• Journal of the Korean Statistical Society
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• v.36 no.3
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• pp.367-372
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• 2007

Classification as a tool to extract information from data plays an important role in science and engineering. Among various classification methodologies, support vector machine has recently seen significant developments. The central problem this paper addresses is the accuracy of support vector machine. In particular, we are interested in the situations where fast rates of convergence to the Bayes risk can be achieved by support vector machine. Through learning examples, we illustrate that support vector machine may yield fast rates if the space spanned by an adopted kernel is sufficiently large.

• Bulletin of the Korean Mathematical Society
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• v.54 no.5
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• pp.1699-1718
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• 2017

We give a construction of the second Chern number of a vector bundle over a smooth projective surface by means of adelic transition matrices for the vector bundle. The construction does not use an algebraic K-theory and depends on the canonical ${\mathbb{Z}}-torsor$ of a locally linearly compact k-vector space. Analogs of certain auxiliary results for the case of an arithmetic surface are also discussed.

• Journal of the Chungcheong Mathematical Society
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• v.24 no.4
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• pp.869-881
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• 2011

The main goal in the present paper is to obtain a necessary and sufficient condition for a new connection with zero torsion vector to be an Einstein's connection and derive some useful representation of the vector defining the Einstein's connection in even-dimensional UFT $X_n$.

• Communications of the Korean Mathematical Society
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• v.11 no.2
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• pp.391-405
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• 1996

In this article, we calculate the cohomology groups of flat vector bundles on some manifolds.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.462-465
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• 2002

This paper presents a basic theory of information flow from single sending point to multiple receiving points, where new theories of algebraic system called "Hybrid Vector Space" and flow vector space play important roles. Based on the theory, a new algorithm for finding maximum homogenous information flow is proposed, where homogenous information flow means the flow of the same contents of information delivered to multiple clients at a time. Effective multi-routing algorithms fur tree-shape delivery rout search are presented.

• Journal of the Korean Mathematical Society
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• v.11 no.1
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• pp.29-31
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• 1974

In the first paper of this series, [2], we investigated how the conformal change enforces the connections and gave the complete relations between connections in Einstein's $^*g^{{\lambda}{\nu}}$-unified field theory. In the current paper we wish to investigate how the vector def $$S_{{\lambda}{{\mu}}{{^\mu}}{=^{def}}S_{\lambda}$$ is transformed by the conformal change. This topics will be studied for all classes and all possible indices of inertia.

• Bulletin of the Korean Mathematical Society
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• v.48 no.6
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• pp.1225-1233
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• 2011

In this paper, without assumption of monotonicity, we study the compactness and the connectedness of the weakly efficient solutions set to vector equilibrium problems by using scalarization method in locally convex spaces. Our results improve the corresponding results in [X. H. Gong, Connectedness of the solution sets and scalarization for vector equilibrium problems, J. Optim. Theory Appl. 133 (2007), 151-161].

• Journal of the Korea Society of Computer and Information
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• v.17 no.12
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• pp.179-185
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• 2012

This paper proposes a design of RSIDS(RST and SVM based Intrusion Detection System) using RST(Rough Set Theory) and SVM(Support Vector Machine) algorithm. The RSIDS consists of PrePro(PreProcessing) module, RRG(RST based Rule Generation) module, and SAD(SVM based Attack Detection) module. The PrePro module changes the collected information to the data format of RSIDS. The RRG module analyzes attack data, generates the rules of attacks, extracts attack information from the massive data by using these rules, and transfers the extracted attack information to the SAD module. The SAD module detects the attacks by using it, which the SAD module notifies to a manager. Therefore, compared to the existing SVM, the RSIDS improved average ADR(Attack Detection Ratio) from 77.71% to 85.28%, and reduced average FPR(False Positive ratio) from 13.25% to 9.87%. Thus, the RSIDS is estimated to have been improved, compared to the existing SVM.

• The Transactions of the Korean Institute of Power Electronics
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• v.11 no.2
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• pp.172-183
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• 2006

This paper analyzes instantaneous power compensation theory through comparing p-q theory and cross-vector theory which were proposed by Akagi and Nabae respectively in three-phase four-wire systems. The two compensation theories are identical when there is no zero-sequence voltage component in three-phase three-wire systems, However, when the zero-sequence voltage and/or current components exist in three-phase four-wire systems, the two compensation theories we different in definition on instantaneous real power and instantaneous imaginary power. Based on the analysis, this paper presents instantaneous power compensation method that can eliminate neutral current completely without using energy storage element when the zero-sequence current and voltage components exist in three-phase four-wire systems.

• Computers and Concrete
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• v.9 no.3
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• pp.215-226
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• 2012

This article employs Support Vector Machine (SVM) for determination of fracture parameters critical stress intensity factor ($K^s_{Ic}$) and the critical crack tip opening displacement ($CTOD_c$) of concrete. SVM that is firmly based on the theory of statistical learning theory, uses regression technique by introducing ${\varepsilon}$-insensitive loss function has been adopted. The results are compared with a widely used Artificial Neural Network (ANN) model. Equations have been also developed for prediction of $K^s_{Ic}$ and $CTOD_c$. A sensitivity analysis has been also performed to investigate the importance of the input parameters. The results of this study show that the developed SVM is a robust model for determination of $K^s_{Ic}$ and $CTOD_c$ of concrete.