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synchronization of coupled reaction-diffusion neural networks with mixed delays

Complexity 2016年第S2期21卷

作者： Ping He Yangmin Li Department of Electromechanical Engineering Faculty of Science and Technology University of Macau Taipa Macao Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin China

The reaction-diffusion neural network is often described by semilinear diffusion partial differential equation (PDE). This article focuses on the asymptotical synchronization and synchronization for coupled reaction-diffusion neural networks with mixed delays (that is, discrete and infinite distributed delays) and Dirichlet boundary condition. First, using the Lyapunov–Krasoviskii functional scheme, the sufficient condition is obtained for the asymptotical synchronization of coupled semilinear diffusion PDEs with mixed time-delays and this condition is represented by linear matrix inequalities (LMIs), which is easy to be solved. Then the robust synchronization is considered in temporal-spatial domain for the coupled semilinear diffusion PDEs with mixed delays and external disturbances. In terms of the technique of completing squares, the sufficient condition is obtained for the robust synchronization. Finally, a numerical example of coupled semilinear diffusion PDEs with mixed time-delays is given to illustrate the correctness of the obtained results. © 2016 Wiley Periodicals, Inc. Complexity 21: 42–53, 2016

关键词： asymptotical synchronization synchronization coupled reaction-diffusion neural networks linear matrix inequality (LMI) partial differential systems (PDSs) mixed delays

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Wire in the Cable-Driven System of Surgical Robot

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IOP Conference Series: Materials Science and Engineering 2017年第1期224卷

作者： X F Wang N Lv H Z Mu L J Xue Tianjin Key Laboratory of the Design and Intelligent Control of the Advanced Mechatronical System Tianjin University of Technology School of Mechanical Engineering Tianjin University of Technology School of Mechanical Engineering Zhonghuan Information College Tianjin University of Technology

During the evolution of the surgical robot, cable plays an important role. It translates motion and force precisely from surgeon's hand to the tool's tips. In the paper, the vertical wires, the composition of cable, are mathematically modeled from a geometric point of view. The cable structure and tension are analyzed according to the characteristics of wire screw twist. The structural equations of the wires in different positions are derived for both non-bent cable and bent cable, respectively. The bending moment formula of bent cable is also obtained. This will help researchers find suitable cable and design more matched pulley.

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DQPS: An intelligent Multi-Hop Computation Offloading Scheme for Workflow Applications in Vehicular Edge computing Networks

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IEEE Transactions on Consumer Electronics 2024年

作者： Lin, Bing Chen, Qiaoxin Chen, Xing Jia, Wen-Kang Lu, Yu Xiong, Neal N. Fujian Normal University College of Physics and Energy Fujian Provincial Key Laboratory of Quantum Manipulation and New Energy Materials Fuzhou350117 China Fujian Provincial Collaborative Innovation Center for Advanced High-Field Superconducting Materials and Engineering Fuzhou350117 China Peking University School of Computer Science 100871 China Xiamen University Department of Informatics and Communication Engineering Xiamen361005 China Fuzhou University College of Computer and Data Science Fuzhou350118 China Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou350118 China Fujian Normal University College of Photonic and Electronic Engineering Fuzhou350117 China Fujian Normal University Concord University College Fuzhou350117 China Sul Ross State University Department of Computer Mathematical and Physical Sciences AlpineTX79830 United States

Vehicular Edge computing (VEC) is a feasible solution for autonomous driving as it can offload latency-sensitive and computation-intensive tasks from vehicle terminals to roadside units (RSUs) for real-time processing. Due to the high computational resource the workflow applications (i.e., autonomous driving) required, the small vehicle-to-RSUs communication range, and the scarce available resources for each vehicle, it might be difficult to accomplish complex workflow applications through the single-hop offloading paradigm in the Internet of Vehicles (IoV). In this paper, we propose a reinforcement learning (RL) based multi-hop computation offloading scheme for workflow applications to reduce their execution latency in the VEC networks, which considers the data dependency in workflow applications as well as the trust relationship and communication interference among RSUs. Firstly, a preprocessing method is employed to merge the cut-edges in a workflow to reduce the offloading scale of tasks and compress the encoding dimension of offloading solutions. Then, a Deep Q-network algorithm using Phase-optimal State update (DQPS) is proposed to update the offloading policy distribution, in which the deviation of the phase-optimal state from the current state is estimated as the reward of RL to promote the algorithm's convergence to adapt the dynamic VEC networks. Simulation results show that DQPS has the best performance compared to other benchmark schemes. Moreover, the latency of the identical applications can be reduced by 2.5%-25.3% through our offloading scheme with a multi-hop model compared to that with the single-hop paradigm in IoV. © 1975-2011 IEEE.

关键词： Computation offloading

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Research on the Relationship between Virtual Reality Content and Physiological Response

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Journal of Physics: Conference Series 2021年第1期2026卷

作者： Chen Chen Liangliang Yao Gen Li Linyan Wang Kaiyuan Liu Guangjun Wang Xiaohui Chen Games Design Brunel University London Uxbridge UK The University Key Laboratory of Intelligent Perception and Computing of Anhui Province Anqing Normal University Anqing China School of Information Technology Anqing Vocational & Technical College Anqing China

The development of VR (virtual reality) technology has greatly promoted immersion, but it may cause people to worry about the safety of humans. This study aims to determine the effect of virtual reality based on 9D-VR seat (9 Dimension VR Seat) on the physiological response of users. Recruit 20 volunteers to experience the VR roller coaster and VR big pendulum. Through analysis of heart rate data with visualization and statistical, it is found that there is a significant effect on heart rate when users experience virtual reality, and the excitement points of the VR content were related to the changes in heart rate. Further, we found that the difference between the first experience and the second experience for the same VR content, and the changes in heart rate have eased. These findings provide references for the analysis of users for VR and the design of content of the VR.

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Effect of tungsten on creep properties of martensitic 9Cr steel

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IOP Conference Series: Materials Science and Engineering 2020年第1期838卷

作者： F Y Hu S J Zhang J J Shen Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education (Tianjin University of Technology) China

The effects of tungsten on the creep behavior and microstructure of tempered martensite 9Cr steel with different W concentrations ranging from 0–2.5 wt% were studied. The matrix consisted of tempered lath martensite structure and M23C6 located along the grain boundary or inside the grain. As the W concentration increased, the number of M23C6 increased while the particle size decreased. Also, with the increasing W concentration, the minimum creep rate and elongation decreased while the time to rupture increased. The rise in W concentration led to the refinement of M23C6, which enhanced the creep strength but reduced the creep plasticity.

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Digital twin-driven machining process for multi-process irregular-shaped parts manufacturing

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Computers & Industrial Engineering 2024年

作者： Zhiwen Lin Zhifeng Liu Yueze Zhang Baobao Qi Jinyan Guo Chuanhai Chen Key Laboratory of Advanced Manufacturing and Intelligent Technology for High-end CNC Equipment Jilin Province Changchun 130025 China Key Laboratory of CNC Equipment Reliability Ministry of Education Jilin University Changchun 130025 China Machinery Industry Key Laboratory of Heavy Machine Tool Digital Design and Testing Technology Beijing University of Technology Beijing 100124 China

With the advancement of high-end manufacturing industries, certain critical parts exhibit peculiar shapes and characteristics of multi-process manufacturing, which intensify milling difficulties and give rise to error propagation effects during the machining process. This necessitates machining systems to be adaptive to different working conditions and capable of real-time error analysis and optimization. Digital twin technology can create virtual replicas of physical entities to observe, analyze, and optimize the machining process. Therefore, this paper proposes a framework for digital twin-driven machining of multi-process irregular-shaped parts, consisting of preparation, processing, and optimization stages. In the preparation stage, a mapping relationship between the workpiece and machine tool motion coordinates is established to create a twin simulation environment consistent with actual operational parameters. In the processing stage, the digital thread dynamically updates the digital twin workpiece and machine tool status in real-time, analyzing the machining errors for each process to assess the finished quality. In the optimization stage, a cloud-based machining knowledge graph is constructed to enhance the precision of machining optimization decisions under different error sources and causes in the digital twin system. Finally, a case study of a typical multi-process irregular-shaped part machining task validates the reliability and superiority of the digital twin-driven method. The case study demonstrates that in a total of 260 machining processes, the digital twin-driven method improves machining accuracy by 40%, saves 34.9% of machining time, and alleviates 70% of machining downtime compared to existing machining methods.

关键词： Digital Twin-driven machining Multi-process irregular-shaped parts machining Digital twin enabling technologies Digital twin machine tool Reliable manufacturing

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Dynamic Constructing 3D Electronic Technical Manual of Mechanical Products Based on Publishing Rules

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Journal of Physics: Conference Series 2019年第2期1176卷

作者： Feng Zhao Aijian Wu Lijuan Yan Shen li State Key Laboratory of Intelligent Manufacturing of Advanced Construction Machinery Jiangsu XCMG Construction Machinery Research Institute Ltd. Xuzhou 221000 China Key Laboratory of Electronic Equipment Structure Design of Ministry of Education School of Mechano-electronic Engineering Xidian Univ. Xi'an 710071 China

In order to solve the different contents of 3D Electronic Technical Manual (3DETM) for classified users in the Process of Publishing Mechanical Products, a method of dynamic constructing 3DETM is presented based on publishing rules. Firstly, the object data of 3DETM was extracted automatically; then the publishing behavior of 3DETM was encapsulated by CAD API method. Finally, the dynamic mapping between different classified users and the publishing contents modes of 3DETM was realized by defining Publishing Rules. Validation in the prototype software developed shows that the 3DETM was constructed dynamically for classified users.

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Ultrafast demagnetization in ferromagnetic materials: origins and progress

arXiv

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arXiv 2024年

作者： Chen, Xiaowen Adam, Roman Bürgler, Daniel E. Wang, Fangzhou Lu, Zhenyan Pan, Lining Heidtfeld, Sarah Greb, Christian Liu, Meihong Liu, Qingfang Wang, Jianbo Schneider, Claus M. Cao, Derang College of Physics Qingdao University Qingdao266071 China National Demonstration Center for Experimental Applied Physics Education Qingdao University Qingdao266071 China Spin-X Institute South China University of Technology Guangzhou511442 China Peter Grünberg Institute Forschungszentrum Jülich Jülich52425 Germany Hunan Provincial Key Laboratory of Intelligent Sensors and Advanced Sensor Materials School of Physics and Electronics Hunan University of Science and Technology Xiangtan411201 China CAS Key Laboratory of Magnetic Materials and Devices Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Ningbo315201 China Key Laboratory for Magnetism and Magnetic Materials of Ministry of Education Lanzhou University Lanzhou730000 China Key Laboratory of Special Functional Materials and Structural Design Ministry of Education Lanzhou University Lanzhou730000 China Faculty of Physics University of Duisburg-Essen Duisburg47057 Germany Department of Physics University of California Davis DavisCA95616-5270 United States

Since the discovery of ultrafast demagnetization in Ni thin films in 1996, laser-induced ultrafast spin dynamics have become a prominent research topic in the field of magnetism and spintronics. This development offers new possibilities for the advancement of spintronics and magnetic storage technology. The subject has drawn a substantial number of researchers, leading to a series of research endeavors. Various models have been proposed to elucidate the physical processes underlying laser-induced ultrafast spin dynamics in ferromagnetic materials. However, the potential origins of these processes across different material systems and the true contributions of these different origins remain challenging in the realm of ultrafast spin dynamics. This predicament also hinders the development of spintronic terahertz emitters. In this review, we initially introduce the different experimental methods used in laser-induced ultrafast spin dynamics. We then systematically explore the magnetization precession process and present seven models of ultrafast demagnetization in ferromagnetic materials. Subsequently, we discuss the physical processes and research status of four ultrafast demagnetization origins (including spin-flipping, spin transport, non-thermal electronic distribution, and laser-induced lattice strain). Since attosecond laser technique and antiferromagnetic materials exhibit promising applications in ultrahigh-frequency spintronics, we acknowledge the emerging studies used by attosecond pules and studies on ultrafast spin dynamics in antiferromagnets, noting the significant challenges that need to be addressed in these burgeoning field. © 2024, CC BY.

关键词： Spin dynamics

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A meta-inspired termite queen algorithm for global optimization and engineering design problems

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Engineering Applications of Artificial Intelligence 2022年 111卷

作者： Peng Chen Shihua Zhou Qiang Zhang Nikola Kasabov Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University Dalian 116622 China School of Computer Science and Technology Dalian University of Technology Dalian 116024 China Knowledge Engineering and Discovery Research Institute Auckland University of Technology Auckland 1010 New Zealand Intelligent Systems Research Center Ulster University Londonderry BT52 1SA UK

This paper proposes a novel bio-inspired termite queen algorithm (TQA) to solve optimization problems by simulating the division of labor in termite populations under a queen’s rule. TQA is benchmarked on a set of 23 functions to test its performance at solving global optimization problems, and applied to six real-world engineering design problems to verify its reliability and effectiveness. Comparative simulation studies with other algorithms are conducted, from whose results it is observed that TQA satisfactorily solves global optimization problems and engineering design problems.

关键词： Termite queen algorithm Benchmarked functions Loss minimization Metaheuristic technique Engineering design problems

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Graph Confidence Intercalibration Network for Intracranial Aneurysm Lesion Instance Segmentation in Dsa

SSRN

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SSRN 2024年

作者： Ye, Haili Mo, Yancheng Tang, Chen Liao, Mingqian Zhang, Xiaoqing Dai, Limeng Li, Baihua Liu, Jiang Research Institute of Trustworthy Autonomous Systems Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China Department of Computer Science Loughborough University LoughboroughLE11 3TU United Kingdom School of Ophthalmology and Optometry Eye Hospital Wenzhou Medical University Wenzhou325027 China Center for High Performance Computing and Shenzhen Key Laboratory of Intelligent Bioinformatics Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Shenzhen People’s Hospital Neurosurgery Department Shenzhen518020 China China

Intracranial aneurysm (IA) lesion segmentation is significant for its treatment and prognosis. Although exiting deep network-based instance methods have good IA lesion segmentation results based on digital subtraction angiography (DSA) images, they still face great challenges with instance confidence bias and imprecise boundary segmentation, which may negatively affect IA diagnosis. To tackle these problems, this paper proposes a novel graph confidence intercalibration network (GCINet) to automatically segment IA lesions from DSA images. To be specific, we design a graph confidence intercalibration (GCI) module to mitigate instance confidence bias by dynamically adjusting their confidence distributions. At the same time, we propose an edge space perception (ESP) module to correct ambiguous segmentation boundaries. Extensive experiments on a clinical IA-DSA and a publicly available LiTS dataset demonstrate that our GCINet outperforms state-of-the-art methods. Additionally, visual analysis and ablation studies are provided to verify the effectiveness of each module in GCINet. © 2024, The Authors. All rights reserved.

关键词： Image segmentation

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