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Polynomial-time algorithms for learning typed pattern languages

Polynomial-time algorithms for learning typed pattern langua...

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6th international conference on Language and Automata theory and Applications, LATA 2012

作者： Geilke, Michael Zilles, Sandra Fachbereich Informatik Technische Universität Kaiserslautern D-67653 Kaiserslautern Germany Department of Computer Science University of Regina Regina SK S4S 0A2 Canada

ISBN: (纸本)9783642283314

this article proposes polynomial-time algorithms for learning typed pattern languages-formal languages that are generated by patterns consisting of terminal symbols and typed variables. A string is generated by a typed pattern by substituting all variables with strings of terminal symbols that belong to the corresponding types. the algorithms presented consitute non-trivial generalizations of Lange and Wiehagen's efficient algorithm for learning patterns in which variables are not typed. this is achieved by defining type witnesses to impose structural conditions on the types used in the patterns. It is shown that Lange and Wiehagen's algorithm implicitly uses a special case of type witnesses. Moreover, the type witnesses for a typed pattern form characteristic sets whose size is linear in the length of the pattern;our algorithm, when processing any set of positive data containing such a characteristic set, will always generate a typed pattern equivalent to the target pattern. thus our algorithms are of relevance to the area of grammatical inference, in which such characteristic sets are typically studied. © 2012 Springer-Verlag.

关键词： Formal languages

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Context prediction based on pattern matching with association rules and variable weights

Context prediction based on pattern matching with associatio...

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6th international conference on Convergence and Hybrid Information Technology, ICHIT 2012

作者： Choi, Young-Hwan Lee, Sang-Yong Department of Computer Engineering Kongju National University Korea Republic of

ISBN: (纸本)9783642326448

In order to provide personalized services that use context with various properties and types in a mobile environment, a context prediction method(COPPAM) that can increase the prediction accuracy is presented in this paper. In COPPAM, each context property is relatively normalized to produce a pattern so that various types and properties can be dealt with. Also, association rules between the context properties are used to reflect the relevance between the context property to be predicted and other properties. then, the weight of the prediction result(success/failure) is updated in real time, resulting in an improvement in prediction accuracy. When performing pattern matching for context prediction, the confidence and weight is used to calculate the prediction factor where the pattern with the largest prediction factor value is selected as the prediction pattern among the prediction candidate patterns with equal similarity. the evaluation results of COPPAM revealed that in the user location prediction using AILTB, the prediction accuracy average was 83.68%, which was an improvement over other methods by an average of 3.45%. © 2012 Springer-Verlag.

关键词： Association rules

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Assessment of a change of blood volume during hemodialysis

Assessment of a change of blood volume during hemodialysis

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6th international conference on Complex Medical Engineering, CME 2012

作者： Fueda, Yuri Hattori, Takumu Minato, Kotaro Ohyama, Toshiharu Katayama, Toshiro Department of Bioinformatics and Genomics Nara Institute of Science and Technology Graduate School of Information Science 8916-5 Takayama Ikoma Nara 630-0192 Japan Room of Artificial Dialysis Kouseikai Takai Hospital 461-2 Kuranosyo Tenri Nara 632-0006 Japan Depertment of Medical Engineering Himeji Dokkyo University Faculty of Health Sciences 7-2-1 Kamiohno Himeji Hyogo 670-8524 Japan

ISBN: (纸本)9781467316163

Hemodialysis influences intradialytic hypotension, decreasing the blood volume (BV) in circulation. If intradialytic hypotension has continued, the patient may occur an unconscious. In this study, we focused on the changes of the BV in circulation to prevent them from intradialytic hypotension and unconscious. Based of hematocrit value correlate with the reflected light intensity from blood, we estimated BV. We constructed the mathematical model to explain the water movement from the extracellular to the intravascular compartment during hemodialysis. As a result, the changing pattern of BV differed on each patient, a coefficient of the water movement were estimated in this study. the coefficient of the water movement was invariable in the individual case and differed among patients. We could expect the individual change of BV by using the coefficient. © 2012 IEEE.

关键词： Dialysis

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M.C. Escher wrap artist: Aesthetic coloring of ribbon patterns

M.C. Escher wrap artist: Aesthetic coloring of ribbon patter...

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6th international conference on Fun with Algorithms, FUN 2012

作者： Gethner, Ellen Kirkpatrick, David G. Pippenger, Nicholas J. Department of Computer Science University of Colorado Denver Denver CO 80217 United States Department of Computer Science University of British Columbia Vancouver BC V6T 1Z4 Canada Harvey Mudd College Department of Mathematics Claremont CA 91711 United States

ISBN: (纸本)9783642303463

At the heart of the ideas of the work of Dutch graphic artist M.C. Escher is the idea of automation;we consider a problem that was inspired by some of his earlier and lesser known work. Specifically, a motif fragment is a connected region contained in a closed unit square. Consider a union of motif fragments and call the result an Escher tile T. One can then construct a pattern in the Euclidean plane, as Escher did, with the set of horizontal and vertical unit length translations of T. the resulting pattern gives rise to infinitely many sets of motif fragments (each set may be finite or infinite) that are related visually by way of the interconnections across boundaries of the unit squares that underly the construction;a set of related motif fragments sometimes gives the appearance of a ribbon and thus the resulting pattern in the plane is called a ribbon pattern. Escher's designs gave rise to beautiful artwork and inspired equally aesthetic combinatorial questions as well. In his sketchbooks, Escher colored the ribbon patterns with pleasing results. Coloring the ribbon patterns led naturally to a question of periodicity: is there a prototile that generates a well-colored pattern? the current work answers the question in the affirmative by way of tools from graph theory, algorithms, and number theory. We end with a list of open questions. © 2012 Springer-Verlag Berlin Heidelberg.

关键词： Number theory

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An on-line NMF model for temporal pattern learning: theory with application to automatic speech recognition

An on-line NMF model for temporal pattern learning: Theory w...

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10th international conference on Latent Variable Analysis and Signal Separation, LVA/ICA 2012

作者： Van Hamme, Hugo University of Leuven Department ESAT Leuven Belgium

ISBN: (纸本)9783642285509

Convolutional non-negative matrix factorization (CNMF) can be used to discover recurring temporal (sequential) patterns in sequential vector non-negative data such as spectrograms or posteriorgrams. Drawbacks of this approach are the rigidity of the patterns and that it is intrinsically a batch method. However, in speech processing, like in many other applications, the patterns show a great deal of time warping variation and recognition should be on-line (possibly with some processing delay). therefore, time-coded NMF (TC-NMF) is proposed as an alternative to CNMF to locate temporal patterns in time. TC-NMF is motivated by findings in neuroscience. the sequential data are first processed by a bank of filters such as leaky integrators with different time constants. the responses of these filters are modeled jointly by a constrained NMF. Algorithms for learning, decoding and locating patterns in time are proposed and verified with preliminary ASR experiments. © 2012 Springer-Verlag.

关键词： Non-negative matrix factorization

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Evolving spiking neural networks for spatio-and spectro-temporal pattern recognition

Evolving spiking neural networks for spatio-and spectro-temp...

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international IEEE conference on Intelligent Systems, IS

作者： Nikola Kasabov Institute for Neuroinformatics-INI ETH University of Zurich Auckland New Zealand Knowledge Engineering and Discovery Research Institute-KEDRI Auckland University of Technology Auckland New Zealand

this paper provides a survey on the evolution of the evolving connectionist systems (ECOS) paradigm, from simple ECOS introduced in 1998 to evolving spiking neural networks (eSNN) and neurogenetic systems. It presents... 详细信息

关键词： Biological system modeling Neurons Brain models Adaptation models Data models Computational modeling

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pattern graphs: A knowledge-based tool for multivariate temporal pattern retrieval

Pattern graphs: A knowledge-based tool for multivariate temp...

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international IEEE conference on Intelligent Systems, IS

作者： Sebastian Peter Frank Höppner Michael R. Berthold Nycomed-Chair for Bioinformatics and Information Mining University of Konstanz Konstanz Germany Department of Computer Science Ostfalia University of Applied Sciences Wolfenb¨uttel Germany

We introduce a new, powerful query formulation formalism for complex, multivariate sequence data. the new query language, termed pattern graphs, is capable of reflecting more aspects of temporal patterns than earlier proposals. the underlying graph structure of the pattern graph makes the query intuitive to use and therefore understandable not only for the data analyst. We present algorithms to match patterns against data and demonstrate its usefulness on real data from the automobile industry.

关键词： pattern matching Time series analysis Indexes Data mining Educational institutions Database languages Vectors

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Application of Bayesian networks for pattern recognition: Character recognition case

Application of Bayesian networks for pattern recognition: Ch...

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international conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)

作者： Khlifia Jayech Mohamed Ali Mahjoub Nabil Ghanmi Research Unit SAGE National Engineering School of Sousse Sousse Tunisia

pattern recognition is a wide field in progress. In particular, handwriting recognition has known a great development in the recent years. Several solutions have been directed towards the use of Bayesian networks, which have shown their ability to solve complex problems in many areas, and that is thanks to their ability to model inaccuracies, which are lacunae highly present in the manuscript field. In this paper, we recall the basics of these networks and the difficulties come across in their learning and inference algorithms to make a good decision. We present a state of using the BNs and especially RBDs in the pattern recognition and more exactly in the character recognition. We show, through the various considered works, the contribution of this technique in solving the limitations of the Markov models and its ability to represent efficiently the temporal notion and the dependencies between the variables during the writing process. Moreover, we retain the recorded limitations and some development perspectives.

关键词： Bayes methods Hidden Markov models Handwriting recognition Speech recognition Character recognition Probabilistic logic Junctions

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Cooperative static and dynamic neural networks for phoneme recognition

Cooperative static and dynamic neural networks for phoneme r...

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international conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT)

作者： Jamil Arous Dorra Ben Ayed Noureddine Ellouze UR: Signal Image and Pattern Recognition ENIT Tunis Tunisia

this paper investigates the use of static and dynamic neural networks in phoneme recognition. Besides this, the paper also proposes a cooperative static and dynamic neural networks model. the cooperative model integrates a decision system for phoneme recognition. Mel cepstrum coding has been applied to represent speech signal in frames. Features from the selected frames are used to train neural networks based models. the comparative study show that the proposed cooperative model provides more accurate recognition rates both in auto-coherence test and generalization test.

关键词： Artificial neural networks Hidden Markov models Speech recognition Speech Training Cooperative systems

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Identifying the cold and hot properties of medicinal herbs based on the associated target proteins by pattern recognition technology

Identifying the cold and hot properties of medicinal herbs b...

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international conference on New Trends in Information and Service Science, NISS

作者： Haibo Gao Jianxin Cui Yao Gao Fei Liang Junping Zhan Li Li Guang Zheng Cheng Lu Aiping Lu Miao Jiang Yingying Wang Jinsheng Yang Institute of Basic Research in Clinical Medicine Institute of Acupuncture and Moxibustion China Academy of Chinese Medical Sciences Beijing China Institute of Electrical Engineering Yanshan University Qinhuangdao China College of Life Science and Technology Beijing University of Chemical Technology Beijing China Institute of Basic Research in Clinical Medicine China Academy of Chinese Medical Sciences Beijing China Institute of Acupuncture and Moxibustion China Academy of Chinese Medical Sciences Beijing China

this study is aiming to develop a novel pattern recognition approach for identifying the cold and hot properties of Chinese medicinal herbs. All associated target proteins in the herbs with different properties were obtained from PubChem and other public databases, and the pattern recognition algorithms were used to analyze the proteins coupled with pathway analysis with IPA software. A small-scale data was adopted to test the reliability and feasibility of the algorithms.

关键词： Chinese herbal medicine/CHM cold property hot property pattern recognition target proteins

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