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Semi-supervised learning with local and global consistency by geodesic distance and sparse representation 1

3rd Sino-Foreign-Interchange Workshop on intelligent Science and intelligent Data engineering, IScIDE 2012

作者： Gui, Jie Zhao, Zhongqiu Hu, Rongxiang Jia, Wei Intelligent Computing Lab. Hefei Institute of Intelligent Machines Chinese Academy of Sciences Hefei Anhui 230031 China State Key Laboratory for Novel Software Technology Nanjing University China College of Computer Science and Information Engineering Hefei University of Technology China Institue of Energy Safety Chinese Academy of Sciences Hefei Anhui 230031 China

ISBN: (数字)9783642366697

ISBN: (纸本)9783642366680

In many practical data mining applications, such as web categorization, key gene selection, etc., generally, unlab.led training examples are readily availab.e, but lab.led ones are fairly expensive to obtain. Therefore, in recent years, semi-supervised learning algorithms such as graph-based methods have attracted much attention. However, most of these traditional methods adopted a Gaussian function to calculate the edge weights of the graph. In this paper, a novel weight for semi-supervised graph-based methods is proposed. The new method adds the lab.l information from problem into the target function, and adopts the geodesic distance rather than Euclidean distance as the measure of the difference between two data points when conducting the calculation. In addition, we also add class prior knowledge from problem into semi-supervised learning algorithm. Here we address the problem of learning with local and global consistency (LGC). It was found that the effect of class prior knowledge was probably different between under high lab.l rate and low lab.l rate. Furthermore, we integrate sparse representation (SR) in LGC algorithm. Experiments on a UCI data set show that our proposed method outperforms the original algorithms. © Springer-Verlag 2013.

关键词： Learning algorithms

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Towards a taxonomy framework of evolution for SOA solution: From a practical point of view

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Combined Workshops on Web Information Systems engineering, WISE 2011 and WISE 2012

作者： Feng, Zaiwen Hung, Patrick C. K. He, Keqing Ma, Yutao Farwick, Matthias Li, Bing Peng, Rong State Key Lab. of Software Engineering Wuhan University China School of Computer Wuhan University China Hubei Provincial Key Laboratory of Intelligent Robot Wuhan Institute of Techonology China Faculty of Business and IT University of Ontario Institute of Technology Canada Institute of Computer Science University of Innsbruck Austria

ISBN: (纸本)9783642383328

Presently, the research on evolution of SOA solution is becoming more and more important in industry. It is necessary to extract a taxonomy framework for evolution of SOA solution because by using it, evolution of SOA-based systems can be analyzed and compared comprehensively and objectively. In this paper, a taxonomy framework for evolution of SOA solution is proposed that is illustrated from four perspectives: (a) motivations for evolutionary changes (why), (b) locations where evolutionary changes happen (where), (c) times when evolutionary changes happen (when), and (d) support mechanisms in the process of evolutionary changes (how). Furthermore, the taxonomy framework is applied on analyzing a SOA-based configurable system for urban logistics delivery management, as an application of taxonomy framework. © 2013 Springer-Verlag.

关键词： Taxonomies

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Online balance strategy on byproduct gas in iron and steel industry

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Xitong Gongcheng Lilun yu Shijian/System engineering Theory and Practice 2013年第6期33卷 1486-1491页

作者： Cao, Yong-Feng Xu, Yin-Feng School of Management Xi'an Jiaotong University Xi'an 710049 China Ministry of Education Key Lab. for Intelligent Networks and Network Security Xi'an Jiaotong University Xi'an 710049 China The MOE Key Lab. for Process Control and Efficiency Engineering Xi'an Jiaotong University Xi'an 710049 China

This paper develops a new framework for the analysis of byproduct gas supply in iron and steel industry. Based on the online theory, this paper studies the online balance assignment problem of the byproduct gas. In the production process, the online decision maker makes decisions to balance the supply of byproduct gas in the online case. Under some reasonable assumptions, the paper constructs a balance assignment model of the byproduct gas to solve the balance range unknown problem. First, this researcher attempts to analyze the special nature of the offline case and the characteristics of the online case under different scenes. Then the paper designs an online balance strategy with a competitive ratio of (1+3M/m)/4 without the knowledge of supply interval. This study provides some ideas and theories for the balance assignment and use of the byproduct in manufacture industry.

关键词： Steelmaking

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Transient performance improvement using composite nonlinear feedback and integral sliding surface for matched and unmatched uncertain MIMO linear systems

Transient performance improvement using composite nonlinear ...

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International Conference on control, Instrumentation, and Automation

作者： Saleh Mobayen Mohammad Hasan Asemani Vahid Johari Majd Electrical Engineering Department University of Zanjan Zanjan Iran Department of Power and Control Engineering Shiraz University Shiraz Iran Intelligent Control Systems Lab. Tarbiat Modares University Tehran Iran

This paper offers a combination of composite nonlinear feedback and integral sliding mode to achieve high performance and robustness for matched and unmatched uncertain MIMO linear systems. The control law is designed to guarantee the existence of the sliding mode around the nonlinear surface, and the damping ratio of the closed-loop system is increased as the output approaches the set-point. Simulation results are presented to show the effectiveness of the proposed method as a promising way for controlling similar nonlinear systems.

关键词： Uncertainty Closed loop systems Robustness Feedback control Linear systems Eigenvalues and eigenfunctions

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A New Evolutionary-Incremental Framework for Feature Selection

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Advances in Artificial Intelligence 2014年第1期2014卷

作者： Mohamad-Hoseyn Sigari Muhammad-Reza Pourshahabi Hamid-Reza Pourreza Machine Vision Research Lab. Computer Engineering Department Ferdowsi University of Mashhad Mashhad 91779 Iranum.ac.ir Control and Intelligent Processing Center of Excellence (CIPCE) School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran 14399 Iranut.ac.ir

Feature selection is an NP-hard problem from the viewpoint of algorithm design and it is one of the main open problems in pattern recognition. In this paper, we propose a new evolutionary-incremental framework for feature selection. The proposed framework can be applied on an ordinary evolutionary algorithm (EA) such as genetic algorithm (GA) or invasive weed optimization (IWO). This framework proposes some generic modifications on ordinary EAs to be compatible with the variable length of solutions. In this framework, the solutions related to the primary generations have short length. Then, the length of solutions may be increased through generations gradually. In addition, our evolutionary-incremental framework deploys two new operators called addition and deletion operators which change the length of solutions randomly. For evaluation of the proposed framework, we use that for feature selection in the application of face recognition. In this regard, we applied our feature selection method on a robust face recognition algorithm which is based on the extraction of Gabor coefficients. Experimental results show that our proposed evolutionary-incremental framework can select a few number of features from existing thousands features efficiently. Comparison result of the proposed methods with the previous methods shows that our framework is comprehensive, robust, and well-defined to apply on many EAs for feature selection.

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Spelling out opinions: Difficult cases of sentiment analysis

Spelling out opinions: Difficult cases of sentiment analysis

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IEEE International Conference on Ubi-Media Computing

作者： Ivan Khozyainov Evgeny Pyshkin Vitaly Klyuev Institute of Computing and Control St. Petersburg State Polytechnical University St. Petersburg Russia Software Engineering Lab. University of Aizu Fukushima Japan

In recent years there is growing interest to the opinion mining applications in numerous areas of information and social science. In this paper we investigate main problems in opinion mining and sentiment analysis systems development. We review examples of difficulties in process of opinion extraction and introduce essential multidimensionality of opinion mining. We carried out a series of experiments with different sentiment analyzers and classified main reasons of incorrect sentiment recognition.

关键词： Data mining Context Motion pictures Monitoring Media Grammar Text recognition

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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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IEEE International Conference on High Performance Computing and Communications (HPCC)

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

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.

关键词： Graphics processing units Instruction sets Kernel Accuracy Histograms Optimization Memory management

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Calculating the Electric Fields in the Human Brain by Deep Transcranial Magnetic Stimulation

Calculating the Electric Fields in the Human Brain by Deep T...

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URSI Commission B International Symposium on Electromagnetic Theory

作者： Mai Lu Shoogo Ueno Key Lab. of Opt-Electronic Technology and Intelligent Control of Ministry of Education Lanzhou Jiaotong University Department of Applied Quantum Physics Graduate School of Engineering Kyushu University

ISBN: (纸本)9781467349390

Stimulation of deeper brain structures by transcranial magnetic stimulation (TMS) may be beneficial in the treatment of several neurological and psychiatric disorders. This paper presents numerical simulation of deep transcranial magnetic stimulation (dTMS) by considering double cone, H- and Halo coils. Three-dimensional distributions of the induced electric fields in realistic head model by dTMS coils were calculated by impedance method and the results were compared with that of standard figure-of-eight coil. Simulation results show that double cone and H-coils have significantly deep field penetration at the expense of induced higher and wider spread electrical fields in superficial cortical regions. The combination of Halo coil with a conventional circular coil produce deeply penetrating electric field the same as double cone and H-coils, but the stimulation in superficial brain tissues are much lower.

关键词： Coils Magnetic stimulation Magnetic heads Head Solid modeling Numerical models Impedance measurement

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Calculating the Induced Electromagnetic Fields in Real Human Head by Deep Transcranial Magnetic Stimulation

Calculating the Induced Electromagnetic Fields in Real Human...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society

ISBN: (纸本)9781457702150

Stimulation of deeper brain structures by transcranial magnetic stimulation (TMS) may be beneficial in the treatment of several neurological and psychiatric disorders. This paper presents numerical simulation of deep transcranial magnetic stimulation (dTMS) by considering double cone, H-and Halo coils. Three-dimensional distributions of the induced fields i.e. magnetic flux density, current density and electric fields in realistic head model by dTMS coils were calculated by impedance method and the results were compared with that of figure-of-eight coil. It was found that double cone and H-coils have significantly deep field penetration at the expense of induced higher and wider spread electrical fields in superficial cortical regions. The Halo coil working with a circular coil carrying currents in opposite directions provides a flexible way to stimulate deep brain structures with much lower stimulation in superficial brain tissues.

关键词： Double Cone Transcranial Magnetic Stimulation haloes Coils Characteristic impedance Stimuli Electric fields Electromagnetic fields induction field Head numerical simulation

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3D model estimation using a single RGB-D image

3D model estimation using a single RGB-D image

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2012 International Conference on Machine Learning and Cybernetics, ICMLC 2012

作者： Li, Ricky Jun-Bo Luo, Rong-Hua Min, Hua-Qing Intelligent Software and Robot Lab. School of Computer Science and Engineering South China University of Technology Guangzhou China

ISBN: (纸本)9781467314855

Model estimation is important for robotic grasping. Since in order to make a decision about how to grasp the object, the robot should know where the target is and what it looks like. In this paper we propose a method of 3D model estimation using a single RGB-D image. The target object is segmented out from background using RANSAC and convex hull algorithm. And a clustering method is designed to separate different objects. After recognizing the types of the objects, the parameters of the model of objects are estimated according partial observed information and the symmetrical property of objects. Although the parameter estimation process may vary for different kinds of model, yet the key of the method are RANSAC and Ordinary Least Squares (OLS). Experimental results show that our method is effective in model analyzing. © 2012 IEEE.

关键词： Parameter estimation

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