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International Conference on Information Visualisation (IV)

作者： C. Frauenberger T. Stockman V. Putz R. Holdrich Signal Processing and Speech Communication Laboratory Graz University of Technology Austria Department of Computer Science Queen''s Mary University of London UK

This paper proposes an approach for cross-modal user interface design using interaction patterns. A meta-domain is introduced in which the user interface can be designed without the determination of its realisation in a particular interaction domain. When fully described in the meta-domain, the user interface can be realised in different domains (visual, auditory, tactile etc) exploiting the strengths of each different mode to its maximum. The paper proposes a set of interaction patterns along with visual and auditory realisations. To prove the concept, a prototype was designed for a real-world application, Microsoft Explorer. An auditory display prototype was developed making extensive use of virtual audio environments for non-visual visualisation of objects in the Explorer interface, taking advantage of a spatial layout. The prototype was evaluated with visually impaired, blind and sighted computer users.

关键词： User interfaces Auditory displays Prototypes Visualization Layout Information technology Humans Computational modeling Acoustic signal processing Oral communication

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Investigating manifold learning algorithms based on magnification factors and principal spread directions

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Jisuanji Xuebao/Chinese Journal of computers 2005年第12期28卷 2000-2009页

作者： He, Li Zhang, Jun-Ping Zhou, Zhi-Hua Shanghai Key Laboratory of Intelligent Information Processing Department of Computer Science and Engineering Fudan University Shanghai 200433 China Key Laboratory of Complex Systems and Intelligence Science Chinese Academy of Sciences Shanghai 200433 China Department of Computer Science and Engineering School of Mathematical Sciences Fudan University Shanghai 200433 China National Laboratory for Novel Software Technology Nanjing University Nanjing 210093 China

As a new unsupervised learning technique, manifold learning has captured the attention of many researchers in the field of machine learning and cognitive sciences. The major algorithms include Isometric mapping (ISOMAP) and Locally Linear Embedding (LLE). The approaches can be used for discovering the intrinsic dimensions of nonlinear high-dimensional data effectively and aim researchers to analyze the data better. How to quantitatively analyze the relationship between the intrinsic dimensions and the observation space, however, has fewer reports. And thus further works in manifold learning may have suffered some difficulties. The paper focuses on two kinds of manifold learning algorithms (ISOMAP, LLE), and discusses magnification factors and principal spread directions from the observation space to the intrinsic low-dimensional space. Also the corresponding algorithm is proposed. Experiments show the effectiveness and advantages of the research.

关键词： Learning algorithms

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Parallel performance of ensemble self-generating neural networks for chaotic time series prediction problems

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Systems and computers in Japan 2005年第10期36卷 82-92页

作者： Inoue, Hirotaka Narihisa, Hiroyuki Graduate School of Engineering Okayama University of Science Okayama 700-0005 Japan Department of Information and Computer Engineering Faculty of Engineering Okayama University of Science Okayama 700-0005 Japan Kure National College of Technology Information Processing Society of Japan Japanese Society of Artificial Intelligence Department of Information and Computer Engineering Okayama University of Science Information Processing Society of Japan Operations Research Society of Japan

Sell-Generating Neural Networks (SGNN) have the feature of fast processing by automatically constructing a self-generating neural tree (SGNT) from a given training data set. The prediction accuracy of SGNNs for chaotic time series prediction is improved by ensemble averaging of various SGNNs. However, the computation time increases with the number of SGNNs on a single processor. In this paper, we investigate improvement of the prediction accuracy and parallel efficiency of ensemble SGNNs for chaotic time series prediction problems on an MIMD parallel computer. We allocate each SGNN to one processor. Our results show that as the number of node processors increases, a continuing improvement of prediction accuracy is obtained for all problems, while maintaining the high-speed processing performance of the single SGNN. © 2005 Wiley Periodicals Inc.

关键词： Neural networks

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Multicast routing algorithm with multiple trees

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Journal of Systems Engineering and Electronics 2005年第2期16卷 426-432页

作者： Cui, Xunxue Gao, Wei Fang, Hongyu New Star Research Institute of Applied Technology Hefei 230031 China Jiangsu Key Laboratory of Computer Information Processing Technology Soochow University Suzhou 215006 China Department of Electronic Engineering and Information Science University of Science and Technology of China Hefei 230027 China School of Electronic Science and Technology Anhui University Hefei 230039 China

Quality of service (QoS) multicast routing has continued to be a very important research topic in the Internet. A method of multicast routing is proposed to simultaneously optimize several parameters based on multiobjective genetic algorithm, after the related work is reviewed. The contribution lies on that the selection process of such routing is treated with multiobjective optimization. Different quality criterions in IP network are taken into account for multicast communications. A set of routing trees is generated to approximate the Pareto front of multicast problem. Multiple trees can be selected from the final set of nondominated solutions, and applied to obtain a good overall link cost and balance traffic distribution according to some simulation results.

关键词： Multicasting

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A competitive learning neural network for auditory information processing using the pulsed neuron model

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Systems and computers in Japan 2005年第13期36卷 13-22页

作者： Kuroyanagi, Susumu Iwata, Akira Graduate School of Engineering Nagoya Institute of Technology Nagoya 466-8555 Japan Nagoya Institute of Technology Nagoya 466-8555 Japan Department of Computer Science and Engineering Graduate School of Engineering Acoustic Society of Japan Japan Neural Network Society JSMEBE Department of Computer Science and Engineering Graduate School Information Processing Society JSMEBE Japan Electrocardiography Society Japan Neural Network Society Japan Society for Medical Information Processing IEEE

The purpose of this study is to construct an auditory information processing system using the pulsed neuron model, which is suited to hardware implementation. The realization of a competitive learning network composed only of pulsed neuron models is investigated. A new winner neuron decision process is proposed in which the threshold of each neuron is controlled by a state-detection neuron, which monitors the firing situation of the competitive learning neurons. A competitive learning network is constructed on the basis of the proposed method. An operation simulation demonstrates that the winner neuron can be determined by the proposed method, following the change of the input signal, by using only pulsed neuron models, thus realizing vector quantization suited to auditory information processing. © 2005 Wiley Periodicals, Inc.

关键词： Neural networks

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A multicast routing algorithm with multiple trees

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Journal of Systems Engineering and Electronics 2005年第2期000卷 426-432页

作者： Cui Xunxue Gao Wei Fang Hongyu New Star Research Institute of Applied Technology， Hefei 230031， P. R. China Jiangsu Key Laboratory of Computer Information Processing Technology，Soochow University， Suzhou 215006， P. R. China Department of Electronic Engineering and Information Science， University of Science and Technology of China， Hefei 230027， P. R. China School of Electronic Science and Technology， Anhui University， Hefei 230039， P. R. China

Quality of service (QoS) multicast routing has continued to be a very important research topic in the Internet.A method of multicast routing is proposed to simultaneously optimize several parameters based on multiobjective genetic algorithm, after the related work is reviewed. The contribution lies on that the selection process of such routing is treated with multiobjective optimization. Different quality criterions in IP network are taken into account for multicast communications. A set of routing trees is generated to approximate the Pareto front of multicast problem. Multiple trees can be selected from the final set of nondominated solutions, and applied to obtain a good overall link cost and balance traffic distribution according to some simulation results.

关键词： multicast routing quality of service multiobjective optimization genetic algorithms

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DSA image registration based on multiscale Gabor filters and mutual information

DSA image registration based on multiscale Gabor filters and...

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International Conference on Information and Automation (ICIA)

作者： Zhiguo Cao Xiaoxiao Liu Bo Peng Yiu-Sang Moon Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China Department of Computer Science and Engineering Chinese University of Hong Kong New Territories Hong Kong China

In clinical practice, digital subtraction angiography (DSA) is a powerful technique for the visualization of blood vessels in X-ray image sequences. Different with traditional DSA image registration processes, in our proposed image registration method, the control points are selected from the vessel centerlines using multiscale Gabor filters, and mutual information (MI) is then taken as the similarity criterion to find the correspondences. Experimental results demonstrate our algorithm efficiently yields satisfying registration result for DSA images.

关键词： Image registration Gabor filters Mutual information Biomedical imaging Angiography Visualization Displacement control Blood vessels Image sequences Pixel

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Journal of Information science and Engineering: Editorial notice

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Journal of Information science and Engineering 2005年第5期21卷 i-ii页

作者： Lee, Der-Tsai Amato, Nancy M. Chang, Shih-Fu Chen, Homer H. Chen, Tsuhan Hsu, Tsan-Sheng Hwang, Jenq-Neng Kuo, Sy-Yen Kuo, Tei-Wei Li, Chung-Sheng Tokuyama, Takeshi Wing, Jeannette Wu, Tzong-Chen Yen, John Computer Science at Texas A and M University United States Parasol Laboratory United States IEEE Transactions on Parallel and Distributed Systems Computing Research Association's Committee on the Status of Women in Computing Research CRA-W's Distributed Mentor Program United States Department of Electrical Engineering Columbia University United States Lab. United States College of Electrical Engineering and Computer Science National Taiwan University Taiwan IEEE Transactions on Circuits and Systems for Video Technology IEEE Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh PA United States ACM ACM SIGACT IEEE Computer Society IICM Austria Research and Development of the Department Multimedia Signal Processing Technical Committee IEEE Signal Processing Society United States IEEE Transactions on Circuits and systems for Video Technology College of Electrical Engineering and Computer Science National Taiwan Ocean University Keelung Taiwan Department of Electrical Engineering National Taiwan University Taiwan Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan IEEE Technical Committee on Real-Time Systems Computer Science Division IBM T.J. Watson Research Center United States IBM Research Division Graduate School of Information Sciences Tohoku University Japan ACM IPSJ Mathematical Society of Japan Japan Department of Computer Science Computer Science Department Carnegie Mellon University United States National Academies of Science's Computer Science and Telecommunications Board United States Microsoft's Trustworthy Academic Advisory Board Intel Research Pittsburgh's Advisory Board United States Dartmouth's Institute for Security Technology Studies Advisory Committee Canada Sloan Research Fellowships Program Committee United States ACM Taiwan China Information Sciences and Technology Pennsylvania State University United States Laboratory for Intelligent Agents Penn State's School of Info

No abstract available

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Incorporating a mixed excitation model and postfilter into HMM-based text-to-speech synthesis

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Systems and computers in Japan 2005年第12期36卷 43-50页

作者： Yoshimura, Takayoshi Tokuda, Keiichi Masuko, Takashi Kobayashi, Takao Kitamura, Tadashi Research-Domain 21 Toyota Central R and D Labs. Inc. Aichi 480-1192 Japan Department of Computer Science Nagoya Institute of Technology Nagoya 466-8555 Japan Interdisciplinary Graduate School of Science and Engineering Tokyo Institute of Technology Yokohama 226-8502 Japan Toyota Central R and D Labs Acoustical Society of Japan Nagoya Institute of Technology Acoustical Society of Japan Japanese Society for Artificial Intelligence Information Processing Society of Japan Toshiba Corporate R and D Center Acoustical Society of Japan IEEE ICSA Department of General Engineering Acoustical Society of Japan Information Processing Society of Japan ISCA Graduate School

In this paper we introduce a mixed excitation model into an HMM-based speech synthesis system with the objective of improving the quality of synthesized speech. In previous work we have proposed a text-to-speech synthesis system that synthesized speech by outputting speech parameters using HMMs that model Mel frequency ceptral coefficients, fundamental frequencies, and duration. In that system we used a simple model as the excitation source model for exciting the synthesis filter (an MLSA filter) whereby we switched between a pulse sequence and white noise for intervals of voiced and unvoiced speech, respectively. When using that type of excitation model, it is not possible to synthesize speech such as voiced fricatives that contains both a periodic and an aperiodic component, and this is a cause of poor synthesized speech quality. Therefore, in this paper we incorporate a mixed excitation model based on a narrowband vocoding method MELP that combines a pulse stream with white noise with a view to realizing high-quality speech synthesis. Since this excitation model can be applied to wideband vocoding as well as narrowband, we anticipate that it will prove effective for speech synthesis. In addition, we introduce a widely used vocoding method, a postfilter, in order to improve the quality of the synthesized speech. In addition, the results of subjective evaluation show the effectiveness of the mixed excitation model and postfilter in this system. © 2005 Wiley Periodicals, Inc.

关键词： Speech synthesis

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A computer-aided system for mass detection and classification in digitized mammograms

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Biomedical Engineering - Applications, Basis and Communications 2005年第5期17卷 215-228页

作者： Yang, Sheng-Chih Wang, Chuin-Mu Chung, Yi-Nung Hsu, Giu-Cheng Lee, San-Kan Chung, Pau-Choo Chang, Chein-I. Department of Electrical Engineering National Cheng Kung University Tainan Taiwan Department of Computer Science and Information Engineering National Chin Yi Institute of Technology Taichung Taiwan Department of Electrical Engineering Da-Yeh University Chunghua Taiwan Department of Radiology Tri-Service General Hospital National Defense Medical Center Taipei Taiwan Administrative Office Suao Veterans Hospital Yilan Taiwan Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore MD United States

This paper presents a computer-assisted diagnostic system for mass detection and classification, which performs mass detection on regions of interest followed by the benign-malignant classification on detected masses. In order for mass detection to be effective, a sequence of preprocessing steps are designed to enhance the intensity of a region of interest, remove the noise effects and locate suspicious masses using five texture features generated from the spatial gray level difference matrix (SGLDM) and fractal dimension. Finally, a probabilistic neural network (PNN) coupled with entropic thresholding techniques is developed for mass extraction. Since the shapes of masses are crucial in classification between benignancy and malignancy, four shape features are further generated and joined with the five features previously used in mass detection to be implemented in another PNN for mass classification. To evaluate our designed system a data set collected in the Taichung Veteran General Hospital, Taiwan, R.O.C. was used for performance evaluation. The results are encouraging and have shown promise of our system.

关键词： computer aided analysis

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