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4th IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2024

作者： Yue, Zhijian Shen, Zhen Dong, Xiangyang Fang, Qihang Wang, Weixing Dong, Xisong Xiong, Gang Wang, Fei-Yue University of Chinese Academy of Sciences School of Artificial Intelligence Beijing100049 China Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Beijing100190 China Qingdao Academy of Intelligent Industries Intelligent Manufacturing Center Qingdao266109 China Chinese Academy of Sciences Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Dongguan523808 China Chinese Academy of Sciences State Key Laboratory for Management and Control for Complex Systems Institute of Automation Beijing100190 China

ISBN: (纸本)9798350349252

With the development of continuous fiber-reinforced composites (CFRCs) 3D printing technology, timely, efficient and accurate detection of fiber path defects is essential for ensuring product quality and performance. However, challenges still need to be addressed in this field, such as inadequate training data coverage and the complexity of fiber path structures. These factors hinder the capability of traditional methods to accurately assess the status of printed products. Therefore, developing accurate and robust fiber path defect detection techniques is crucial for CFRCs 3D printing technology. In this paper, we propose a precise detection method for fiber path defects in CFRCs 3D printing using the YOLOv7 object detection model combined with a Squeeze-and-Excitation (SE) attention mechanism. By introducing the SE attention mechanism, we enhance the perception capability of the YOLOv7 model for crucial features, thereby improving the accuracy of fiber path defect detection. The experimental results show that the YOLOv7 model, when augmented with an attention mechanism, achieves an average accuracy of 93.9% in identifying fiber path defects during the printing process. Compared to models without this attention mechanism, the results show that there is 10.7% increase, with a notably enhanced learning capacity during the training phase, which substantiates the efficacy and practicality of the proposed approach. © 2024 IEEE.

关键词： Fiber reinforced plastics

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Vehicle Motion Prediction at Intersections Based on the Turning Intention and Prior Trajectories Model

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自动化学报（英文版） 2021年第10期8卷 1657-1666页

作者： Ting Zhang Wenjie Song Mengyin Fu Yi Yang Meiling Wang State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of TechnologyBeijing 100081 Nanjing University of Science and Technology Nanjing 210014China

Intersections are quite important and complex traffic scenarios, where the future motion of surrounding vehicles is an indispensable reference factor for the decision-making or path planning of autonomous vehicles. Considering that the motion trajectory of a vehicle at an intersection partly obeys the statistical law of historical data once its driving intention is determined, this paper proposes a long short-term memory based (LSTM-based) framework that combines intention prediction and trajectory prediction together. First, we build an intersection prior trajectories model (IPTM) by clustering and statistically analyzing a large number of prior traffic flow trajectories. The prior trajectories model with fitted probabilistic density is used to approximate the distribution of the predicted trajectory, and also serves as a reference for credibility evaluation. Second, we conduct the intention prediction through another LSTM model and regard it as a crucial cue for a trajectory forecast at the early stage. Furthermore, the predicted intention is also a key that is associated with the prior trajectories model. The proposed framework is validated on two publically released datasets, next generation simulation (NGSIM) and INTERACTION. Compared with other prediction methods, our framework is able to sample a trajectory from the estimated distribution, with its accuracy improved by about 20％. Finally, the credibility evaluation, which is based on the prior trajectories model, makes the framework more practical in the real-world applications.

关键词： Autonomous vehicle intersection motion prediction prior trajectories model turning intention

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Acoustically Driven Micropipette for Hydrodynamic Manipulation of Mouse Oocytes

Acoustically Driven Micropipette for Hydrodynamic Manipulati...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Zhaofeng Zuo Xiaoming Liu Zhuo Chen Yuyang Li Xiaoqing Tang Dan Liu Qiang Huang Tatsuo Arai Beijing Advanced Innovation Center for Intelligent Robots and Systems and School of Mechatronical Engineering Key Laboratory of Biomimetic Robots and Systems Ministry of Education State Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing China Center for Neuroscience and Biomedical Engineering The University of Electro-Communications Tokyo Japan

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Micromanipulation techniques that can achieve controlled fine operations at the micro scale play an important role in biomedical fields including embryo engineering, gene engineering, drug screening, and cell analysis. However, micromanipulation of biological micro-objects, such as cells and micro tissues, suffers from mechanical damage and low efficiency. Several techniques have been introduced to manipulate cells more easily, but most of them are restricted by expensive devices, limited work area, and potential damage to cellular structure. Here we develop a hydrodynamic manipulation method to rotate and transport mouse oocytes, which utilizes acoustic waves and micropipette to generate acoustic radiation force and excite microstreaming. This method can accomplish rotational and translational operations precisely and controllably. We tested the process of trapping, rotation, and transportation of the mouse oocytes, and measured rotational and translational speed with a range of applied voltage. The method was able to shorten the cost time of delivery and posture adjustment before oocyte injection. Our study provides an easy-to-use technique for oocyte manipulation without contact, and it has the potential to be universally applied in many cellular studies.

关键词： Visualization Voltage measurement Three-dimensional displays Force Transportation Hydrodynamics Biology

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Full Attention Tracker: A Good Combination of Pixel-Level and Region-Level Cross-Correlation

Full Attention Tracker: A Good Combination of Pixel-Level an...

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第42届中国控制会议

作者： Yuxuan Wang Liping Yan Zihang Feng Yuanqing Xia Bo Xiao Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology School of Artificial Intelligence Beijing University of Posts and Telecommunications

The tracker based on Siamese neural network is currently a technical method with high accuracy in the tracking *** the introduction of transformer in the visual tracking field, the attention mechanism has gradually emerged in tracking ***, due to the characteristics of attention operation, Transformer usually has slow convergence speed, and its pixel-level correlation discrimination in tracking is more likely to lead to overfitting, which is not conducive to long-term tracking. A brand new framework FAT was designed, which is the improvement of MixFormer. The operation for simultaneous feature extraction and target information integration in MixFormer is retained, and the Mixing block is introduced to suppress the background as much as possible before the information interaction. In addition, a new operation is designed: the result of region-level crosscorrelation is used as a guidance to help the learning of pixel-level cross-correlation in attention, thereby accelerating the model convergence speed and enhancing the model generalization. Finally, a joint loss function is designed to further improve the accuracy of the model. Experiments show that the presented tracker achieves excellent performance on five benchmark datasets.

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Forming Circle Formations of Multi-agent systems Under Actuator Faults 5th

Forming Circle Formations of Multi-agent Systems Under Actu...

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5th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2021

作者： Liu, Jiajun Ru, Xinfeng Xia, Weiguo Wang, Chen China National Aeronautical Radio Electronic Research Institute and National Key Laboratory of Science and Technology on Avionics System Integration Shanghai China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education and School of Control Science and Engineering Dalian University of Technology Dalian China National Engineering Research Center of Software Engineering and the State Key Laboratory of Turbulence and Complex Systems Intelligent Biomimetic Design Lab College of Engineering Peking University Beijing China

ISBN: (纸本)9789811939976

A distributed fault-tolerant formation control law is designed in this paper for multi-agent systems under external disturbances and actuator faults including time-varying loss of effectiveness faults. The initial position of each agent is already on a circle and the control purpose is to form a desired formation on this circle. Based on this local information, a distributed adaptive formation control law is designed by employing the congelation of variables method to deal with time-varying actuator faults. Finally, a simulation example is given to verify the effectiveness of the adaptive fault-tolerant control design method. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Multi agent systems

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Distributed solver for linear matrix inequalities: an optimization perspective

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control Theory and Technology 2021年第4期19卷 507-515页

作者： Weijian Li Wen Deng Xianlin Zeng Yiguang Hong Department of Automation University of Science and Technology of ChinaHefei 230027AnhuiChina Key Lab of Systems and Control Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of TechnologyBeijing 100081China Department of Control Science and Engineering Tongji UniversityShanghai 201804China

In this paper,we develop a distributed solver for a group of strict(non-strict)linear matrix inequalities over a multi-agent network,where each agent only knows one inequality,and all agents co-operate to reach a consensus solution in the intersection of all the feasible *** formulation is transformed into a distributed optimization problem by introducing slack variables and consensus ***,by the primal–dual methods,a distributed algorithm is proposed with the help of projection operators and derivative ***,the convergence of the algorithm is analyzed,followed by illustrative simulations.

关键词： Distributed computation Distributed optimization Linear matrix inequalities Primal-dual method

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Power System Events Classification Technology Based on Deep-Learning

Power System Events Classification Technology Based on Deep-...

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IEEE International Symposium on Circuits and systems (ISCAS)

作者： Xin Lei Hongwei Ma Bin Liu Zhen Li School of Automation and Key Laboratory for Intelligent Control & Decision on Complex Systems Beijing Institute of Technology Beijing China College of Information Science and Engineering China University of Petroleum (Beijing) Beijing China

ISBN: (数字)9798350330991

ISBN: (纸本)9798350331004

As the complexity of the power system continues to increase, the frequency of the power system anomalies is on the rise. These anomalies have significant and widespread impacts on the stability of the power grid. Therefore, the rapid and accurate classification of these anomalies is crucial in preventing their further propagation and mitigating potential economic losses. This study presents an algorithm based on Phasor Measurement Unit (PMU) data for monitoring the state of power systems and identifying the types of anomalies. First, a dataset for anomaly event classification is created based on PMU data, which is used to train and validate the anomaly event classification model. Subsequently, a robust anomaly event classification model is constructed, consisting of a residual module with one-dimensional Convolutional Neural Networks (CNN) and a cascaded fully connected neural network classifier. This algorithm has undergone rigorous testing in the IEEE New England 39 bus test system, demonstrating exceptional event recognition accuracy.

关键词： Accuracy Power system stability Propagation losses Phasor measurement units Data models Stability analysis Classification algorithms

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An Immersive Learning System with Multimodal Cognitive Processes Inference

An Immersive Learning System with Multimodal Cognitive Proce...

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2022 Chinese Automation Congress, CAC 2022

作者： Bian, Siyu Liu, Xiwei Zhao, Hongxia Gong, Xiaoyan Jing, Sifeng The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Institute of Smart Education Systems Qingdao Academy of Intelligent Industries Qingdao266044 China

ISBN: (纸本)9781665465335

Using multimodal technology to infer learners' cognitive processes is an important means to support personalized learning. Previous cognitive process analysis is more about subjective reasoning, and less about combining physiological signals. With the rapid development of virtual reality technology, new requirements and more immersive schemes for learner's cognitive process inferring have been proposed. Based on this, this paper proposes an immersive learning system with multimodal cognitive processes inference, which is composed of macro, mesoscopic and micro environments. The system analyzes learner's actions, emotions and attention to infer learner's cognitive process through more comprehensive and objective multimodal data. The system also combines eye movement, brainwaves and other data, and proposes a multimodal data acquisition and analysis scheme using HMD-based VR. This paper also provides an immersive learning cognitive processes inference scheme for individual online learning, offline classroom learning scenarios. © 2022 IEEE.

关键词： Learning systems

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System Dynamics-Based Analysis on Factors Influencing Comprehensive Competence of Primary and Secondary School Students

System Dynamics-Based Analysis on Factors Influencing Compre...

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2022 Chinese Automation Congress, CAC 2022

作者： Jing, Sifeng Liu, Xiwei Gong, Xiaoyan Zhao, Hongxia Institute of Automation Chinese Academy of Sciences The State Key Laboratory for Management and Control of Complex Systems Beijing100190 China Qingdao Academy of Intelligent Industries Institute of Smart Education Systems Qingdao266044 China

ISBN: (纸本)9781665465335

With rapid progress of artificial intelligence (AI), it is urgent to promote educational reform to improve comprehensive competence level of primary and secondary school students (CCLPSSS). However, educational reform is a system engineering involving multiple and intertwined factors. In this research, a system dynamics-based model of education reform is developed. Then, based on this model, a series of simulation experiments are carried out to find main factors affecting improvement of CCLPSSS. Results show that: 1) this model could simulate trends of CCLPSSS under different educational reform measures;2) Measures including teaching mode reform, development and application of AI-based new teaching method, implementation of Double Reduction in compulsory education, implementation of deepening education evaluation reform policy, and development and application of AI-based education evaluation technology could play significant roles in promoting CCLPSSS and further strengthening cultivation of AI compound talents. © 2022 IEEE.

关键词： Students

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Research on intelligent methods in virtual reality games

Research on intelligent methods in virtual reality games

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2022 Chinese Automation Congress, CAC 2022

作者： Wang, JiaWei Liu, Xiwei Gong, Xiaoyan Chinese Academy of Sciences The State Key Laboratory for Management Control of Complex Systems Institute of Automation Beijing100190 China Qingdao Academy of Intelligent Industries Institute of Smart Education Systems Qingdao266044 China

ISBN: (纸本)9781665465335

Introduction of virtual reality technology enriches the expression of traditional games and greatly improves the sense of substitution and interactive experience of users. Realization of virtual reality is inseparable from artificial intelligence technology. In order to improve immersion and interactivity of virtual reality games, it is necessary to propose more intelligent solutions to existing technologies. This paper aims to discuss some intelligent methods of virtual reality games. Firstly, it discusses artificial intelligence means to enhance the virtual reality experience, which can improve the tracking and force / tactile interaction system of existing virtual reality games from software and hardware aspects;Then it proposes the concept of human-machine hybrid enhanced intelligence: by introducing human cognitive model to improve perception and decision-making ability of virtual reality games, so as to make interaction of virtual reality games more friendly and more real. © 2022 IEEE.

关键词： Virtual reality

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