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Future Development Trend of Multimedia Network

IOP Conference Series: Materials Science and Engineering 2018年第1期466卷

作者： Li Huang Kai Zhang Wei Hu Chengcheng Li College of Computer Science and Technology Wuhan University of Science and Technology Hubei Wuhan 430081 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Hubei Wuhan 430081 China Key Laboratory of Metallurgical Equipment and Control Technology Ministry of Education Wuhan University of Science and Technology Hubei Wuhan 430081 China

With the rapid development of computer network, multimedia technology has gradually spread throughout all aspects of people's life. This article, based on the concept and characteristics of multimedia, expounds the application of multimedia technology and the trend of future development. It makes a heavy analysis of multimedia teaching and analyses the meaning and advantage of multimedia teaching.

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Analysis of underwater locomotion and improvement of FroBot

Analysis of underwater locomotion and improvement of FroBot

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2016 IEEE International Conference on Advanced intelligent Mechatronics, AIM 2016

作者： Yi, Yang Jianqing, Zhang Han, Xu Maokuan, Chen Lu, Zhang Zhongjing, Zhu School of Automation Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing China Department of Electronic Engineering School of Information Science and Technology Tsinghua University Beijing China

ISBN: (纸本)9781509020652

The main characteristic of FroBot is the dual-swing-legs propulsion mechanism, and it is necessary for us to conduct a series of experiments to study its propulsion model, both on land and underwater. As the propulsion of FroBot comes from the interaction force between caudal fins and water when it locomotes underwater, this paper presents an analysis about the propulsion and control of angle Θ. Then a number of underwater hydrodynamic simulations and analysis are also conducted to get a better control in reality. Finally, on the basis of propulsion model and experiments, we present the latest mechanical structure designs and further improvements to eliminate the limitations exposed in the previous generations of FroBot. © 2016 IEEE.

关键词： Propulsion

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Parameters Optimization Improvement of SVM on Load Forecasting

Parameters Optimization Improvement of SVM on Load Forecasti...

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International Conference on intelligent Human-Machine systems and Cybernetics, IHMSC

作者： Meiyan Yang Weiqin Li Haiying Zhang Huiqin Wang Complex System Control and Intelligent Information Processing Laboratory Xi'an University of Technology Xi'an China Environmental Monitoring Station in Xi'an Xi'an China

ISBN: (纸本)9781509007691

The SVM regression algorithm has shorter convergence time, high precision, and less adjustable parameters, the structure can be confirmed difficultly in the power load forecasting. In view of the grid search method of parameter optimization in support vector machine (SVM) exists the shortage of high complexity and computation, an improved grid search method is revealed, which is based on the idea of uniform particles, this paper apply it to the load forecast. Compared with the traditional grid method, the improved grid search method can effectively reduce the computational complexity and ensure the accuracy of the prediction precision. We illuminate the method of new ideas, and prove the feasibility of this view through the experiment.

关键词： Support vector machines Search methods Load forecasting Kernel Optimization Standards Training

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Shadow lane robust detection by image signal local reconstruction

International Journal of Signal Processing, Image Processing...

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International Journal of Signal processing, Image processing and Pattern Recognition 2016年第3期9卷 89-102页

作者： Du, Mingfang Junzheng, Wang Nan, Li Duoyang, Li School of Automation Beijing Union University Beijing China State Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing China Beijing Key Laboratory of Information Service Engineering

In order to resolve shadow interference and slow image processing speed in the visual navigation of unmanned vehicles on city roads, a new lane detection algorithm based on the Inverse Perspective Mapping(IPM) of vertical sub-image reconstruction using local bands was proposed. The lane’s IPM aerial image was obtained using the projective transformation of three-dimensional images of city roads. The ROI portion of the IPM map was decomposed and analyzed using the sym3 wavelet, and after analyzing and comparing the experimental results the first and second levels of the vertical sub images were selected for the reconstruction, compression, and removal of shadows from the original image. The Canny algorithm was proposed and adopted in order to extract the edge features of the reconstructed images according to real-time road image quality. A modified, polar angle, constraint-based, fast Hough transform was used to locate the candidate lanes. Finally, the main control point, straight-line-fitting algorithm was used to fit the final lanes, which achieved the precise location and recognition of the lane lines. The California Polytechnic lane data set, a public data platform, which is now widely used in road visual recognition fields around the world, was selected for the testing and verification of the algorithm. The results of the experiment and actual operation indicated that, despite having a storage space of approximately one tenth the size of similar algorithms, this detection algorithm effectively solves the issue of shadow removal, meets the real-time requirements of roadway image processing systems for unmanned vehicles with a recognition time of less than 20ms, and is robust. © 2016 SERSC.

关键词： Wavelet transforms

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Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

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Nature 2024年第8003期627卷 347-357页

作者： Ken Suzuki Konstantinos Hatzikotoulas Lorraine Southam Henry J Taylor Xianyong Yin Kim M Lorenz Ravi Mandla Alicia Huerta-Chagoya Giorgio E M Melloni Stavroula Kanoni Nigel W Rayner Ozvan Bocher Ana Luiza Arruda Kyuto Sonehara Shinichi Namba Simon S K Lee Michael H Preuss Lauren E Petty Philip Schroeder Brett Vanderwerff Mart Kals Fiona Bragg Kuang Lin Xiuqing Guo Weihua Zhang Jie Yao Young Jin Kim Mariaelisa Graff Fumihiko Takeuchi Jana Nano Amel Lamri Masahiro Nakatochi Sanghoon Moon Robert A Scott James P Cook Jung-Jin Lee Ian Pan Daniel Taliun Esteban J Parra Jin-Fang Chai Lawrence F Bielak Yasuharu Tabara Yang Hai Gudmar Thorleifsson Niels Grarup Tamar Sofer Matthias Wuttke Chloé Sarnowski Christian Gieger Darryl Nousome Stella Trompet Soo-Heon Kwak Jirong Long Meng Sun Lin Tong Wei-Min Chen Suraj S Nongmaithem Raymond Noordam Victor J Y Lim Claudia H T Tam Yoonjung Yoonie Joo Chien-Hsiun Chen Laura M Raffield Bram Peter Prins Aude Nicolas Lisa R Yanek Guanjie Chen Jennifer A Brody Edmond Kabagambe Ping An Anny H Xiang Hyeok Sun Choi Brian E Cade Jingyi Tan K Alaine Broadaway Alice Williamson Zoha Kamali Jinrui Cui Manonanthini Thangam Linda S Adair Adebowale Adeyemo Carlos A Aguilar-Salinas Tarunveer S Ahluwalia Sonia S Anand Alain Bertoni Jette Bork-Jensen Ivan Brandslund Thomas A Buchanan Charles F Burant Adam S Butterworth Mickaël Canouil Juliana C N Chan Li-Ching Chang Miao-Li Chee Ji Chen Shyh-Huei Chen Yuan-Tsong Chen Zhengming Chen Lee-Ming Chuang Mary Cushman John Danesh Swapan K Das H Janaka de Silva George Dedoussis Latchezar Dimitrov Ayo P Doumatey Shufa Du Qing Duan Kai-Uwe Eckardt Leslie S Emery Daniel S Evans Michele K Evans Krista Fischer James S Floyd Ian Ford Oscar H Franco Timothy M Frayling Barry I Freedman Pauline Genter Hertzel C Gerstein Vilmantas Giedraitis Clicerio González-Villalpando Maria Elena González-Villalpando Penny Gordon-Larsen Myron Gross Lindsay A Guare Sophie Hackinger Liisa Hakaste Sohee Han Andrew T Hattersley Christian Herder Momoko Horikoshi Annie-Green Howard Willa Centre for Genetics and Genomics Versus Arthritis Centre for Musculoskeletal Research Division of Musculoskeletal and Dermatological Sciences University of Manchester Manchester UK. Department of Diabetes and Metabolic Diseases Graduate School of Medicine University of Tokyo Tokyo Japan. Department of Statistical Genetics Osaka University Graduate School of Medicine Suita Japan. Institute of Translational Genomics Helmholtz Zentrum München German Research Center for Environmental Health Neuherberg Germany. konstantinos.hatzikotoulas@helmholtz-munich.de. Institute of Translational Genomics Helmholtz Zentrum München German Research Center for Environmental Health Neuherberg Germany. Center for Precision Health Research National Human Genome Research Institute National Institutes of Health Bethesda MD USA. British Heart Foundation Cardiovascular Epidemiology Unit Department of Public Health and Primary Care University of Cambridge Cambridge UK. Heart and Lung Research Institute University of Cambridge Cambridge UK. Department of Epidemiology School of Public Health Nanjing Medical University Nanjing China. Department of Biostatistics and Center for Statistical Genetics University of Michigan Ann Arbor MI USA. Corporal Michael J. Crescenz VA Medical Center Philadelphia PA USA. Department of Systems Pharmacology and Translational Therapeutics University of Pennsylvania Perelman School of Medicine Philadelphia PA USA. Department of Genetics University of Pennsylvania Perelman School of Medicine Philadelphia PA USA. Programs in Metabolism and Medical and Population Genetics Broad Institute of Harvard and MIT Cambridge MA USA. Diabetes Unit and Center for Genomic Medicine Massachusetts General Hospital Boston MA USA. TIMI Study Group Division of Cardiovascular Medicine Brigham and Women's Hospital Harvard Medical School Boston MA USA. William Harvey Research Institute Barts and the London School of Medicine and Dentistry Queen Mary University of London L

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes and molecular mechanisms that are often specific to cell type. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.

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Nonnegative Edge Consensus of Networked Linear systems

Nonnegative Edge Consensus of Networked Linear Systems

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第35届中国控制会议

作者： Xiaoling Wang Housheng Su Xiaofan Wang Guanrong Chen Department of Automation Shanghai Jiaotong Universityand Key Laboratory of System Control and Information ProcessingMinistry of Education of China School of Automation Image Processing and Intelligent Control Key Laboratory of Education Ministry of ChinaHuazhong University of Science and Technology Department of Electronic Engineering City University of Hong Kong

ISBN: (纸本)9781509009107

In this paper,nonnegative edge consensus of systems steered by general linear dynamics on directed network is *** the new approach,one first endows dynamics to each directed edge and then designs a distributed edge consensus protocol guiding all edges to reach a common *** the help of line graph theory,it is proved that strongly connected network can ensure reaching nonnegative edge consensus,if the initial conditions of all edges are *** simulations are provided to verify the theoretical results.

关键词： Networked system Nonnegative edge consensus Distributed algorithm Line graph

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An overview of coordinated control for multi-agent systems subject to input saturation

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Perspectives in Science 2016年 7卷 133-139页

作者： Xiaoling Wang Housheng Su Xiaofan Wang Guanrong Chen Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China School of Automation Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 China Department of Electronic Engineering City University of Hong Kong Hong Kong China

Coordinated control of multi-agent systems has widespread application in engineering such as unmanned aerial vehicles and unmanned ground vehicles. Due to the fact that input saturation can lead a control system to deterioration and instability, a lot of efforts have been devoted to investigating this subject of great importance. The present article offers a survey of recent developments on coordinated control of multi-agents systems subject to input saturation. Some preliminaries about graph theory, stability theory and input saturation are first provided, followed by some important results in the area, which are categorized into semi-global and global coordinated controls. Future research topics are finally discussed.

关键词： Multi-agent system Coordinated control Consensus tracking Input saturation Low-and-high-gain feedback

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Architectural distortion recognition based on a subclass technique and the sparse representation classifier

Architectural distortion recognition based on a subclass tec...

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International Congress on Image and Signal processing, BioMedical Engineering and Informatics (CISP-BMEI)

作者： Xiaoming Liu Leilei Zhai Ting Zhu Zhou Yang School of Automation Huazhong University of Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan China College of Computer Science and Technology Wuhan University of Science and Technology Wuhan China

ISBN: (纸本)9781509037117

Architectural distortion is the third most common sign of breast cancer in mammograms. The accurate recognition is important for computer aided diagnosis of breast cancer. However, due to the subtle symptom and complex structures in the mammogram images, it is difficult to recognize whether a region of interest (ROI) is truly an architectural distortion. In this paper, we proposed a new method for architectural distortion recognition. In the proposed method, several texture features are extracted for each region of interest, including features from GLCM matrix, spiculated related features, entropy features, etc. Feature selection is obtained by a sub-classes clustering based multi-task learning method (SMTL), which can utilize the discriminative label information and reflect the multi-clustering characteristic of the data samples. Finally, the powerful sparse representation based classifier is used for the classification of AD or non-AD. The proposed method has been tested on DDSM dataset and compared with several other methods, the experimental results showed the effectiveness of the proposed method.

关键词： Feature extraction Distortion Entropy Training Mammography Delta-sigma modulation Breast cancer

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Data-Based Health State Analysis for the Axle of High Speed Train

Data-Based Health State Analysis for the Axle of High Speed ...

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International Conference on Computational Intelligence and Security

作者： Guo Xie Minying Ye Xinhong Hei Jinwei Zhao Fucai Qian Xi'an University of Technology Xi'an China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an China

Taking into account that the present popular methods, such as the judgement of the axle failure based on temperature threshold, and the early warning of axle based on real-time temperature analysis, cannot analyze the changing of performance trends, a health state analysis method for the axle of high-speed train based on long-term temperature monitoring data is proposed in this paper, which including the following main steps: (1) Preprocessing of the original data to correct the singular zero value and complement the missing values, (2) Smoothing of the processed data in order to automatically extract the beginning and end points of every temperature rising stage of axles, (3) Establishment of the calculation method of temperature rising rate, and evaluating the health sate of axles based on the temperature rising rate. Finally, the proposed method is validated based on the data from a test line, the results demonstrate the effectiveness and practicability of the method.

关键词： Axles Temperature distribution Aging Safety Data mining Fault diagnosis Monitoring

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A sub-pixel SAR and optical image registration method 66

A sub-pixel SAR and optical image registration method

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66th International Astronautical Congress 2015: Space - The Gateway for Mankind's Future, IAC 2015

作者： Zhang, Hanmo Lu, Shan You, Hongjian Shanghai Key Laboratory of Aerospace Intelligent Control Technology Shanghai Aerospace Control Technology Institution China Key Laboratory of Geo-Spatial Information Processing and Application System Technology Institute of Electronics Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781510818934

Automatic image registration method is important because data amount acquired and processed is increasingly heavy. For SAR and optical sensor images, it is important to align the same object shown in different images from multi sensors. Considering extracting and matching features in SAR and optical images, a template registration strategy is proposed in this paper. A particular similarity measurement which is robust in matching remote sensing images of general sceneries is hardly to construct. Being the invertible and essential tendency nowadays in the field of earth observation, high pixel-resolution images can offer much more information of the ground. Thus subpixel image registration methods have been researched, among which can successfully achieve 1/50 pixel level accuracy in matching homologous sensor image. This paper firstly investigated the performance of 2D Gaussian fitting for low correlated synthetic images and real satellite images acquired by Radat SAT-2, COSMO and TerraSAR-X satellites. Three algorithms for subpixel locating have been utilized with consideration of the low correlated coefficient peak and corrupted shape of neighbourhood around it. The results show 2D Gaussian fitting is the most efficient on noisy coefficient maps. Then a subpixel image registration method for SAR and optical images is proposed. Normalized gradient correlation (NGC) algorithm is used to solve the problem of different intensity property at first, and by combining 2D Gaussian fitting to relocate matched points at a subpixel level accuracy. Experiment results have shown that the proposed method has enough capabilities in handling differences between images from multi-sensors. The proposed approach has been found to be simple and efficient in implementation with a low computation load. And the most important performance is the results presented here have achieved matching accuracy within 1 pixel.

关键词： Image registration

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