• Title/Summary/Keyword: normal vector

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HOPF HYPERSURFACES IN COMPLEX TWO-PLANE GRASSMANNIANS WITH LIE PARALLEL NORMAL JACOBI OPERATOR

  • Jeong, Im-Soon;Lee, Hyun-Jin;Suh, Young-Jin
    • Bulletin of the Korean Mathematical Society
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    • v.48 no.2
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    • pp.427-444
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    • 2011
  • In this paper we give some non-existence theorems for Hopf hypersurfaces in the complex two-plane Grassmannian $G_2(\mathbb{C}^{m+2})$ with Lie parallel normal Jacobi operator $\bar{R}_N$ and totally geodesic D and $D^{\bot}$ components of the Reeb flow.

Analysis of Normal Induced Voltage on Telecommunication Line according to Earth Resistivity in Distrbution Lines (배전선로에서의 대지 저항율에 따른 통신선 상시 유도전압 분석)

  • Kim, Hyoun-Su;Yeo, Sang-Min;Kim, Chul-Hwan;Lyu, Seung-Heon
    • Proceedings of the KIEE Conference
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    • 2009.07a
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    • pp.223_224
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    • 2009
  • This paper investigates a normal induced voltage according to earth resistivity from distribution lines using calculation method of the normal induced voltage on telecommunication line. The induced voltage according to earth resistivity from distribution lines is verified by vector analysis and EMTP(Electro-Magnetic Transients Program).

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Properties of alternative VaR for multivariate normal distributions (다변량 정규분포에서 대안적인 VaR의 특성)

  • Hong, Chong Sun;Lee, Gi Pum
    • Journal of the Korean Data and Information Science Society
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    • v.27 no.6
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    • pp.1453-1463
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    • 2016
  • The most useful financial risk measure may be VaR (Value at Risk) which estimates the maximum loss amount statistically. The VaR tends to be estimated in many industries by using transformed univariate risk including variance-covariance matrix and a specific portfolio. Hong et al. (2016) are defined the Vector at Risk based on the multivariate quantile vector. When a specific portfolio is given, one point among Vector at Risk is founded as the best VaR which is called as an alternative VaR (AVaR). In this work, AVaRs have been investigated for multivariate normal distributions with many kinds of variance-covariance matrix and various portfolio weight vectors, and compared with VaRs. It has been found that the AVaR has smaller values than VaR. Some properties of AVaR are derived and discussed with these characteristics.

Normal Meshes for Multiresolution Analysis on Irregular Meshes with a Boundary (다중해상도해석을 위한 Boundary를 가지는 비정규 메쉬의 Normal 메쉬화 방법)

  • 강성찬;이규열;김태완
    • Korean Journal of Computational Design and Engineering
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    • v.6 no.3
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    • pp.184-192
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    • 2001
  • In this paper we present a remeshing algorithm for irregular meshes with boundaries. The irregular meshes are approximated by regular meshes where the topological regularity is essential for the multiresolutional analysis of the given meshes. Normal meshes are utilized to reduce the necessary data size at each resolution level of the regularized meshes. The normal mesh uses one scalar value, i.e., normal offset value which is based on the regular rule of a uniform subdivision, while other remeshing schemes use one 3D vector at each vertex. Since the normal offset cannot be properly used for the boundaries of meshes, we use a combined subdivision scheme which resolves a problem of the proposed normal offset method at the boundaries. Finally, we show an example to see the effectiveness of the proposed scheme to reduce the data size of a mesh model.

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Cancer Gene Therapy. History and Major Developments (암 유전자 치료제의 개발 현황)

  • 정인재
    • Toxicological Research
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    • v.19 no.3
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    • pp.247-257
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    • 2003
  • Medicine is undergoing a revolution in the understanding of the mechanisms through which disease processes develop. The advent of genetics and molecular biology to oncology not only is providing surrogate predictors of therapy response and survival which are forming the basis for selection among established treatment options, but is providing targets for new directions in therapy as well. Molecular modification of somatic cells for the purposes of protecting the normal cells from the toxicity of cancer chemotherapy, for the sensitization of the tumor cells to therapy and use of conditionally replicating viral vector have been new directions of cancer treatment which have reached the clinical arena. Advances in molecular pharmacology and vector design summarized in this paper may provide solutions to some of the existing problems in the technology of gene transfer therapy. Continued basic research into the biological basis of human disease, systemic studies of the application of these discoveries to therapy and the improvement of vector for gene delivery all combined may result in advances in this important field of therapy over the next few years.

Generic submanifolds of a quaternionic kaehlerian manifold with nonvanishing parallel mean curvature vector

  • Jung, Seoung-Dal;Pak, Jin-Suk
    • Journal of the Korean Mathematical Society
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    • v.31 no.3
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    • pp.339-352
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    • 1994
  • A sumbanifold M of a quaternionic Kaehlerian manifold $\tilde{M}^m$ of real dimension 4m is called a generic submanifold if the normal space N(M) of M is always mapped into the tangent space T(M) under the action of the quaternionic Kaehlerian structure tensors of the ambient manifold at the same time.The purpose of the present paper is to study generic submanifold of quaternionic Kaehlerian manifold of constant Q-sectional curvature with nonvanishing parallel mean curvature vector. In section 1, we state general formulas on generic submanifolds of a quaternionic Kaehlerian manifold of constant Q-sectional curvature. Section 2 is devoted to the study generic submanifolds with nonvanishing parallel mean curvature vector and compute the restricted Laplacian for the second fundamental form in the direction of the mean curvature vector. As applications of those results, in section 3, we prove our main theorems. In this paper, the dimension of a manifold will always indicate its real dimension.

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A Fault Detection of Cyclic Signals Using Support Vector Machine-Regression (Support Vector Machine-Regression을 이용한 주기신호의 이상탐지)

  • Park, Seung-Hwan;Kim, Jun-Seok;Park, Cheong-Sool;Kim, Sung-Shick;Baek, Jun-Geol
    • Journal of Korean Society for Quality Management
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    • v.38 no.3
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    • pp.354-362
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    • 2010
  • This paper presents a non-linear control chart based on support vector machine regression (SVM-R) to improve the accuracy of fault detection of cyclic signals. The proposed algorithm consists of the following two steps. First, the center line of the control chart is constructed by using SVM-R. Second, we calculate control limits by variances that are estimated by perpendicular and normal line of the center line. For performance evaluation, we apply proposed algorithm to the industrial data of the chemical vapor deposition process which is one of the semiconductor processes. The proposed method has better fault detection performance than other existing method

C-parallel Mean Curvature Vector Fields along Slant Curves in Sasakian 3-manifolds

  • Lee, Ji-Eun;Suh, Young-Jin;Lee, Hyun-Jin
    • Kyungpook Mathematical Journal
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    • v.52 no.1
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    • pp.49-59
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    • 2012
  • In this article, using the example of C. Camci([7]) we reconfirm necessary sufficient condition for a slant curve. Next, we find some necessary and sufficient conditions for a slant curve in a Sasakian 3-manifold to have: (i) a $C$-parallel mean curvature vector field; (ii) a $C$-proper mean curvature vector field (in the normal bundle).

One-Class Support Vector Learning and Linear Matrix Inequalities

  • Park, Jooyoung;Kim, Jinsung;Lee, Hansung;Park, Daihee
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.3 no.1
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    • pp.100-104
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    • 2003
  • The SVDD(support vector data description) is one of the most well-known one-class support vector learning methods, in which one tries the strategy of utilizing balls defined on the kernel feature space in order to distinguish a set of normal data from all other possible abnormal objects. The major concern of this paper is to consider the problem of modifying the SVDD into the direction of utilizing ellipsoids instead of balls in order to enable better classification performance. After a brief review about the original SVDD method, this paper establishes a new method utilizing ellipsoids in feature space, and presents a solution in the form of SDP(semi-definite programming) which is an optimization problem based on linear matrix inequalities.

An improvement of estimators for the multinormal mean vector with the known norm

  • Kim, Jaehyun;Baek, Hoh Yoo
    • Journal of the Korean Data and Information Science Society
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    • v.28 no.2
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    • pp.435-442
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    • 2017
  • Consider the problem of estimating a $p{\times}1$ mean vector ${\theta}$ (p ${\geq}$ 3) under the quadratic loss from multi-variate normal population. We find a James-Stein type estimator which shrinks towards the projection vectors when the underlying distribution is that of a variance mixture of normals. In this case, the norm ${\parallel}{\theta}-K{\theta}{\parallel}$ is known where K is a projection vector with rank(K) = q. The class of this type estimator is quite general to include the class of the estimators proposed by Merchand and Giri (1993). We can derive the class and obtain the optimal type estimator. Also, this research can be applied to the simple and multiple regression model in the case of rank(K) ${\geq}2$.