing development of intelligent robots and wearable electronics,the demand for high-performance flexible energy storage devices is drastically *** this study,flexible symmetric microsupercapacitors(MSCs)that could operate in a wide working voltage window were developed by combining laser-direct-writing graphene(LG)electrodes with a phosphoric acid-nonionic surfactant liquid crystal(PA-NI LC)gel *** increase the flexibility and enhance the conformal ability of the MSC devices to anisotropic surfaces,after the interdigitated LG formed on the polyimide(PI)film surface,the devices were further transferred onto a flexible,stretchable and transparent polydimethylsiloxane(PDMS)substrate;this substrate displayed favorable flexibility and mechanical characteristics in the bending ***,the electrochemical performances of the symmetric MSCs with various electrode widths(300,400,500 and 600μm)were *** findings revealed that symmetric MSC devices could operate in a large voltage range(0–1.5 V);additionally,the device with a 300μm electrode width(MSC-300)exhibited the largest areal capacitance of 2.3 mF cm^(−2)at 0.07 mA cm^(−2)and an areal(volumetric)energy density of 0.72μWh cm−2(0.36 mWh cm^(−3))at 55.07μWcm−2(27.54mWcm−3),along with favorable mechanical and cycling *** charging for~20 s,two MSC-300 devices connected in series could supply energy to a calculator to operate for~130 s,showing its practical application potential as an energy storage ***,the device displayed favorable reversibility,stability and *** 12 months of aging in air at room temperature,its electrochemical performance was not altered,and after charging-discharging measurements for 5000 cycles at 0.07 mA cm^(−2),~93.6%of the areal capacitance was still retained;these results demonstrated its practical long-term application potential as an energy storage device.

关键词： cycling durability electrode

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Influence of contact layer on the sulphur corrosion of copper conductors in power transformers

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High Voltage 2022年第1期7卷 176-184页

作者： Lijun Yang Dong Ding Yuan Yuan Sihang Gao Yuncai Lu State Key Laboratory of Power Transmission Equipment and System Security and New Technology Chongqing UniversityChongqingChina College of Material Science and Engineering Chongqing UniversityChongqingChina Key Laboratory of Industrial Internet of Things and Networked Control Ministry of EducationChongqing University of Posts and TelecommunicationsChongqingChina State Grid Jiangsu Electric Power Co. Ltd.Electric Power Research InstituteNanjingChina

Owing to the corrosive sulphides in the mineral insulating oil such as dibenzyl disul-phide(DBDS),copper windings in oil‐immersed transformers may suffer sulphur *** study investigates the influence of different contact conditions on the corrosion of copper conductors in ***‐immersed accelerated corrosion experiment was conducted on copper conductors with various contact materials and different layers of insulating *** surface micromorphology,deposition compo-nent and the potentiodynamic polarization characteristics of copper conductors were *** results show that copper with different contact materials suffer sulphur corrosion;conversely,bare copper rarely *** was also verified that the existence of a particular gap between copper and contact layer is a significant factor in sulphur corrosion by the formation of a concentration cell on the copper *** insu-lating paper wrapped around copper conductors does not increase the corrosion ten-dency of copper;however,it contributes to the formation of a region concentrated with DBDS,Cu^(2+),H^(+)by adsorption and impediment,which plays a key role in facilitating the sulphur corrosion of copper ***,sulphur corrosion can also occur on other metal parts in transformers when there is a particular gap on surfaces other than copper.

关键词： corrosion copper sulphur

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Multi-Access Edge Computing Empowered Integrated Hybrid Sensing and Communication: A Computation-Efficient Design

Multi-Access Edge Computing Empowered Integrated Hybrid Sens...

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Ubiquitous Communication (Ucom), International Conference on

作者： Chenglong Dou Xumin Huang Yuan Wu Liping Qian Tony Q. S. Quek State Key Laboratory of Internet of Things for Smart City University of Macau Macau China Information Engineering Zhejiang University of Technology Hangzhou China Information System Technology and Design Singapore University of Technology and Design Singapore

ISBN: (数字)9798350374216

ISBN: (纸本)9798350374223

Integrated sensing and communication (ISAC) system has been emerged as a crucial paradigm for addressing the growing demand of emerging wireless applications that require both ultra-reliable data transmission and high-precision sensing. However, due to the limited computation capability of ISAC devices, the large amount of collected sensing data is difficult to be timely processed. In this paper, we consider that the ISAC device can offload the sensing data to a group edge helper nodes via multi-access edge computing to improve the efficiency of sensing data processing. We propose a multi-access edge computing empowered ISAC with hybrid active and passive sensing, in which the ISAC device can perform passive sensing through the sensing reflected signal from the edge helper nodes while performing active sensing. To investigate this problem, we formulate a joint optimization of the transmit beamforming for active sensing, passive sensing and offloading, as well as the computation rates of both the ISAC device and the edge helper nodes, with the objective of maximizing the total computation rates for the sensing data. Despite the non-convexity of the formulated problem, we propose an efficient algorithm to obtain its solutions. Simulation results validate the performance advantages of our multi-access edge computing empowered integrated hybrid sensing and communication.

关键词： Performance evaluation Wireless communication Wireless sensor networks Multi-access edge computing Array signal processing Simulation Large language models Signal processing algorithms Integrated sensing and communication Optimization

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Improving Urban Canyons Based on a Graph Transformer

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Navigation, Journal of the Institute of Navigation 2024年第4期71卷

作者： Zheng, Shaolong Zeng, Kungan Li, Zhenni Wang, Qianming Xie, Kan Liu, Ming Xie, Shengli School of Automation Guangdong University of Technology Guangzhou China Guangdong–HongKong–Macao Joint Laboratory for Smart Discrete Manufacturing Guangzhou China 111 Center for Intelligent Batch Manufacturing Based on Internet of Things Technology Guangzhou China Techtotop Microelectronics Technology Co. Ltd Guangzhou China Department of Electronic and Computer Engineering Hong Kong University of Science and Technology China Key Laboratory of Intelligent Detection and the Internet of Things in Manufacturing Guangzhou China Guangdong Provincial Key Laboratory of Intelligent Systems and Optimization Integration Guangzhou China

Signals from global navigation satellite systems (GNSSs) in urban areas suffer from serious multipath errors caused by building blockages and reflections. The use of deep neural networks offers great potential for predicting and eliminating com-plex multipath/non-line-of-sight (NLOS) errors. However, existing methods for predicting the original signals face two remaining challenges. The first challenge is an inability to effectively exploit irregular GNSS measurement data caused by an inconsistent number of visible satellites in different epochs. The second challenge is degradation in the generalization performance of the multipath/NLOS prediction model when using data collected from different locations and periods. To address these challenges, this paper proposes a novel graph transformer neural network (GTNN) for predicting satellite visibility that effectively learns environment representations from irregular GNSS measurements to both alleviate multipath interference and improve the generalization performance of the multipath prediction model. To learn from irregular GNSS measurements, a sky satellite graph is constructed as input to a graph neural network by using satellites captured in the same epoch, which can represent the spatial relationships between satellites and enable the model to learn satellite-related features sufficiently well. To improve the generalization ability of our multipath prediction model, a multihead attention mechanism is introduced to aggregate satellite node information by computing the correlation between satellites to extract the environment representation around the receiver. Based on the constructed sky satellite graph and the multihead attention mechanism, our novel GTNN for predicting satellite visibility can not only handle irregular GNSS measurements but can also learn an environment representation via graph attention. Comparative experiments were conducted on real-world GNSS measurement data in urban areas, demonstrating that

关键词： Graph neural networks

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Meta-analysis in the production chain of aquaculture: A review

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Information Processing in Agriculture 2022年第4期9卷 586-598页

作者： Guanghui Yu Chunhong Liu Yingying Zheng Yingyi Chen Daoliang Li Wei Qin National Innovation Center for Digital Fishery China Agricultural UniversityChina Beijing Engineering and Technology Research Centre for Internet of Things in Agriculture China Agriculture University Beijing 100083China Precision Agricultural Technology Integration Research Base(Fishery) Ministry of Agriculture and Rural AffairsChina Key Laboratory of Agricultural Information Acquisition Technology Ministry of AgricultureChina Agriculture UniversityBeijing 100083China College of Information and Electrical Engineering China Agricultural UniversityBeijing 100083China Biological Engineering Utah State UniversityLoganUT 84341United States

Meta-analysis is a statistical analysis of the data obtained from multiple studies and pro-vides a quantitative synthesis of research *** can be a key tool for facilitating rapid progress in aquaculture by quantifying what is known and identifying what is not yet ***,due to the complexity of the environment and problems associated with the use of model in aquaculture,it remain few guidelines for the design,implementation or interpretation of meta-analysis in the field of ***,we first briefly reviewed the history of meta-analysis,then summarized the applications of meta-analysis in terms of major procedures,standards,and ***,we critically reviewed the results of meta-analysis studies in the production chain of aquaculture and identified the potentials for improving yield in both quantity and ***,there is a large room for improving yield along the production *** contributions can be found in breeding,feed,and farm *** example,improving breeding can increase yield by 5.6%to 49%,depending on fish species and type of *** study revealed large potentials for improving yield in the production chain of aquaculture and summarized the application of meta-analysis in *** recommendations of standardizing and improving meta-analysis in aquaculture were proposed.

关键词： Aquaculture Quantitative analysis Meta-analysis Production

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RHNet: A Real-Time High-Resolution Network for Surface Defect Detection

RHNet: A Real-Time High-Resolution Network for Surface Defec...

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第43届中国控制会议

作者： Yijie Wang Zhigang Ren Jianpu Cai Zongze Wu Shengli Xie School of Automation Key Laboratory of Intelligent Information Processing and System Integration of IoT Ministry of EducationGuangdong University of Technology Guangdong-HongKong-Macao Joint Laboratory for Smart Discrete Manufacturing Guangdong University of Technology College of Mechatronics and Control Engineering Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ)Shenzhen University Key Laboratory of Intelligent Detection and The Internet of Things in Manufacturing (GDUT) Ministry of Education

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

In the industrial domain, surface defect detection after multiple processing steps is crucial for improving the outgoing quality of products. However, due to the characteristics of surface defects, such as low contrast, irregular shapes, small and elongated features, and significant noise. To address these issues, this paper proposes a novel real-time high-resolution network(RHNet). Unlike previous models, RHNet emphasizes the importance of modeling spatial information to capture small ***, the output feature maps of each module are maintained at 1/4 resolution of the original image. We introduce a short-term dual-branch module(SDBM) to handle real-time processing of high-resolution feature maps. Additionally, FPAPPM is proposed for swift extraction of deep information and multi-scale context. Through extensive experiments, we demonstrate that our proposed model exhibits robust defect modeling capabilities and detection performance while still meeting real-time requirements.

关键词： Surface defect inspection Anomaly detection Semantic segmentation Deep learning Pattern recognition

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Stackelberg-Game Computation Offloading Scheme for Parked Vehicle-Assisted VEC and Experiment Analysis

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-12页

作者： Liu, Chunhong Zhao, Mengdi Wang, Huaichen Cheng, Bo Liu, Jialei Yuan, Peiyan Engineering Lab of Intelligence Business & Internet of Things and School of Computer and Information Engineering Henan Normal University Xinxiang China State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China Hubei Key Laboratory of Power System Design and Test for Electrical Vehicle and School of Computer Engineering Hubei University of Arts and Science Xiangyang China

Vehicle edge computing (VEC) offers users low-latency and high-reliability services by using computational resources at the network's edge. Nevertheless, because of inadequate infrastructure and limited resources, computation-intensive and delay-sensitive vehicle applications cannot be performed efficiently at the edge. Therefore, several studies have used the idle resources of parked vehicles to assist in computation offloading. In this paper, we propose a parked vehicle-assisted vehicle edge computing architecture considering multi-agent collaboration, including intelligent vehicles and edge servers. Additionally, we propose a framework for a parallel internet of Vehicles (IoV) utilizing computational experiment. The service provider is assigned the role of owning VEC resources and recruiting parking vehicle resources. The model was constructed by using the resource consumption-service relationship of both offloading parties to ensure service quality. First, a Stackelberg game model was constructed based on the interaction between requesting vehicles and a service provider. The latter was the leader, and the requesting vehicles were the followers. The Nash equilibrium for optimal pricing and offloading allocations was attained and verified, and a distributed gradient-based equilibrium algorithm was designed to solve the Stackelberg game model and obtain the final decision through mutual communication. The method also protects the privacy of participants and respects the willingness of requesting vehicles to offload. Finally, the simulation experiments confirmed that the proposed algorithm can achieve game equilibrium. Furthermore, it outperformed state-of-the-art algorithms in improving the service provider's utility. IEEE

关键词： Vehicles

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