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3rd Workshop on Spatio-Temporal Database Management, STDBM 2006, Co-located with the 32nd International Conference on Very Large Data Bases, VLDB 2006

作者： Zhang, Jun Wang, Chaokun Wang, Jianmin Yu, Jeffrey Xu Department of Computer Science and Technology Tsinghua University China School of Software Tsinghua University China Tsinghua National Laboratory for Information Science and Technology China Key Laboratory for Information System Security Ministry of Education China The Chinese University of Hong Kong Hong Kong

It is always attractive and challenging to explore the intricate behavior data and uncover people's motivations, preference and habits, which can greatly benefit many tasks including link prediction, item recommendation, etc. Traditional work usually studies people's behaviors without time information in a static or discrete manner, assuming the underlying factors stay invariant in a long period. However, we believe people's behaviors are dynamic, and the contributing factors including the social influence and personal preference for behaviors are varying continuously over time. Such continuous dynamics convey important knowledge about people's behavior patterns;ignoring them would lead to inaccurate models. In this work, we address the continuous dynamic modeling of temporal behaviors. To model the fully continuous temporal dynamics of behaviors and the underlying factors, we propose the DP-Space, a dynamic preference probability space, which can capture their smooth variation in various shapes over time with flexible basis functions. Upon that we propose a generative dynamic behavior model, ConTyor, which considers the temporal item-adoption behaviors as joint effect of dynamic social influence and varying personal preference over continuous time. We also develop effective inference methods for ConTyor and present its applications. We conduct a comprehensive experimental study using real-world datasets to evaluate the effectiveness of our model and the temporal modeling. Results verify that ConTyor outperforms existing state-of-the-art static and temporal models in behavior predictions. Moreover, in our detailed study on temporal modeling, we show that temporal modeling is superior to static approaches and modeling over continuous time is further better than that over discrete time. We also demonstrate that the ancient behavior data can still become important and beneficial if modeled well. © 2014 VLDB Endowment 21508097/14/11.

关键词： Forecasting

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Traffic Labeller： Collecting Internet Traffic Samples with Accurate Application Information

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China Communications 2014年第1期11卷 69-78页

作者： PENG Lizhi ZHANG Hongli YANG Bo CHEN Yuehui WU Tong School of Computer Science and Technology Harbin Institute of Technology Harbin 150002 China Provincial Key Laboratory for Network Based Intelligent Computing University of Jinan Jinan 250022 China School of Computer and Information Technology Beijing Jiaotong University Beijing 100044 China

Traffic classification research has been suffering from a trouble of collecting accurate samples with ground truth.A model named Traffic Labeller(TL) is proposed to solve this *** system captures all user socket calls and their corresponding application process information in the user mode on a Windows *** a sending data call has been captured,its 5-tuple {source IP,destination IP,source port,destination port and transport layer protocol},associated with its application information,is sent to an intermediate NDIS driver in the kernel *** the intermediate driver writes application type information on TOS field of the IP packets which match the *** this way,each IP packet sent from the Windows host carries their application ***,traffic samples collected on the network have been labelled with the accurate application information and can be used for training effective traffic classification models.

关键词： network measurement traffic cla- ssification data collection ground truth

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Poster abstracts

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J Spinal Cord Med 2018年第5期41卷 576-576页

作者： Juan Asanza Meghan Meinerz Cynthia Arrowood Shawn Matsuwaka Stephen Burns Kari Keys Tommy Yu Erica Walling Michelle Hoefnagel Geneva Jacobs Raine Osborne Maysam Ghovanloo Nazmus Sahadat James Morgan J. Andrew Taylor Isabelle Vivodtzev Beverly Hon Todd Linsenmeyer Carrie Miller Kristin Garlanger Sam Kortes Alyssa Schnorenberg Brooke Slavens Kenneth Lee Elizabeth Braatz Kathryn Fitzgerald Jessica Haven Brittany Durant Venessa Lee Carolyn Campbell Michael Henrie Victor Sudo Roger Williams Pamela Lauer Shu Cole Dubravka Svetina Edward Deci Gale Whiteneck EunKyoung Hong Steven Knezevic Pierre Asselin Stephen Kornfeld Peter H. Gorman Gail Forrest Ann M. Spungen Wesley Chay Travis Edmiston Carlos Marrero-Prats Gizelda Casella Katherine Froehlich-Grobe Maria Cole Rita Hamilton Simon Driver Tammy Isaacs Raj Parmar Rebecca Charbonneau Amanda Miller Ida Fox Aimee James Meredith Whitehead Rebecca Hamm Lorna Kahn Neringa Juknis Rimma Ruvinskaya Margaret Jones Kayla Roddick Nicholas Abramson Margaret Turk Audrey Leung Ki Kim Brittni Micham John Horton Parisa Zarreii Lourdes Alfonso Meghan Cochrane Marika Hess Audrey Chun Arlene Lazaro Dara Jones Miguel Escalon Adam F. Specht Christopher Cirnigliaro Alexander Lombard Michael LaFountaine Joshua Hobson Susan Sauer Steven Kirshblum Cristin McKenna Ann Spungen William Bauman Kyriakos Dalamagkas Lisa Wenzel Kenneth Miller Henry York Jessica Ketchum Kate Delaney Gavin Kolodge Suzan Lisenby Jennifer Piatt Debra Herbenick Lori Eldridge Eric Knee Grace Burton Philippines Cabahug Janet Dean Vidya Jayawardena Chester Ho Kevin Stahr Wendy Koesters VA Puget Sound Seattle Washington USA University of Washington Seattle Washington USA University of Washington Medical Center Seattle Washington USA University of South Florida/James A. Haley Veterans' Hospital and Clinics Tampa Florida USA Brooks Rehabilitation Hospital Jacksonville Florida USA Brooks Rehabilitation Clinical Research Center Jacksonville Florida USA Georgia Institute of Technology Atlanta Georgia USA Cardiovascular Research Laboratory Spaulding Rehabilitation Hospital Cambridge Massachusetts USA Department of Physical Medicine and Rehabilitation Harvard Medical School Boston Massachusetts USA Kessler Institute for Rehabilitation West Orange New Jersey USA Rutgers New Jersey Medical School Newark New Jersey USA Medical College of Wisconsin Affiliated Hospitals Milwaukee Wisconsin USA University of Wisconsin-Milwaukee Department of Occupational Science & Technology Milwaukee Wisconsin USA Roper Rehabilitation Hospital Charleston South Carolina USA James A. Haley Veterans’ Hospital and Clinics Tampa Florida USA University of Utah Salt Lake City Utah USA Zablocki VAMC Milwaukee Wisconsin USA Medical College of Wisconsin Milwaukee Wisconsin USA Craig Hospital Denver Colorado USA Indiana University Bloomington Indiana USA University of Rochester Rochester New York USA Spinal Cord Damage Research Center James J. Peters VA Medical Center Bronx New York USA Department of Rehabilitation Medicine Icahn School of Medicine at Mount Sinai New York New York USA Spinal Cord Injury Service James J. Peters VA Medical Center Bronx New York USA University of Maryland School of Medicine University of Maryland Rehabilitation and Orthopedic Institute Baltimore Maryland USA Kessler Foundation West Orange New Jersey USA Departments of Medicine Icahn School of Medicine at Mount Sinai New York New York USA Shepherd Center Atlanta Georgia USA Kennedy Krieger Institute Baltimore Maryland USA Johns Hopkins Medicine Baltimore Maryl

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On efficient bandwidth allocation for traffic variability in datacenters

On efficient bandwidth allocation for traffic variability in...

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IEEE Annual Joint Conference: INFOCOM, IEEE computer and Communications Societies

作者： Jian Guo Fangming Liu Xiaomeng Huang John C. S. Lui Mi Hu Qiao Gao Hai Jin Key Laboratory of Services Computing Technology and System Huazhong University of Science and Technology Ministry of Education Key Laboratory for Earth System Modeling Tsinghua University Department of Computer Science & Engineering The Chinese University of Hong Kong

Datacenter networks suffer unpredictable performance due to a lack of application level bandwidth guarantees. A lot of attentions have been drawn to solve this problem such as how to provide bandwidth guarantees for Virtualized Machines (VMs), proportional bandwidth share among tenants, and high network utilization under peak traffic. However, existing solutions fail to cope with highly dynamic traffic in datacenter networks. In this paper, we consider the effects of large numbers of short flows and massive bursty traffic in the datacenter, and design a novel distributed rate allocation algorithm based on the Logistic model under the control-theoretic framework. The theoretical analysis and experimental results using OpenFlow show that our algorithm not only guarantees the bandwidth for VMs, but also provides fast convergence to efficiency and fairness, and smooth response to bursty traffic.

关键词： Bandwidth Convergence Heuristic algorithms Algorithm design and analysis Resource management Channel allocation Logistics

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Implementation and test of human-operated and human-like adaptive impedance controls on Baxter robot

Implementation and test of human-operated and human-like ada...

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15th Annual Conference on Advances in Autonomous Robotics systems, TAROS 2014

作者： Liang, Peidong Yang, Chenguang Wang, Ning Li, Zhijun Li, Ruifeng Burdet, Etienne Centre for Robotics and Neural Systems School of Computing and Mathematics Plymouth University United Kingdom MOE Key Lab. of Autonomous System and Network Control College of Automation Science and Engineering South China University of Technology China State Key Laboratory of Robotics and System Harbin Institute of Technology China Department of Computer Science and Engineering Chinese University of Hong Kong Hong Kong Department of Bioengineering Imperial College of Science Technology and Medicine London United Kingdom

ISBN: (纸本)9783319104003

This paper presents an improved method to teleoperate impedance of a robot based on surface electromyography (EMG) and test it experimentally. Based on a linear mapping between EMG amplitude and stiffness, an incremental stiffness extraction method is developed, which uses instantaneous amplitude identified from EMG in a high frequency band, compensating for non-linear residual error in the linear mapping and preventing muscle fatigue from affecting the control. Experiments on one joint of the Baxter robot are carried out to test the approach in a disturbance attenuation task, and to compare it with automatic human-like impedance adaptation. The experimental results demonstrate that the new human operated impedance method is successful at attenuating disturbance, and results similarly to as automatic disturbance attenuation, thus demonstrating its efficiency. © 2014 Springer International Publishing.

关键词： Stiffness

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Projecting points onto planar parametric curves by local biarc approximation 22

Projecting points onto planar parametric curves by local bia...

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22nd Pacific Conference on computer Graphics and Applications, PG 2014

作者： Song, Hai-Chuan Shi, Kan-Le Yong, Jun-Hai Zhang, Sen School of Software Tsinghua University Beijing100084 China Department of Computer Science and Technology Tsinghua University Beijing100084 China Key Laboratory for Information System Security Ministry of Education of China Beijing100084 China Tsinghua National Laboratory for Information Science and Technology Beijing100084 China

ISBN: (纸本)9783905674736

This paper proposes a geometric iteration algorithm for computing point projection and inversion on surfaces based on local biarc approximation. The iteration begins with initial estimation of the projection of the prescribed test point. For each iteration, we construct a 3D biarc on the original surface to locally approximate the original surface starting from the current projection point. Then we compute the projection point for the next iteration, as well as the parameter corresponding to it, by projecting the test point onto this biarc. The iterative process terminates when the projection point satisfies the required precision. Examples demonstrate that our algorithm converges faster and is less dependent on the choice of the initial value compared to the traditional geometric iteration algorithms based on single-point approximation. © The Eurographics Association 2014.

关键词： Iterative methods

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Cooperative and Geometric Learning Algorithm (CGLA) for path planning of UAVs with limited information

Cooperative and Geometric Learning Algorithm (CGLA) for path...

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作者： Zhang, Baochang Liu, Wanquan Mao, Zhili Liu, Jianzhuang Shen, Linlin Science and Technology on Aircraft Control Laboratory School of Automation Science and Electrical Engineering BeiHang University Beijing 100191 China Department of Computing Curtin University Perth WA 6102 Australia Shenzhen Key Laboratory of Spatial Smart Sensing and Services School of Computer Science and Software Engineering Shenzhen University China Media Laboratory Huawei Technologies Co.Ltd. Shenzhen 518129 China

In this paper, we propose a new learning algorithm, named as the Cooperative and Geometric Learning Algorithm (CGLA), to solve problems of maneuverability, collision avoidance and information sharing in path planning for Unmanned Aerial Vehicles (UAVs). The contributions of CGLA are three folds: (1) CGLA is designed for path planning based on cooperation of multiple UAVs. Technically, CGLA exploits a new defined individual cost matrix, which leads to an efficient path planning algorithm for multiple UAVs. (2) The convergence of the proposed algorithm for calculating the cost matrix is proven theoretically, and the optimal path in terms of path length and risk measure from a starting point to a target point can be calculated in polynomial time. (3) In CGLA, the proposed individual weight matrix can be efficiently calculated and adaptively updated based on the geometric distance and risk information shared among UAVs. Finally, risk evaluation is introduced first time in this paper for UAV navigation and extensive computer simulation results validate the effectiveness and feasibility of CGLA for safe navigation of multiple UAVs. © 2014 Elsevier Ltd. All rights reserved.

关键词： Motion planning

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Fusion Coherence: Scalable Cache Coherence for Heterogeneous Kilo-Core system

Fusion Coherence: Scalable Cache Coherence for Heterogeneous...

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10th Annual Conference of Advanced computer Architecture, ACA 2014

作者： Pei, Songwen Kim, Myoung-Seo Gaudiot, Jean-Luc Xiong, Naixue Department of Computer Science and Engineering University of Shanghai for Science and Technology Shanghai 200093 China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Department of Electrical Engineering and Computer Science University of California Irvine CA 92697 United States School of Computer Science Colorado Technical University Springs CO 80907 United States

ISBN: (纸本)9783662444900

Future heterogeneous systems will integrate CPUs and GPUs on a single chip to achieve high computing performance as well as high throughput. In general, it would discard the current discrete pattern and will build a uniformed shared memory system avoiding explicit data movement among CPUs and GPUs connected by high throughput NoC. We propose a scalable cache coherence solution Fusion Coherence for Heterogeneous Kilo-core system Architecture by integrating CPUs and GPUs on a single chip to mitigate the coherence bandwidth side effects of GPU memory requests as well as overhead of copying data among memories of CPUs and GPUs. The Fusion Coherence coalesces L3 data cache of CPUs and GPUs based on a uniformed physical memory, further integrates a region directory and cuckoo directory into two levels of cache coherence directory without modifying cache coherence protocol. According to the experimental results with a subset of Rodina benchmarks, it is effective to decrease the overhead of data transfer and get an average execution speedup by 2.4x. The highest speedup is approximate to 4x for data-intensive applications. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Program processors

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Near-duplicate detection using GPU-based simhash scheme

Near-duplicate detection using GPU-based simhash scheme

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International Conference on Smart computing (SMARTCOMP)

作者： Xiaowen Feng Hai Jin Ran Zheng Lei Zhu Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China Information & Communication Company of Hunan Electric Power Corporation Changsha Hunan China

ISBN: (纸本)9781479957125

With the rapid growth of data, near-duplicate documents bearing high similarity are abundant. Elimination of near-duplicates can reduce storage cost and improve the quality of search indexes in data mining. A challenging problem is to find near-duplicate records in large-scale collections efficiently. There have already been several efforts on implementing near-duplicate detection on different architectures. In this paper, a new implementation, using a special hash function namely simhash, is proposed to identify near-duplicate documents on CUDA enabled devices. Two mechanisms are designed to achieve higher performance, including swapping and dynamic allocating. Experimental results show that our parallel implementation outperforms the serial CPU version, achieving up to 18 times.

关键词： Graphics processing units Fingerprint recognition Instruction sets Hamming distance Dynamic scheduling Kernel computer architecture

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Amorphous localization algorithm based on BP artificial neural network

Amorphous localization algorithm based on BP artificial neur...

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International Conference on Software Intelligence Technologies and Applications & International Conference on Frontiers of Internet of Things 2014

作者： Lin-zhe Zhao Xian-bin Wen Dan Li Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology China School of Computer Science and Technology Tianjin University China

Accurate localization of nodes is one of the key issues of wireless sensor network (WSN). Because the disadvantages of the classical Amorphous algorithm will produce large localization error in the process of localization. In order to solve the problem, an improved localization algorithm is proposed in this paper to reduce the localization error. The improved algorithm introduces the received signal strength threshold to modify the minimum hop from the unknown node to the beacon node, then BP algorithm is introduced to optimize the threshold and reduce the localization error. The simulation results show that the improved algorithm is better than other algorithms in the localization accuracy and energy consumption, and it is simple to achieve in the hardware.

关键词： Amorphous localization algorithm BP artificial neural network Wireless Sensor Network (WSN) localization Artificial neural networks algorithms Wireless sensor networks noncrystalline

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