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36th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2021

作者： Liu, Xinkai Xu, Yunhui Zhou, Bo Fang, Fang Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China

ISBN: (纸本)9781665437127

Spraying technology has been applied more and more widely in aeronautical manufacturing field. However, aeronautical test workpieces usually have unstructured and complex shapes, which makes the spraying inefficient and the quality of coating cannot be guaranteed. Therefore, this paper designs an automatic programming and simulation system for aeronautical workpiece spraying. And the kinematics and inverse kinematics modeling of NACHI robot, spraying parameters optimization and trajectory planning of the robot are studied in detail. This paper also designs the simulation experiments on typical aeronautical test workpieces, and the result shows that this system can improve the spraying efficiency and coating thickness effect, which has a certain universality and effectiveness. © 2021 IEEE.

关键词： Inverse kinematics

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Multiscale Feature Fusion Module for Prohibited Item Detection 9

Multiscale Feature Fusion Module for Prohibited Item Detecti...

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9th International Conference on Intelligent Computing and Signal Processing, ICSP 2024

作者： Xu, Ruiqi Zhang, Chirui School of Automation China University of Geosciences Hubei Wuhan430074 China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Hubei Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Hubei Wuhan430074 China

ISBN: (纸本)9798350376548

X-ray security check is a prevalent placement measure that plays a vital role in ensuring public safety. However, detecting prohibited items poses a complex challenge due to their variable sizes within X-ray images. In this study, we tackle this issue by curating a novel dataset through the integration of open-source data and introducing a Multiscale Feature Fusion Module. This module facilitates robust detection by amalgamating features across different scales. Extensive experiments verified that the superiority of our method compared to existing methods on the prohibited items test set constructed in this paper demonstrates extremely well the practical effectiveness of our proposed method. © 2024 IEEE.

关键词： component Environmental Security Prohibited Items Security Inspection X-ray Images

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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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Formation of the cavity on a planar interface subjected to a perturbed shock wave

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Physical Review Fluids 2023年第6期8卷 063402-063402页

作者： Yifeng He (贺一峰) Naifu Peng (鹏乃夫) Haifeng Li (李海锋) Baolin Tian (田保林) Yue Yang (杨越) State Key Laboratory for Turbulence and Complex Systems College of Engineering Peking University Beijing 100871 China and HEDPS-CAPT Peking University Beijing 100871 China

We report the mechanism and modeling for the formation of cavitylike structures on a planar interface subjected to a perturbed shock wave. The cavity is distinguished from bubbles and spikes formed in the standard Richtmyer-Meshkov instability (RMI). The two-dimensional direct numerical simulation is conducted at a range of shock Mach numbers and Atwood numbers. We elucidate the effects of the interfacial vorticity and the shock-induced vorticity on the cavity formation. The interfacial vorticity, which is important in the standard RMI, only has a minor influence on the cavity width in the linear stage. Alternatively, the cavity width is determined by the Mach-stem height when the shock accelerates the interface. A pair of vorticity patches connecting the Mach stem, as a part of the shock-induced vorticity, penetrate the interface to form the cavity via strong shear layers generated by slipstreams during shock propagation. Inspired by this mechanism, we develop a model of the Mach-stem height to estimate the cavity width in the linear stage at various Mach numbers.

关键词： Richtmyer-Meshkov instability Shock waves

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YOLO-MSP: Effective Cigarette Detection YOLO Network for Surveillance Scenario

YOLO-MSP: Effective Cigarette Detection YOLO Network for Sur...

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International Conference on systems and Informatics (ICSAI)

作者： Zhiwei Zhang Xiaobo Lu School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China

ISBN: (数字)9798331510138

ISBN: (纸本)9798331510145

This paper presents an new approach to enhance the detection of smoking behavior using object detection neural networks, focusing on the challenge of small object detection, namely cigarettes in video frames. We introduce a Multi-Spatial Pooling (MSP) bottleneck mechanism integrated into a YOLOv8 backbone, which significantly improves the network's ability to discern smaller objects without compromising real-time inference capabilities. This enhancement facilitates the extraction of relevant features across various scales and efficiently handles the computational overhead, thereby boosting the detection accuracy and operational efficiency. Our results demonstrate a substantial improvement in performance metrics over traditional and existing neural network approaches, making this method highly suitable for real-time applications in diverse scenarios.

关键词： YOLO Measurement Computational modeling Surveillance Neural networks Focusing Streaming media Feature extraction Real-time systems Informatics

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A repetitive-control method based on sliding-mode control for nonlinear systems with external disturbances 41

A repetitive-control method based on sliding-mode control fo...

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第41届中国控制会议

作者： Yibing Wang Min Wu Manli Zhang Luefeng Chen Jinhua She School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Engineering Tokyo University of Technology

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This paper presents a two-dimensional(2 D) repetitive-control method based on sliding-mode control for a nonlinear system with external *** a sliding-mode controller has a powerful ability to handle nonlinearity and external disturbances during the sliding motion,the reference-tracking and disturbance-suppression problems of the original nonlinear system are decomposed into two subproblems:reference tracking for a linear system and disturbance suppression for a nonlinear modified-repetitive control system(MRCS) with external *** the first one,a repetitive controller constructed with two positive time-delay loops is employed to increase the flexibility of the system design and guarantee high accuracy reference tracking.A continuous-discrete 2 D model of the linear MRCS is established to describe continuous control and discrete learning by using the 2 D property of repetitive control.A sufficient stability condition,in which three parameters are used to adjust control and learning,is given to guarantee the stability of the linear *** design of the system is transformed into parameter *** optimization algorithm is used to yield the optimal *** the other,a sliding-mode controller is developed to eliminate the effect of both nonlinearity and external disturbances on the system.A linear-matrix-inequality(LMI)-based sufficient stability condition is derived to guarantee the stability of the sliding *** condition is used to design the sliding-mode controller,which has a simple structure and does not require any specific information of nonlinearity and external ***,a numerical example and a comparison demonstrate the validity and advantage of the presented method.

关键词： Repetitive control sliding-mode control two-dimensional model

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Hand-Motion Intention Recognition Based on One-Dimensional Convolutional Neural Network 41

Hand-Motion Intention Recognition Based on One-Dimensional C...

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第41届中国控制会议

作者： Hao Wu Feng Wang Juan Zhao Jinhua She School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Engineering Tokyo University of Technology

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Surface electromyographic(sEMG) signals play an important role in human-computer interaction between patients and rehabilitation robots in rehabilitation *** paper shows the effectiveness of one-dimensional convolutional neural networks(1-D CNN) in estimating hand motion intentions from sEMG *** database 1 was employed to train the ***,the data from a single subject was used to train a model,and the accuracy was roughly maintained at 80%.Then,the whole dataset was used to train the network,and the recognition accuracy was improved to 84.16%.This shows that 1-D CNN effectively estimates hand movements and achieves high accuracy even for a small number of data.

关键词： Electromyographic hand motion intention Ninapro database one-dimensional convolutional neural network(1-D CNN)

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A Survey on IMU-and-Vision-based Human Pose Estimation for Rehabilitation 41

A Survey on IMU-and-Vision-based Human Pose Estimation for R...

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第41届中国控制会议

作者： Yuan Niu Jinhua She Chi Xu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Engineering Tokyo University of Technology Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

With the rapid development of human pose estimation,the human-pose-estimation method applied in rehabilitation therapy has attracted more and more attention in today's aging *** them,inertial measurement units(IMU) and computer vision are two significant methods for human pose *** mainly pay attention to the application of these two methods in the rehabilitation therapy *** this paper,we first summarize the research status of IMU and computer vision in the field of rehabilitation ***,we find that combining the two methods can produce better ***,the main problems of the current research and possible development directions are identified.

关键词： Human Pose Estimation IMU Computer Vision Rehabilitation Therapy

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Interaction between trefoil knotted flame and vortex

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Physical Review Fluids 2023年第12期8卷 123201-123201页

作者： Yunde Su (苏运德) Yue Yang (杨越) State Key Laboratory for Turbulent and Complex Systems College of Engineering Peking University Beijing 100871 China and HEDPS-CAPT Peking University Beijing 100871 China

We study the interaction between knotted flame and vortex tubes using the direct numerical simulation. A 3D configuration of the flame-vortex interaction is proposed. The premixed flame is initially located within a vortex tube with the same trefoil knotted centerline, and it propagates outward and interacts with the knotted vortex tube. This configuration is able to investigate the flame extinction, flame-flame interaction, and suppression of the vortex reconnection. Compared to the nonreacting knotted vortex tube, the flame-vortex interaction modifies the helicity dynamics and the morphology of vortex and flame tubes. The combustion generally decreases the helicity due to enhanced viscosity effects, but also slightly increases the helicity during a short time when the local extinction occurs. The nonmonotonic variation of the helicity results from the unsymmetrical flame propagation along the vortex axis after the local flame extinction. Moreover, some parts of the flame and vortex tubes are flattened through the early evolution. The flattening is primarily due to the baroclinic effects arising from the misalignment between the local density gradient and the nonlocal pressure gradient that strongly depends on the flame-vortex configuration.

关键词： Combustion Vortex dynamics

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Federated Graph Learning for Cross-Domain Recommendation 38

Federated Graph Learning for Cross-Domain Recommendation

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38th Conference on Neural Information Processing systems, NeurIPS 2024

作者： Yang, Ziqi Peng, Zhaopeng Wang, Zihui Qi, Jianzhong Chen, Chaochao Pan, Weike Wen, Chenglu Wang, Cheng Fan, Xiaoliang Fujian Key Laboratory of Sensing and Computing for Smart Cities Xiamen University China Key Laboratory of Multimedia Trusted Perception and Efficient Computing Ministry of Education of China Xiamen University China School of Computing and Information Systems The University of Melbourne Australia College of Computer Science and Technology Zhejiang University Hangzhou China College of Computer Science and Software Engineering Shenzhen University Shenzhen China

Cross-domain recommendation (CDR) offers a promising solution to the data sparsity problem by enabling knowledge transfer between source and target domains. However, many recent CDR models overlook crucial issues such as privacy as well as the risk of negative transfer (which negatively impact model performance), especially in multi-domain settings. To address these challenges, we propose FedGCDR, a novel federated graph learning framework that securely and effectively leverages positive knowledge from multiple source domains. First, we design a positive knowledge transfer module that ensures privacy during inter-domain knowledge transmission. This module employs differential privacy-based knowledge extraction combined with a feature mapping mechanism, transforming source domain embeddings from federated graph attention networks into reliable domain knowledge. Second, we design a knowledge activation module to filter out potential harmful or conflicting knowledge from source domains, addressing the issues of negative transfer. This module enhances target domain training by expanding the graph of the target domain to generate reliable domain attentions and fine-tunes the target model for improved negative knowledge filtering and more accurate predictions. We conduct extensive experiments on 16 popular domains of the Amazon dataset, demonstrating that FedGCDR significantly outperforms state-of-the-art methods. We open source the code at https://***/LafinHana/FedGCDR. © 2024 Neural information processing systems foundation. All rights reserved.

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