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25th IEEE China Conference on system Simulation Technology and its Application, CCSSTA 2024

作者： Huang, Jiahui Zheng, Xiangxiang Lv, Guodong Li, Xiaojing Wu, Guohua Xu, Liang Tianjin University of Technology Tianjin Key Laboratory of Complex System Control Theory and Application Tianjin China The First Affiliated Hospital of Xinjiang Medical University State Key Laboratory of Pathogenesis Prevention and Treatment of High Incidence Diseases in Central Asia Urumqi China Beijing University of Posts and Telecommunications School of Electronic Engineering Beijing China

ISBN: (纸本)9798350366600

Alveolar echinococcosis (AE) remains a serious worldwide public health problem as a very harmful human tapeworm disease. Rapid and accurate diagnosis of AE is crucial for treatment and postoperative recovery. This study explored the applicability of tissue surface Raman spectroscopy (SERS) combined with machine learning for rapid AE detection. Specifically, liver tissue section samples were obtained by creating an AE mouse model and SERS spectra were acquired. Five kinds of machine learning methods were used to construct AE diagnosis model, among which the linear kernel support vector machine (SVM) model had the best classification result, and the accuracy rate reached 95.7%. Then, the linear SVM model was subjected to feature significance analysis, which demonstrated that the biochemicals corresponding to the spectra of 641,716 and 1372 cm-1 might be potential biomarkers. Gaussian noise is further added to test the noise interference resistance of different machine learning algorithms, and it is found that SVM with Gaussian radial basis function (RBF) kernel function has better noise interference resistance. The results show that tissue SERS spectroscopy combined with SVM algorithm for rapid detection of AE has a promising application. © 2024 IEEE.

关键词： Raman scattering

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Trajectory-prediction-based Dynamic Tracking of a UGV to a Moving Target under Multi-disturbed Conditions

Trajectory-prediction-based Dynamic Tracking of a UGV to a M...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Jinge Si Bin Li Yongkang Xu Liang Wang Chencheng Deng Shoukun Wang Junzheng Wang State Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology School of Automation Beijing China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Tracking dynamic targets poses a significant challenge for Unmanned Ground Vehicles (UGVs). Existing methods often lack research on multi-disturbed conditions. To address this issue, we propose a trajectory-prediction-based dynamic tracking scheme, which includes target localization, trajectory prediction, and UGV control. Firstly, an estimation algorithm based on the Extended Kalman Filter (EKF) is employed to mitigate noise and estimate the absolute states of the target accurately. To enhance robustness, we present an Adaptive Trajectory Prediction (ATP) algorithm based on prediction anchors. In this method, a quantization standard for trajectory disturbance is designed for adaptive control. Subsequently, we iteratively solve prediction anchor points based on two motion models to robustly predict the target trajectory even in the presence of unknown disturbances. Finally, the Linear Time-Varying Model Predictive control (LTV-MPC) is utilized in the UGV controller for dynamic tracking. Experimental results demonstrate that the ATP exhibits superior prediction robustness and accuracy in perturbed environments compared to other prediction algorithms. In addition, the proposed scheme effectively achieves dynamic tracking of the Unmanned Aerial Vehicle (UAV) by the UGV under multi-disturbed conditions. Specifically, when the target moves at a speed of 1.0 m/s, the UGV can maintain a tracking error within 0.346 m.

关键词： Target tracking Accuracy Heuristic algorithms Noise Prediction algorithms Autonomous aerial vehicles Robustness

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An IMU Error Correction Method Based on Multithreshold ZV Detection and SRCKF

An IMU Error Correction Method Based on Multithreshold ZV De...

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2023 International Conference on Cyber-Physical Social Intelligence, ICCSI 2023

作者： Luo, Jialiang Chen, Shichao Lv, Yisheng Sun, Wenqiao Yang, Fan Xu, Ruijie Institute of Automation Chinese Academy of Sciences School of Information Engineering China University of Geosciences Beijing The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems China Institute of Automation Chinese Academy of Sciences The Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited The State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Institute of Automation Chinese Academy of Sciences The State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Transportation and Economics Research Institute Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences College of Rail Transit Shan Dong JiaoTong University The State Key Laboratory for Management and Control of Complex System Jinan China The Hong Kong Polytechnic University Department of Aeronautical and Aviation Engineering Hong Kong Hong Kong

ISBN: (纸本)9798350312492

With the rapid development and widespread application of Inertial Measurement Units (IMUs), IMU-based human localization has become critically important in environments lacking Global Navigation Satellite systems (GNSS) signals. Methods such as UWB/WIFI and other anchor-based localization have been employed to enhance the positioning accuracy. However, these methods are susceptible to the environmental interference and increased costs. In contrast, SINS-based localization methods eliminate reliance on the external data. However, this method can suffer from drift errors due to cumulative integration errors. Inertial navigation error correction techniques like Zero Detection Update Technology (ZUPT) provide potential solutions to address drift errors. This paper proposes an error correction method based on the multithreshold zero-velocity detection and Square Root Cubature Kalman Filter (SRCKF) updates. Compared to the single fixed threshold detection, the multi-threshold zero-velocity detection reduces the likelihood of missed zero velocity detection and false alarms, providing accurate time intervals for error correction. Experimental results demonstrate that the SRCKF-based algorithm reduces position deviation to approximately 0.3146 meters, corresponding to an error ratio of1.14%. The proposed method enables cost-effective and accurate pedestrian localization, driving advancements in the field. © 2023 IEEE.

关键词： Cost effectiveness

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Towards Intelligent and Trustworthy Crowdsourcing systems with Cyber-physical Social Intelligence via Retrieval-augmented Generation

Towards Intelligent and Trustworthy Crowdsourcing Systems wi...

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2024 International Conference on Cyber-Physical Social Intelligence, ICCSI 2024

作者： Yang, Jing Wang, Xingxia Ni, Qinghua Liu, Yuhang Wang, Jing Wang, Fei-Yue Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Beijing100190 China Macau University of Science and Technology Faculty of Innovation Engineering 999078 China Macau University of Science and Technology 999078 China Chinese Academy of Sciences State Key Laboratory for Management and Control of Complex Systems Beijing100190 China

ISBN: (纸本)9798350376739

In recent years, crowdsourcing systems that tackle complex tasks through the collective efforts of many individuals have garnered substantial attention. However, the existing crowd-sourcing systems face some challenges such as overreliance on human experience and effort, information overload, and risks of privacy breaches. To overcome these challenges, this paper proposes an intelligent and trustworthy crowdsourcing frame-work based on blockchain and retrieval-augmented generation. The framework centers around foundational models to integrate the three distinct and sequentially interdependent phases: task decomposition, task allocation or recommendation, and task execution, enabling the automatic provision of a personalized, comfortable, and efficient user experience. Blockchain and smart contracts are utilized to protect user privacy and interests without leaning on any third trusted authority. Additionally, the operational process of the framework is explained and validated by taking printed circuit board design and manufacturing as a case study and ChatGPT as its generator. © 2024 IEEE.

关键词： Embedded systems

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The engineering of circular causality for specialization and design of complex systems:cad2CAS and casCAD2

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Frontiers of Information Technology & Electronic Engineering 2024年第2期25卷 323-332页

作者： Xiaolong LIANG Rui QIN Juanjuan LI Fei-Yue WANG Faculty of Innovation Engineering Macao University of Science and TechnologyMacao999078China State Key Laboratory of Multimodal Artificial Intelligence Systems Chinese Academy of SciencesBeijing100190China The State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing100190China

The emergence of decentralized autonomous organizations and operations(DAOs),equipped with innovative mechanisms,enables new possibilities for transforming traditional social collaborative *** are the underlying drive... 详细信息

关键词： complexity. circular equipped

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Deep Reinforcement Learning or Lyapunov Analysis?A Preliminary Comparative Study on Event-Triggered Optimal control

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IEEE/CAA Journal of Automatica Sinica 2024年第7期11卷 1702-1704页

作者： Jingwei Lu Lefei Li Qinglai Wei Fei-Yue Wang IEEE the Department of Industrial Engineering Tsinghua UniversityBeijing 100084China The State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China

Dear Editor,This letter develops a novel method to implement event-triggered optimal control(ETOC) for discrete-time nonlinear systems using parallel control and deep reinforcement learning(DRL), referred to as Deep-ETOC. The developed Deep-ETOC method introduces the communication cost into the performance index through parallel control, so that the developed method enables control systems to learn ETOC policies directly without triggering conditions.

关键词： Deep letter enable

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Optimization of Population-Level Testing,Contact Tracing,and Isolation in Emerging COVID-19 Outbreaks:a Mathematical Modeling Study—Tonghua City and Beijing Municipality,China,2021–2022

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China CDC weekly 2023年第4期5卷 82-89,I0010-I0015页

作者： Zengmiao Wang Ruixue Wang Peiyi Wu Bingying Li Yidan Li Yonghong Liu Xiaoli Wang Peng Yang Huaiyu Tian State Key Laboratory of Remote Sensing Science Center for Global Change and Public HealthCollege of Global Change and Earth System ScienceBeijing Normal UniversityBeijingChina School of National Safety and Emergency Management Beijing Normal UniversityBeijingChina Beijing Center for Disease Prevention and Control BeijingChina

Introduction:The transmissibility of the severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)Omicron variant poses challenges for the existing measures containing the virus in *** response,this study investigates the effectiveness of population-level testing(PLT)and contact tracing(CT)to help curb coronavirus disease 2019(COVID-19)resurgences in ***:Two transmission dynamic models(*** and without age structure)were developed to evaluate the effectiveness of PLT and *** simulations were conducted to optimize PLT and CT strategies for COVID-19 control and ***:Urban Omicron resurgences can be controlled by multiple rounds of PLT,supplemented by CT—as long as testing is *** study also evaluated the time needed to detect COVID-19 cases for surveillance under different routine testing *** results show that there is a 90%probability of detecting COVID-19 cases within 3 days through daily ***,it takes around 7 days to detect COVID-19 cases at a 90%probability level if biweekly testing is *** testing applied to the age group 21–60 for COVID-19 surveillance would achieve similar performance to that applied to all ***:Our analysis evaluates potential PLT and CT strategies for COVID-19 control and surveillance.

关键词： testing Mathematical Population

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MRO Configuration management for complex Products

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Journal of systems Science and systems Engineering 2022年第3期31卷 359-380页

作者： Chunliu Zhou Lian Qi Xiaobing Liu Hongguang Bo Key Laboratory of Multidisciplinary Management and Control of Complex Systems of Anhui Higher Education Institutes Anhui University of TechnologyMaanshan 243002China School of Management Science and Engineering Anhui University of TechnologyMaanshan 243032China Rutgers Business School RutgersThe State University of New JerseyPiscatawayNJ 08854United State School of Economics and Management Dalian University of TechnologyDalian 116023China

Configuration management(CM)is an effective method for data modeling and change management in product development,but the study of how it can be adapted for complex product maintenance,repair and overhaul(MRO)has thus far been *** propositions are put forward on the basis of a literature review and verified by a case of a high-speed train MRO *** findings show that CM can be used in MRO data management with adjustments in its ***,MRO-CM planning considers both multistage service and single-stage service to keep data consistent and ***,MRO data integration with the design/production phase should be considered during configuration ***,baselines and change rules are developed for change ***,status accounting and auditing can be repeatedly used in MRO data management.A systematic MRO-CM framework is generated to assist MRO practitioners in understanding the relationships among different MRO-CM *** paper contributes to expanding the theory of CM in MRO for complex products and provides an effective method for managing MRO data from systematic engineering insights.

关键词： Configuration management MRO Service data management case study

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Deep Learning-based Moving Object Segmentation:Recent Progress and Research Prospects

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Machine Intelligence Research 2023年第3期20卷 335-369页

作者： Rui Jiang Ruixiang Zhu Hu Su Yinlin Li Yuan Xie Wei Zou College of Information Engineering Shanghai Maritime UniversityShanghai201306China School of Computer Science and Technology East China Normal UniversityShanghai200062China Research Center of Precision Sensing and Control Institute of AutomationChinese Academy of SciencesBeijing100190China State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing100190China

Moving object segmentation(MOS),aiming at segmenting moving objects from video frames,is an important and challenging task in computer vision and with various *** the development of deep learning(DL),MOS has also entered the era of deep models toward spatiotemporal feature *** paper aims to provide the latest review of recent DL-based MOS methods proposed during the past three ***,we present a more up-to-date categorization based on model characteristics,then compare and discuss each category from feature learning(FL),and model training and evaluation *** FL,the methods reviewed are divided into three types:spatial FL,temporal FL,and spatiotemporal FL,then analyzed from input and model architectures aspects,three input types,and four typical preprocessing subnetworks are *** terms of training,we discuss ideas for enhancing model *** terms of evaluation,based on a previous categorization of scene dependent evaluation and scene independent evaluation,and combined with whether used videos are recorded with static or moving cameras,we further provide four subdivided evaluation setups and analyze that of reviewed *** also show performance comparisons of some reviewed MOS methods and analyze the advantages and disadvantages of reviewed MOS methods in terms of ***,based on the above comparisons and discussions,we present research prospects and future directions.

关键词： Moving object segmentation(MOS) change detection background subtraction deep learning(DL) video understanding

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Line Feature Based Visual Servo control with TDE for Underwater Vehicle Manipulator systems Target Grasping

Line Feature Based Visual Servo Control with TDE for Underwa...

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IEEE International Conference on Unmanned systems (ICUS)

作者： Yunfei Zhang Xinyu Bian Yize Sun Zongyu Zhang Hai Huang Xu Yang National Key Laboratory of Autonomous Marine Vehicle Technology Harbin Engineering University Harbin China State Key Laboratory of Management and Control for Complex System Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (数字)9798350384185

ISBN: (纸本)9798350384192

Underwater vehicle manipulator systems (UVMSs) is becoming a research hotspot in the field of marine intelligent equipment. Introducing visual feedback equipped with cameras in the loop to guide UVMS to complete the grasping has comprehensive advantages of response speed, work efficiency and intelligence. In this paper, mapping between the feature error and the motion of the UVMS generalized degrees of freedom is established to realize the suspended grasping under the coordinated motion of the vehicle body and the manipulator. Then, a UVMS motion control algorithm based on time delay estimation (TDE) is constructed for visual servo autonomous grasping process, the TDE of which is used to estimate and compensate the lumped interference in real time. The Lyapunov theory is applied to analyze its stability and its control performance is verified through simulation experiments. The simulation results shew the effectiveness of the proposed visual servo control with TED method based on line features.

关键词： Visualization Heuristic algorithms Dynamics Estimation Grasping Stability analysis Servomotors Vehicle dynamics Underwater vehicles Manipulator dynamics

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