检索结果-内蒙古大学图书馆

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

作者： Zhenliang Ni Zhen Shen Chao Guo Gang Xiong Timo Nyberg Xiuqin Shang Shuangshuang Li Yiming Wang College of Information Science and Technology Beijing University of Chemical Technology Beijing China Chinese Academy of Sciences Institute of Automation Beijing China Qingdao Academy of Intelligent Industries Qingdao Shandong China Chinese Academy of Sciences Cloud Computing Center Dongguan Guangdong China Department of Industrial Engineering and Management Aalto University Finland Boleni Intelligent Solutions Technology (Su Zhou) Co. Ltd Joint Laboratory of Intelligent IoT & Cloud for Parallel Management & Control Suzhou China

ISBN: (纸本)9781509029280

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： Cameras Solid modeling Time measurement Fitting Mirrors Light sources

来源：评论

学校读者我要写书评

暂无评论

Social manufacturing development with sino-finnish innovation cooperation

Social manufacturing development with sino-finnish innovatio...

引用

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

作者： Jian Liu Gang Xiong Xiuqin Shang Timo R. Nyberg Yiming Wang Tongkai Ji Chinese Academy of Sciences Institute of Automation Beijing China College of Information Science and Technology Beijing University of Chemical Technology Beijing China Department of Industrial Engineering and Management Aalto University Aalto Finland Chinese Academy of Sciences Cloud Computing Center Dongguan Guangdong China Qindao Academy of Intelligent Industries Qingdao China Boleni Intelligent Solutions Technology (SuZhou) Co. Ltd Joint Laboratory of Intelligent IoT & Cloud for Parallel Management & Control Suzhou China

ISBN: (纸本)9781509029280

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： Industries Manufacturing Technological innovation Companies Internet Production facilities

来源：评论

学校读者我要写书评

暂无评论

Bayesian localization microscopy based on intensity distribution of fluorophores

引用

Protein & Cell 2015年第3期6卷 211-220页

作者： Fan Xu Mingshu Zhang Zhiyong Liu Pingyong Xu Fa Zhang Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China University of Chinese Academy of Sciences Beijing 100049 China Laboratory of Non Coding RNA Institute of Biophysics Chinese Academy of Sciences Beijing 100101 China

Super-resolution microscopy techniques have overcome the limit of optical diffraction. Recently, the Bayesian analysis of Bleaching and Blinking data （3B） method has emerged as an important tool to obtain super-resolution fluorescence images. 3B uses the change in information caused by adding or removing fiuorophores in the cell to fit the date. When adding a new fluorophore, 3B selects a random initial position, optimizes this position and then determines its reliability. However, the fluorophores are not evenly distributed in the entire image region, and the fluorescence intensilty at a given position positively correlates with the probability of observing a fluorophore at this position. In this paper, we present a Bayesian analysis of Bleaching and Blinking microscopy method based on fluorescence intensity distribution （FID3B）. We utilize the intensity distribution to select more reliable positions as the initial positions of fluorophores. This approach can improve the reconstruction results and significantly reduce the computational time. We validate the perfor. mance of our method using both simulated date and experimental date from cellular structures. The results confirm the effectiveness of our method.

关键词： super-resolution fluorescence image 3B,intensity distribution

来源：评论

学校读者我要写书评

暂无评论

A separability-entanglement classifier via machine learning

arXiv

引用

arXiv 2017年

作者： Lu, Sirui Huang, Shilin Li, Keren Li, Jun Chen, Jianxin Lu, Dawei Ji, Zhengfeng Shen, Yi Zhou, Duanlu Zeng, Bei Department of Physics Tsinghua University Beijing100084 China Institute for Quantum Computing University of Waterloo WaterlooONN2L 3G1 Canada Institute for Interdisciplinary Information Sciences Tsinghua University Beijing100084 China Beijing Computational Science Research Center Beijing100193 China Department of Mathematics & Statistics University of Guelph GuelphONN1G 2W1 Canada Joint Center for Quantum Information and Computer Science University of Maryland College ParkMD United States Department of Physics Southern University of Science and Technology Shenzhen518055 China Centre for Quantum Computation & Intelligent Systems School of Software Faculty of Engineering and Information Technology University of Technology Sydney Sydney Australia State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China Department of Statistics and Actuarial Science University of Waterloo WaterlooONN2L 3G1 Canada Institute of Physics Chinese Academy of Sciences Beijing100190 China

The problem of determining whether a given quantum state is entangled lies at the heart of quantum information processing, which is known to be an NP-hard problem in general. Despite the proposed many methods such as the positive partial transpose (PPT) criterion and the k-symmetric extendibility criterion to tackle this problem in practice, none of them enables a general, effective solution to the problem even for small dimensions. Explicitly, separable states form a high-dimensional convex set, which exhibits a vastly complicated structure. In this work, we build a new separability-entanglement classifier underpinned by machine learning techniques. Our method outperforms the existing methods in generic cases in terms of both speed and accuracy, opening up the avenues to explore quantum entanglement via the machine learning approach. Copyright © 2017, The Authors. All rights reserved.

关键词： Quantum entanglement

来源：评论

学校读者我要写书评

暂无评论

A Survey on Big Data for Human Body Shape

A Survey on Big Data for Human Body Shape

引用

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

来源：评论

学校读者我要写书评

暂无评论

Online hot event discovery based on Association Link Network

Online hot event discovery based on Association Link Network

引用

作者： Liu, Yang Luo, Xiangfeng Xuan, Junyu School of Computer Engineering and Science Shanghai University China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Science Beijing China

Online hot event discovery has become a flourishing frontier where online document streams are monitored to discover newly occurring events or assigned to previously detected events. However, hot events have the nature to evolve, and their inherent topically related words are also likely to evolve. It makes event discovery a challenging task for traditional-mining approaches. Combining word association and semantic community, Association Link Network (ALN) organizes the loosely distributed associated resources. This paper presents an ALN-based novel online hot event discovery approach. Technically, this approach is enacted around three stages. In the first stage, we extract significant features to represent the content of each document from the online document stream. During the second stage, we classify the online document stream into topically related detected events considering event evolution in the form of ALN. At the third stage, we create an ALN-based event detection algorithm, which is used to timely discover newly occurring hot events. The online datasets used in our empirical studies are acquired from Baidu News, which spans a range of 1315 hot events and 236,300 documents. Experimental results demonstrate the hot events discovery ability with respect to high accuracy, good scalability, and short runtime. © 2015 John Wiley & Sons, Ltd.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Two Intersections Traffic Signal Control Method Based on ADHDP

Two Intersections Traffic Signal Control Method Based on ADH...

引用

2016年IEEE汽车电子与安全国际会议

作者： Lin Cao Bin Hu Xisong Dong Gang Xiong Fenghua Zhu Zhen Shen Dong Shen Yuliang Liu 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 Institute of Smart Education Systems Qingdao Academy of Intelligent Industries Dongguan Research Institute of CASIA Cloud Computing CenterChinese Academy of Sciences Beijing Engineering Research Center of Intelligent Systems and Technology Institute of AutomationChinese Academy of Sciences

With the rapid development of Chinese economy and automotive industry,urban traffic congestion has become increasingly ***,how to effectively alleviate the traffic congestion and improve the efficiency of vehicles has become the main *** signal control is one of the effective ways to solve urban traffic *** this paper,a traffic signal control method based on Action-Dependent Heuristic Dynamic Programming(ADHDP) is *** control algorithm is simulated on two intersections,both of which have two phases with four entrance *** computer simulation results show that the control method has the better ability of on-line learning compared with traditional Fix-Time Control,and can effectively improve the average speed of vehicles,and reduce travel time and alleviate the traffic pressure.

关键词： ADHDP Traffic Signal Control Adaptive Control intelligent Transportation Systems

来源：评论

学校读者我要写书评

暂无评论

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

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

引用

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

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

来源：评论

学校读者我要写书评

暂无评论

Some applications of nonlinear science methods and support vector machine methods to protein problems

引用

Mini-Reviews in Organic Chemistry 2015年第6期12卷 493-505页

作者： Hana, Guo Sheng Yu, Zu-Guo Zhao, Zhi-Qin Hunan Key Laboratory for Computation and Simulation in Science and Engineering and Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University XiangtanHunan411105 China School of Mathematical Sciences Queensland University of Technology GPO Box 2434 BrisbaneQ4001 Australia

Protein folding, prediction of protein structure and functions are most important problems in bioinformatics. The protein fold process mainly reflects in the kinetic order of folding. Predicting the structural classes of low-homology protein is a difficult problem in the prediction of protein structure. In order to understanding the mechanism of programmed cell death, it is very necessary to obtain the information about subcellular locations and functions of apoptosis proteins. Predicting protein subnuclear localizations is a challenging problem which is harder than predicting protein subcellular locations. Predicting membrane protein types is related to the structure and function of proteins. In this review, we introduce some applications of nonlinear science methods and support vector machine methods to the above protein problems. The nonlinear science methods including the horizontal visibility network, kernel method, recurrence quantification analysis, global descriptor, Lempel-Ziv complexity, and Hilbert-Huang transform are used to extract features in these approaches. © 2015 Bentham Science Publishers.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Image authentication and self-recovery scheme based on the rehashing model

引用

Journal of information Hiding and Multimedia Signal Processing 2016年第3期7卷 460-474页

作者： Lyu, Wan-Li Chang, Chin-Chen Wang, Feng Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei230039 China Department of Information Engineering and Computer Science Feng Chia University 100 Wenhwa Rd. Seatwen Taichung40724 Taiwan Department of Computer Science and Information Engineering Asia University Taichung41354 Taiwan Department of Mathematics and Physics Fujian University of Technology FuzhouFujian350108 China

An effective image tamper localization and self-recovery scheme that uses the rehashing model is proposed in this paper. The aim of the proposed scheme was to reduce the failure rate in detecting image tamper areas and achieve high rates of successful detection. To achieve this aim, the proposed scheme uses a set of hash functions which are called the rehashing model, gained an optimal decreasing collision method to detect tamper areas With an improved and accurate tamper detection rate, the tampered image can be recovered more accurately. The quality of the proposed scheme was tested with gray and color images. The experimental results indicated that the proposed scheme has good performance in locating tamper locations and allows image recovery with an acceptable visual quality up to 50% of the image content tampered. © 2016.

关键词： Hash functions

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：