检索结果-内蒙古大学图书馆

IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Xiaoyang Jing Qiwen Dong School of Computer Science Fudan University Shanghai People's Republic of China Shanghai Key Laboratory of Intelligent Information Processing Shanghai People's Republic of China Key Laboratory of Network Oriented Intelligent Computation Harbin Institute of Technology Shenzhen Graduate School Shenzhen Guangdong People's Republic of China Institute for Data Science and Engineering East China Normal University Shanghai People's Republic of China

ISBN: (纸本)9781509016129

Protein residue-residue contacts dictate the topology of protein structure and play an important role in structural biology, especially in de novo protein structure prediction. Accurate prediction of residue contacts could improve the performance of de novo protein structure prediction methods. In this study, a novel method based on learning-to-rank (RRCRank) has been presented to predict protein residue-residue contacts. The proposed method formulates the contacts prediction problem as a ranking problem. Firstly, the contact probabilities of residue pairs are predicted by ensemble machine-learning classifiers and correlated mutations approaches. And then, the proposed method integrates the complementary outputs of machine-learning and correlated mutations approaches and uses the learning-to-rank algorithm to rank residue pairs based on their probabilities to be contacts. Benchmarked on the CASP11 dataset, the proposed method achieves an improved performance for all three categories of contacts (short-range, medium-range and long-range contacts), which shows the proposed method based on learning-to-rank could take advantage of machine-learning and correlated mutations approaches and could provide the state-of-the-art performance.

关键词： Proteins Protein engineering Training Predictive models Feature extraction Classification algorithms Prediction algorithms

来源：评论

学校读者我要写书评

暂无评论

MR-COF: A genetic MapReduce configuration optimization framework 15th

MR-COF: A genetic MapReduce configuration optimization frame...

引用

15th International Conference on Algorithms and Architectures for Parallel processing, ICA3PP 2015

作者： Liu, Chao Zeng, Deze Yao, Hong Hu, Chengyu Yan, Xuesong Fan, Yuanyuan Hubei Key Laboratory of Intelligent Geo-Information Processing China University of Geosciences Wuhan430074 China China Services Computing Technology and System Lab and Cluster and Grid Computing Lab Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9783319271392

Hadoop/MapReduce has emerged as a de facto programming framework to explore cloud-computing resources. Hadoop has many configuration parameters, some of which are crucial to the performance of MapReduce jobs. In practice, these parameters are usually set to default or inappropriate values. This severely limits system performance (e.g., execution time). Therefore, it is essential but also challenging to investigate how to automatically tune these parameters to optimize MapReduce job performance. In this paper, we propose an automatic MapReduce configuration optimization framework named as MR-COF. By monitoring and analyzing the runtime behavior, the framework adopts a cost-based performance prediction model that predicts the MapReduce job performance. In addition, we design a genetic search algorithm which iteratively tunes parameters in order to find out the best one. Testbed-based experimental results show that the average MapReduce job performance is increased by 35% with MR-COF compared to the default configuration. © Springer International Publishing Switzerland 2015.

关键词： MapReduce

来源：评论

学校读者我要写书评

暂无评论

A sub-pixel SAR and optical image registration method 66

A sub-pixel SAR and optical image registration method

引用

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

来源：评论

学校读者我要写书评

暂无评论

Entanglement depth for symmetric states

引用

Physical Review A 2016年第4期94卷 042333-042333页

作者： Ji-Yao Chen Zhengfeng Ji Nengkun Yu Bei Zeng State Key Laboratory of Low Dimensional Quantum Physics Department of Physics Tsinghua University Beijing China Perimeter Institute for Theoretical Physics Waterloo Ontario Canada Centre for Quantum Computation & Intelligent Systems Faculty of Engineering and Information Technology University of Technology Sydney NSW 2007 Australia Institute for Quantum Computing University of Waterloo Waterloo Ontario Canada Department of Mathematics & Statistics University of Guelph Guelph Ontario Canada Canadian Institute for Advanced Research Toronto Ontario Canada

Entanglement depth characterizes the minimal number of particles in a system that are mutually entangled. For symmetric states, there is a dichotomy for entanglement depth: An N-particle symmetric state is either fully separable or fully entangled—the entanglement depth is either 1 or N. We show that this dichotomy property for entangled symmetric states is even stable under nonsymmetric noise. We propose an experimentally accessible method to detect entanglement depth in atomic ensembles based on a bound on the particle number population of Dicke states, and demonstrate that the entanglement depth of some Dicke states, for example the twin Fock state, is very stable even under a large arbitrary noise. Our observation can be applied to atomic Bose-Einstein condensates to infer that these systems can be highly entangled with the entanglement depth that is on the order of the system size (i.e., several thousands of atoms).

关键词： Entanglement detection

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

Adaptive sparse recovery based on difference algorithm

引用

Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of Computer-Aided Design and Computer Graphics 2015年第6期27卷 1047-1052页

作者： Zhang, Fengzhen Zhao, Ruizhen Cen, Yigang Hu, Shaohai Zhang, Yongdong Institute of Information Science Beijing Jiaotong University Beijing100044 China Key Laboratory of Advanced Information Science and Network Technology of Beijing Beijing100044 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China

To improve the disadvantages that iterative reconstruction algorithms of compressed sensing need priori knowledge of the sparsity of original signal or iterative threshold, an adaptive sparse recovery based on difference algorithm is proposed. When the sparsity of original signal is unknown, the proposed algorithm takes advantage of unbalance of correlation coefficient between the measurement matrix and residual. With those properties, the proposed algorithm can select the support set of the original signal, and approach the sparsity of the original signal. Simulation results show that the proposed algorithm obtains better recovery results under the same conditions. Especially in the lower sampling rate, the advantage is more obvious. ©, 2015, institute of computing technology. All right reserved.

关键词： Recovery

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

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

来源：评论

学校读者我要写书评

暂无评论

Public Service Management System of Urban Placenames for Sanya Case

Public Service Management System of Urban Placenames for San...

引用

2016年IEEE/INFORMS服务运筹、物流与信息化国际会议

作者： Wei Liu Fenghua Zhu Xisong Dong Gang Xiong Yongqiang Zhu Huazhou Wu Taozhong Liu Yuexiang Hu 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 Beijing Engineering Research Center of Intelligent Systems and Technology Institute of AutomationChinese Academy of Sciences Dongguan Research Institute of CASIA Cloud Computing CenterChinese Academy of Sciences Instituteof Smart Education Systems Qingdao Academy of Intelligent Industries Xiamen Kingtopinfo Technology Co.Ltd

The rapidly growing amount of social interaction makes geographical names an important and indispensable medium for people in social and economic exchanges. Especially in today's information age, the frequency of usage of name information has increased greatly. In this paper, a method for the construction of a cities' names database is proposed. This will include the processing of the outcome data from the names pilot survey, the consolidation into the database, the development of the cloud service and management system based on the geographical names and zoning database, and the construction of a relatively complete set of the public service system of geographical names based on a website and touch screen interface. The method has been applied in San Ya, China successfully, and very good results have been obtained. The platform can provide not only accurate and convenient services of geographical names, but also promote its economic development and social progress.

关键词： Public service system geographical names geographical names database cloud service platform

来源：评论

学校读者我要写书评

暂无评论

A kind of binary image complete level authentication method based on hamming code and digital watermark

引用

Journal of information and Computational Science 2015年第1期12卷 181-190页

作者： Li, Min Deng, Shaobo Scholar of Information Engineering Nanchang Institute of Technology Nanchang China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

Each pixel of the binary image can be viewed as a binary number. Base on this characteristic, we design a supervisory relationship. A detection image is gotten from the supervisory relationship and binary image. Based on this, a kind of pixel level digital watermark complete authentication method is put forward. This method is able to conduct binary image pixel authentication. When authenticating, only from the detection image, people can accurately identify whether a pixel point is falsified or not, furthermore, it has falsification localization and repair capacity.

关键词： Authentication

来源：评论

学校读者我要写书评

暂无评论

OMEG: Oulu multi-pose eye gaze dataset 19th

OMEG: Oulu multi-pose eye gaze dataset

引用

19th Scandinavian Conference on Image Analysis, SCIA 2015

作者： He, Qiuhai Hong, Xiaopeng Chai, Xiujuan Holappa, Jukka Zhao, Guoying Chen, Xilin Pietikäinen, Matti Department of Computer Science and Engineering University of Oulu Oulu Finland Key Lab of Intelligent Information Processing of the Chinese Academy of Sciences The Institute of Computing Technology of the Chinese Academy of Sciences Beijing China

ISBN: (纸本)9783319196640

Data is in a very important position for pattern recognition tasks including eye gaze estimation. In the literature, most researchers used normal face datasets, which are not specifically designed for eye gaze estimation. As a result, it is difficult to obtain fine labeled eye gaze direction. Therefore large datasets with well-defined gaze directions are desired. To facilitate related researches, we collect and establish the Oulu Multi-pose Eye Gaze Dataset. Inspired by the psychological observation that gaze direction is intrinsically linked with the head orientation, we are devoted to a new data set of eye gaze images captured under multiple head poses. It finally results in a dataset containing over 40K images from 50 subjects, who were asked to fixate on 10 special points on screen under different poses respectively. We investigate a new eye gaze estimation approach by using the IGO based description, and compare it with other popular eye gaze estimation approaches to provide the baseline results on our dataset. © Springer International Publishing Switzerland 2015.

关键词： Pattern recognition

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：