• Journal of applied mathematics & informatics
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• v.7 no.2
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• pp.409-438
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• 2000

In this paper we develop a new procedure to control stepsize for Runge- Kutta methods applied to both ordinary differential equations and semi-explicit index 1 differential-algebraic equation In contrast to the standard approach, the error control mechanism presented here is based on monitoring and controlling both the local and global errors of Runge- Kutta formulas. As a result, Runge-Kutta methods with the local-global stepsize control solve differential of differential-algebraic equations with any prescribe accuracy (up to round-off errors)

• Journal of applied mathematics & informatics
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• v.31 no.1_2
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• pp.285-297
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• 2013

This paper deals with parabolic equations coupled via nonstandard growth sources, subject to homogeneous Dirichlet boundary conditions. Three kinds of necessary and sufficient conditions are obtained, which determine the complete classifications for non-simultaneous and simultaneous blowup phenomena. Moreover, blowup rates are given.

• Honam Mathematical Journal
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• v.39 no.3
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• pp.317-330
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• 2017

In this paper we introduce some new kinds of injectivities, namely, LC (resp. Ind, PInd) injectivity and investigate the relation among various kinds of injectivities. Some classifications of monoids by properties of these kinds of injective acts are presented. Among other results, it is shown that over a principal right ideal monoid, right completely LC-injectivity implies right completely injectivity. Also over a monoid with a zero Ind-injective (resp. PInd-injective) acts are injective.

• International Journal of Control, Automation, and Systems
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• v.2 no.1
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• pp.125-133
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• 2004

In this paper, we present a new method that combines the characteristics of edge in-formation and second-order neural networks for the classification of structural textures. The edges of a texture are extracted using an edge detection approach. From this edge information, classification features called second-order features are obtained. These features are fed into a second-order neural network for training and subsequent classification. It will be shown that the main disadvantage of using structural methods in texture classifications, namely, the difficulty of the extraction of texels, is overcome by the proposed method.

• Proceedings of the Korea Concrete Institute Conference
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• 1992.10a
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• pp.240-244
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• 1992

The values of a linguistic variable are words, phrases, or sentences in a given language. For example, structural damage can be considered as linguistic variable with values such a 'severely damaged', 'moderately damaged', which are meaningful classifications but not clearly defined, This paper is to evaluate reasonably the correction factor of bridge capacity with the aid of fuzzy sets theory. By using the above mentioned fuzzy measure, the concept of fuzzy integral and linear membership function can be defined. It is concluded that the fuzzy sets theory cam be applied to determine reasonably the correction factor of bridge capacity.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.04a
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• pp.287-290
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• 2007

본 논문에서는 신호의 상호정보 추출에 의한 효율적인 군집화 방법을 제안하였다. 여기서 상호정보는 신호상호간의 상관관계를 나타내는 정보로 군집화를 위한 유사성을 나타내는 척도이다. 특히 적응적 분할을 이용하여 신호의 확률밀도를 계산함으로써 신호 상호간의 종속성을 좀 더 정확하고 빠르게 측정하였다. 제안된 방법을 500개 샘플을 가진 6개의 인위적인 신호군집화에 적용한 결과 정확한 분류성능이 있음을 확인하였다.

• Journal of the Korean Data and Information Science Society
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• v.14 no.1
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• pp.119-129
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• 2003

We propose a new logistic regression model of normality curves for normal(diseased) and abnormal(nondiseased) classifications by neural networks in data mining. The fitted logistic regression lines are estimated, interpreted and plotted by the neural network technique. A few goodness-of-fit test statistics for normality are discussed and the performances by the fitted logistic regression lines are conducted.

• 한국경영정보학회:학술대회논문집
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• 2007.06a
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• pp.571-575
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• 2007

For better predictions and classifications in customer recommendation, this study proposes an integrative model that efficiently combines the currently-in-use statistical and artificial intelligence models. In particular, by integrating the models such as Association Rule, Connection Frequency Matrix, and Rule Induction, this study suggests an integrative prediction model.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1998.10a
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• pp.366-369
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• 1998

To get the knowledge of land uses for watersheds, Thematic Mapper image from Landsat 5 satellite was used. The image was classified into land covers/uses by maximum likelihood classification technique. Land uses from the satellite image in this study was compared with those from the topographical map in previous. It was found that Land uses from the satellite image had a good reflection of real situations and more advantage in the reduction of time and cost.

• Journal for History of Mathematics
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• v.23 no.3
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• pp.75-90
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• 2010

In this paper function concept is classified in the phenomenological aspect. According to the study, function concept is classified as causality, designation, operation, change, figure, morhism, variables, functional, and operator. This classifications are categorized as pre-level function, basic level function, and upper level function.