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16th International Conference on Communication Software and Networks, ICCSN 2024

作者： Wang, Hongliang Wang, Kaizhu Ji, Binglong Deng, Changyi Shenyang Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences Liaoning Province Human- Computer Interaction System Engineering Research Center Based on DigitTwin Shenyang China Shenyang Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences Shenyang China Institute of Software China Industrial Control Systems Cyber Emergency Response Team Beijing China

ISBN: (纸本)9798331506322

In the production and assembly process, the accuracy of detection is usually low due to limited resources and small quantities. In this paper, we propose a few-shot learning method for object detection based on the combination of YOLOv8 and Mamba-Like Linear Attention (MLLA) module. This method utilizes a high-pixel camera to capture the shape and size of the workpiece. By consistency-based mutual augmentation structure for few-shot samples data augmentation. By introducing the efficient and lightweight MLLA module, the model's speed and accuracy in object detection and segmentation tasks on mobile devices are significantly improved. Specifically, MLLA mainly integrates the two key elements of 'forget gate' and 'block design' in Mamba, and MLLA replaces forget gate by using position coding (RoPE) to provide necessary location information while maintaining parallel computation and fast inference speed. This makes MLLA improves the accuracy of detection and segmentation recognition. Experimental results show that compared to the original YOLOv8 model, the model with the MLLA module exhibits improvements in segmentation precision and recognition accuracy. This method demonstrates high accuracy and robustness in workpiece recognition, making it suitable for real-time industrial applications. © 2024 IEEE.

关键词： Object detection

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Synthesis of Decoherence-Free Modes in Linear Quantum Passive systems via Robust Pole Placement

Synthesis of Decoherence-Free Modes in Linear Quantum Passiv...

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

作者： Miao, Zibo Pan, Yu Gao, Qing School of Mechanical Engineering and Automation Adaptive Robotics Harbin Institute of Technology Guangdong Key Laboratory of Intelligent Morphing Mechanisms Shenzhen518055 China The Institute of Cyber-Systems and Control College of Control Science and Engineering Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou310027 China The School of Automation Science and Electrical Engineering Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 China

ISBN: (纸本)9781665410205

In this paper we extend our previous research on coherent observer-based pole placement approach to study the synthesis of robust decoherence-free (DF) modes for linear quantum passive systems, which is aimed at preservation of quantum information. In particular, DF modes can be generated by placing the poles on the imaginary axis via a coherent feedback design scheme, and these modes can further be simultaneously made robust against perturbations to the system parameters by minimizing the condition number associated with imaginary poles. We develop explicit algebraic conditions for the existence of such a coherent quantum controller, with the corresponding deign procedure provided. Examples are given to illustrate the process of tuning the DF modes towards perfect robustness via the proposed pole placement technique. © 2024 IEEE.

关键词： Poles

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Research on Deterministic Communication Model for industrial Internet Based on OPC UA-TSN 5

Research on Deterministic Communication Model for Industrial...

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5th International Conference on Information Technologies and Electrical Engineering, ICITEE 2022

作者： Chai, Anying Zhu, Hao Xue, Qiang Li, Mingshi Ma, Xian Wang, Shiyu Liaoning Branch of China Academy of Industrial Lnternet China Academy of Industrial Internet Shenyang China Institute of Standardization Technology China Academy of Industrial Internet Beijing China Institute of Software China Industrial Control Systems Cyber Emergency Response Team Beijing China Liaoning Branch of China Academy of Industrial Internet China Academy of Industrial Internet Beijing China Shenyang Institute of Computing Technology Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9781450396806

The industrial Internet accelerates the network integration and collaborative communication of IT and OT, and has become the critical technical support for smart factories. Using OPC UA as the industrial network communication infrastructure can realize the interconnection and intercommunication of heterogeneous network devices, breaking information islands and data barriers. However, with the diversification of industrial data types and the continuous increase of data volume, the single communication mode based on OPC UA has poor performance in real-time data transmission and high network delay. It is difficult to meet high real-time and high reliability requirements. Aiming at the above problems, this paper proposes a deterministic communication model for industrial Internet based on OPC UA-TSN. Integrate the two communication architectures of OPC UA and TSN, and use OPC UA as the communication specification for heterogeneous network devices to realize the interconnection and intercommunication of the underlying industrial network. We use TSN to replace traditional industrial Ethernet as the network data transmission medium to ensure the deterministic transmission of time-sensitive data. In addition, an OPC UA-TSN message mapping method and an OPC UA-TSN network configuration scheme are constructed to realize the intercommunication between OPC UA and TSN. At the same time, we propose a frame-preemptive dynamic scheduling algorithm for TSN (FPDS), which reasonably allocates bandwidth resources to each priority data stream. The experimental results show that this model realizes the network communication between OPC UA and TSN. It can schedule different types of data streams, effectively reducing the transmission delay of time-sensitive data. This model ensures the efficient utilization of TSN queues and improves the quality of service level of the smart factory communication network. © 2022 ACM.

关键词： Heterogeneous networks

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A Vein Segmentation Method Based on Improved U-Net 12

A Vein Segmentation Method Based on Improved U-Net

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12th International Conference of Information and Communication Technology, ICTech 2023

作者： Wang, Hongliang Zhu, Liang Deng, Changyi Xiu, Pengfei Shenyang Institute of Computing Technology Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China Liaoning Province Human-Computer Interaction System Engineering Research Center Based on Digital Twin Shenyang China Institute of Software China Industrial Control Systems Cyber Emergency Response Team Beijing100040 China

ISBN: (纸本)9798350332919

Recently, medical research has revealed that diffusion weighted imaging (DWI) is less sensitive than susceptibility-weighted imaging (SWI) for acute ischemic stroke. Brain vein analysis in SWI is very important for personalised therapy, quantitative diagnosis, and prognosis of acute ischemic stroke. Therefore, the accurate segmentation of veins in SWI images has important significance in supplementary diagnosis and medical research. However, vein segmentation in SWI is a challenging task because different veins show distinct variability and uneven intensity and are difficult to manually split. This paper proposes an improvement method based on U-net, by using dense connection and mixing loss function, the best Dice coefficient and the ASSD were obtained by other comparison methods. The method presented in this article can be used as a potential tool to accurately measure SWI cerebral veins and help physicians in decision making. © 2023 IEEE.

关键词： Image segmentation

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Design and Implementation of a High-speed Data Acquisition and Analysis System for Robot Grinding and Polishing Force Position 24

Design and Implementation of a High-speed Data Acquisition a...

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Proceedings of the 7th International Conference on Information Technologies and Electrical Engineering

作者： Changyi Deng Zhentao Ma Hongliang Wang Mingshi Li Institute of Software China Industrial Control Systems Cyber Emergency Response Team Beijing China Shenyang Institute of Computing Technology Chinese Academy of Sciences Shenyang Liaoning China University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798400707087

In the process of grinding the surface of complex curved parts, simply controlling the position of the robot cannot ensure the consistency of the grinding removal amount, which is easy to lead to the phenomenon of over-grinding and under-grinding. Aiming at the above problems, this paper designed a high-speed data acquisition and analysis system for robot grinding and polishing force position based on ARM+FPGA, including hardware circuit design and software system implementation. The system could control the contact force in real time and monitor the distance between the grinding tool and the surface of the part. The experiments show that the system can effectively improve the precision and quality of surface grinding of complex curved parts. Its functions and performance in high-speed acquisition and data interaction can meet the consistent requirements of surface grinding removal of curved parts.

关键词： Complex surface grinding

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Research on Deterministic Communication Model for industrial Internet Based on OPC UA-TSN 22

Research on Deterministic Communication Model for Industrial...

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Proceedings of the 5th International Conference on Information Technologies and Electrical Engineering

作者： Anying Chai Hao Zhu Qiang Xue Mingshi Li Xian Ma Shiyu Wang Liaoning Branch of China Academy of Industrial lnternet China Academy of Industrial lnternet China Institute of Standardization Technology China Academy of Industrial lnternet China Institute of Software China Industrial Control Systems Cyber Emergency Response Team China Shenyang Institute of Computing Technology Chinese Academy of Sciences China

ISBN: (纸本)9781450396806

关键词： TSN Frame preemption OPC UA industrial Internet Deterministic network Real-time

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Generalized-Extended-State-Observer and Equivalent-Input-Disturbance Methods for Active Disturbance Rejection: Deep Observation and Comparison

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IEEE/CAA Journal of Automatica Sinica 2023年第4期10卷 957-968页

作者： Jinhua She Kou Miyamoto Qing-Long Han Min Wu Hiroshi Hashimoto Qing-Guo Wang School of Engineering Tokyo University of TechnologyHachiojiTokyo 192-0982Japan K.Miyamoto is with the Institute of Technology Shimizu CorporationKotoTokyo 135-0044Japan School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourneVIC 3122Australia School of Automation China University of GeosciencesWuhan 430074 Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of EducationWuhan 430074China School of Industrial Technology Advanced Institute of Industrial TechnologyTokyo 140-0011Japan Institute of Artificial Intelligence and Future Networks Beijing Normal UniversityZhuhai 519087 Guangdong Key Lab of AI and Multi-Modal Data Processing Guangdong Provincial Key Laboratory of Interdisciplinary Research and Application for Data Science BNUHKBU United International College Zhuhai 519087China

Active disturbance-rejection methods are effective in estimating and rejecting disturbances in both transient and steady-state *** paper presents a deep observation on and a comparison between two of those methods:the generalized extended-state observer(GESO)and the equivalent input disturbance(EID)from assumptions,system configurations,stability conditions,system design,disturbance-rejection performance,and extensibility.A time-domain index is introduced to assess the disturbance-rejection performance.A detailed observation of disturbance-suppression mechanisms reveals the superiority of the EID approach over the GESO method.A comparison between these two methods shows that assumptions on disturbances are more practical and the adjustment of disturbance-rejection performance is easier for the EID approach than for the GESO method.

关键词： Active disturbance-rejection control(ADRC) disturbance observer(DOB) equivalent input disturbance(EID) extendedstate observer(ESO) generalized extended-state observer(GESO)

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Experiences with Postdoctoral Training in Human Factors: Mentor and Trainee Perspectives 67th

Experiences with Postdoctoral Training in Human Factors: Men...

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67th International Annual Meeting of the Human Factors and Ergonomics Society, HFES 2023

作者： Caine, Kelly Catchpole, Ken Sasangohar, Farzan Chen, Karen B. Hegde, Sudeep Souders, Dustin McDonald, Anthony McLaurin, Elease J. Clemson University School of Computing ClemsonSC United States Medical University of South Carolina Clinical Practice and Human Factors CharlestonSC United States Texas A&M University Industrial and Systems Engineering CentralSC United States North Carolina State University Edward P. Fitts Department of Industrial and Systems Engineering RaleighNC United States Clemson University Department of Industrial Engineering CentralSC United States Clemson University Psychology Department ClemsonSC United States University of Wisconsin-Madison Department of Industrial and Systems Engineering MadisonWI United States Oak Ridge Institute for Science & Education Fellowship Program Centers for Disease Control & Prevention PhiladelphiaPA United States

Postdoctoral training positions are becoming more common in the human factors and ergonomics (HFE) discipline. However, conversations related to training in the HFE discipline have largely focused on undergraduate and graduate education. This panel assembles both postdoctoral mentors and former trainees who collectively have a diverse set of HFE-related postdoctoral experiences. By panelists discussing their experiences, observations, and recommendations related to postdoctoral training with the audience, the panel session will support HFE faculty and students in making more informed decisions about if and how a postdoctoral experience (either as a mentor or trainee) could be a part of their career development in HFE. © 2023 Human Factors and Ergonomics Society.

关键词： education human factors mentorship postdoctoral training

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Improved Action Recognition Algorithm for Video Surveillance Based on PoseC3D

Improved Action Recognition Algorithm for Video Surveillance...

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International Conference on Computer and Communications (ICCC)

作者： Ruifeng Guo Chao Yang Changyi Deng Ying Bai Xiaoxing Zhang Shenyang Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences Liaoning Province Human-Computer Interaction System Engineering Research Center Based on DigitTwin Shenyang China Institute of Software China Industrial Control Systems Cyber Emergency Response Team Beijing China

ISBN: (数字)9798331507077

ISBN: (纸本)9798331507084

The precise recognition of human action is of great significance for intelligent monitoring and video analysis. Previous researchers have utilized many methods to detect human action, but the accuracy and robustness of these methods remain to be improved. Skeleton-based action recognition methods have reported high accuracy and robustness, but these methods have not fully utilized multiple modalities for feature fusion. In order to solve the above problems, a multi-modality feature fusion based video surveillance personnel action recognition method is proposed by combining the two methods. The SlowOnly network is used to extract RGB modality features. The Faster R-CNN and Lite-HRNet networks are used to obtain skeleton modality data. The PoseC3D network is used to extract skeleton modality features. The early and late fusion of RGB modality features and skeleton modality features are performed. Then the action recognition results of video surveillance personnel are obtained. The experimental results on the NTU RGB+D public dataset under the X-Sub standard show the following points. In the action recognition model based on a single skeleton modality, PoseC3D has a higher recognition accuracy than GCN methods, reaching 92.8%. In the action recognition model based on RGB modality, recognition accuracy has reached 95.4%. The action recognition model based on multi-modality feature fusion has a higher recognition accuracy than the recognition model based on a single modality, reaching 96.1%.

关键词： Accuracy Computational modeling Feature extraction Video surveillance Skeleton Robustness Personnel Standards Monitoring

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Few-shot Object Detection Algorithm Based on YOLOv8-Mamba-Like Linear Attention

Few-shot Object Detection Algorithm Based on YOLOv8-Mamba-Li...

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International Conference on Communication Software and Networks, ICCSN

作者： Hongliang Wang Kaizhu Wang Binglong Ji Changyi Deng Liaoning Province Human- Computer Interaction System Engineering Research Center Based on DigitTwin Shenyang Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences Shenyang China Shenyang Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences Shenyang China Industrial Control Systems Cyber Emergency Response Team Institute of Software China Beijing China

ISBN: (数字)9798331506322

ISBN: (纸本)9798331506339

In the production and assembly process, the accuracy of detection is usually low due to limited resources and small quantities. In this paper, we propose a few-shot learning method for object detection based on the combination of YOLOv8 and Mamba-Like Linear Attention (MLLA) module. This method utilizes a high-pixel camera to capture the shape and size of the workpiece. By consistency-based mutual augmentation structure for few-shot samples data augmentation. By introducing the efficient and lightweight MLLA module, the model’s speed and accuracy in object detection and segmentation tasks on mobile devices are significantly improved. Specifically, MLLA mainly integrates the two key elements of “forget gate” and “block design” in Mamba, and MLLA replaces forget gate by using position coding (RoPE) to provide necessary location information while maintaining parallel computation and fast inference speed. This makes MLLA improves the accuracy of detection and segmentation recognition. Experimental results show that compared to the original YOLOv8 model, the model with the MLLA module exhibits improvements in segmentation precision and recognition accuracy. This method demonstrates high accuracy and robustness in workpiece recognition, making it suitable for real-time industrial applications.

关键词： Accuracy Shape Computational modeling Object detection Production Logic gates Feature extraction Robustness Software Real-time systems

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