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Progress in Electromagnetic research Symposium (PIERS)

作者： C. Zhou C. X. Yang M. S. Tong Shanghai Engineering Research Center of Intelligent Education and Bigdata Shanghai Normal University China Shanghai Institute of Intelligent Science and Technology Tongji University China

ISBN: (数字)9798350375909

ISBN: (纸本)9798350375916

Microwave imaging is a technique that uses information as a carrier. It enables non-contact acquisition of information from unknown targets, playing a pivotal role in various applications such as radar detection, medical imaging, and industrial inspection. However, practical applications often face challenges in meeting the requirements of traditional imaging algorithms due to limitations imposed by observation environments or economic constraints. Therefore, it is of great research value to explore how limited measurement data can be effectively utilized for reconstructing the target under test. Compressed sensing technology enables high-precision signal reconstruction with sampling frequencies lower than the Nyquist frequency, but its application scope is greatly restricted by the requirement for sparse target distribution measurements, particularly in non-uniform background imaging scenarios. In this study, we propose an inverse scattering method utilizing the total variation-based compressed sensing technique. And through-wall imaging scenes are chosen to validate the robustness of the algorithm. Firstly, by incorporating the gradient of the contrast function as a sparse prior, we reformulate the two-dimensional inverse scattering problem in a time-harmonic regime into an equivalent augmented Lagrange problem with the use of the first-order Born approximation. Subsequently, we construct a compressed sensing matrix. Then, we repeat the aforementioned steps and iteratively solve for the unknown total field and target to be reconstructed alternatively using the distorted Born iteration method framework until meeting certain convergence criteria. The proposed method effectively addresses the reconstruction problem of scattering targets with piecewise constant contrast, while remaining unaffected by non-uniform background. Numerical simulation results validate both the feasibility and efficiency of our proposed method.

关键词： Inverse problems Imaging Scattering Radar imaging Microwave theory and techniques Frequency measurement Sparse matrices

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Dynamic Event-Triggered Consensus on Matrix-Weighted Networks: Leadless Case 42

Dynamic Event-Triggered Consensus on Matrix-Weighted Network...

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42nd Chinese Control Conference, CCC 2023

作者： Dou, Lintao Wei, Haoyu Huang, Jian Pan, Lulu Shao, Haibin Li, Dewei College of Intelligent Science National University of Defense Technology Changsha410003 China Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Department of Automation Shanghai200240 China

ISBN: (纸本)9789887581543

This paper examines the event-triggered consensus of the multi-agent system on matrix-weighted networks, where the interdependencies among higher-dimensional states of neighboring agents are characterized by matrix-weighted edges in the network. Specifically, a novel distributed dynamic event-triggered coordination strategy is proposed for this category of generalized networks, in which an auxiliary system is employed for each agent to dynamically adjust the triggering threshold, which plays an essential role in guaranteeing that the triggering time sequence does not exhibit Zeno behavior. Distributed event-triggered control protocols are proposed to guarantee leaderless consensus for multi-agent systems on matrix-weighted networks, respectively. Remarkably, the spectrum of matrix-valued weights is crucial in event-triggered mechanism design for matrix-weighted networks, generalizing those results only applicable for scalar-weighted networks. The proposed approach allows each agent to broadcast and receive information only at its triggering instants. Finally, simulation examples are provided to demonstrate the theoretical results. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Multi agent systems

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Targeted-tuning competitive acidic CO2RR via metalloid antagonism sites

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Materials Today 2025年 83卷 54-63页

作者： Sheng, Beibei Cao, Dengfeng Qi, Zhenghang Shou, Hongwei Xia, Yujian Su, Xiaozhi Chen, Shuangming Wu, Chuanqiang Liu, Hengjie Chimtali, Peter Joseph Chu, Yongheng Liu, Chongjing Wu, Xiaojun Song, Li National Synchrotron Radiation Laboratory CAS Center for Excellence in Nanoscience Key Laboratory of Precision and Intelligent Chemistry School of Nuclear Science and Technology University of Science and Technology of China Hefei230029 China SINOPEC Shanghai Research Institute of Petrochemical Technology Co. Ltd. Shanghai201208 China Engineering Laboratory of Chemical Resources Utilization in South Xinjiang of Xinjiang Production and Construction Corps College of Chemistry and Chemical Engineering Tarim University Alar843300 China School of Chemistry and Materials Science CAS Center for Excellence in Nanoscience and Synergetic Innovation of Quantum Information & Quantum Technology Hefei National Laboratory for Physical Sciences at the Microscale University of Science and Technology of China Hefei230026 China Advanced Light Source Lawrence Berkeley National Laboratory Berkeley CA94720 United States Shanghai Synchrotron Radiation Facility Shanghai Institute of Applied Physics Chinese Academy of Sciences Shanghai201204 China Information Materials and Intelligent Sensing Laboratory of Anhui Province Institutes of Physical Science and Information Technology Anhui University Hefei230601 China

To mitigate the high separation costs associated with conventional neutral/alkaline electrocatalysis for CO2 reduction reactions (CO2RR), acidic CO2RR offers economic advantages and improved efficiency in CO2 utilization. However, it typically involves the cleavage of M−H bonds at a relatively negative potential, leading to the predominant formation of H2 and poor HCOOH selectivity. Herein, we develop a facile solid-phase thermal diffusion approach to controllably synthesize a novel metalloid-metal single atom alloys (m-SAAs) electrocatalyst Te1Bi with unique metalloid antagonistic sites, thus enabling high-efficient acidic CO2-to-HCOOH conversion. Electrochemical test and operando synchrotron radiation multi-techniques (SRMS) characterization reveal that metalloid Te sites bring steric hindrance effect and blocks *H coupling. Furthermore, it actively adsorbs OH− species as a proton source, allowing for effective separation of protons and electrons in space. Thus, leading to enhanced hydrogenation in acidic CO2RR to produce HCOOH. The flow cell test results demonstrate that the carefully designed Te1Bi catalyst exhibits a milder reaction potential, along with higher HCOOH Faraday efficiency (∼94.5 %) and single-pass carbon efficiency (SPCE, ∼40 %) in acidic media. This work significantly expands the family of SAAs and offers a novel perspective to analyze the regulation of competitive reactions through site-specific modifications for industrial acidic CO2RR. © 2024 Elsevier Ltd

关键词： Synchrotron radiation

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From Unmanned Systems to Autonomous intelligent Systems

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engineering 2022年第5期8卷 16-19页

作者： Jie Chen Jian Sun Gang Wang Department of Control Science and Engineering Tongji UniversityShanghai 201804China Shanghai Research Institute for Intelligent Autonomous Systems Shanghai 200092China Key Lab of Intelligent Control and Decision of Complex Systems Beijing Institute of TechnologyBeijing 100081China Beijing Institute of Technology Chongqing Innovation Center Chongqing 401120China

*** Artificial intelligence(AI)is a rapidly growing field of technol-ogy,which“will enliven inert objects,much as electricity did more than a century *** that we formerly electrified will now cognitize”[1].AI advances are constantly pushing the frontier of what machines can *** attention is being placed on AI research,as well as its development and deployment by commer-cial investors,defense strategists,and policy makers[2].

关键词： frontier inert policy

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Multi-omics graph convolutional networks for digestive system tumour classification and early-late stage diagnosis

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CAAI Transactions on Intelligence technology 2024年第6期9卷 1572-1586页

作者： Lin Zhou Zhengzhi Zhu Hongbo Gao Chunyu Wang Muhammad Attique Khan Mati Ullah Siffat Ullah Khan School of Information Science and Technology University of Science and Technology of ChinaHefeiAnhuiChina Anhui Engineering Research Center on Information Fusion and Control of Intelligent Robot WuhuAnhuiChina Department of Breast Center West District of The Affiliated Hospital of University of Science and Technology of ChinaDivision of Life Sciences and MedicineUniversity of Science and Technology of ChinaHefeiAnhuiChina Institute of Advanced Technology University of Science and Technology of ChinaHefeiAnhuiChina School of Electrical and Electronic Engineering Nanyang Technological UniversitySingaporeSingapore School of Biological and Environmental Engineering Chaohu UniversityChaohu Regional Collaborative Technology Service Center for Rural RevitalizationHefeiChina Department of Artificial Intelligence College of Computer Engineering and SciencePrince Mohammad Bin Fahd UniversityAl-KhobarSaudi Arabia School of Automation Northwestern Polytechnical UniversityXi'anShaanxiChina Institute of Engineering and Computing Science University of Science and Technology of BannuKPKBannuPakistan

The prevalence of digestive system tumours(DST)poses a significant challenge in the global crusade against *** neoplasms constitute 20%of all documented cancer diagnoses and contribute to 22.5%of cancer-related *** accurate diagnosis of DST is paramount for vigilant patient monitoring and the judicious selection of optimal *** this challenge,the authors introduce a novel methodology,denominated as the Multi-omics Graph Transformer Convolutional Network(MGTCN).This innovative approach aims to discern various DST tumour types and proficiently discern between early-late stage tumours,ensuring a high degree of *** MGTCN model incorporates the Graph Transformer Layer framework to meticulously transform the multi-omics adjacency matrix,thereby illuminating potential associations among diverse samples.A rigorous experimental evaluation was undertaken on the DST dataset from The Cancer Genome Atlas to scrutinise the efficacy of the MGTCN *** outcomes unequivocally underscore the efficiency and precision of MGTCN in diagnosing diverse DST tumour types and successfully discriminating between early-late stage DST *** source code for this groundbreaking study is readily accessible for download at https://***/bigone1/MGTCN.

关键词： digestive system tumors early-late stage multi-omics tumor types

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Active learning attraction basins of dynamical system

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Chinese Physics B 2025年第5期 118-126页

作者：曹小尾茹小磊严钢 MOE Key Laboratory of Advanced Micro-Structured Materials and School of Physical Science and Engineering Tongji University National Key Laboratory of Autonomous Intelligent Unmanned Systems MOE Frontiers Science Center for Intelligent Autonomous Systemsand Shanghai Research Institute of Intelligence Science and Technology Tongji University

Dynamical systems often exhibit multiple attractors representing significantly different functioning conditions. A global map of attraction basins can offer valuable guidance for stabilizing or transitioning system states. Such a map can be constructed without prior system knowledge by identifying attractors across a sufficient number of points in the state space. However, determining the attractor for each initial state can be a laborious task. Here, we tackle the challenge of reconstructing attraction basins using as few initial points as possible. In each iteration of our approach, informative points are selected through random seeding and are driven along the current classification boundary, promoting the eventual selection of points that are both diverse and enlightening. The results across various experimental dynamical systems demonstrate that our approach requires fewer points than baseline methods while achieving comparable mapping ***, the reconstructed map allows us to accurately estimate the minimum escape distance required to transition the system state to a target basin.

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"Optical Clone" Holographic Three-dimensional Video-rate Display

"Optical Clone" Holographic Three-dimensional Video-rate Dis...

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International Conference on Display technology, 2024

作者： Gao, Hongyue Liu, Jicheng Fu, Xinge Hu, Jinxuan Zhu, Hailei Xu, Yaguang Liu, Huimin Chen, Chengwei Yang, Ding Chen, Yanni Zhou, Yucong Wang, Xinglin Guo, Yiren Shen, Ziyi Multi-dimensional Spatial Display and Intelligent Manufacturing Equipment Research Center School of Mechatronic Engineering and Automation Shanghai University Shanghai 200072 China Suzhou GoldShine Photoelectric Technology Co. Ltd Suzhou China Suzhou GoldenLion Photoelectric Technology Co. Ltd Suzhou China

"Optical clone" represents an advanced conceptualization of traditional holography, transcending the dichotomy between reality and virtuality by replicating authentic three-dimensional optical images for display purposes. Holographic true three-dimensional display technology is thus acknowledged globally as a pinnacle future display modality. The systems demonstrated in this paper are flat-panel "optical clone" holographic true three-dimensional display and the space floating holographic three-dimensional display system, which surmounted the significant challenge of substituting dual-beam coupling with single-beam direct writing in hologram inscription systems, paving the way for compatibility with existing two-dimensional display technologies. © 2024 John Wiley and Sons Inc. All rights reserved.

关键词： Geometrical optics

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Hybrid Data-Mechanism Modeling for Tire Response Dynamics in Estimating Tire-Road Friction Coefficient

Hybrid Data-Mechanism Modeling for Tire Response Dynamics in...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Lu, Jiaxing Cheng, Liangzhu Liang, Jun Wang, Nian Li, Bin Zhang, Lin Chen, Hong Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai200092 China Dongfeng Automotive Technology Center Wuhan China Dongfeng Motor Corporation Wuhan China College of Electronic and Information Engineering Tongji University Shanghai201804 China School of Automotive Studies Tongji University Shanghai201804 China

ISBN: (纸本)9781665410205

Advanced control and safety systems are crucial for electric vehicles, and the accurate estimation of the tire-road friction coefficient (TRFC) is crucial for developing effective safety control strategies. The hybrid data-mechanism model (HDMM), introduced in this paper, addresses the performance challenges posed by the inaccuracies of physical models and the limited interpretability of data-driven models in tire force estimation for TRFC estimation. Tire dynamics often exhibit transient responses, while mechanism-based models(MBM) typically reflect steady-state characteristics. Neglecting transient characteristics leads to a decrease in model accuracy. A neural network is used to learn the transient response characteristics of tire dynamics. These characteristics are then integrated with the steady-state tire forces from MBM to estimate the lateral and vertical forces acting on the wheel. The estimated tire forces serve as virtual measurements to calibrate parameters in the TRFC estimator, based on the Unscented Kalman Filter (UKF). During real-world vehicle tests, the proposed method reduced the Mean Error (ME) in lateral and vertical forces by 1271.85 N and 996.7 N, respectively, compared to the estimated tire forces from MBM. Additionally, the estimated TRFC converged to the reference value approximately 40ms earlier than the result from the MBM, with an estimated deviation within 0.1. © 2024 IEEE.

关键词： Transient analysis

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Out-of-Distribution Fault Diagnosis of Industrial Cyber-Physical Systems Based on Orthogonal Anchor Clustering With Adaptive Balance

IEEE Transactions on Industrial Cyber-Physical Systems

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IEEE Transactions on Industrial Cyber-Physical Systems 2025年 3卷 48-60页

作者： Liu, Ruonan Hu, Puyuan Zhao, Siheng Sun, Zhijian Han, Te Pang, Zhibo Zhang, Weidong Shanghai Jiao Tong University Department of Automation Shanghai200240 China National Key Laboratory of Marine Engine Science and Technology Shanghai201108 China Crossocean of Suzhou Technology Suzhou215121 China Beijing Institute of Technology Center for Energy and Environmental Policy Research School of Management Beijing100081 China ABB Corporate Research Sweden Department of Automation Technology Vasteras722 26 Sweden KTH Royal Institute of Technology Department of Intelligent Systems Stockholm114 28 Sweden Henan University Henan Key Laboratory of Big Data Analysis and Processing School of Computer and Information Engineering Kaifeng475001 China Shanghai Jiaotong University Department of Automation Shanghai200240 China

Given the critical role of rotating machinery in industrial cyber-physical systems (ICPS), ensuring their reliable operation is essential for the stability and safety of ICPS. Deep neural networks have demonstrated competitive results for intelligent fault diagnosis, which are usually trained via the historical data of all fault modes. However, in real engineering, it is usually difficult to collect samples and exhaust all failures during the training stage. As a result, out-of-distribution fault diagnosis (OOD-FD) becomes a more realistic problem that requires the methods to not only accurately diagnose the known faults, but also effectively recognize unknown ones. Therefore, a novel orthogonal anchor clustering with focal attention (FA-OAC) is proposed in this paper for OOD-FD. Firstly, an orthogonal anchor clustering (OAC) algorithm is proposed to fix the class center of each fault mode orthogonally and distinguish the known and unknown faults at the class level. Then, because the identifiability of different fault modes changes a lot in OOD-FD, the focal attention mechanism is applied to dynamically adjust the attention to different fault modes according to the distance loss of OAC, thus addressing the identifiability imbalance problem. To verify the effectiveness of the proposed method, different OOD-FD tasks are designed based on two rotating machinery datasets. The experimental results and comparison with state-of-the-art fault diagnosis methods have demonstrated that the proposed method has improved the OOD-FD performance greatly and therefore provides an effective tool in real engineering. © 2023 IEEE.

关键词： Rotating machinery

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Data augmentation method for light guide plate based on improved CycleGAN

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Optoelectronics Letters 2024年

作者： GONG Yefei YAN Chao XIAO Ming LU Mingli GAO Hua School of Electrical and Automation Engineering，Changshu Institute of Technology Jiangsu Engineering Research Center of Industrial Robot Complex Process Intelligent Control School of Electrical Engineering， Yancheng Institute of Technology Wuxi Novo Automation Technology Corp

An improved CycleGAN network method for defect data augmentation based on feature fusion and self attention residual module is proposed to address the insufficiency of defect sample data for light guide plate(LGP) in production， as well as the problem of minor defects. Two optimizations are made to the generator of CycleGAN: 1) Fusion of low resolution features obtained from partial up-sampling and down-sampling with high-resolution features. 2) Combine self attention mechanism with residual network structure to replace the original residual module. Qualitative and quantitative experiments were conducted to compare different data augmentation methods， and the results showed that the defect images of the LGP generated by the improved network were more realistic， and the accuracy of the YOLOv5 detection network for the LGP was improved by 5.6%， proving the effectiveness and accuracy of the proposed method.

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