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Protection of Large Sparse Network Through Optimal Cropped Depth-First Traversal Tree

IEEE Transactions on Network Science and Engineering 2025年

作者： Wei, Wei Hu, Qiuyuan Zhang, Qinghui Li, Peng Henan University of Technology Key Laboratory of Grain Information Processing and Control Ministry of Education Zhengzhou450001 China Henan University of Technology Henan Key Laboratory of Grain Storage Information Intelligent Perception and Decision Making Zhengzhou450001 China Henan University of Technology Henan Grain Big Data Analysis and Application Engineering Research Center Zhengzhou450001 China Beijing Institute of Technology No. 5 Zhongguancun South Street Haidian District Beijing100086 China

The robustness of the network is its ability to withstand unexpected failures. There is an urgent need to enhance the robustness of sparse networks as they are prone to breakage. Among the various ways to enhance network robustness measured by the edge connectivity of the entire network, shielding candidate edges is a popular method when redundant edges are not affordable. However, existing tree-cutting favors dense graphs with exponential cropped-tree growth of search space, but the search space only scales linearly in sparse graphs. We explore sparse-graph limitations by extending cropping to maximum depth while maintaining sublinear overhead, leveraging ancestor-node constraints and cropping-chain theorems for optimal efficiency. Compared with the optimal algorithm, the results in representative network types show that the robustness measurement of small-scale graphs can be enhanced to 100%, and the ratio of acceleration can be greater than 105. In large-scale graphs with millions of nodes, robustness can be improved to over 99%, while the time can be as low as tens of seconds. © 2013 IEEE.

关键词： Trees (mathematics)

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Volume Measuring Method for Forming Additive Manufacturing Based on SGBM

Volume Measuring Method for Forming Additive Manufacturing B...

引用

Chinese Automation Congress (CAC)

作者： Ruidong Xie Haichuan Yang Yingmin Yi Qimeng Shi keying Wang Xiaolin Fan Key Lab of Manufacturing Equipment of Shaanxi Province Xi’an University of Technology Xi’an China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an China

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

For volume measurement problems in the processes of additive manufacturing, a volume measurement method is proposed through using the SGBM algorithm in this paper. In this method, the internal and external parameters of the camera are calibrated by the binocular vision system. And the image processes by SGBM are performed for the image acquired by binocular stereo vision system. The processes are including filtering, correction and stereo matching to obtain the disparity information of the object to be tested in the left and right cameras. The volume of the work-piece to be tested can be obtained by the calculation that measured the three-dimensional coordinate information through the disparity information. The experimental results illustrate that the method is of certain reliability and accuracy for volume measurement.

关键词： Cameras Calibration Volume measurement Three-dimensional printing Mathematical model Measurement by laser beam Three-dimensional displays

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Resilient Distributed Predefined Time Secondary control for Cyber-Physical Microgrids

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IET Renewable Power Generation 2025年第1期19卷

作者： Tan, Junfeng Zhang, Fan Huang, Yanlu Zhao, Shuai Su, Hongyu China Southern Power Grid Digital Grid Research Institute Co. Ltd. China Southern Power Grid Artificial Intelligence Technology Co. Ltd. Guangzhou China School of Artificial Intelligence and Automation and Technology and also with the Key Laboratory of Image Processing and Intelligent Control Ministry of Education Huazhong University of Science and Technology Wuhan China

This paper proposed a resilient distributed predefined-time sliding mode control for islanded AC microgrids with external disturbances caused by noisy circumstances or cyber-attacks. By utilizing the predefined-time convergence theory, the voltage regulation and frequency restoration as well as active power sharing can be achieved within a predefined time, which is directly equal to an adjustable parameter. Furthermore, based on the integral sliding mode control approach, the proposed method can completely compensate the external disturbance. Different from some voltage control methods based on complex second-order consensus, a novel secondary controller is designed by adopting the virtual control technique, such that the voltage regulation can be achieved under a first-order consensus with a corresponding tracking controller. In addition, the direct Lyapunov method is utilized to prove the stability of islanded AC microgrids under the proposed controller, and the analysis of predefined-time convergence is also given. Finally, case studies on a microgrid test system with four distributed generator is built in the MATLAB/SimPowerSystems software environment are conducted to demonstrate the effectiveness and superior performance of the proposed control scheme. © 2025 The Author(s). IET Renewable Power Generation published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology.

关键词： Robust control

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Correction to: Visual Servoing of Unknown Objects for Family Service Robots

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Journal of intelligent & Robotic Systems 2022年第4期106卷 1-1页

作者： Xin, Jing Dong, Caixia Zhang, Youmin Yao, Yumeng Gong, Ailing Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an China Department of Mechanical Industrial and Aerospace Engineering Concordia University Montreal Canada

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An Optimal Tracking control Method with Q-learning for Discrete-time Linear Switched System

An Optimal Tracking Control Method with Q-learning for Discr...

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第三十九届中国控制会议

作者： Shangwei Zhao Jingcheng Wang Hongyuan Wang Haotian Xu Automation Department Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Autonomous Systems and Intelligent Control International Joint Research Center Xi'an Technological University

In this paper, a novel approach combining Q-learning method and two-stage optimization is proposed to solve linear quadratic tracking(LQT) problem for unknown discrete-time switched system. An augmented system consisting of switched subsystem and reference trajectory is built and Q-learning method is introduced to identify each subsystem without requiring any knowledge of augmented system state dynamics. Then, based on the optimal control laws for each subsystem obtained by Q-learning in advance, the optimal hybrid control law including switching mode and control input is obtained by the two-stage optimization framework. Furthermore, the optimality of the algorithm is proved. Finally, a simulation case is used to testify the effectiveness of the proposed algorithm.

关键词： Tracking control Linear switched system Q-learning

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A method of laser point temperature detection based on CNN

A method of laser point temperature detection based on CNN

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Chinese Automation Congress (CAC)

作者： Ruidong Xie Haichuan Yang Yingmin Yi Qimeng Shi keying Wang Jiabin Huang Key Lab of Manufacturing Equipment of Shaanxi Province Xi’an University of Technology Xi’an China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an China

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

There has been a direct relationship between the temperature of the laser point and the quality of the casting in the process of the 3D printing. In the paper, a method based on convolutional neural network (CNN) was proposed to estimate the temperature of the laser point. The collected temperature data used were trained by the deep-learning method. A new structure of the model was proposed on the part of the CNN model, which improved from original LeNet. The process of the prediction for the testing set was carried out through the new model. The unknown temperature in the testing set can be estimated. The experimental result illustrates that the proposed method is satisfactory.

关键词： Laser modes Temperature measurement Training Temperature distribution Surface emitting lasers Testing Measurement by laser beam

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The Research of the Accessibility and Transitivity of Topological Group

The Research of the Accessibility and Transitivity of Topolo...

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International Conference on Virtual Reality and intelligent Systems (ICVRIS)

作者： Ji Zhan-Jiang Shi Wei School of Information and Electronic Engineering Wuzhou University China Guangxi Colleges and Universities Key Laboratory of Image Processing and Intelligent Information System Wuzhou University China Guangxi Colleges and Universities Key Laboratory of Professional Software Technology Wuzhou University China Wuzhou Vocational College China

The accessibility and transitivity have an important significance in terms of theory and application. The concept of the accessibility and transitivity are introduced in this paper. We study their dynamical properties. The following result are obtained: (l)Let (K , G ) be the hyperspace of (X , G ). Then ( X , G ) is accessible if and only if (K , G ) is accessible; (2) Let (K , G) be the hyperspace of (X , G). Then (X , G ) is transitive if and only if (K , G ) is transitive. These results enriched the theory of the accessibility and transitivity of topological group.

关键词： Virtual reality intelligent systems

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Pool-Based Unsupervised Active Learning for Regression Using Iterative Representativeness-Diversity Maximization (iRDM)

arXiv

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arXiv 2020年

作者： Liu, Ziang Jiang, Xue Luo, Hanbin Fang, Weili Liu, Jiajing Wu, Dongrui Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology China School of Civil Engineering and Mechanics Huazhong University of Science and Technology China

Active learning (AL) selects the most beneficial unlabeled samples to label, and hence a better machine learning model can be trained from the same number of labeled samples. Most existing active learning for regression (ALR) approaches are supervised, which means the sampling process must use some label information, or an existing regression model. This paper considers completely unsupervised ALR, i.e., how to select the samples to label without knowing any true label information. We propose a novel unsupervised ALR approach, iterative representativeness-diversity maximization (iRDM), to optimally balance the representativeness and the diversity of the selected samples. Experiments on 12 datasets from various domains demonstrated its effectiveness. Our iRDM can be applied to both linear regression and kernel regression, and it even significantly outperforms supervised ALR when the number of labeled samples is small. Copyright © 2020, The Authors. All rights reserved.

关键词： Regression analysis

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Transfer Learning for Motor imagery Based Brain-Computer Interfaces: A Complete Pipeline

arXiv

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arXiv 2020年

作者： Wu, Dongrui Jiang, Xue Peng, Ruimin Kong, Wanzeng Huang, Jian Zeng, Zhigang Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Zhejiang Key Laboratory for Brain-Machine Collaborative Intelligence Hangzhou Dianzi University Hangzhou310018 China

Transfer learning (TL) has been widely used in motor imagery (MI) based brain-computer interfaces (BCIs) to reduce the calibration effort for a new subject, and demonstrated promising performance. While a closed-loop MI-based BCI system, after electroencephalogram (EEG) signal acquisition and temporal filtering, includes spatial filtering, feature engineering, and classification blocks before sending out the control signal to an external device, previous approaches only considered TL in one or two such components. This paper proposes that TL could be considered in all three components (spatial filtering, feature engineering, and classification) of MI-based BCIs. Furthermore, it is also very important to specifically add a data alignment component before spatial filtering to make the data from different subjects more consistent, and hence to facilitate subsequential TL. Offline calibration experiments on two MI datasets verified our proposal. Especially, integrating data alignment and sophisticated TL approaches can significantly improve the classification performance, and hence greatly reduces the calibration effort. Copyright © 2020, The Authors. All rights reserved.

关键词： Electroencephalography

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Bioimage-based protein subcellular location prediction： a comprehensive review

引用

Frontiers of Computer Science 2018年第1期12卷 26-39页

作者： Ying-Ying XU Li-Xiu YAO Hong-Bin SHEN Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai 200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China

Subcellular localization of proteins can provide key hints to infer their functions and structures in cells. With the breakthrough of recent molecule imaging techniques, the usage of 2D bioimages has become increasingly popular in automatically analyzing the protein subcellular location pat- terns. Compared with the widely used protein 1D amino acid sequence data, the images of protein distribution are more intuitive and interpretable, making the images a better choice at many applications for revealing the dynamic char- acteristics of proteins, such as detecting protein translocation and quantification of proteins. In this paper, we systemati- cally reviewed the recent progresses in the field of automated image-based protein subcellular location prediction, and clas- sified them into four categories including growing of bioim- age databases, description of subcellular location distribution patterns, classification methods, and applications of the pre- diction systems. Besides, we also discussed some potential directions in this field.

关键词： bioimage informatics protein subcellular loca-tion prediction global and local features multi-location pro-tein recognition

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