• East Asian mathematical journal
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• v.34 no.5
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• pp.643-649
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• 2018

Let M be a connected n-dimensional submanifold of a Euclidean space $E^{n+k}$ equipped with the induced metric and ${\Delta}$ its Laplacian. If the position vector x of M is decomposed as a sum of three vectors $x=x_1+x_2+x_0$ where two vectors $x_1$ and $x_2$ are non-constant eigenvectors of the Laplacian, i.e., ${\Delta}x_i={\lambda}_ix_i$, i = 1, 2 (${\lambda}_i{\in}R$) and $x_0$ is a constant vector, then, M is called a 2-type submanifold. In this paper we proved that a connected 2-type hypersurface M in $E^{n+1}$ whose postion vector x satisfies ${\langle}{\Delta}x,x-x_0{\rangle}=c$ for a constant c, where ${\langle}$, ${\rangle}$ is the usual inner product in $E^{n+1}$, is of null 2-type and has constant mean curvature and scalar curvature.

• Communications of the Korean Mathematical Society
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• v.38 no.4
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• pp.1215-1231
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• 2023

The present article contains the study of D-homothetically deformed f-Kenmotsu manifolds. Some fundamental results on the deformed spaces have been deduced. Some basic properties of the Riemannian metric as an inner product on both the original and deformed spaces have been established. Finally, applying the obtained results, soliton functions, Ricci curvatures and scalar curvatures of almost Riemann solitons with several kinds of potential vector fields on the deformed spaces have been characterized.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.579-583
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• 2001

In the area of data clustering in high dimensional space, one of the difficulties is the time-consuming process for computing vector similarities. It becomes worse in the case of the agglomerative algorithm with the group-average link and mean centroid method, because the cluster similarity must be recomputed whenever the cluster center moves after the merging step. As a solution of this problem, we present an incremental method of similarity computation, which substitutes the scalar calculation for the time-consuming calculation of vector similarity with several measures such as the squared distance, inner product, cosine, and minimum variance. Experimental results show that it makes clustering speed significantly fast for very high dimensional data.

• Honam Mathematical Journal
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• v.45 no.4
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• pp.585-597
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• 2023

We introduce the rotational hypersurface x = x(u, v, s, t) constructed by double rotation in five dimensional Euclidean space 𝔼⁵. We reveal the first and the second fundamental form matrices, Gauss map, shape operator matrix of x. Additionally, defining the i-th curvatures of any hypersurface via Cayley-Hamilton theorem, we compute the curvatures of the rotational hypersurface x. We give some relations of the mean and Gauss-Kronecker curvatures of x. In addition, we reveal Δx=𝓐x, where 𝓐 is the 5 × 5 matrix in 𝔼⁵.

• East Asian mathematical journal
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• v.33 no.5
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• pp.571-585
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• 2017

Let M be a connected n-dimensional submanifold of a Euclidean space $E^{n+k}$ equipped with the induced metric and ${\Delta}$ its Laplacian. If the position vector x of M is decomposed as a sum of three vectors $x=x_1+x_2+x_0$ where two vectors $x_1$ and $x_2$ are non-constant eigen vectors of the Laplacian, i.e., ${\Delta}x_i={\lambda}_ix_i$, i = 1, 2 (${\lambda}_i{\in}R$) and $x_0$ is a constant vector, then, M is called a 2-type submanifold. In this paper we showed that a 2-type surface M in $E^3$ satisfies ${\langle}{\Delta}x,x-x_0{\rangle}=c$ for a constant c, where ${\langle},{\rangle}$ is the usual inner product in $E^3$, then M is an open part of a circular cylinder. Also we showed that if a quadric hypersurface M in a Euclidean space satisfies ${\langle}{\Delta}x,x{\rangle}=c$ for a constant c, then it is one of a minimal quadric hypersurface, a genaralized cone, a hypersphere, and a spherical cylinder.

• Proceedings of the KIEE Conference
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• 1996.07a
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• pp.262-264
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• 1996

This paper presents a new dual loop control using novel vector phase locked loop(VP-PLL) for a high power static var compensator(SVC) with three-level GTO voltage source inverter(VSI). Through circuit DQ-transformation, a simple dq-axis equivalent circuit is obtained. From this, DC analysis is carried out to obtain maximum controllable phase angle ${\alpha}_{max}$ per unit current between the three phase source and the switching function of inverter, and AC open-loop transfer function is given. Because ${\alpha}_{max}$ becomes small in high power SVC, this paper proposes VP-PLL for more accurate $\alpha$-control. As a result, the overall control loop has dual loop structure, which consists of inner VP-PLL for synchronizing the phase angle with source and outer Q-loop for compensating reactive power of load. Finally, the validity of the proposed control method is verified through the experimental results.

• Journal of the Korean Mathematical Society
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• v.54 no.2
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• pp.697-711
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• 2017

Let X, Y be real normed vector spaces. We exhibit all the solutions $f:X{\rightarrow}Y$ of the functional equation f(rx + sy) + rsf(x - y) = rf(x) + sf(y) for all $x,y{\in}X$, where r, s are nonzero real numbers satisfying r + s = 1. In particular, if Y is a Banach space, we investigate the Hyers-Ulam stability problem of the equation. We also investigate the Hyers-Ulam stability problem on a restricted domain of the following form ${\Omega}{\cap}\{(x,y){\in}X^2:{\parallel}x{\parallel}+{\parallel}y{\parallel}{\geq}d\}$, where ${\Omega}$ is a rotation of $H{\times}H{\subset}X^2$ and $H^c$ is of the first category. As a consequence, we obtain a measure zero Hyers-Ulam stability of the above equation when $f:\mathbb{R}{\rightarrow}Y$.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.4
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• pp.18-29
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• 1994

For the efficient recognition of Korean Alphabets, we proposed the tree structure algorithm which was based on K-tuple NRF-SDF using representative images as training images. Representative images consisted of ECP-SDF images of several consonants or vowels. To reduce the effect of sidelobe in the output correlation plane, we used the representative images as training images and obtained the elements of a vector inner product matrix using the peak value of AMPOF correlation of training images with one another. The proposed algorithm consisted of three main-step containing several substeps. In filter synthesis of each step, representative images were used as training images in the first and the second main-step and each consonant or vowel was used as training images in the third main-step. The performance of this algorithm is demonstrated by computer simulation and optical experiment.

• 한국전산유체공학회:학술대회논문집
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• 1997.10a
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• pp.49-54
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• 1997

Rice's monotone streamline upwind finite element method, which was proposed to treat convection-dominated flows, is applied to the linear triangular element. An alignment technique of unstructured grids with given velocity fields is used to prevent the interpolation error produced in evaluating the convection term in the upwind method. The alignment of grids is accomplished by optimizing a target function defined with the inner-product of a properly chosen side vector in the element with the velocity field. Two pure advection problems are considered to demonstrate the superiorities of the present approach in solving the convection-dominated flow on the unstructured grid. Solutions obtained with aligned grids are much closer to the exact solutions than those with initial regular grids. The capability of the present approach in predicting the appearance of the secondary vortex in the laminar confined jet impingement is shown by comparing streamlines to those produced by SIMPLE on a highly stretched grid toward the impingement plate.

• Bulletin of the Korean Mathematical Society
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• v.30 no.1
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• pp.99-107
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• 1993

A vector space K with scalar product <.,.> is called a Krein space if it can be decomposed as a northogonal sum of a Hilbert space and an anti-space of a Hilbert space. The space K induces a Hilbert space $K_{J}$ in the inner product <.,.> $K_{J}$=<.,.>K, where $J^{2}$=I. the eigenspaces of J are denoted by $K^{+}$$_{J}$, which is a Hilbert space and $K^{-}$$_{J}$, which is an anti-space of a Hilbert space. Then the Krein space K is the orthogonal sum of $K^{+}$$_{J}$ and $K^{-}$$_{J}$. Such a decomposition of K is called a fundamental decomposition. In general, fundamental decompositions are not unique. The norm of the Hilbert space depends on the choice of a fundamental decomposion, but such norms are equivalent. The topology generated by these norms is called the strong or Mackey topology of K. It is used to define all topological notions on the Krein space K with respect to this topology. The Pontryagin index of a Krein space is the dimension of the antispace of a Hilbert space in any such decomposition. the dimension does not depend on the choice of orthogonal decomposition. A Krein space is called a Pontryagin space if it has finite Pontryagin index.dex.yagin index.dex.