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24th ACM International Conference on Information and Knowledge Management, CIKM 2015

作者： Zhang, Yaogong Xu, Jun Lan, Yanyan Guo, Jiafeng Xie, Maoqiang Huang, Yalou Cheng, Xueqi College of Computer and Control Engineering Nankai University China CAS Key Lab. of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences China College of Software Nankai University China

ISBN: (纸本)9781450337946

Ranking SVM, which formalizes the problem of learning a ranking model as that of learning a binary SVM on preference pairs of documents, is a state-of-the-art ranking model in information retrieval. The dual form solution of Ranking SVM model can be written as a linear combination of the preference pairs, i.e., w = Σ(i,j)αij(xi - xj), where αij denotes the Lagrange parameters associated with each pair (i,j). It is obvious that there exist significant interactions over the document pairs because two preference pairs could share a same document as their items. Thus it is natural to ask if there also exist interactions over the model parameters αij, which we may leverage to propose better ranking model. This paper aims to answer the question. Firstly, we found that there exists a low-rank structure over the Ranking SVM model parameters αij, which indicates that the interactions do exist. Then, based on the discovery, we made a modification on the original Ranking SVM model by explicitly applying a low-rank constraint to the parameters. Specifically, each parameter αij is decomposed as a product of two low-dimensional vectors, i.e., αij = (υi,υj), where vectors vi and vj correspond to document i and j, respectively. The learning process, thus, becomes to optimize the modified dual form objective function with respect to the low-dimensional vectors. Experimental results on three LETOR datasets show that our method, referred to as Factorized Ranking SVM, can outperform state-of-the-art baselines including the conventional Ranking SVM. © 2015 ACM.

关键词： Information retrieval

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Social sensing enhanced time estimation for bus service

Social sensing enhanced time estimation for bus service

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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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Parameters adaption of Lebesgue sampling-based diagnosis and prognosis for Li-ion batteries

Parameters adaption of Lebesgue sampling-based diagnosis and...

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2015 Annual Conference of the Prognostics and Health Management Society, PHM 2015

作者： Yan, Wuzhao Dou, Wanchun Liu, Datong Peng, Yu Zhang, Bin Department of Electrical Engineering University of South Carolina ColumbiaSC29208 United States Department of Computer Science and Technology State Key Lab. for Novel Software Technology Nanjing University NanjingJiangsu210093 China Department of Automatic Test and Control Harbin Institute of Technology HarbinHeilongjiang150080 China

ISBN: (纸本)9781936263202

Traditional fault diagnosis and prognosis (FDP) approaches are based on Riemann sampling (RS), in which samples are taken and algorithms are executed in a periodic time interval. With the increase of system complexity, the real-time implementation of this Riemann sampling-based FDP (RS-FDP) becomes a bottleneck, especially for distributed applications. To overcome this problem, a Lebesgue sampling-based FDP (LS-FDP) is proposed. LS-FDP takes samples on the fault dimension axis and provides a need-based diagnostic philosophy in which the algorithm is executed only when necessary. In previous Lebesgue sampling-based FDP, the Lebesgue length is a constant. To accommodate the change of fault dynamics, it is desirable to execute FDP algorithm more frequently when the fault growth is fast while less frequently when fault growth is slow. This requires to change the Lebesgue length adaptively. The goal of this paper is to deliver an improved LS-FDP method with varying Lebesgue length, which enables the FDP to be executed according to needs. The design and implementation of varying Lebesgue length LS-FDP based on a particle filtering algorithm are illustrated with experimental results on Li-ion batteries to verify the performances of the proposed approach. The experimental results show that the new varying LS-FDP is accurate and time-efficient on long term prognosis and also keeps a closer monitoring on the fast increase of fault size. © 2015, Prognostics and Health Management Society. All rights reserved.

关键词： Real time control

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Removing water fluctuation via motion field-based kernel regression

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Journal of Information and Computational Science 2014年第15期11卷 5289-5296页

作者： Hu, Wenrui Xie, Yuan Zhang, Wensheng Tan, Yuanhua State Key Lab. of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Karamay Hongyou Software Co. Ltd. Xinjiang China

A new approach is proposed in this paper to recover the original image of an underwater scene from a given sequence distorted by water fluctuation. The contribution of our method is to use a motion field-based kernel regression to reconstruct an undistorted image. It first utilizes the image registration method to generate registered frames and the corresponding motion fields, and then detect a set of stationary patches from registered frames by calculating the movement energy of local regions. Finally, a temporal kernel regression is carried out to combine the detected stationary patches to reconstruct an undistorted stationary image. Experiments illustrate that this approach can effectively alleviate distortions and significantly improve visual quality of the distorted images. Copyright © 2014 Binary Information Press.

关键词： Image registration

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Fusion modeling of the hot rolling strip width

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Journal of Computational Information Systems 2014年第12期10卷 5373-5380页

作者： Tian, Jianyan Wang, Fang Qiu, Huadong Li, Wenting College of Information Engineering Taiyuan University of Technology Taiyuan 030024 China Key Lab. of Advanced Transducers and Intelligent Control Syst. at Taiyuan Univ. of Technol. Ministry of Education Taiyuan 030024 China

By organically integrating the computation formulas of hot rolling strip width mechanism model with the intelligent modeling technique, this paper proposes an intelligent fusion modeling method for a hot rolling strip width model. Due to the relations between the variations of hot rolling strip width and factors such as the chemical composition of the slab., side compression of vertical rollers, thickness compression ratios, plate temperature, velocity and strain, and also the distinct influences by these factors mentioned afore, this paper adopts a neural network based on the improved particle swarm optimization to adjust parameters in the width mechanism model. It aims to give the mechanism model some level of self-learning and adaptive abilities, as to improve the model accuracy, broaden the range of applications, and also ensure modeling speed. In addition, in order to better control the head and tail shapes of the strip, an improvement about short stroke control has been made to the head and tail width model. Practical applications at a steelworks indicate that this method is feasible and effective by reducing width fluctuations of finished strips, raising steel yield rates and achieving favorable economical benefits. 1553-9105/Copyright © 2014 Binary Information Press.

关键词： Particle swarm optimization (PSO)

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The 5th International Conference on Biomedical engineering and Biotechnology (ICBEB 2016) Abstracts

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BMC MEDICAL IMAGING 2016年第SUPPL 1期16卷 65-65页

作者： [Anonymous] Department of MRI Shandong Medical Imaging Research Institute Affiliated to Shandong University Jinan Shandong 250021 People’s Republic of China Department of Interventional Radiology Shandong Provincial Hospital Affiliated to Shandong University Jinan Shandong 250021 People’s Republic of China College of Information Science and Technology Engr. Research Center of Digitized Textile & Fashion Tech. for Ministry of Education Donghua University Shanghai 201620 China Intelligent multimedia information processing Lab College of Software Northeastern University Shenyang Liaoning Province 110004 China Institute of Biomedical and Health Engineering Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China School of Computer Science and Technology Nanjing Normal University Nanjing China Department of Electrical Engineering The City College of New York CUNY New York USA Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing Nanjing China School of Electronic Science and Engineering Nanjing University Nanjing Jiangsu 210046 China College of Engineering Nanyang Technological University Singapore 639798 Singapore School of Electronic Information Shanghai Dianji University Shanghai China School of Natural Sciences and Mathematics Shepherd University Shepherdstown WV 25443 USA Davis College of Agriculture Natural Resources and Design West Virginia University Morgantown WV 26505 USA State Key Laboratory of Millimeter Waves Southeast University Nanjing 210096 China Center of Medical Physics and Technology Hefei Institutes of Physical Science Chinese Academy of Sciences Hefei China College of Agricultural and Life Sciences University of Florida Gainesville FL 32611 USA Courant Institute of Mathematical Sciences New York University New York NY 10012 USA Translational Imaging Division & MRI Unit Columbia University and New York State Psychiatric Institute New York NY 10032 USA Guangxi Key Laboratory of Manufacturing System & Adv

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Real-time control for traffic signal based on fuzzy hybrid petri net

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Journal of Computational Information Systems 2014年第5期10卷 2079-2090页

作者： Tian, Zhao Zhang, Zundong Dong, Honghui She, Wei Ye, Yangdong Jia, Limin State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing 100044 China Beijing Key Lab. of Urban Road Transportation Intelligent Control Technology North China University of Technology Beijing 100041 China Beijing Research Center of Urban Trafic Information Intelligent Sensing and Service Technologies Beijing 100044 China School of Information Engineering Zhengzhou University Zhengzhou 450052 China

According to the problem of not making full use of the road resources and not adapting the changeable traffic situation based on the traffic lights with the fixed cycle and the fixed phase sequence, this paper defines a kind of Fuzzy Hybrid Petri nets (FHPN) to simulate the real-time control for the traffic signal. The traffic signal control based on the Fuzzy Hybrid Petri nets not only can compute the best green light duration of each phase in time but also can determine the reasonable and alterable phase sequence. The simulation analysis shows that the real-time traffic signal control based on the Fuzzy Hybrid Petri nets can reduce furthest the count of the vehicle second stops, so the average delay time of the vehicles and the passengers can be reduced. © 2014 Binary Information Press.

关键词： Real time control

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CLSIFT: An optimization study of the scale invariance feature transform on GPUs

CLSIFT: An optimization study of the scale invariance featur...

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15th IEEE International Conference on High Performance Computing and Communications, HPCC 2013 and 11th IEEE/IFIP International Conference on Embedded and Ubiquitous Computing, EUC 2013

作者： Wang, Weiyan Zhang, Yunquan Guoping, Long Yan, Shengen Jia, Haipeng Lab. of Parallel Software and Computational Science Institute of Software Chinese Academy of Sciences China State Key Laboratory of Computing Science Institute of Software Chinese Academy of Sciences China School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9780769550886

Scale Invariance Feature Transform (SIFT) is quite suitable for image matching because of its invariance to image scaling, rotation and slight changes in illumination or viewpoint. However, due to high computation complexity it's technically challenging to deploy SIFT in real time application situations. To address this problem, we propose CLSIFT, an OpenCL based highly speeded up and performance portable SIFT solution. Important optimization techniques employed in CLSIFT such as: (1) For less global memory traffic, independent logical functions are merged into the same kernel to reuse data.(2) loop buffers are introduced in for data and intermediate results reusing.(3)Task queue used to schedule threads in the same branch to remove branch divergences. (4) Data partition is based on the statics patterns for workload balance among workgroups. (5) Overlap of CPU time and better parallel strategies are used too. With all mentioned efforts, CLSIFT processes lena. jpg at 74.2 FPS and 43.4FPS respectively on NVidia and AMD GPUS, much higher than CPU's nearly 10 FPS and the known fastest SIFTGPU's 39.8 FPS and 13FPS. Moreover in a quantitative comparison approach we analyze those successful strategies beating SIFTGPU, a famous existing GPU implementation. Additionally, we observe and conclude that NVidia GPU achieves better occupancy and performance due to some factors. Finally, we summarize some techniques and empirical guiding principles that may be shared by other applications on GPU. © 2013 IEEE.

关键词： Graphics processing unit

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Numerical simulation of deep transcranial magnetic stimulation by multiple circular coils

Numerical simulation of deep transcranial magnetic stimulati...

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13th Mediterranean Conference on Medical and Biological engineering and Computing 2013, MEDICON 2013

作者： Lu, M. Ueno, S. Lanzhou Jiaotong University Key Lab. of Opt-Electronic Technology and Intelligent Control of Ministry of Education Lanzhou 730070 China Kyushu University Department of Applied Quantum Physics Graduate School of Engineering Fukuoka 812-8581 Japan

ISBN: (纸本)9783319008455

Stimulation of deeper brain structures by tran-scranial magnetic stimulation (TMS) plays a role in the study of reward and motivation mechanisms, which may be beneficial in the treatment of several neurological and psychiatric disor-ders. This paper presents a numerical simulation of deep tran-scranial magnetic stimulation (dTMS) in a realistic head model by considering large circular coil surrounding the head combi-nation of smaller coils. Three-dimensional distributions of the induced electric fields in the head were calculated by employing impedance method. Simulation results show that multiple circu-lar coils provides a potential way to produce deeply penetrating electric fields in deep brain regions with less fields in superficial cortical tissues. © Springer International Publishing Switzerland 2014.

关键词： Electric fields

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Embedding of nonlinear systems in a linear parameter-varying representation 19

Embedding of nonlinear systems in a linear parameter-varying...

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19th IFAC World Congress on International Federation of Automatic control, IFAC 2014

作者： Abbas, Hossam S. Tóth, Roland Petreczky, Mihály Meskin, Nader Mohammadpour, Javad Department of Electrical Engineering College of Engineering Qatar University PO Box 2713 Doha Qatar Control Systems Group Eindhoven University of Technology P.O. Box 513 Eindhoven5600 MB Netherlands Department of Computer Science and Automatic Control Ecole des Mines de Douai Douai59508 France Intelligent Control Systems Lab. College of Engineering University of Georgia AthensGA30602 United States Electrical Engineering Department Faculty of Engineering Assiut University Assiut Egypt

ISBN: (纸本)9783902823625

This paper introduces a systematic approach to synthesize linear parameter-varying (LPV) representations of nonlinear (NL) systems which are originally defined by control affine state-space representations. The conversion approach results in LPV state-space representations in the observable canonical form. Based on the relative degree concept of NL systems, the states of a given NL representation are transformed to new coordinates that provide its normal form. In the SISO case, all nonlinearities of the original system are embedded in one NL function which is factorized to construct the LPV form. An algorithms is proposed for this purpose. The resulting transformation yields an LPV model where the scheduling parameter depends on the derivatives of the inputs and outputs of the system. In addition, if the states of the NL model can be measured or estimated, then the procedure can be modified to provide LPV models scheduled by these states. Examples are included for illustration. © IFAC.

关键词： State space methods

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