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Babylon bookmarks: A taxonomic approach to the management of WWW bookmarks

Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2003年 2641卷 42-48页

作者： Karousos, Nikos Panaretou, Ioannis Pandis, Ippokratis Tzagarakis, Manolis Computer Engineering and Informatics Department Patras University Rio Patras Greece Business Management and Administration Department Patras University Rio Patras Greece Computer Technology Institute Patras Greece

ISBN: (纸本)3540402187

Taxonomic reasoning can be a useful organization paradigm to address issues dealing with the management of WWW bookmarks. Management of WWW bookmarks comprise one of the most frequent activities of WWW users. In this paper, "Babylon Bookmarks" are presented allowing users to apply taxonomic reasoning on WWW bookmarks. "Babylon Bookmarks" is based on the "Babylon System," an infrastructure to support general taxonomic reasoning tasks. The "Babylon System" allows the development of arbitrary taxonomic services based on Open Hypermedia Specifications. © Springer-Verlag Berlin Heidelberg 2003.

关键词： computers

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Accessee controlled type selection for a multiple-type object 03

Accessee controlled type selection for a multiple-type objec...

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Proceedings of the 2003 ACM Symposium on Applied Computing

作者： Sato, Hideki Aritsugi, Masayoshi School of Informatics Daido Institute of Technology 10-3 Takiharu-cho Minami-ku Nagoya 457-8530 Japan Department of Computer Science Faculty of Engineering Gunma University 1-5-1 Tenjin-cho Kiryu 376-8515 Japan

ISBN: (纸本)9781581136241

INADA is an enhanced C++ persistent programming language, compliant with ODMG standard. INADA supports multiple-type objects facility which enables any persistent objects to obtain any type at any time the type is needed, and to lose any unnecessary types dynamically. Using the facility, we can model changes in roles/aspects which a real-world entity possesses. Access to a multiple-type object needs to select one from among its own types. The selection is conventionally left to an object accessing a multiple-type object, A real-world entity is, however, flexible enough to decide its roles/aspects depending on a meeting entity whom it exchanges messages with. From the consideration, this paper proposes AccessEE Controlled Type Selection (AEE) method in which a multiple-type object selects one from among its own types depending on an object accessing it. The implementation of AEE method in INADA is also presented, which does not need any modification to the language specification and the processing system of INADA.

关键词： Object oriented programming

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Pattern recognition of EEG signals during right and left motor imagery

Pattern recognition of EEG signals during right and left mot...

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SICE Annual Conference

作者： K. Inoue K. Sugioka K. Ishii G. Pfurtscheller K. Kumamaru Department of Control Engineering and Science Factory of Computer Science and Systems Engineering Kyushu Institute of Technology Fukuoka Japan Department of Medical Informatics Institute of Biomedical Engineering Graz University of Technology Graz Austria

In this paper, statistical pattern recognition method based on AR model was introduced to discriminate the electroencephalograph (EEG) signals recorded during right and left motor imagery. And learning methods were investigated. Also, correlation between C3 and C4 signals were investigated, and thereby which AR (combine AR or multivariable AR) model must be used in each EEC recording method.

关键词： Pattern recognition Electroencephalography Electrodes Brain modeling Monitoring Artificial neural networks Feedback Biomedical engineering Laplace equations Vectors

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Integrating adaptive Web techniques with Web services

Integrating adaptive Web techniques with Web services

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International Conference on Information technology: Coding and Computing (ITCC)

作者： J. Garofalakis E. Sakkopoulos S. Sirmakessis A. Tsakalidis Computer Engineering & Informatics Department University of Patras Patras Greece Technologies Research Unit Research Academic Computer Technology Institute Greece Hellenic Open University Patras Greece

Enterprise software infrastructure traditionally comprises a number of independent systems in order to support customer needs and business processes complicating productivity, performance and maintenance. Instead there are hypermedia facilities based on widespread standards that provide over a user-friendly, well-known framework richer functionality and features. In the paper, we present the design, implementation and evaluation of the combined use of Web services and adaptive Web-based techniques. We describe a large-scale hypermedia framework that improves the efficiency and performance of conventional enterprise activities like customer services (registration, activation, billing, support) and document management. The presented approach aims to cover these fundamental needs for a network of customers, collaborators and intranet employees.

关键词： Web services Information technology

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Pattern recognition of EEG signals during right and left motor imagery

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IFAC Proceedings Volumes 2003年第16期36卷 139-144页

作者： Katsuhiro Inoue Gert Pfurtscheller Christa Neuper Kousuke Kumamaru Department of Control Engineering and Science Faculty of Computer Science and Systems Engineering Kyushu Institute of Technology 680-4 Kawazu Iizuka Fukuoka 820-8502 Japan Department of Medical Informatics Institute of Biomedical Engineering Graz University of Technology Inffeldgasse 16a 8010 Graz Austria

Electroencephalograph (EEG) recordings during right and left motor imagery can be used to move a cursor to a target on a computer screen. Such an EEG-based brain-computer interface (BCI) can provide a new communication channel to replace an impaired motor function. It can be used by e.g., handicap users with amyotrophic lateral sclerosis (ALS). In this study, statistical pattern recognition method based on AR model was introduced to discriminate the EEG signals recorded during right and left motor imagery. And learning methods (processing period for parameter estimation, AR order, etc.) were investigated. Finally, the effectiveness of our method was confirmed through the experimental studies.

关键词： EEG AR-model statistical pattern recognition brain computer interface motor imagery

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Extreme Nash equilibria

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2003年 2841卷 1-20页

作者： Gairing, Martin Lucking, Thomas Mavronicolas, Marios Monien, Burkhard Spirakis, Paul Faculty of Computer Science Electrical Engineering and Mathematics University of Paderborn Fürstenallee 11 33102 Paderborn Germany Department of Computer Science University of Cyprus 1678 Nicosia Cyprus Computer Technology Institute P. O. Box 1122 261 10 Patras Greece Department of Computer Engineering and Informatics University of Patras Rion 265 00 Patras Greece

We study the combinatorial structure and computational complexity of extreme Nash equilibria, ones that maximize or minimize a certain objective function, in the context of a selfish routing game. Specifically, we assume a collection of n users, each employing a mixed strategy, which is a probability distribution over m parallel links, to control the routing of its own assigned traffic. In a Nash equilibrium, each user routes its traffic on links that minimize its expected latency cost. Our structural results provide substantial evidence for the Fully Mixed Nash Equilibrium Conjecture, which states that the worst Nash equilibrium is the fully mixed Nash equilibrium, where each user chooses each link with positive probability. Specifically, we prove that the Fully Mixed Nash Equilibrium Conjecture is valid for pure Nash equilibria and that under a certain condition, the social cost of any Nash equilibrium is within a factor of 6 + Ε, of that of the fully mixed Nash equilibrium, assuming that link capacities are identical. Our complexity results include hardness, approximability and inapproximability ones. Here we show, that for identical link capacities and under a certain condition, there is a randomized, polynomial-time algorithm to approximate the worst social cost within a factor arbitrarily close to 6 + Ε. Furthermore, we prove that for any arbitrary integer k > 0, it is NP-hard to decide whether or not any given allocation of users to links can be transformed into a pure Nash equilibrium using at most k selfish steps. Assuming identical link capacities, we give a polynomial-time approximation scheme (PTAS) to approximate the best social cost over all pure Nash equilibria. Finally we prove, that it is NP-hard to approximate the worst social cost within a multiplicative factor 2 - 2/m+1 - Ε. The quantity 2 - 2/m+1 is the tight upper bound on the ratio of the worst social cost and the optimal cost in the model of identical capacities. © Springer-Verlag Berlin Heid

关键词： Probability distributions

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Efficient multipath channel estimation using a semi-blind parametric technique

Efficient multipath channel estimation using a semi-blind pa...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： A.A. Rontogiannis A. Marava K. Berberidis J. Palicot School of Natural Resources and Enterprises Management University of Ioannina (UoI) Agrinio Greece Department of Computer Engineering & Informatics/Computer Technology Institute University of Patras Rio Greece INRIA/IRISA Rennes France

A parametric method for estimating the unknown channel impulse response (CIR) in a semi-blind manner is proposed. The main trait of this method is that, instead of seeking the whole CIR sequence, only the unknown time delays and attenuation factors of the physical channel multipath components are estimated. The technique is based on a suitable application of the subchannel response matching (SRM) criterion. The resulting cost function is separable with respect to the two sets of unknown parameters, i.e. time delays and attenuations. Thus, an efficient two step optimization procedure can be applied. The new method offers significant computational savings and a lower mean square estimation error as compared to existing semi-blind channel estimation methods.

关键词： Multipath channels Delay effects Attenuation Channel estimation Parameter estimation Delay estimation Wireless communication Least squares methods Resource management technology management

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Dynamic-footprint based person identification using mat-type pressure sensor

Dynamic-footprint based person identification using mat-type...

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

作者： Jin-Woo Jung Z. Bien Sang-Wang Lee T. Sato Department of Electrical Engineering and Computer Science Korea Advanced Institute of Science and Technology Daejeon Korea Department of Mechano-Informatics University of Tokyo Bunkyou-Ku Tokyo Japan

Many diverse methods have been developing in the field of biometric identification as human-friendliness has been emphasized in the intelligent system's area. And one of emerging method is to use human walking behavior. But, in the previous methods based on human gait, stable somewhat long-term walking data are an essential condition for person recognition. Therefore, these methods are difficult to cope with various change of walking velocity which may be generated frequently during real walking. In this paper, we suggest a new method which uses just one-step walking data from mat-type pressure sensor. When a human walk through the pressure sensor, we get quantized COP (center of pressure) trajectory and HMM (hidden Markov model) is used to make probability models for user's each foot. And then, HMMs for two feet are combined for better performance by Levenberg-Marquart learning method. Finally, we prove the usefulness of the suggested method using 8 people recognition experiments.

关键词： Legged locomotion Hidden Markov models Identification of persons Biometrics Face recognition Sensor systems Learning systems Fingerprint recognition

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Synchronous machine-turbine drive system with indirect speed control

Synchronous machine-turbine drive system with indirect speed...

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IEEE International Conference on Electric Machines and Drives (IEMDC)

作者： R.K. Jardan I. Nagy Faculty of Electrical Engineering and Informatics Department of Automation and Applied Informatics Budapest University슠of슠Technology슠and슠Economics Budapest Hungary Computer and Automation Institute Hungarian Academy of Sciences (ATOMKI) Budapest Hungary

Dynamic properties of a hybrid system are analyzed that has been developed to generate electric energy by utilizing alternative, renewable and waste energies. The solution is based on a system that consists of a high-speed turbine, coupled to a three-phase permanent magnet synchronous generator, an AC/AC converter and a supervisory control unit. The function of the system is to utilize the energy content of some working medium by a special turbine that converts the energy content of the working medium into electric energy by the generator and the AC/AC converter. The alternative renewable energy sources may include solar energy (direct solar steam system or solar energy with heat exchanger), geothermal energy (with or without heat exchanger) and energy obtained from biomass. Various waste energy sources can also be utilized by applying the system such as the energy that can be obtained during the process of pressure reduction in steam, gas and fluid networks. The electric power generated by the system can be fed back to the utility mains or it can be used in stand-alone mode to supply a selected group of loads. The paper analyses a novel control strategy and principle of the system to ensure optimum performance and economy by using a special solution for ensuring the power equilibrium in the combined mechanical-electric drive.

关键词： Velocity control Turbines Geothermal power generation Solar energy Solar heating Magnetic analysis Hybrid power systems Couplings Permanent magnets Synchronous generators

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Nonlinear model structure identification of complex biomedical data using a genetic programming based technique

Nonlinear model structure identification of complex biomedic...

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IEEE International Symposium on Intelligent Signal Processing

作者： G.N. Beligiannis L.V. Skarlas S.D. Likothanassis K. Perdikouri University of Patras Artificial Intelligence Research Center (U.P.A.I.R.C.) University of Patras Patras Greece Computer Technology Institute Patras Greece Department of Computer Engineering and Informatics University of Patras Patras Greece University of Patras Patras GR Dept. of Comput. Eng. & Informatics Patras Univ. Greece

In this contribution, a genetic programming based technique, which combines the ability of genetic programming to explore both automatically and effectively, the whole set of candidate model structures and the robustness of evolutionary multimodel partitioning filters, is presented. The method is applied to the nonlinear system identification problem of complex biomedical data. Simulation results show that the algorithm identifies the true model and the true values of the unknown parameters for each different model structure, thus assisting the genetic programming technique to converge more quickly to the (near) optimal model structure. The method has all the known advantages of the evolutionary multimodel partitioning filters, that is, it is not restricted to the Gaussian case, it is applicable to online/adaptive operation and is computationally efficient. Furthermore, it can be realized in a parallel processing fashion, a fact, which makes it amenable to VLSI implementation.

关键词： Bioinformatics Genetic programming Autoregressive processes Signal processing algorithms Nonlinear systems Mathematical model Biomedical signal processing Nonlinear dynamical systems Biomedical computing Biomedical engineering

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