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第三十九届中国控制会议

作者： Duqiao Zhao Ding Liu Xia Zhang National & Local Joint Engineering Research Center of Crystal Growth Equipment and System Integration Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing

This paper proposes an asynchronous algorithm for distributed optimization problem(Asy-DOP) in multi-agent network with gradient *** algorithm can be implemented in an asynchronous distributed *** objective function of the algorithm is the sum of the local functions of multiple nodes in the network,each node only knows its own local objective function and can exchange information with its *** addition,the algorithm is based on the undirected connected graph and requires the objective function is Lipschitz *** step-size of the proposed algorithm is homogeneous and when the step-size is in a suitable range,it is proved that the convergence rate of the proposed algorithm is O(1/(?)),where the k is the number of iterations.

关键词： asynchronous algorithm distributed optimization multi-agent gradient method

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UAV Trajectory Generation Based on Integration of RRT and Minimum Snap Algorithms

UAV Trajectory Generation Based on Integration of RRT and Mi...

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Chinese Automation Congress (CAC)

作者： Bohui Shi Youmin Zhang Lingxia Mu Jing Huang Jing Xin Yingmin Yi Shangbin Jiao Guo Xie Han Liu Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an Shaanxi China Industrial and Aerospace Engineering Concordia University Montreal Quebec Canada

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

Aiming at the problems that carrying out forest fire monitoring and fighting missions by using the Rapidly-exploring Randomized Tree (RRT) algorithm to plan paths cannot adapt to the autonomous movement of an Unmanned Aerial Vehicle (UAV) and that high-order dynamic characteristics may mutate during the mission, this paper investigates a trajectory generation algorithm based on the integration of the RRT algorithm and the minimum snap algorithm. First, the RRT algorithm is used to generate the initial path, then the minimum snap algorithm is used to smooth the initial path and obtain a trajectory suitable for the actual flight of the UAV. However, because the UAV is considered as a particle in the simulation, during the actual flight, this trajectory may not guarantee the safe flight of the UAV and may cause the UAV to collide with an obstacle or other nearby UAVs in the cases of formation flight. To solve this problem, flight corridor concept is used to limit the UAV's flight trajectory for ensuring the safe flight of the UAV. Simulation results show that the algorithm can effectively ensure the safety, smoothness, feasibility, and trajectory of unmanned aerial vehicles.

关键词： Vegetation Forestry Path planning Unmanned aerial vehicles Heuristic algorithms Trajectory optimization Safety

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Nonlinear variational inequality problems involving uncertain variable

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UPB Scientific Bulletin, Series A: Applied Mathematics and Physics 2019年第4期81卷 65-74页

作者： Li, Cunlin Jia, Zhifu Ningxia Key Laboratory of intelligent information and Big Data Processing Governance and social management research center of Northwest Ethnic regions North Minzu University Yinchuan China State Key Laboratory of Mechanics Control of Mechanical Structures Institute of Nano Science and Department of Mathematics Nanjing University of Aeronautics and Astronautics Nanjing210016 China School of Mathematics and Information Science North Minzu University Yinchuan China

Variational inequality problems have been extensively studied and applied in the area of optimization theory, but much of it has been developed in a deterministic domain. In this paper, the uncertain variational inequality is studied. Under the compact uncertain event space, we establish an uncertain nonlinear expected residual minimization (UNERM) model. Considering that uncertain variable usually has no density function, we propose integration by parts method to solve UNERM model. Under reasonable assumptions and Slater’s constraint qualification, two kinds of convergence, such as convergence of global optimal solutions and convergence of stationary points, are investigated. © 2019, Politechnica University of Bucharest. All rights reserved.

关键词： Uncertainty analysis

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Augmented reality-based pre-visualization for film making 2nd

Augmented reality-based pre-visualization for film making

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2nd International Conference on Smart Vehicular Technology, Transportation, Communication and Applications, VTCA 2018

作者： Xue, Tong Ding, Gangyi Zhang, Fuquan School of Computer Science and Technology Beijing Institute of Technology Beijing100081 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350108 China

ISBN: (纸本)9783030045845

With the development of the augmented reality technologies, wearing devices such as Microsoft Hololens and Google glass become highly popular recently. In this paper, we proposed a novel augmented reality application that helps the film directors to complete and facilitate their film rehearsal process. We simulated a design space to provide film directors with a high-fidelity visual-audio experience. The directors wearing the hololens are allowed to observe the synthesized virtual-reality space in which they can recognize the whole design space, prefabricated boxes, and modify the space by defined gestures. Feedbacks from directors indicate the proposed tool is effective and the preliminary experimental results agree with our observations. In general, our research offers the guidelines for novel film rehearsal tactics. © Springer Nature Switzerland AG 2019.

关键词： Visualization

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Neural Network-Based Prescription of Chinese Herbal Medicines

Neural Network-Based Prescription of Chinese Herbal Medicine...

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IEEE International Symposium on information (IT) in Medicine and Education, ITME

作者： Wen Zhao Weikai Lu Chang'en Zhou Zuoyong Li Haoyi Fan Xuejuan Lin Zhaoyang Yang Candong Li School of Traditional Chinese Medicine Fujian University of Traditional Chinese Medicine Fuzhou China School of Electronic Electrical Engineering and Physics Fujian University of Technology Fuzhou China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou China School of Computer Science and Technology Harbin University of Science and Technology Harbin China

ISBN: (纸本)9781728194202

Objective: To develop a neural network model that recommends traditional Chinese medicine (TCM) herbal prescriptions. Methods: We constructed a new dataset of diagnosis and treatment knowledge from the Treatise on Febrile Diseases. Based on TCM's logical principles of “syndrome differentiation” and “state recognition”, a back-propagation neural network model is proposed that simulates clinical diagnosis and treatment. Results: The proposed model is a four-layer BP neural network. Experiments on the constructed dataset show that the proposed method achieved the best precision, recall, and F1-scores. Conclusion: The proposed method provides much more accurate herbal prescription recommendations than logistic regression.

关键词： Neural networks Education Clinical diagnosis information technology Logistics Diseases

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Using quantum thinking to construct a musical appreciation system 2nd

Using quantum thinking to construct a musical appreciation s...

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2nd International Conference on Smart Vehicular Technology, Transportation, Communication and Applications, VTCA 2018

作者： Peng, Mei Gangyi, Ding Qiankun, Jin Fuquan, Zhang School of Computer Science and Technology Beijing Institute of Technology Beijing100081 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou350121 China

ISBN: (纸本)9783030045845

With the richness of material and cultural life, participating in music activities and enjoying music works has become an indispensable activity in people’s leisure time. The rich emotions in music have different performances according to individual differences. After the composers create the music, the performer’s deductive processing and then the emotion is sublimated by the viewers finally. This paper proposes a new emotional system for basic emotional joy, anger, sadness, joy, etc., and interprets the superposition state of emotional expression in detail. The paper believes that the generation of consciousness and the resonance of thinking are precisely the result of the quantum collapse of mutual entanglement. © Springer Nature Switzerland AG 2019.

关键词： Music

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Pneumatically Actuated MR-Safe Parallel Robot for Deep Brain Stimulation Electrode Implantation

Pneumatically Actuated MR-Safe Parallel Robot for Deep Brain...

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IEEE International Conference on Robotics and Biomimetics

作者： Weihang Huang Shenghao Dai Anze Xu Xianyi He Shaoping Huang Anzhu Gao School of Mechanical Engineering Shanghai Jiao Tong University Shanghai Jiao Tong University Institute of Medical Robotics and School of Biomedical Engineering Shanghai Jiao Tong University Shanghai China the Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiao Tong University Shanghai China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

ISBN: (纸本)9781665405362

Deep brain stimulation (DBS) has been widely used in clinical practice as an effective therapy for neurological disorders. MR-conditional robot-assisted electrode implantation has attracted more attention for DBS because of its great accuracy and high-quality guiding images by using MRI. This paper develops a pneumatically actuated MR-safe parallel robot for deep brain electrode implantation. Its fully plastic components and MR-safe pneumatic actuators enable the robotic system to be MR-safe, posing no known hazards in MR environment. A 6-DOF parallel robot is developed using six slider-crank mechanisms for prismatic motions. Inverse kinematics is built to investigate its workspace and achieve the precise control. Experiments are carried out to validate the feasibility, and results shows that the average error of the motion is 0.11 mm. The developed parallel robot shows the potential advantages in the automatic and precise robot-assisted neurosurgical surgery in future.

关键词： Electrodes Pneumatic actuators Neurological diseases Parallel robots Magnetic resonance imaging Satellite broadcasting Deep brain stimulation

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Mem Brain: An Easy-to-Use Online Webserver for Transmembrane Protein Structure Prediction

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Nano-Micro Letters 2018年第1期10卷 12-19页

作者： Xi Yin Jing Yang Feng Xiao Yang Yang Hong-Bin Shen Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Department of Computer Science Shanghai Jiao Tong University Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering

Membrane proteins are an important kind of proteins embedded in the membranes of cells and play crucial roles in living organisms, such as ion channels,transporters, receptors. Because it is difficult to determinate the membrane protein's structure by wet-lab experiments,accurate and fast amino acid sequence-based computational methods are highly desired. In this paper, we report an online prediction tool called Mem Brain, whose input is the amino acid sequence. Mem Brain consists of specialized modules for predicting transmembrane helices, residue–residue contacts and relative accessible surface area of a-helical membrane proteins. Mem Brain achieves aprediction accuracy of 97.9% of ATMH, 87.1% of AP,3.2 ± 3.0 of N-score, 3.1 ± 2.8 of C-score. Mem BrainContact obtains 62%/64.1% prediction accuracy on training and independent dataset on top L/5 contact prediction,respectively. And Mem Brain-Rasa achieves Pearson correlation coefficient of 0.733 and its mean absolute error of13.593. These prediction results provide valuable hints for revealing the structure and function of membrane *** Brain web server is free for academic use and available at ***/bioinf/Mem Brain/.

关键词： Transmembrane a-helices Structure prediction Machine learning Contact map prediction Relative accessible surface area

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Black-box domain adaptation for cross-domain on-device machinery fault diagnosis via hierarchical debiased self-supervised learning

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Knowledge-Based Systems 2025年 324卷

作者： Zhu, Mengliang Liu, Jie Lu, Yanglong Hu, Zhongxu Yuan, Li Zhou, Kaibo MOE Key Laboratory of Image Information Processing and Intelligent Control Belt and Road Joint Laboratory on Measurement and Control Technology School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China National Center of Technology Innovation for Digital Construction School of Civil and Hydraulic Engineering Huazhong University of Science and Technology Wuhan430074 China Department of Mechanical and Aerospace Engineering The Hong Kong University of Science and Technology Clear Water Bay Hong Kong SAR China School of Mechanical Science and Engineering Huazhong University of Science and Technology Wuhan430074 China

This paper explores black-box domain adaptation (BBDA) for cross-domain on-device machinery fault diagnosis. Specifically, a pre-trained black-box source model is deployed on a cloud platform with only its input-output API accessible, and a randomly initialized target model is trained locally utilizing unlabeled target data on an edge device. In BBDA, neither raw data nor model parameters are transmitted across domains, and the only available supervised information for adaptation is API-queried predictions on unlabeled target data. However, API-queried predictions are inevitably noisy and class-imbalanced due to cross-domain distribution discrepancy and inherent category bias. Directly utilizing them for on-device training easily leads to confirmation bias and exacerbates category bias, thereby severely degrading performance. This paper proposes a hierarchical debiased self-supervised learning framework for BBDA from a novel research perspective of concurrently alleviating both confirmation and category biases. Specifically, debiased knowledge distillation is proposed to gradually enhance discriminability of the randomly initialized target model by providing debiased training predictions. An adaptive category-unbiased sample division strategy is devised to divide unlabeled target data into certain-aware and uncertain-aware sets, enabling fully exploiting intrinsic data structures and utilizing underlying sample relationships within the target domain. On this basis, debiased prototypical self-training is proposed for the certain-aware set to obtain reliable pseudo-labels for self-training, leveraging global semantic structure. Hierarchical neighborhood adaptation is customized for the uncertain-aware set to enforce the cluster assumption for noise refinement, exploiting local clustering structure and utilizing underlying sample relationships. Extensive experiments and analyses on public and practical datasets validate the proposed framework's superiority in cross-dom

关键词： Self-supervised learning

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Alternate control time delay systems with input delays

Alternate control time delay systems with input delays

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International Conference on information Science and Technology (ICIST)

作者： Xin Ming Liyuan Qi Dan Tu Wei Zhang Yuming Feng B. O. Onasanya School of Electronic and Information Engineering Chongqing Three Gorges University Wanzhou China School of Physical Education and Health Chongqing Three Gorges University Wanzhou China Key Laboratory of Intelligent Information Processing and Control Chongqing Three Gorges University Wanzhou China School of Three Gorges Artificital Intelligence Chongqing Three Gorges University Wanzhou China University of Ibadan Ibadan Nigeria

The alternate control systems have been elaborated in detail and have been applied in many areas, such as smart home, smart transportation, etc. However, although alternate control systems with input delays widely exist in real life, not so much attention has been given to them. This paper mainly studies the stability of alternate control systems with input delays. A new mathematical model of the alternate control system with time delay input is proposed. By using a Lyapunov function and linear matrix inequalities, the exponential stability conditions is given. At last, the effectiveness and feasibility of the method are verified through experimental simulations.

关键词： Delay effects Smart homes control systems Stability analysis Delays Smart transportation Linear matrix inequalities

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