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作者： Liu, Jin Li, Juan Cui, Xiaohui Niu, Xiaoguang Sun, Xiaoping Zhou, Jing State Key Lab. of Software Engineering Computer School Wuhan University Wuhan China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology Guilin China International School of Software Wuhan University Wuhan China Computer School Wuhan University Wuhan China Key Lab of Intelligent Information Processing Institute of Computing Technology CAS Beijing China School of Computer Science Communication University of China China

The precise prediction of bus routes or the arrival time of buses for a traveler can enhance the quality of bus service. However, many social factors influence people's preferences for taking buses. These social factors may include heavy traffic cost, traffic congestion, poor air quality and so forth. Existing prediction techniques rarely consider social sensing when predicting the bus arrival time. Accordingly, this paper proposes a social sensing enhanced service for predicting bus routes, which integrates sensing ability and social networks to understand and measure the influence between social events and vehicle velocity. We focus on the analysis of two different attributions: PT service quality attributions PEAs and road condition attributions PRCAs. Both of them synthesize the social sensing in their evaluation of bus routes. PEA represents individual preferences and PRCA represents physical factors that significantly influence vehicle velocity. Bus relevant social events were further categorized into PEA events or PRCA events. PEAs of buses were scored according to the tendency of bus conditions reflected in social events. Furthermore, an artificial neural network prediction model is established to estimate the bus travel time. © 2015 John Wiley & Sons, Ltd.

关键词： Buses

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Ranking Sentences in scientific Literatures

Ranking Sentences in Scientific Literatures

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International Conference on Semantics, Knowledge and Grid (SKG)

作者： Jiao Tian Mengyun Cao Jin Liu Xiaoping Sun Zhuge Hai University of Chinese Academy of Sciences Beijing China Knowledge Grid Group CAS Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China Wuhan University CAS Key Lab. of Intell. Inf. Process. Institute of Computing Technology Chinese Academy of Sciences Beijing CN

Sentence ranking is one of the most important research issues in text analysis. It can be used in extracted textual summarization and information retrieval. Graph-based methods are a common way of ranking and extracting sentences. In graph based methods, sentences are nodes of graph and edges are built based on the sentence similarities or on sentence co-occurrence relationship. PageRank style algorithms can be applied to get sentence ranks. In this paper, we focus on how to rank sentences in a single scientific paper. A scientific literature has more structural information than general texts and this structural information has not been fully explored yet in graph based ranking models. We investigated several different methods that used structural information such as paragraph and section information to construct a heterogeneous graph for ranking sentences. We conducted experiments on these methods to compare the results on sentence ranking. It shows that structural information can help identify more representative sentences.

关键词： Semantics Algorithm design and analysis Web pages Data mining Iterative methods Current measurement

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Fusion of polarization image based on curvelet transform

Fusion of polarization image based on curvelet transform

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2014 2nd International Conference on Mechatronics, Robotics and Automation, ICMRA 2014

作者： Zhang, De Xiang Wang, Hong Hai Xue, Feng The Department of Information and Communication Technology Anhui Sanlian University Hefei 230601 China Key Lab. of Intelligent Computing and Signal Processing Anhui University Hefei 230039 China

ISBN: (纸本)9783038350781

Curvelet transform is the combination of the multi-scale analysis and multi-directional analysis transforms, which is more suitable for objects with curves. Applications of the curvelet transform have increased rapidly in the field of image fusion. Firstly, using the curvelet transform, several polarization images can be decomposed into low-frequency coefficients and high-frequency coefficients with multi-scales and multi-directions. For the low-frequency coefficients, the average fusion method is used. For the each directional high frequency sub-band coefficients, the larger value of region variance information measurement is used to select the better coefficients for fusion. At last the fused image can be obtained by utilizing inverse transform for fused curvelet coefficients. In the present work an algorithm for image fusion based on the curvelet transform was implemented, analyzed, and compared with a wavelet-based fusion algorithm. Experimental results show that the proposed algorithm works better in preserving the edges and texture information compared with the wavelet-based image fusion algorithms. © (2014) Trans Tech Publications, Switzerland.

关键词： Image fusion

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A parallel scheme for three-dimensional reconstruction in large-field electron tomography

A parallel scheme for three-dimensional reconstruction in la...

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10th International Symposium on Bioinformatics Research and Applications, ISBRA 2014

作者： Zhang, Jingrong Wan, Xiaohua Zhang, Fa Ren, Fei Wang, Xuan Liu, Zhiyong Key Lab. of Intelligent Information Processing and Advanced Computing Research Lab Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Yanshan University Yanshan China

ISBN: (纸本)9783319081700

Large-field high-resolution electron tomography enables visualizing detailed mechanisms under global structure. As field enlarges, the processing time increases and the distortions in reconstruction become more critical. Adopting a nonlinear projection model instead of a linear one can compensate for curvilinear trajectories, nonlinear electron optics and sample warping. But the processing time for the reconstruction with nonlinear projection model is rather considerable. In this work, we propose a new parallel strategy for block iterative reconstruction algorithms. We also adopt a page-based data transfer in this strategy so as to dramatically reduce the processing time for data transfer and communication. We have tested this parallel strategy and it can yield speedups of approximate 40 times according to our experimental results. © 2014 Springer International Publishing Switzerland.

关键词： Iterative methods

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An improved correlation method based on rotation invariant feature for automatic particle selection

An improved correlation method based on rotation invariant f...

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10th International Symposium on Bioinformatics Research and Applications, ISBRA 2014

作者： Chen, Yu Ren, Fei Wan, Xiaohua Wang, Xuan Zhang, Fa Key Lab. of Intelligent Information Processing and Advanced Computing Research Lab Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing Beijing China Yanshan University Yanshan China

ISBN: (纸本)9783319081700

Particle selection from cryo-electron microscopy (cryo-EM) images is very important for high-resolution reconstruction of macromolecular structure. However, the accuracy of existing selection methods are normally restricted to noise and low contrast of cryo-EM images. In this paper, we presented an improved correlation method based on rotation invariant features for automatic, fast particle selection. We first selected a preliminary particle set applying rotation invariant features, then filtered the preliminary particle set using correlation to reduce the interference of high noise background and improve the precision of correlation method. We used Divide and Conquer technique and cascade strategy to improve the recognition ability of features and reduce processing time. Experimental results on the benchmark of cryo-EM images show that our method can improve the accuracy of particle selection significantly. © 2014 Springer International Publishing Switzerland.

关键词： Correlation methods

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Corrigendum to “Fast and scalab.e lock methods for video coding on many-core architecture” [J. Vis. Commun. Image R. 25(7) (2014) 1758–1762]

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Journal of Visual Communication and Image Representation 2015年 27卷 57-57页

作者： Weizhi Xu Hui Yu Dianjie Lu Fenglong Song Da Wang Xiaochun Ye Songwei Pei Dongrui Fan Hongtao Xie Institute of Microelectronics Tsinghua University Beijing China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing China Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China School of Information Science and Engineering Shandong Normal University Jinan China Department of Computer Science and Technology Beijing University of Chemical Technology Beijing China Institute of Information Engineering Chinese Academy of Sciences National Engineering Laboratory for Information Security Technologies Beijing China

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Corrigendum to “Fast and scalab.e lock methods for video coding on many-core architecture” [J. Vis. Commun. 25 (7) (2014) 1758–1762]

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Journal of Visual Communication and Image Representation 2015年 26卷 350-350页

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Efficiently Finding Top-K Items from Evolving Distributed Data Streams

Efficiently Finding Top-K Items from Evolving Distributed Da...

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International Conference on Semantics, Knowledge and Grid (SKG)

作者： Baoyuan Qi Gang Ma Zhongzhi Shi Wei Wang University of Chinese Academy of Sciences Beijing China Key Lab of Intelligent Information Processing Institute of Computing Technology Cas Beijing China Key Lab. of Intell. Inf. Process. Institute of Computing Technology Chinese Academy of Sciences Beijing CN Beijing Lexo Technologies Co. Ltd. Beijing China

ISBN: (纸本)9781479967162

The problem of efficiently finding top-k frequent items has attracted much attention in recent years. Storage constraints in the processing node and intrinsic evolving feature of the data streams are two main challenges. In this paper, we propose a method to tackle these two challenges based on space-saving and gossip-based algorithms respectively. Our method is implemented on SAMOA, a scalab.e advanced massive online analysis machine learning framework. The experimental results show its effectiveness and scalab.lity.

关键词： Peer-to-peer computing Data mining Distributed databases Protocols Machine learning algorithms Monitoring Radiation detectors

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Social sensing enhanced time estimation for bus service

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Concurrency and Computation: Practice and Experience 2015年第15期27卷

作者： Jin Liu Juan Li Xiaohui Cui Xiaoguang Niu Xiaoping Sun Jing Zhou State Key Lab. of Software Engineering Computer School Wuhan University Wuhan China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology Guilin China International School of Software Wuhan University Wuhan China Computer School Wuhan University Wuhan China Key Lab of Intelligent Information Processing Institute of Computing Technology CAS Beijing China School of Computer Science Communication University of China China

The precise prediction of bus routes or the arrival time of buses for a traveler can enhance the quality of bus service. However, many social factors influence people's preferences for taking buses. These social factors may include heavy traffic cost, traffic congestion, poor air quality and so forth. Existing prediction techniques rarely consider social sensing when predicting the bus arrival time. Accordingly, this paper proposes a social sensing enhanced service for predicting bus routes, which integrates sensing ability and social networks to understand and measure the influence between social events and vehicle velocity. We focus on the analysis of two different attributions: PT service quality attributions PEA s and road condition attributions PRCA s. Both of them synthesize the social sensing in their evaluation of bus routes. PEA represents individual preferences and PRCA represents physical factors that significantly influence vehicle velocity. Bus relevant social events were further categorized into PEA events or PRCA events. PEA s of buses were scored according to the tendency of bus conditions reflected in social events. Furthermore, an artificial neural network prediction model is established to estimate the bus travel time. Copyright © 2015 John Wiley & Sons, Ltd.

关键词： social sensing in-time bus service bus route arrival time estimation

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ObjectSense: A scalab.e multi-objects recognition system based on partial-duplicate image retrieval 13

ObjectSense: A scalable multi-objects recognition system bas...

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3rd ACM International Conference on Multimedia Retrieval, ICMR 2013

作者： Wang, Shuang Xue, Yunfeng Chu, Lingyang Jiang, Yuhao Jiang, Shuqiang Key Lab. of Intelligent Information Processing Institute of Computing Tech. CAS Beijing China College of Information Science and Engineering Shandong University of Science and Technology Qingdao China

ISBN: (纸本)9781450320337

In this demo, we present ObjectSense, a scalab.e object recognition system that recognizes multiple objects present in a static image or in the camera frames. Instead of applying learning based recognition framework, this system identifies objects through Partial-Duplicate Image Retrieval (PDIR) based method. First, objects are identified by measuring the similarity between an incoming image and reference image corpus that are lab.led with the objects. To compute image similarities, we explore the Consistency Graph Model (CGM), which robustly rejects spatially inconsistent feature matches with the advantage of orientations and positions of local features. Then a kNN voting method is used to decide the object category based on the quantized image similarities. ObjectSense is scalab.e with promisingly high recall and accuracy, which fits well into recognition-guided shopping and human computer interaction. We built ObjectSense on two platforms, PC and Android. © 2013 Authors.

关键词： Object recognition

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