• Journal of KIISE:Computing Practices and Letters
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• v.16 no.4
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• pp.492-496
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• 2010

Wikipedia as an open encyclopedia contains immense human knowledge written by thousands of volunteer editors and its reliability is also high. In this paper, we propose to automatically construct a Korean named entity dictionary using the several features of the Wikipedia. Firstly, we generate class hierarchies using the class information from each article of Wikipedia. Secondly, the titles of each article are mapped to our class hierarchies, and then we calculate the entropy value of the root node in each class hierarchy. Finally, we construct named entity dictionary with high performance by removing the class hierarchies which have a higher entropy value than threshold. Our experiment results achieved overall F1-measure of 81.12% (precision : 83.94%, recall : 78.48%).

• Journal of the Chungcheong Mathematical Society
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• v.25 no.4
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• pp.655-668
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• 2012

An operator $T\;{\varepsilon}\;B(\mathcal{H})$ is said to be $k$-quasi-paranormal operator if $||T^{k+1}x||^2\;{\leq}\;||T^{k+2}x||\;||T^kx||$ for every $x\;{\epsilon}\;\mathcal{H}$, $k$ is a natural number. This class of operators contains the class of paranormal operators and the class of quasi - class A operators. In this paper, using the operator matrix representation of $k$-quasi-paranormal operators which is related to the paranormal operators, we show that every algebraically $k$-quasi-paranormal operator has Bishop's property ($\beta$), which is an extension of the result proved for paranormal operators in [32]. Also we prove that (i) generalized Weyl's theorem holds for $f(T)$ for every $f\;{\epsilon}\;H({\sigma}(T))$; (ii) generalized a - Browder's theorem holds for $f(S)$ for every $S\;{\prec}\;T$ and $f\;{\epsilon}\;H({\sigma}(S))$; (iii) the spectral mapping theorem holds for the B - Weyl spectrum of T.

• Bulletin of the Korean Mathematical Society
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• v.41 no.2
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• pp.241-256
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• 2004

In this paper, we introduce and study a new class of variational inclusions, called the general variational inclusion. We prove the equivalence between the general variational inclusions, the general resolvent equations, and the fixed-point problems, using the resolvent operator technique. This equivalence is used to suggest and analyze a few iterative algorithms for solving the general variational inclusions and the general resolvent equations. Under certain conditions, the convergence analyses are also studied. The results presented in this paper generalize, improve and unify a number of recent results.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.842-847
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• 2005

This paper proposes a novel real-time EMG pattern recognition for the control of a multifunction myoelectric hand from four channel EMG signals. To cope with the nonstationary signal property of the EMG, features are extracted by wavelet packet transform. For dimensionality reduction and nonlinear mapping of the features, we also propose a linear-nonlinear feature projection composed of PCA and SOFM. The dimensionality reduction by PCA simplifies the structure of the classifier, and reduces processing time for the pattern recognition. The nonlinear mapping by SOFM transforms the PCA-reduced features to a new feature space with high class separability. Finally a multilayer neural network is employed as the pattern classifier. We implement a real-time control system for a multifunction virtual hand. From experimental results, we show that all processes, including virtual hand control, are completed within 125 msec, and the proposed method is applicable to real-time myoelectric hand control without an operation time delay.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.33A no.10
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• pp.12-21
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• 1996

The trellis shaping is the method of selecting a minimum weight sequence from an equivalent class of possible transmitted sequences. It is perforemed by searching through the trellis diagram of a shaping convolutional code Cs. A shaping gain of the order of 1dB may be obtained with a simple 4-state shaping code. But when the rellis shaping is applied to multi-dimensional constellation, the shaping gain is decreased and the transmission delay is increased, which make it difficult to apply the trellis shaping to multi-dimensional constellation. In this paper, in order to solve these problems, the shell mapping algorithm is used for the mapper in the proposed trellis shaping. The simulatio result shows that the proposed trellis shaping is better than coventional trellis shaping to multi-dimensional constellation. In this paper, in order to solve these problems, the shell mapping on multi-dimensional costellation with respect to shaping gain and transmission delay. And the constellation expansion ratio (CER) and the capacity of transmitted injformation are identical to those of conventional trellis shaping on multi-dimensional constellation.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.71-76
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• 2003

The purpose of this study is the development, application and assessment of probability and artificial neural network methods for assessing landslide susceptibility in a chosen study area. As the basic analysis tool, a Geographic Information System (GIS) was used for spatial data management. A probability method was used for calculating the rating of the relative importance of each factor class to landslide occurrence, For calculating the weight of the relative importance of each factor to landslide occurrence, an artificial neural network method was developed. Using these methods, the landslide susceptibility index was calculated using the rating and weight, and a landslide susceptibility map was produced using the index. The results of the landslide susceptibility analysis, with and without weights, were confirmed from comparison with the landslide location data. The comparison result with weighting was better than the results without weighting. The calculated weight and rating can be used to landslide susceptibility mapping.

• Bulletin of the Korean Chemical Society
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• v.11 no.5
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• pp.450-455
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• 1990

Fifty eight obsidian artifacts and four obsidian source samples have been analyzed by instrumental neutron activation analysis. Artifact samples have been classified into classes by unsupervised learning techniques such as eigenvector projection and nonlinear mapping. The source samples have thereafter been connected to the classes by the supervised learning techniques such as SLDA and SIMCA so as to characterize each class by possible source sites. Some difference attributable to different nonlinear mapping techniques and the elemental effects on the separation between classes have been discussed.

• Kyungpook Mathematical Journal
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• v.59 no.1
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• pp.83-99
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• 2019

In this paper, we introduce a hybrid subgradient method for finding an element common to both the solution set of a class of pseudomonotone equilibrium problems, and the set of fixed points of a finite family of ${\kappa}$-strictly presudononspreading mappings in a real Hilbert space. We establish some weak and strong convergence theorems of the sequences generated by our iterative method under some suitable conditions. These convergence theorems are investigated without the Lipschitz condition for bifunctions. Our results complement many known recent results in the literature.

• Journal of the Korean association of regional geographers
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• v.22 no.1
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• pp.251-266
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• 2016

Intelligent interpolation methods such as dasymetric mapping are considered to be the best way to disaggregate zone-based population data by observing and utilizing the internal variation within each source zone. This research reviews the advantages and problems of the dasymetric mapping method, and presents a geographically weighted regression (GWR) based method to take into consideration the spatial heterogeneity of population density - land cover relationship. The locally adaptive intelligent interpolation method is able to make use of readily available ancillary information in the public domain without the need for additional data processing. In the case study, we use the preclassified National Land Cover Dataset 2011 to test the performance of the proposed method (i.e. the GWR-based multi-class dasymetric method) compared to four other popular population estimation methods (i.e. areal weighting interpolation, pycnophylactic interpolation, binary dasymetric method, and globally fitted ordinary least squares (OLS) based multi-class dasymetric method). The GWR-based multi-class dasymetric method outperforms all other methods. It is attributed to the fact that spatial heterogeneity is accounted for in the process of determining density parameters for land cover classes.

• Journal of the Chungcheong Mathematical Society
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• v.19 no.1
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• pp.101-110
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• 2006

In this paper, we develop existence and uniqueness criteria to certain class of three point boundary value problems associated with third order nonlinear fuzzy differential equations, with the help of Green's functions and contraction mapping principle.