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Annual Conference of the IEEE Industrial Electronics Society

作者： Qi Zhang Yongping Zhang Xiangdong Sun Dong Liu Fujin Deng Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an China Department of Electrical Enginnering Department of Energy Technology Aalborg University Aalborg Denmark

A soft-switching solution implemented to the traditional bidirectional DC/DC converter is developed. The soft-switching cell, which composed of three auxiliary switches, one resonant capacitor and one resonant inductor, is equipped in the traditional bidirectional DC/DC converter to realize circuit ZCT or ZVT operations in both energy transmission directions. Two driving methods are presented to charging energy for different storage applications according to the storage materials' electrical characteristics. There are two methods in buck mode. The first method with low conduction losses suffers from a hard turning off process in one of the auxiliary switches, while the others experience the soft operation. As for the other method, the zero voltage or zero current transmissions in all switches are realized, however, the relative higher but fixed conduction losses are introduced by the resonant circle. And the proposed topology of bidirectional soft-switching dc-dc converter (TASBC) performs ideal soft switching at boost operations. The characteristics of the proposed converter has been verified by MATLAB simulations and experimental results.

关键词： Turning Capacitors Equivalent circuits Mathematical model Topology Soft switching Inductors

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Research on high-accuracy gait recognition technique based on parallel genetic algorithm

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Journal of Information Hiding and Multimedia Signal processing 2018年第1期9卷 244-255页

作者： Lin, Xiao Jia Zhang, Fu Quan Xu, Lin Department of Computing and Information Technology Fujian Business University No. 19 Huang Pu Road Gulou District Fuzhou350012 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University School of Software Beijing Institute of Technology Room A9. 301 Juyuan Jinshan Jiyuan Fuzhou350008 China Innovative Information Industry Research Institute Fujian Normal University Fuqing Brunch of Fujian Normal University Campus County 1. Longjiang Road Fuqing Fuzhou350300 China

In the field of sports science, gait recognition has a wide range of applications. However, compared to other biometric technologies, it has the problem of low recognition accuracy. Therefore, a technique combining the parallel genetic algorithm based on hierarchical fair competition with neural network ensemble is proposed to be applied in gait recognition. First, parallel genetic algorithm is adopted to increase individual diversity, and only appropriate features are selected to train each neural network candidate. Then, a set of individual neural networks are selected to complete the neural network ensemble so as to minimize the generalization error and maximize the negative correlation. Experiments on the CASIA gait database demonstrate the effectiveness of the proposed gait recognition method. The results show that the proposed method has a higher recognition rate than the existing methods. © 2018, Ubiquitous International. All rights reserved.

关键词： Genetic algorithms

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The classification and retrieval of the image affective semantics based on integration of multi features and svm

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Journal of Information Hiding and Multimedia Signal processing 2018年第4期9卷 864-873页

作者： Chen, Hui Xu, Lin Zhang, Fu Quan College of Electronics and Information Science Fujian Jiangxia University Room 4#608Jincheng Garden Xindian Fuzhou350012 China Innovative Information Industry Research Institute Fujian Normal University Fuqing Brunch of Fujian Normal University Campus County 1# Longjiang Road Fuqing Fuzhou350300 China School of Computer Science & Technology Beijing Institute of Technology Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Room A9#301 Juyuan Jinshan Jiyuan Fuzhou350008 China

images contain rich emotions. The traditional image classification and retrieval methods mainly classify images according to the bottom visual features of the images. Most of them ignore the influence and effect of emotions. The image affective classification and retrieval method in this paper combines the bottom visual features with the high-level affective semantics. Aiming at the insufficiency of the retrieval based on the single bottom visual features, it combines the bottom image color feature with the shape feature, and establishes the image feature space. Aiming at the semantic gap between low-level visual features and high-level semantics of the image, it establishes the emotional semantic space through cognitive psychology experiments and factor analysis. The method in this paper uses SVM to fill the semantic blanks to achieve the affective semantics annotation of the image, maps feature space to the emotional space of the image to realize the classification and retrieval of the image affective semantics. The result of the experiment shows that this method improves the efficiency and performance of image retrieval, and provides an effective solution to the affective semantics research of images. © 2018, Ubiquitous International. All rights reserved.

关键词： Semantics

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Indoor 3D scene reconstruction for mobile robots using Microsoft kinect sensor 35

Indoor 3D scene reconstruction for mobile robots using Micro...

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第35届中国控制会议

作者： LI Jiang-Wei ZHENG Ding-Fu GUAN Zhi-Hong CHEN Chao-Yang JIANG Xiao-Wei ZHANG Xian-He College of Automation Huazhong University of Science and Technology The Key Laboratory of Ministry of Education for Image Processing and Intelligent Control (Huazhong University of Science and Technology) School of Information and Electrical Engineering Hunan University of Science and Technology College of Mechatronics and Control Engineering Hubei Normal University

ISBN: (纸本)9781509009107

3D mapping for unknown environments is a crucial issue for mobile service robots,which has many important applications in navigation and path *** this paper,we use Microsoft kinect sensor mounted on a mobile robot to obtain3 D *** the process,consistent frames of RGB-D data are captured and *** Closest Point(ICP)algorithm and incremental registration method are employed to perform the fine ***,we use OctoMap to store 3D map of octree representation,an efficient data ***,our results demonstrate the practical applicability and effectiveness of the proposed approach.

关键词： 3D mapping Kinect OctoMap Mobile Robots

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Spike-burst chimera states in an adaptive exponential integrate-and-fire neuronal network

arXiv

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arXiv 2019年

作者： Santos, Moises S. Protachevicz, Paulo R. Iarosz, Kelly C. Caldas, Iberê L. Viana, Ricardo L. Borges, Fernando S. Ren, Hai-Peng Szezech, José D. Batista, Antonio M. Grebogi, Celso Department of Physics Federal University of Paraná CuritibaPR80060-000 Brazil Graduate in Science Program - Physics State University of Ponta Grossa Ponta Grossa PR84030-900 Brazil Institute of Physics University of São Paulo São PauloSP05508-900 Brazil Center for Mathematics Computation and Cognition Federal University of ABC São Bernardo do CampoSP09606-045 Brazil Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xian University of Technology Xi'an710048 China Xian Technological University Xi'an710021 China Graduate in Science Program - Physics State University of Ponta Grossa Ponta Grossa PR84030-900 Brazil Institute for Complex Systems and Mathematical Biology King's College University of Aberdeen AberdeenAB24 3UE United Kingdom

Chimera states are spatiotemporal patterns in which coherence and incoherence coexist. We observe the coexistence of synchronous (coherent) and desynchronous (incoherent) domains in a neuronal network. The network is composed of coupled adaptive exponential integrate-and-fire neurons that are connected by means of chemical synapses. In our neuronal network, the chimera states exhibit spatial structures both with spikes and bursts activities. Furthermore, those desynchronised domains not only have either spike or burst activity, but we show that the structures switch between spikes and bursts as the time evolves. Moreover, we verify the existence of multicluster chimera states. Copyright © 2019, The Authors. All rights reserved.

关键词： Neural networks

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Distributed optimization problem for second-order multi-agent networks with only position interaction 35

Distributed optimization problem for second-order multi-agen...

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第35届中国控制会议

作者： TRAN Ngoc-Tu LIU Xiao-Kang WANG Yan-Wu School of Automation Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control(Huazhong University of Science and Technology) Ministry of Education Hubei Provincial Collaborative Innovation Center for New Energy Microgrid China Three Gorges University

ISBN: (纸本)9781509009107

In this paper, distributed optimization problem is investigated under a second-order multi-agent network, in which each agent is described as the double integrator. The multi-agent network is introduced for solving a large scale optimization problem by the cooperation of coupled agents. Based on the interaction over the network, the optimal solution of the problem can be obtained. Since the existing distributed algorithms for second-order multi-agent network enforce each agent to transmit complete information(both state information and derivation information of the independent variable, i.e., corresponded position and velocity information of the agent), this paper is motivated to design the distributed algorithm with only using the position information of neighbors, which reduces the requirement on communication bandwidth. With the help of Lyapunov analysis and La Sallel's Invariance Principle, the optimal solution is derived and the optimization problem is solved via the second-order multi-agent network. Finally, a numerical example is presented to illustrate the theoretical result.

关键词： Second-order multi-agent networks Distributed optimization Consensus

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VEHICLE DATA processing AND ANALYSIS PLATFORM BASED ON SPARK

VEHICLE DATA PROCESSING AND ANALYSIS PLATFORM BASED ON SPARK

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2017 2nd World Symposium on Mechanical and control Engineering（WSMCE 2017）

作者： Xiaolan Xie Tianwei Yuan Xiao Zhou College of Information Science and Engineering Guilin University of Technology Guangxi Universities Key Laboratory of Embedded Technology and Intelligent Information Processing Guilin University of Technology College of Mechanical and Control Engineering Guilin University of Technology

Based on the Spark big data analysis platform, using Yarn management resource scheduling problem, using Hbase as the storage mode of distributed data. Through the mass of car data, dig out the key factors that affect the safety of car performance, and show in the form of visualization. An effective scheme is put forward for the maintenance and fault detection of the user's vehicle. The experimental results show that the analysis method based on Spark platform can quickly, effectively and accurately analyze the key information and play a guiding and analytical role for users.

关键词： Vehicle Spark Hbase Platform

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RESEARCH ON CLOUD PLATFORM OF CASTINGS QUALITY MANAGEMENT BASED ON SPARK

RESEARCH ON CLOUD PLATFORM OF CASTINGS QUALITY MANAGEMENT BA...

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2017 2nd World Symposium on Mechanical and control Engineering（WSMCE 2017）

作者： Xiaolan Xie Xiao Zhou Tianwei Yuan College of Information Science and Engineering Guilin University of Technology Guangxi Universities Key Laboratory of Embedded Technology and Intelligent Information Processing Guilin University of Technology College of Mechanical and Control Engineering Guilin University of Technology

The casting quality management costs too much manpower, material and financial resources and is still lack of scientific status. In view of these conditions, this paper builds the casting quality management cloud platform based on Spark. Build and deploy Spark Standalone on the local computer. Parallel computing and cloud storage mechanism are implemented by Spark. Task management scheduling is implemented by Standalone. The foundry enterprise uses this platform to carry on the big data analysis to the influence factors of casting quality in the casting production. According to the results of the analysis, the scientific guidance and efficient scheduling of the manufacturing process are carried out. The quality management of castings is standardized and scientific. The scrap rate of castings is reduced. Through the large data analysis of various factors affecting the quality of casting, a set of scientific and efficient management scheme is provided.

关键词： Castings quality management Spark Cloud platform Big data

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Deep learning for robust outdoor vehicle visual tracking

Deep learning for robust outdoor vehicle visual tracking

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Ji-ng Xin Xing Du Jian Zhang Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an P.R.China Faculty of Engineering and Information Technology University of Technology (UTS) Sydney Australia

ISBN: (纸本)9781509060689

Robust visual tracking for outdoor vehicle is still a challenging problem due to large appearance variations caused by illumination variation, occlusion and scale variation, etc. In this paper, a deep-learning-based approach for robust outdoor vehicle tracking is proposed. Firstly, a stacked denoising auto-encoder is pre-trained to learn the feature representation way of images. Then, a k-sparse constraint is added to the stacked denoising auto-encoder and the encoder of k-sparse stacked denoising auto-encoder (kSSDAE) is connected with a classification layer to construct a classification neural network. After fine-tuning, the classification neural network is applied to online tracking under particle filter framework. Extensive tracking experiments are conducted on a challenging single object online tracking evaluation platform benchmark to verify the effectiveness of our tracker. Experiments show that our tracker outperforms most state-of-the-art trackers.

关键词： Robustness Object tracking Machine learning Feature extraction Biological neural networks Visualization

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INTERNET OF VEHICLES DATA SERVICE SYSTEM BASED ON CLOUD PLATFORM

INTERNET OF VEHICLES DATA SERVICE SYSTEM BASED ON CLOUD PLAT...

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2017 2nd World Symposium on Mechanical and control Engineering（WSMCE 2017）

作者： Xiaolan Xie Qiangqing Zheng Zhihong Guo College of Information Science and Engineering Guilin University of Technology Guangxi Universities key Laboratory of Embedded Technology and Intelligent Information Processing (Guilin University of Technology) College of Mechanical and Control Engineering Guilin University of Technology

The technology of Internet of automobile is designed to solve problems in field of transportation about safety, efficiency and environment. The system is based on data supplied by hardware in vehicles, design a mobile client APP and a management system for sellers through cloud computing, mass data distribution technology, which achieve the automobile driving data collection and analysis, fault reminders, track search, vehicle positioning, tips information release and other functions, and also achieve the intelligent analysis of automobile driving data. To some extent, the technology solves the problems such as automobile mileage not clear, hard to locate the automobile location, complicated ownership transfer, unable to self-help troubleshooting, hard to find the nearest repair point and so on.

关键词： Internet of vehicles BDS Automotive hardware Hadoop

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