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

作者： A. Holobar D. Zazula Laboratory of Engineering of Neuromuscular System and Motor Rehabilitation Politecnico di Turino Torino Italy Faculty of Electrical Engineering and Computer Science University of Maribor Maribor Slovenia

Recently, gradient Convolution Kernel Compensation method was introduced for blind assessment of sparse pulse sequences (PS) out of their convolutive mixtures. This method employs multichannel recordings, is fully automatic and is minimally biased by assumptions about underlying mixing process. In the first step, the unknown mixing channels (convolution kernels) are compensated, whereas in the second step the gradient algorithm is used to blindly optimize the estimated PSs. This paper discusses the selection of the cost functions for aforementioned gradient-based optimization and provides analytical framework for their mutual comparison. Theoretical derivations are validated on both synthetic signals with random mixing matrices and experimental surface electromyograms from abductor pollicis brevis muscle. The analytical derivations agree very well with the results obtained from numerical simulations and establish theoretical guidelines for developing new gradient-based decomposition methods.

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Pointwise Logic on Completely Distributive Lattices and Approximate Reasoning

Pointwise Logic on Completely Distributive Lattices and Appr...

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International Conference on Fuzzy systems and Knowledge Discovery (FSKD)

作者： Yalin Zheng Guang Yang Jing Zheng Jinsheng Xing State Key Laboratory for Intelligent Technology and Systems Department of Automation Faculty of Information Science and Technology Tsinghua University Beijing China Research Center of Intelligent Information Technology Department of Computer Science and Technology Faculty of Software Dongguan University of Science and Technology Dongguan China Research Center of Dongguan Economy Department of Economy and Commerce Dongguan University of Science and Technology Dongguan China Faculty of Mathematics and Computer Science Shanxi Normal University Linfen China Research Center of System Engineering Faculty of Electronic and Information Engineering Xi'an Jiaotong University Xi'an China

In this paper, we propose the basic framework of point- wise topological logic on completely distributive lattices and explore approximate reasoning in it. The logic of this paper is based on pointwise characterization, therefore the pointwise conception is pervasive. We explore approximate reasoning in abstract logical framework Fl on completely distributive lattice L. We propose the structure of point- wise topological logic F TL , the structure of matching function sigma. and the structure of matching neighborhood group. We investigate approximate reasoning in pointwise topological logic F TL with matching function sigma, develop pointwise topological algorithm of simple approximate reasoning, introduce the essential characteristics of this scheme.

关键词： Lattices Fuzzy logic computer science Knowledge engineering Fuzzy systems Information technology Laboratories Intelligent systems Automation Information science

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Research on rough set theory and applications in China

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Lecture Notes in computer science

作者： Wang, Guoyin Zhang, Qinghua Huang, Houkuan Ye, Dongyi Hu, Qinghua Hu, Xuegang Shi, Zhongzhi Li, Yongli Shang, Lin An, Liping Sai, Ying Chen, Shanben Liang, Jiye Qin, Keyun Zeng, Huanglin Xie, Keming Miao, Duoqian Min, Fan Wu, Zhaocong Wu, Weizhi Dai, Jianhua Institute of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing 400065 China School of Information Science and Technology Southwest Jiaotong University Chengdu 610031 China School of Computer and Information Technology Beijing Jiaotong University Beijing 100044 China College of Math. and Computer Fuzhou University Fuzhou 350002 China Harbin Institute of Technology PO Box 458 Harbin 150006 China School of Computer and Information Hefei University of Technology Hefei 230009 China Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China Lanzhou University No.222 Tianshui South Rd. Lanzhou 730000 China State Key Laboratory for Novel Software Technology Nanjing University Nanjing 210093 China Management Science and Engineering Department Business School Nankai University Tianjin 300071 China Shandong University of Finance No.40 Shun-geng Road Jinan 250014 China Welding Engineering Institute Shanghai Jiaotong University Shanghai 200030 China School of Computer and Information Technology Shanxi University Taiyuan 030006 China Intelligent Control Development Center Southwest Jiaotong University Chengdu 610031 China Artificial Intelligence of Key Laboratory Sichuan University of Science and Engineering Zigong 643000 China Department of Automation College of Information Engineering Taiyuan University of Technology Taiyuan 030024 China 4800 CaoAn Highway Shanghai 201804 China School of Computer Science and Technology University of Electronic Science and Technology of China Chengdu 610054 China School of Remote Sensing Information Engineering Wuhan University Wuhan 430079 China Institute for Information and System Sciences Faculty of Science Xi'an Jiaotong University Xi'an 710049 China Information College Zhejiang Ocean University Zhejiang 316004 China Institute of Artificial Intelligence Zhejiang University Hangzhou 310027 China

ISBN: (纸本)3540850635

This article gives a capsule view of research on rough set theory and applications ongoing at universities and laboratories in China. Included in this capsule view of rough set research is a brief description of the following things: Chinese research groups on rough set with their URLs for web pages, names of principal researchers (supervisors), numbers of graduate students, and topics being investigated. Statistical summaries showing the growth in the research on rough set theory and application in China are included. In addition, an introduction summarizing the research interests of Chinese researchers is included in this article. The contribution of this article is a complete overview of the principal research directions in rough set theory and its applications in China. © 2008 Springer-Verlag Berlin Heidelberg.

关键词： Rough set theory

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Hybrid splitting criteria based on purity measures

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WSEAS Transactions on computers 2007年第5期6卷 843-850页

作者： Povalej, Petra Kokol, P. Laboratory for System Design Faculty for Electrical Engineering and Computer Science University of Maribor Smetanova ulica 17 2000 Maribor Slovenia

Decision trees are one of the most transparent methods probably most often used for solving classification, tasks. In the process of decision tree induction a lot of input parameters have to be fine-tuned in order to obtain good results. However the most important and probably most influential parameter in top-down induction method is a splitting criterion, which can vary from one classification task to another. In this paper we empirically tested four of them, based on well known purity measures, on 54 UCI databases. Although none of the proposed splitting criterion in the literature has proved to be universally better than the rest, they are not always suitable for solving any classification task. Therefore we propose two new splitting criteria: hybrid linear combination of purity measures and voting of purity measures, which obtain at least comparable results to other well-known criteria used in greedy decision tree induction method, while their structure makes them ideal for non-expert users. Boosting was also applied as one of the most successful ensemble methods, which once again proved the ability to significantly improve the classification accuracy on many databases.

关键词： Classification (of information)

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Estimation of Power system Variability due to Wind Power

Estimation of Power System Variability due to Wind Power

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Power Tech Conference

作者： George Papaefthymiou Jody Verboomen Lou van der Sluis Electrical Power System Laboratory (EPS) Faculty of Electrical Engineering Mathematics ' Computer Science Delft University of Technnology Delft Netherlands

The incorporation of wind power generation to the power system leads to an increase in the variability of the system power flows. The assessment of this variability is necessary for the planning of the necessary system reinforcements. For the assessment of this variability, the uncertainty in the system inputs should be modeled, comprising of the time-dependent stochasticity of the system loads and the correlated wind resources. In this contribution, a unified Monte-Carlo simulation methodology is presented that addresses both issues. The application of the method for the analysis of the wind power integration in the New England test system is presented.

关键词： Power systems Wind energy Power system modeling Wind energy generation Wind power generation Load flow Wind speed Stochastic systems Power generation Power system planning

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Intelligent Data Analysis for Diagnostics of Alcohol Dependency

Intelligent Data Analysis for Diagnostics of Alcohol Depende...

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Annual IEEE Symposium on computer-Based Medical systems

作者： Petra Povalej Matej Kravos Peter Kokol Laboratory for System Design Faculty of Electrical Engineering and Computer Science University of Maribor Slovenia Psychiatric Hospital Ormož Ormoz Slovenia

The alcohol dependency is hard to diagnose since none of the existing laboratory markers has sufficient specificity and sensitivity. Therefore the goal of our study was to find better laboratory markers and / or their combinations. For that purpose the intelligent data analysis using the decision tree induction method was used. The results show that the combination of three or even two markers can prove alcohol dependency with almost 85% accuracy. However the remark has to be made that the induced decision tree offers a qualitatively different access to diagnostic evaluation of laboratory findings and varies from common practice, because it sets up its new and own borders and criteria what is the unlike from generally accepted or set up reference values. All selected markers are widely accessible, inexpensive and part of a routine laboratory tests.

关键词： Data analysis Laboratories Decision trees Medical diagnostic imaging Alcoholism Testing Biochemistry Databases Decision making Learning systems

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Intelligent Data Analysis of Out-of-Hospital Cardiac Arrest

Intelligent Data Analysis of Out-of-Hospital Cardiac Arrest

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Annual IEEE Symposium on computer-Based Medical systems

作者： Mateja Verlic Miljenko Krizmaric Stefek Grmec Peter Kokol Laboratory for System Design Faculty of Electrical Engineering and Computer Science University of Maribor Slovenia Faculty of Health Sciences University of Maribor Slovenia Centre for Emergency Medicine Maribor Slovenia

The rate of survival for the out-of-hospital cardiac arrest (OHCA) is not encouraging. Quick and quality prognosis affects the OHCA outcome. Identification of important factors in prognosis can improve the survival rate. Intelligent data analysis of data obtained in a 4 year study of OHCA outcome in Maribor shows that arrival time of emergency medical team, witnessed arrest, bystander cardiopulmonary resuscitation and especially end-expired CO 2 are of great importance for the OHCA outcome.

关键词： Data analysis Cardiac arrest Rhythm Medical diagnostic imaging Decision trees Cardiology Fibrillation Ventilation Carbon dioxide Pulse measurements

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Multiscale Edge Detector

Multiscale Edge Detector

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International Symposium on Electronics in Marine (ELMAR)

作者： D. Heric B. Potocnik Faculty of Laboratory of Electrical Engineering and Computer Science System Software Laboratory University of Maribor Maribor Slovenia

The purpose of this paper is to introduce an novel edge detector using directional wavelet transform and signal registration. Directional wavelet transform decomposes an image into four-dimensional space which augments the image by the scale and directional information. We show the directional information significantly improves edge detection in noisy images in comparison with the classical multiscale edge detector, and enables more reliable edge tracing along an object boundary. Edge detection is based on the modulus maximum principle with an adaptive threshold whose value is calculated via maximum entropy measure. Edge tracing is done with signal alignment between neighbour edges

关键词： Image edge detection Detectors Wavelet transforms Discrete wavelet transforms Laboratories computer science system software Object detection Entropy Image registration

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Edge Relaxation in Images using Directional Hierarchical Image Decomposition

Edge Relaxation in Images using Directional Hierarchical Ima...

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Proceedings of the Nordic Signal Processing Symposium (NORSIG)

作者： Dusan Heric Bozidar Potocnik Faculty of Electrical Engineering and Computer Science System Software Laboratory University of Maribor Maribor Slovenia

This paper presents a new hierarchical method of the edge relaxation by using an edge confidence measure. Proposed method is an adaptive and based on directional hierarchical image decomposition and an edge connecting algorithm. It is shown that such combination has low sensitivity to noise, while it is highly robust to outliers, and provide a quality edge connection mechanism

关键词： Image decomposition Image edge detection Image segmentation Image processing Relaxation methods Joining processes Labeling Image analysis computer science system software

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Image enhancement by using directional wavelet transform

Image enhancement by using directional wavelet transform

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International Conference on Information Technology Interfaces

作者： D. Heric B. Potocnik Faculty of Electrical Engineering and Computer Science System Software Laboratory University of Maribor Maribor Slovenia

The purpose of this paper is to introduce a novel image enhancement technique by using directional wavelet transform. Directional wavelet transform decomposes an image into four-dimensional space which augments the image by the scale and directional information. We show the directional information significantly improves image enhancement in noisy images in comparison with the classical techniques. Image enhancement is based on the multiscale singularity detection with an adaptive threshold whose value is calculated via maximum entropy measure. The proposed technique was tested on synthetic images at different signal-to-noise ratios and clinical images

关键词： Image enhancement Wavelet transforms Histograms Laplace equations Image processing Entropy Testing Signal to noise ratio Noise reduction Image analysis

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