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A Novel Agricultural Data Sharing Mode Based on Rice Disease Identification

Plant Diseases and Pests 2024年第2期15卷 9-16页

作者： Mengmeng ZHANG Xiujuan WANG Mengzhen KANG Jing HUA Haoyu WANG Feiyue WANG State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing100190China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of AutomationChinese Academy of SciencesBeijing 100190China Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China State Key Laboratory for Management and Control of Complex System Institute of AutomationChinese Academy of SciencesBeijing 100190China

In this paper,a variety of classical convolutional neural networks are trained on two different datasets using transfer learning *** demonstrated that the training dataset has a significant impact on the training results,in addition to the optimization achieved through the model ***,the lack of open-source agricultural data,combined with the absence of a comprehensive open-source data sharing platform,remains a substantial *** issue is closely related to the difficulty and high cost of obtaining high-quality agricultural data,the low level of education of most employees,underdeveloped distributed training systems and unsecured data *** address these challenges,this paper proposes a novel idea of constructing an agricultural data sharing platform based on a federated learning(FL)framework,aiming to overcome the deficiency of high-quality data in agricultural field training.

关键词： Rice disease and pest identification Convolutional neural networks Distributed training Federated learning(FL) Open-source data sharing platform

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Mean square exponential stabilization of sampled-data Markovian jump systems

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International Journal of Robust and Nonlinear control 2018年第18期28卷

作者： Guoliang Chen Jian Sun Jie Chen School of Automation Beijing Institute of Technology Beijing China Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing China

In this paper, the problem of mean square exponential stabilization for sampled-data Markovin jump systems is studied. A time-scheduled Lyapunov functional consisting of a exponential-type looped function is constructed using segmentation technology and linear interpolation. Based on this new Lyapunov functional, a less conservative mean square exponential stability criterion is obtained such that a bigger maximum decay rate can be easily calculated. Meanwhile, the quantitative relationship among some system parameters, maximum sampling period, and decay rate is established. Moreover, a time-dependent state feedback sample-data controller is designed. Significant improvements of the proposed exponential-type time-scheduled Lyapunov functional method over some existing ones are verified by numerical examples.

关键词： Markovian jump system mean square exponential stabilization sampled-data control time-scheduled Lyapunov functional

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Moving object detection in framework of compressive sampling

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Chinese Journal of systems Engineering and Electronics 2010年第5期000卷

作者： Jing Li Junzheng Wang Wei Shen Key Laboratory of Complex System Intelligent Control and Decision School of AutomationBeijing Institute of Technology Beijing 100081 P. R. China

Compressive sensing is a revolutionary idea proposed recently to achieve much lower sampling rate for signals. In the image application with limited resources the camera data can be stored and processed in compressed form. An algorithm for moving object and region detection in video using a compressive sampling is developed. The algorithm estimates motion information of the moving object and regions in the video from the compressive measurements of the current image and background *** algorithm does not perform inverse compressive operation to obtain the actual pixels of the current image nor the estimated background. This leads to a computationally efficient method and a system compared with the existing motion estimation *** experimental results show that the sampling rate can reduce to 25% without sacrificing performance.

关键词： compressive sampling compressive measurements moving object detection

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Input-to-state stability of impulsive switched nonlinear time-delay systems with two asynchronous switching phenomena

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International Journal of Robust and Nonlinear control 2020年第12期30卷

作者： Zhichuang Wang Jian Sun Jie Chen School of Automation Beijing Institute of Technology Beijing China Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing China

This summary addresses the input-to-state stability (ISS) and integral ISS (iISS) problems of impulsive switched nonlinear time-delay systems (ISNTDSs) under two asynchronous switching effects. In our investigated systems, impulsive instants and switching instants do not necessarily coincide with each other. Meanwhile, systems switching signals are not simultaneous with the corresponding controllers switching signals, which will induce instability seriously, and cause many difficulties and challenges. By utilizing methods of Lyapunov-Krasovskii and Lyapunov-Razumikhin, mode-dependent average dwell time approach, and mode-dependent average impulsive interval technique, some stability criteria are presented for ISNTDSs under two asynchronous switching effects. Our proposed results improve the related existing results on the same topic by removing some restrictive conditions and cover some existing results as special cases. Finally, some simulation examples are presented to illustrate the effectiveness and advantages of our results.

关键词： impulsive switched systems input-to-state stability nonlinear time-delay systems two asynchronous switching phenomena

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Procedure Recognition by Knowledge-Driven Segmentation in Robotic-Assisted Vitreoretinal Surgery

Procedure Recognition by Knowledge-Driven Segmentation in Ro...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Zhen Li Yawen Deng Qiang Ye Weihong Yu Haoxiang Qi Yaliang Liu Zhangguo Yu Gui-Bin Bian School of Electronic and Information Engineering Tongji University Shanghai China Institute of Automation Chinese Academy of Sciences Beijing China School of Mechatronic Engineering Beijing Institute of Technology Beijing China Department of Ophthalmology Peking Union Medical College Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China Key Laboratory of Biomimetic Robots and Systems Ministry of Education Beijing China International Joint Research Laboratory of Biomimetic Robots and Systems Ministry of Education Beijing China State Key Laboratory of Intelligent Control and Decision of Complex System Beijing China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Internal limiting membrane (ILM) peeling is a vital vitreoretinal surgery procedure. However, due to the thickness of just 1-2 micrometers and the intricacies associated with its varying density and adhesion, the difficulty of manipulation exceeds the physiological limits of human perception and operation. Surgical robot is characterized by high precision and stability. However, navigating intricate intraocular environments and handling minuscule high-precision areas remain enormous challenges. These include issues of uneven lighting, field-of-view loss, and motion blur. This paper proposed a perception method named ‘Multimodal Surgical Process Recognition based on Domain Knowledge and Segmentation (MSPR-DKS),’ designed to address these challenges and provide input for the precise control of robots. Moreover, a comprehensive dataset focused on ILM peeling during macular hole surgeries was established. Experimental results underscore the efficacy of this approach, with segmentation accuracies exceeding 99.27% for instruments and macular holes and an average accuracy of 98.97% in recognizing surgical processes. This study paves the way for leveraging domain knowledge and image segmentation to improve robot-assisted manipulation of soft tissues in ophthalmology.

关键词： Image segmentation Visualization Accuracy Medical robotics Motion segmentation Surgery Lighting

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Bionic Geomagnetic Navigation for Autonomous Underwater Vehicle with Temporal Attention-based Data-Driven Dead Reckoning

TechRxiv

引用

TechRxiv 2023年

作者： Yang, Songnan Zhang, Xiaohui Liu, Ding Bai, Wenqi Liu, Fan The School of Automation and Information Engineering Xi’an University of Technology Shaanxi 710048 China The Institute of Advanced Navigation and Electromagnetics Xi’an University of Technology Shaanxi 710048 China The State Key Laboratory of Eco-Hydraulics in the Northwest Arid Region of China Xi’an University of Technology Shaanxi 710048 China The Shaanxi Key Laboratory of Complex System Control with the Intelligent Information Processing Xi’an University of Technology Shaanxi 710048 China

Numerous studies have demonstrated that numerous animal species are capable of goal-directed navigation using environmental information for dead reckoning. The stable magnetic field of the earth provides important information for the migration of animals over long distances. Inspired by the goal-directed navigation of animals, a novel Geomagnetic Navigation with Temporal Attention-based Data-Driven Dead Reckoning (Attention-DR) method for Autonomous Underwater Vehicles (AUV) is presented in this article, which only utilizes the inclination angle (I) and the declination angle (D) of the Geomagnetic Field (GF) for underwater navigation without any prior knowledge of the geographical location or geographic map. This article proposes a Temporal Attention-based Long Short-Term Memory (TA-LSTM) neural network by combining history, GF information, and location in time series to achieve the optimization heading angle of underwater dead reckoning. Due to its ability to adjust the utilization weights of local and global temporal information in the path, TA-LSTM possesses the capability to continually update neural network model parameters through a data-driven process during the navigation process. This enables the Attention-DR to achieve efficient navigation in regions without prior magnetic maps and overcome navigation failures caused by magnetic field anomalies. The simulation outcomes confirm the efficiency, precision, and practicability of the proposed algorithm. © 2023, CC BY.

关键词： Navigation

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Shaping Effect of Phase-locked Loop on Impedance Characteristics of PMSG Wind Turbines Connected to Weak-grid

Shaping Effect of Phase-locked Loop on Impedance Characteris...

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IEEE General Meeting Power& Energy Society

作者： Feiya Wan Zhen Li Bin Liu Guanghui Li Xiaoliang Dong Xi Chen Samson S. Yu Amanullah M. T. Oo Zhenyu Shan Xiangdong Liu School of Automation and Key Laboratory for Intelligent Control & Decision on Complex Systems Beijing Institute of Technology Beijing China China Electric Power Research Institute Beijing China State Grid Corporation of China and North China Branch of State Grid Corporation of China Beijing China GEIRI North America USA School of Engineering Deakin University 75 Pigdon Rd Waurn Ponds Victoria Australia School of Electrical and Control Engineering North China University of Technology Beijing China

ISBN: (数字)9781728155081

ISBN: (纸本)9781728155098

With the booming installed capacity of permanent magnet synchronous generator (PMSG) for wind energy generation, the grid becomes weaker and the oscillation events are frequently observed in weak-grid-tied large-scale grid-connected PMSG wind farms. Although the impedance-based method is effective to analyze the stability of grid-connected systems, the mathematical relationship between external impedance characteristics and the internal controllers has not been quantitatively analyzed in depth, which is beneficial to the controller design. This paper studies the influence of phase-locked loop (PLL) on the impedance characteristics based on the analytical sequence impedance model of PMSG with typical topology and control structure. The shaping effect of PLL on the impedance characteristics is described so as to clearly describe the relationship between the external impedance characteristics of the wind turbines and the internal controller. Finally, the stability analysis of the grid-connected PMSG wind turbine system is provided in Matlab and simulation results are given to verify the oscillating mechanism caused by PLL.

关键词： Synchronous generators Stability analysis Wind turbines Topology Impedance Phase locked loops Oscillators

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Defining digital quadruplets in the cyber-physical-social space for parallel driving

arXiv

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arXiv 2020年

作者： Liu, Teng Xing, Yang Chen, Long Cao, Dongpu Wang, Fei-Yue Vehicle Intelligence Pioneers Inc Shandong Qingdao266109 China Qingdao Academy of Intelligent Industries QingdaoShandong266109 China Department of Mechanical and Mechatronics Engineering University of Waterloo N2L 3G1 Canada State Key Laboratory of Management and Control for Complex System Institute of Automation Beijing China

Parallel driving is a novel framework to synthesize the vehicle intelligence and transport automation. This article aims to define the digital quadruplets in parallel driving. In the cyber-physical-social systems (CPSS), based on the ACP method, the names of the digital quadruplets are first given, which are descriptive, predictive, prescriptive and real vehicles. The objectives of the three virtual digital vehicles are interacting, guiding, simulating and improving with the real vehicles. Then, the three virtual components of the digital quadruplets are introduced in detail and their applications are also illustrated. Finally, the real vehicles in parallel driving system and the research process of the digital quadruplets are depicted. The presented digital quadruplets in parallel driving are expected to make the future connected automated driving safety, efficiently and synergistically. Copyright © 2020, The Authors. All rights reserved.

关键词： Vehicles

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Chaos characteristic analysis on the time series of wend power generation capacity

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Taiyangneng Xuebao/Acta Energiae Solaris Sinica 2007年第11期28卷 1290-1294页

作者： Dong, Lei Gao, Shuang Liao, Xiaozhong Feng, Chengbo College of Information and Science Technology Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing 100081 China Internet Education School Xi'an Jiaotong University Xi'an 710049 China

The time series of wind power generating capacity were examined by nonlinear dynamical methods, in order to identify chaos characteristic from its random-like waveform. The analysis of modeling with low dimensions nonlinear dynamics indicated that time series of wind power generation capacity have chaos characteristic, and wind power generating capacity can be predicted in short time.

关键词： Wind power

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Self-adaptation of chimera states

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Physical Review E 2019年第1期99卷 010201(R)-010201(R)页

作者： Nan Yao Zi-Gang Huang Hai-Peng Ren Celso Grebogi Ying-Cheng Lai Department of Applied Physics Xi'an University of Technology Xi'an 710048 China The Key Laboratory of Biomedical Information Engineering of Ministry of Education National Engineering Research Center of Health Care and Medical Devices The Key Laboratory of Neuro-informatics & Rehabilitation Engineering of Ministry of Civil Affairs and Institute of Health and Rehabilitation Science School of Life Science and Technology Xi'an Jiaotong University Xi'an 710049 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an 710048 China Institute for Complex Systems and Mathematical Biology King's College University of Aberdeen Aberdeen AB24 3UE United Kingdom School of Electrical Computer and Energy Engineering Arizona State University Tempe Arizona 85287 USA Department of Physics Arizona State University Tempe Arizona 85287 USA

Chimera states in spatiotemporal dynamical systems have been investigated in physical, chemical, and biological systems, and have been shown to be robust against random perturbations. How do chimera states achieve their robustness? We uncover a self-adaptation behavior by which, upon a spatially localized perturbation, the coherent component of the chimera state spontaneously drifts to an optimal location as far away from the perturbation as possible, exposing only its incoherent component to the perturbation to minimize the disturbance. A systematic numerical analysis of the evolution of the spatiotemporal pattern of the chimera state towards the optimal stable state reveals an exponential relaxation process independent of the spatial location of the perturbation, implying that its effects can be modeled as restoring and damping forces in a mechanical system and enabling the articulation of a phenomenological model. Not only is the model able to reproduce the numerical results, it can also predict the trajectory of drifting. Our finding is striking as it reveals that, inherently, chimera states possess a kind of “intelligence” in achieving robustness through self-adaptation. The behavior can be exploited for the controlled generation of chimera states with their coherent component placed in any desired spatial region of the system.

关键词： Chimera states Collective dynamics Coupled oscillators Chaos & nonlinear dynamics

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