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2016年IEEE/INFORMS服务运筹、物流与信息化国际会议

作者： Jian Liu Gang Xiong Xiuqin Shang Timo R.Nyberg Yiming Wang Tongkai Ji The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences College of Information Science and Technology Beijing University of Chemical Technology Cloud Computing Center Chinese Academy of Sciences Department of Industrial Engineering and Management School of ScienceAalto University Beijing Engineering Research Center of Intelligent Systems and Technology Institute of AutomationChinese Academy of Sciences

Innovation is changing the world every day by offering new technical solutions for the society, and the technology development powered by innovation has been changing the operation and structure of traditional manufacturing. Social manufacturing is the new trend of manufacturing development, especially in the field of apparel industry. Social manufacturing can create opportunities for customers to participate in the produce process of tailoring, and to make more personalizing clothes, which will also benefit for the related companies' brand making process. With the assistance of internet technology and industry globalization, we can establish several modes about the trend of social manufacturing and new related technology, social manufacturing can also prompt the international division of labor by reducing the producing costs and enlarging the market capacity, we will analyze the advance of Sino-Finland cooperation in the field of innovation and apparel industry, the international cooperation in manufacturing industry will benefit both customers and industry revolution with the assistance of social manufacturing.

关键词： social manufacturing innovation apparel industry international cooperation

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Change management on improvement project for success

Change management on improvement project for success

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IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI

作者： Guangyu Xiong Aping Zhao Timo R. Nyberg Gang Xiong Department of Industrial Engineering and Management School of Science Helsinki Finland FINLAND Internal Consulting Group Beijing China Cloud Computing Center Chiense Academy of Sciences Dongguan China Teamosuking Investment Project Management CO Ltd Nanjing CHINA Department of Industrial Engineering and Management Aalto University AALTO FINLAND The State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Science Beijing P.R. China

ISBN: (纸本)9781509029280

A success of an improvement project on solving a problem in an organization is not only depending an appropriate methodology on problem solving with Lean, TOC or 6 sigma with relevant tools, but also it is very important to have an appropriate methodology and process on change management integrated with project management during the improvement project. This paper describes the principle of change management based on existing literature, and illustrates a case study on how an improvement project apply theory and methodology of change management to make successful change. Firstly, the literature review relevant to concerns for support change in a business environment is introduced. General tools, models, and solutions to make a change effectively in an organization are explained. Next one framework with relevant tools and models are selected to the case study that conducts a manufacturing with ETO (engineering-to-order) product. Next regarding the readiness for change, and the implementation of the change the paper introduces how the selected framework and the tools and models on change management is integrated with project management during different phases of the improvement project. As a result, it shows a success both from improvement project and change management perspective. In particular, achievement in the change management is not only showing the successful improvement project, but also the organization realizes another great positive change - people's improved behavior on daily work. Hence a long-term benefit from the improvement project and change management is gained. The achievement shows that similar approach on change management in an organization may be applied to more organizations.

关键词： Problem-solving Project management Companies Industrial engineering Bibliographies

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A New Logistic Map Based Chaotic Biogeography-based Optimization Approach for Cluster Analysis

A New Logistic Map Based Chaotic Biogeography-based Optimiza...

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2016 IEEE International Conference on Progress in Informatics and computing

作者： Shui-Hua Wang Hui-Min Lu Yu-Jie Li Yang Wang Zhi-Min Chen Yu-Min Wei Wen-Juan Jia Fang-Yuan Liu Yu-Dong Zhang School of Computer Science and Technology Nanjing Normal University Hunan Provincial Key Laboratory of Network Investigational Technology Hunan Policy Academy Department of Electrical Engineering The city college of New YorkCUNY Department of Mechanical and Control Engineering Kyushu Institute of Technology School of Information Engineering Yangzhou University School of Physics and Electronic Engineering Taizhou University School of Electronic Information Shanghai Dianji University School of Energy and Mechanical Engineering Nanjing Normal University Key Laboratory of Intelligent Computing and Information Processing in Fujian Provincial University Quanzhou Normal University

Cluster analysis is important in scientific and industrial fields. In this study, we proposed a novel chaotic biogeography-based optimization(CBBO) method, and applied it in centroid-based clustering methods. The results over three types of simulation data showed that this proposed CBBO method gave better performance than chaotic particle swarm optimization, genetic algorithm, firefly algorithm, and quantum-behaved particle swarm optimization. In all, our CBBO method is effective in centroid-based clustering.

关键词： chaotic biogeography-based optimization cluster analysis centroid-based clustering simulation particle swarm optimization

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Classification of facial diagnosis gloss in Chinese medicine based on different algorithms

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Chinese journal of integrative medicine 2016年 2016 Apr 4页

作者： Fu-Feng Li Rui Zhou Guo-Zheng Li Rui-Wei Zhao Four Diagnosis Laboratory of Traditional Chinese Medicine Shanghai University of Traditional Chinese Medicine Shanghai 201203 China. li_fufeng@***. Four Diagnosis Laboratory of Traditional Chinese Medicine Shanghai University of Traditional Chinese Medicine Shanghai 201203 China. The Key Laboratory of Embedded System and Service Computing Ministry of Education Department of Control Science & Engineering Tongji University Shanghai 201804 China.

OBJECTIVE:To design a face gloss classification model and to provide an automatic and quantitative approach for the diagnosis of Chinese medicine (CM) based on the face images. METHODS:To classify the face gloss images into two groups (gloss and non-gloss), feature extraction methods were applied to the original images. The original images were supposed to obtain a more ideal representation in which gloss information was better revealed in four color spaces [including red, green, blue (RGB), hue, saturation, value (HSV), Gray and Lab]. Principal component analysis (PCA), 2-dimensional PCA (2DPCA), 2-directional 2-dimensional PCA [(2D)PCA], linear discriminant analysis (LDA), 2-dimensional LDA (2DLDA), and partial least squares (PLS) were used as the feature extraction methods of face gloss. k nearest neighbor was used as the classifification method. RESULTS:All the six feature extraction methods were useful in extracting information of face gloss, especially LDA, which had the best prediction accuracy in the 4 color spaces. The average accuracy of LDA in the Lab was 7%-10% higher than that of PCA, 2DPCA, (2D)PCA and 2DLDA P<0.05). The prediction accuracy of LDA reached 98% in the Lab color space and showed practical usage in clinical diagnosis. The consistent rate between the CM experts and the facial diagnosis system was 81%. CONCLUSION:A computer-assisted classifification model was designed to provide an automatic and quantitative approach for the gloss diagnosis of CM based on the face images.

关键词： Chinese medicine computer-assisted face gloss diagnosis feature extraction image processing

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A Survey on Big Data for Human Body Shape

A Survey on Big Data for Human Body Shape

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2016年IEEE/INFORMS服务运筹、物流与信息化国际会议

作者： Hongli Peng Xiuqin Shang Chao Guo Gang Xiong Timo R.Nyberg Dong Fan Yiming Wang The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences College of Information Science and Technology Beijing University of Chemical Technology Qingdao Academy of Intelligent Industries Beijing Engineering Research Center of Intelligent Systems and Technology Institute of AutomationChinese Academy of Sciences Cloud Computing Center Chinese Academy of Sciences Department of Industrial Engineering and Management School of ScienceAalto University

In recent years, the rapid development of network and E-commerce technologies, promotes the development of human body big data. New technologies, such as 3D scanning and 3D printing will improve our life quality. The new socialized manufacturing network composed of Io T, advanced logistics network and 3D printers. Everyone is allowed to have chance to participate in any process of the whole production manufacturing lifecycle by some ways, such as crowdsourcing. Boosts the creation, production and consumption patterns of individuation, real-time transformation and E-commerce, possibly will lead to a new industrial revolution. In this revolutionary change wave, public concerns focus on the human body big data used for social manufacturing of wearable products or personalized medical treatment. Although many scholars have done a lot of research work, the collection of the human body shape big data still faces many challenges. There is no complete, separated theoretical research works in progress, it should be summarized and improved systematically. In this paper, we review that big data for human body shape is gaining momentum. The 3D scanning and 3D modeling of human body shape are summarized and concluded. The main applications of these big data are analyzed.

关键词： big data human body shape 3D scanning 3D modeling clothing footwear mass customization

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The Application of the Depth Camera in the Social Manufacturing: A review

The Application of the Depth Camera in the Social Manufactur...

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2016年IEEE/INFORMS服务运筹、物流与信息化国际会议

作者： Zhen Liang Ni Zhen Shen Chao Guo Gang Xiong Timo R.Nyberg Xiuqin Shang Shuangshuang Li Yiming Wang The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences College of Information Science and Technology Beijing University of Chemical Technology Cloud Computing Center Chinese Academy of Sciences Qingdao Academy of Intelligent Industries Beijing Engineering Research Center of Intelligent Systems and Technology Institute of AutomationChinese Academy of Sciences Department of Industrial Engineering and Management School of ScienceAalto University

In recent years, the Information Technology develops rapidly. With the development of the Information Technology, the social manufacturing, a new mode of manufacturing, has been proposed. The social manufacturing combines the Internet technology, the three-dimensional scanning technology and the virtual reality technology, and is used in the apparel industry and other fashion industries for the mass customization. The three-dimensional scanning technology and the virtual fitting mirror technology are inseparable from the depth camera. Depth cameras play an important role in the social manufacturing. Manufacturers use depth cameras to obtain three-dimensional models of the body of customers to design suitable clothes. Customers can visually see the effect of clothes by using a virtual fitting mirror which is based on the depth camera. The social manufacturing makes mass customization possible, and the depth camera help develop the social manufacturing. This paper introduces the principles of depth cameras, and the application of depth cameras in the social manufacturing.

关键词： social manufacturing depth camera PMD Kinect time of flight structured light

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Identifiability and Parameter Estimation of Linear Continuous-time Systems under Irregular and Random Sampling

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IFAC-PapersOnLine 2015年第28期48卷 332-337页

作者： Mu, Biqiang Guo, Jin Wang, Le Yi Yin, George Xu, Lijian Zheng, Wei Xing Key Laboratory of Systems and Control Chinese Academy of Sciences Beijing100190 China School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing100083 China Department of Electrical and Computer Engineering Wayne State University DetroitMI48202 United States Department of Mathematics Wayne State University DetroitMI48202 United States Department of Electrical and Computer Engineering Technology Farmingdale State College State University of New York FarmingdaleNY11735 United States School of Computing Engineering and Mathematics University of Western Sydney PenrithNSW2751 Australia

This paper considers the problem of identifiability and parameter estimation of single-input-single-output, linear, time-invariant, stable, continuous-time systems under irregular and random sampling schemes. Conditions for system identifiability are established under inputs of exponential polynomial types and a tight bound on sampling density. Identification algorithms of Gauss-Newton iterative types are developed to generate convergent estimate sequences. When the sampled output is corrupted by observation noises, input design, sampling times, and convergent algorithms are intertwined. Persistent excitation (PE) conditions for strongly convergent algorithms are derived. Unlike the traditional identification, the PE conditions under irregular and random sampling involve both sampling times and input values. Under the given PE conditions, iterative and recursive algorithms are developed to estimate the original continuous-time system parameters. The corresponding convergence results are obtained. Several simulation examples are displayed to verify the theoretical results. © 2015

关键词： Continuous time systems Iterative methods Lyapunov methods Nonlinear control systems Parameter estimation Sampling convergence and asymptotical normality Estimation algorithm Identifiability Irregular sampling Linear continuous time system Non linear least squares

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Multichannel time-series modelling and Prediction by wavelet networks 8

Multichannel time-series modelling and Prediction by wavelet...

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8th European Signal Processing Conference, EUSIPCO 1996

作者： Prochazka, Ales Smith, Jonathan Department of Computing and Control Engineering Prague University of Chemical Technology Technicka 1905 Prague 616628 Czech Republic School of Engineering Systems and Design South Bank University 103 Borough Road LondonSE1OAA United Kingdom

Multichannel time-series result from observations of a given engineering, biomedical, econometric or environ mental variable taken at different locations. Processing this type of signal presents problems associated with its extrapolation in given space ranges and its possible prediction. This paper presents a comparison of sea sonal AH modelling of such signals and the application of wavelet networks to the system identification and pre diction of a particular signal. The choice of wavelet functions and the optimization of their coefficients is discussed as well. Each method suggested in the paper is verified for simulated signals at first and then used for the analysis of real signals, including the observa tion of air pollution. All algorithms are written in the MATLAB environment. © 2015 European Signal Processing Conference, EUSIPCO. All rights reserved.

关键词： Time series

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The Curse of Dimensionality and Variable Selection in Nonlinear Non-parametric System Identification

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IFAC-PapersOnLine 2015年第28期48卷 1279-1284页

作者： Bai, Er-Wei Zhao, Wenxiao Zheng, Wei Xing University of Iowa Department of Electrical and Computer Engineering Iowa52242 United States School of Electronics Electrical Engineering and Computer Science Queens University Belfast United Kingdom Key Laboratory of Systems and Control Academy of Mathematics and Systems Science National Center for Mathematics and Interdisciplinary Sciences Chinese Academy of Sciences Queens University Beijing China School of Computing Engineering and Mathematics University of Western Sydney Chinese Academy of Sciences PenrithNSW2751 Australia

The problem of variable selection in system identification of a high dimensional nonlinear non-parametric system is described. The inherent difficulty, the curse of dimensionality, is introduced. Some recent results of variable selection in system identification are presented. Finally, a simulation example is given to justify the theoretical results. © 2015

关键词： Parameter estimation Religious buildings Curse of dimensionality High dimensional Non parametric Simulation example Variable selection

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Home Health Smart TV — Platform for accessing multimedia e-health content

Home Health Smart TV — Platform for accessing multimedia e-...

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International Symposium on Electronics in Marine (ELMAR)

作者： Leon Dragić Igor Piljić Petar Franček Mano Kovač Hrvoje Mlinanć Darko Gvozdanović Faculty of Electrical Engineering and Computing Department of Control and Computer Engineering Zagreb Croatia Sveuciliste u Zagrebu Zagreb Zagreb HR

In this paper we present the novel platform for accessing multimedia e-health content adapted for elders. Health market is filled with different ICT solutions which provide access to the patient's healthcare records through patient portals. The problem is that none of them are adapted to elder population. Home Health Smart TV platform was developed in order to solve this issue. Elder population is accustomed to TV devices and with this specially designed platform they can access their medical data in a simple way that does not require computer literacy.

关键词： TV Androids Humanoid robots Medical services Computers Servers Navigation

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