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2nd International Conference on Cloud computing and Big Data, CloudCom-Asia 2015

作者： Lin, Xiuyan Liu, Zhanghui Guo, Wenzhong Fujian Provincial Key Lab of the Network Computing and Intelligent Information Processing College of Mathematics and Computer Science Fuzhou University Fuzhou350116 China

ISBN: (纸本)9783319284293

Cloud is the computing paradigm which provides computing resource as a service through network. The client can use computing resource in a convenient and on-demand way, just like the water and the electricity we use daily. The mapping between virtual machine and physical machine is the key of the VM scheduling problem. Nowadays we advocate low-carbon life. It calls for the green cloud computing solutions whether protecting the environment or saving the cost of cloud suppliers. The proposed VM placement algorithm is energy-efficient, and considers the multi-dimentional resource constrains, such as CPU, memory, network bandwidth, and so on. The experimental results show that the proposed algorithms not only contribute a lot to energy saving, but also try best to meet the quality of service (QoS). Therefore, we make significant savings in operating cost and make full use of various resources in the cloud data center. The algorithm has promising prospect in application. © Springer International Publishing Switzerland 2015.

关键词： Virtual machine

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EXPRESS WAYBILL EXTRACTION ON PARCEL IMAGES BY LOGO MATCHING

EXPRESS WAYBILL EXTRACTION ON PARCEL IMAGES BY LOGO MATCHING

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IEEE International Conference on Image processing

作者： Shujing Lu Jie Zhao Yue Lu ECNU-SRI Joint Lab for Pattern Analysis and Intelligent System Shanghai Research Institute of China Post Group Shanghai Key Laboratory of Multidimensional Information Processing Department of Computer Science and Technology East China Normal University

ISBN: (纸本)9781467399623

We propose an efficient method for automatically extracting express waybills from parcel images, which is challenging due to varied resolution of parcel images, arbitrary direction of waybills and different information filled by senders. To address these challenges, logo matching is employed to extract the waybills. We begin by extracting scale-invariant feature-transformation (SIFT) keypoints from both the reference logo image and a parcel image, and matching them subject to a consistent projective transformation (homography) by using random sample consensus (RANSAC). Once the homography matrix is computed, we extract the waybill of parcel image by mapping all pixels from a standard waybill image to the parcel image. Experimental results on test datasets demonstrate the effectiveness of the proposed method.

关键词： Logo matching Express waybill extraction SIFT images Sifting Fields LOGO Imagery (Psychotherapy) Image homography

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Bayesian localization microscopy based on intensity distribution of fluorophores

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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

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Memory bandwidth optimization of SpMV on GPGPUs

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Frontiers of Computer Science 2015年第3期9卷 431-441页

作者： Chenggang Clarence YAN Hui YU Weizhi XU Yingping ZHANG Bochuan CHEN Zhu TIAN Yuxuan WANG Jian YIN Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Institute of Microelectronics Tsinghua University Beijing 100084 China Automation Department Tsinghua University Beijing 100084 China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China State Grid Information & Communication Company of Hunan EPC Changsha 410007 China Department of Computer Shandong University Weihai 250101 China

It is an important task to improve performance for sparse matrix vector multiplication （SpMV）, and it is a difficult task because of its irregular memory access. Gen- eral purpose GPU （GPGPU） provides high computing abil- ity and substantial bandwidth that cannot be fully exploited by SpMV due to its irregularity. In this paper, we propose two novel methods to optimize the memory bandwidth for SpMV on GPGPU. First, a new storage format is proposed to exploit memory bandwidth of GPU architecture more effi- ciently. The new storage format can ensure that there are as many non-zeros as possible in the format which is suitable to exploit the memory bandwidth of the GPU. Second, we pro- pose a cache blocking method to improve the performance of SpMV on GPU architecture. The sparse matrix is partitioned into sub-blocks that are stored in CSR format. With the block- ing method, the corresponding part of vector x can be reused in the GPU cache, so the time to access the global memory for vector x is reduced heavily. Experiments are carried out on three GPU platforms, GeForce 9800 GX2, GeForce GTX 480, and Tesla K40. Experimental results show that both new methods can efficiently improve the utilization of GPU mem- ory bandwidth and the performance of the GPU.

关键词： GPGPU performance tuning SpMV cacheblocking memory bandwidth

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Real-time task scheduling algorithm for cloud computing based on particle swarm optimization 2nd

Real-time task scheduling algorithm for cloud computing base...

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2nd International Conference on Cloud computing and Big Data, CloudCom-Asia 2015

作者： Chen, Huangning Guo, Wenzhong College of Mathematics and Computer Science Fuzhou University Fuzhou China Fujian Provincial Key Lab of the Network Computing and Intelligent Information Processing Fuzhou University Fuzhou China

ISBN: (纸本)9783319284293

As a new computing paradigm, cloud computing is receiving considerable attention in both industry and academia. Task scheduling plays an important role in large-scale distributed systems. However, most previous work only consider cost or makespan as optimized objective for cloud computing. In this paper, we propose a soft real-time task scheduling algorithm based on particle swarm optimization approach for cloud computing. The optimized objectives include not only cost and makespan, but also deadline missing ratio and load balancing degree. In addition, to improve resource utilization and maximize the profit of cloud service provider, a utility function is employed to allocate tasks to machines with high performance. Simulation results show the proposed algorithm can effectively minimize deadline missing ratio, maximize the profit of cloud service provider and achieve better load balancing com- pared with baseline algorithms. © Springer International Publishing Switzerland 2015.

关键词： Cloud computing

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

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

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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

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Proteomic identification of intact glycopeptides

Proteomic identification of intact glycopeptides

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2016 International Symposium on Analytical Chemistry Frontiers & China-US Analytical Chemistry Workshop

作者： Ming-Qi Liu Wen-Feng Zeng Pan Fang Yang Zhang Wei-qian Cao Jian-Qiang Wu Rui-Xiang Sun Chao Peng Catherine C.L.Wong Si-Min He Peng-Yuan Yang Department Chemistry and Institutes of Biomedical Sciences Fudan University Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS) Institute of Computing Technology CAS and University of Chinese Academy of Sciences National Center for Protein Science (Shanghai) Institute of Biochemistry and Cell Biology Shanghai Institutes for Biological Sciences CAS

We have developed a workflow that robustly identifies intact glycopeptides at a proteome scale using stepped-energy mass-spectrometry. This workflow has decoded as a computational strategy called as pGlyco+, a dedicated search engine for glycopeptide analysis. Our high-throughput method has enable us to interpret a total of 5,564 distinct site-specific N-glycoforms, on 1,478 glycosylation sites of relative 809 glycoproteins from five mouse tissues, and in 20 hours of mass-spectrometry analysis. Strict quality control(1% false discovery rate) was performed not only for the peptide matches but novel for glycan ones as well. We have also compared our search engine with a routinely used glycoproteomic software and believed that our method is a rather robust tool for site-specific glycosylation study likely. To demonstrate the importance of comprehensive quality control for both the glycan and peptide matches, we have conducted a fair performance comparison between pGlyco+ and Byonic, a routinely used glycoproteomic software: exactly same MS/MS data, and parameters such as tolerance, databases of protein and glycan were used. Under 1% FDR, pGlyco+ identified 23,086 glycopeptide spectra, while Byonic only identified 8,866 glycopeptide spectra. The corresponding number of identified distinct glycopeptides were 5,430 for pGlyco+ and 2,206 for Byoinc. To reach the same sensitivity of pGlyco+(23,086 identified spectra under 1% FDR), Byonic would have unacceptably 30% FDR using the same criteria.

关键词： Glycopeptide Mass Spectrometry pGlyco+

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OMEG: Oulu multi-pose eye gaze dataset 19th

OMEG: Oulu multi-pose eye gaze dataset

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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

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Understanding taxi drivers＇ routing choices from spatial and social traces

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Frontiers of Computer Science 2015年第2期9卷 200-209页

作者： Siyuan LIU Shuhui WANG Ce LIU Ramayya KRISHNAN Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China University of Chinese Academy of Sciences Beijing 100049 China Heinz CoUege Carnegie Mellon University Pittsburgh PA 15213 USA Key Lab of Intellectual Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China School of Information Sciences University of Pittsburgh Pittsburgh PA 15260 USA

Most of our learning comes from other people or from our own experience. For instance, when a taxi driver is seeking passengers on an unknown road in a large city, what should the driver do？ Alternatives include cruising around the road or waiting for a time period at the roadside in the hopes of finding a passenger or just leaving for another road enroute to a destination he knows （e.g., hotel taxi rank）？ This is an interesting problem that arises everyday in cities all over the world. There could be different answers to the question poised above, but one fundamental problem is how the driver learns about the likelihood of finding passengers on a road that is new to him （as he has not picked up or dropped off passengers there before）. Our observation from large scale taxi driver trace data is that a driver not only learns from his own experience but through interactions with other drivers. In this paper, we first formally define this problem as socialized information learning （SIL）, second we propose a framework including a series of models to study how a taxi driver gathers and learns information in an uncertain environment through the use of his social network. Finally, the large scale real life data and empirical experiments confirm that our models are much more effective, efficient and scalable that prior work on this problem.

关键词： routing choices socialized information learn-ing social network

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The face object based HEVC system for video call 8

The face object based HEVC system for video call

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8th International Conference on Mobile Multimedia Communications, MOBIMEDIA 2015

作者： Wang, Xi Yan, Chenggang Clarence Huang, Qingming Su, Li Jiang, Shuqiang Huang, Xianglin Institute of Computing Technology University of Chinese Academy of Sciences Beijing100190 China Department of Automation Tsinghua University Key Lab of Intelligent Information Processing CAS Institute of Computing Technology Beijing100190 China Beijing100024 China

ISBN: (纸本)9781631900662

Guaranteing the quality of face object in video call is the key task for video coding systems under the constrained bandwidth of network. Conventionally, the face object is divided into disperse blocks under the hybrid coding framework. Therefore, the characteristics of the complete face object have not been fully used. Meanwhile, it is difficult to predict the complex affine transformations such as rotation and scaling of the face object in neighboring frames based on the current translation motion model. In this paper, we propose an improved video coding scheme for video call. The complex transformation of complete face object is used to improve the compression effect. Experimental results show that our proposed method has better performance compared with HM12.0, the bits rate saving of face region is up to 19.59% under the similar visual quality. Copyright © 2015 ICST.

关键词： Image coding

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