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A multi-criteria programming model for intelligent tutoring planning

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10th International Conference on Knowledge-Based intelligent information and Engineering Systems, KES 2006

作者： Ruihong, Shi Peng, Lu Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China Graduate School Chinese Academy of Sciences China College of Computer Science and Technology Beijing Institute of Technology China

ISBN: (纸本)3540465359

This paper proposed a practical approach to personalized tutoring planning by exploiting existing tutoring resources (e.g., a book, a courseware). More exactly, it does not build an instructional course from scratch - from the domain curriculum, as most intelligent Tutoring Systems (ITS) do. Instead, information in the curriculum model is used as metadata, together with other metadata, to describe tutoring resources. Given a learning requirement (learning objectives and/or constraints), it finds out the most appropriate tutoring resource(s) and proposes a proper learning sequence of them. Based on the proposed fuzzy instructional model and learner model, the tutoring planning problem is defined as a multi-criteria programming (MCP) model. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Computer programming

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Content-based 3-D Shape Retrieval for Pervasive computing

Content-based 3-D Shape Retrieval for Pervasive Computing

引用

International Conference on Pervasive computing and Applications (ICPCA)

作者： Dong Xu Hua Li Zongkai Lin Chinese Academy of Sciences China Key Laboratory of Intelligent Information Processing Chinese Academy of Sciences Key Laboratory of Computer System and Architecture Institute of Computing Technology Chinese Academy of Science National Research Center for Intelligent Computing Systems Institute of Computing Technology Chinese Academy of Science. lihua@*** Key Laboratory of Intelligent Information Processing Chinese Academy and Sciences China

3D models are a new kind of cross-media resource which can be frequently seen in the network. Since the amount of them is very huge now, content-based retrieval can help to recognize a certain object or retrieve similar ones from the giant database. This paper presents a new method for deriving 3D moment invariants and uses them as shape descriptors for the representation of 3D models. They are insensitive to surface noise and can be used in pervasive environment conveniently. We also illustrate how to build up experimental system and simulate 3D shape retrieval in wireless environment

关键词： Shape Content based retrieval Pervasive computing information retrieval Humans Internet Application software Laboratories intelligent networks Computer networks

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Classification Algorithm of Land Quality Based on PLS

Classification Algorithm of Land Quality Based on PLS

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World Congress on intelligent Control and Automation (WCICA)

作者： Shifei Ding Zhongzhi Shi Yong Liang College of Information Science and Engineering Shandong Agricultural University Taian China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China

Based on modeling idea of partial least squares (PLS) and divided the values of response variable into two classes denoted by 0 and 1, a novel classification algorithm of land quality is set up in this paper. Firstly, the algorithms of multiple linear regression (MLR) and principal component regression (PCR) are introduced and analysed their shortages. Then on the basis of modeling idea of PLS, the classification algorithm of land quality is constructed. The experiment shows that the PLS algorithm doesn't request distribution of the data, and has best classification pattern ability compared with the algorithms of MLR and PCR. It has more advantages than MLR, PCR, such as simplicity and robustness, clearly qualitative explanation. It is powerful for multicollinearity, particularly when the number of predictor variables is large and the sample size is small, and provides a novel research method for classification of land quality

关键词： Classification algorithms Least squares methods Electronic mail Linear regression Principal component analysis Educational institutions information science Agricultural engineering Laboratories information processing

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Classification algorithm of land quality based on PLS

Classification algorithm of land quality based on PLS

引用

6th World Congress on intelligent Control and Automation, WCICA 2006

作者： Shifei, Ding Zhongzhi, Shi Yong, Liang College of Information Science and Engineering Shandong Agricultural University Taian 271018 Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100080

ISBN: (纸本)1424403324

Based on modeling idea of partial least squares (PLS) and divided the values of response variable into two classes denoted by 0 and 1, a novel classification algorithm of land quality is set up in this paper. Firstly, the algorithms of multiple linear regression (MLR) and principal component regression (PCR) are introduced and analysed their shortages. Then on the basis of modeling idea of PLS, the classification algorithm of land quality is constructed. The experiment shows that the PLS algorithm doesn't request distribution of the data, and has best classification pattern ability compared with the algorithms of MLR and PCR It has more advantages than MLR, PCR, such as simplicity and robustness, clearly qualitative explanation. It is powerful for multicollinearity, particularly when the number of predictor variables is large and the sample size is small, and provides a novel research method for classification of land quality. © 2006 IEEE.

关键词： Image quality

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Online Infomax Algorithm and its Application to Remove EEG Artifacts

Online Infomax Algorithm and its Application to Remove EEG A...

引用

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

作者： Xiaopei Wu Zhongfu Ye School of Information Science and Technology University of Science and Technology Hefei Anhui China The Key Laboratory of Intelligent Computing & Signal Processing Anhui University Hefei Anhui China

An online infomax algorithm is proposed in this paper. The performances and properties of this online algorithm is investigated in detail. To the problem of the artifacts removal in real life EEG signal, both the online-and batch infomax algorithm are applied and compared. The experiment results show that the online infomax algorithm proposed in this paper has the good performance both in artifacts removal and convergence in time-varying mixing system

关键词： Electroencephalography Signal processing algorithms Independent component analysis Equations Electrocardiography Gaussian processes World Wide Web Biology computing Biomedical engineering Biomedical signal processing

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Mean-shift blob tracking with adaptive feature selection and scale adaptation

Mean-shift blob tracking with adaptive feature selection and...

引用

14th IEEE International Conference on Image processing, ICIP 2007

作者： Dawei, Liang Qingming, Huang Shuqiang, Jiang Hongxun, Yao Wen, Gao School of Computer Science and Technology Harbin Institute of Technology Harbin 150001 China Graduate School Chinese Academy of Sciences Beijing 100080 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China Institute of Digital Media Peking University Beijing 100871 China

ISBN: (纸本)1424414377

When the appearances of the tracked object and surrounding background change during tracking, fixed feature space tends to cause tracking failure. To address this problem, we propose a method to embed adaptive feature selection into mean shift tracking framework. From a feature set, the most discriminative features are selected after ranking these features based on their Bayes error rates, which are estimated from object and background samples. For the selected features, a criterion is proposed to evaluate their stability for tracking and to guide feature reselection. The selected features are used to generate a weight image, in which mean shift is employed to locate the object. Moreover, a simple yet effective scale adaptation method is proposed to deal with object changing in size. Experiments on several video sequences show the effectiveness of the proposed method. ©2007 IEEE.

关键词： Feature Selection

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information CLASSIFIED RECOGNITION METHOD BASED ON FUZZY CONTROL

INFORMATION CLASSIFIED RECOGNITION METHOD BASED ON FUZZY CON...

引用

2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)

作者： SHI-FEI DING ZHONG-ZHI SHI XI-JUN ZHU College of Information Science and Engineering Shandong Agricultural University Taian 271018China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Aca School of Science Qingdao Technological University Qingdao 266033 China

In this paper, an information pattern recognition method based on fuzzy control is set up. On one hand, the modeling method of fuzzy information classified recognition pattern has been established. On the other hand, the data from Qufu City of Shandong Province during 14 years from 1990 to 2003 is processed and analyzed. The average temperature (℃) and rainfall (mm) in April each year are considered as the input of the system, a number of Aphis gossypii Glover (AGG)occurred for the Cotton in high period are considered as the output, Fuzzy information classified recognition pattern is set up in order to recognize the occurrence degree of the *** results of the returning recognition from 1990 to 2003 and the recognition for 2004 are satisfactory.

关键词： Fuzzy control Pattern recognition Classified recognition pattern The Aphis gossypii Glover (AGG)

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Studies on Fuzzy information Measures

Studies on Fuzzy Information Measures

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Firth IEEE International Conference on Cognitive Informatics(第五届认知信息国际会议)

作者： Shifei Ding Zhongzhi Shi Fengxiang Jin College of Information Science and Engineering Shandong Agricultural University Taian 271018 P.R.C Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Aca College of Geo-Information Science and Engineering Shandong University of Science and Technology Q

ISBN: (纸本)9781424404759

Fuzzy information measure is a measure between two pattern vectors in fuzzy circumstance. In this paper, an axiom theory about fuzzy entropy is surveyed, and all kinds of definitions of fuzzy entropy are discussed firstly. And then based on the idea of Shannon information entropy, two concepts of fuzzy joint entropy and fuzzt conditional entropy are proposed and the basic properties of them are given and proved. At last, the classical similarity measures, such as dissimilarity measure (DM) and similarity measure (SM) are studied, and then two new measures, fuzzy absolute information measure (FAIM) and fuzzy relative information measure (FRIM) are set up, which can be a measure between a fuzzy set A and B. So, It provides a new research approach for studies on pattern similarity measure.

关键词： Fuzzy entropy similarity measure fuzzy absolute information measurement (FAMI) fuzzy relative information measurement (FRIM).

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Gait Recognition Using Fractal Scale and Wavelet Moments

Gait Recognition Using Fractal Scale and Wavelet Moments

引用

International Conference on Pattern Recognition

作者： Guoying Zhao Li Cui Hua Li M. Pietikainen Machine Vision Group Infotech Oulu and Department of Electrical and Information Engineering University of Oulu Finland Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China School of Mathematics Science Beijing Normal University Beijing China

Video-based gait recognition is a challenging problem in computer vision. In this paper, fractal scale wavelet analysis is applied to describe and automatically recognize gait. Fractal scale based on wavelet analysis represents the self-similarity of signals, and improves the flexibility of wavelet moments. Optimal wavelets based on generalized multi-resolution analysis are used to improve the recognition rate. Descriptors of fractal scale are translation, scale and rotation invariant. Moreover, a combination of fractal scale and wavelet moments improves the recognition rate. Experiments show that the proposed descriptor is efficient for gait recognition

关键词： Fractals Wavelet analysis Image recognition Signal resolution Image sequences Continuous wavelet transforms Discrete wavelet transforms Wavelet coefficients Machine vision Laboratories

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Understanding the Dynamical Characteristics of Neural Networks by Universal Fuzzy Logical Framework

Understanding the Dynamical Characteristics of Neural Networ...

引用

2005 International Conference on Neural Networks and Brain(ICNN&B’05)

作者： Hong Hu Zhongzhi Shi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Science

ISBN: (纸本)0780394224

The analytical study of a large scale nonlinear neural network is an uneasy *** try to analyze the function of neural systems by probing into the fuzzy logical framework of the neural ceUs'dynamical *** papers investigate the relation between fuzzy logic and neural *** most investigations focus on finding new function of neural system by combining fuzzy logical and neural system. In this paper,a novel approach is used to understand the nonlinear dynamic characteristics of neural system by analyzing the fuzzy logic framework of neural *** is the only way to understand the behavior of a large scale nonlinear neural *** abstracting the fuzzy logical framework of a neural cell,our analysis enables the delicate design of network *** an example,a difficulty task to build a recurrent network model of primary visual cortex by common dynamical analysis can be easily completed by this kind approach.

关键词： Understanding the Dynamical Characteristics of Neural Networks by Universal Fuzzy Logical Framework Fuzzy

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