• 전자공학회논문지B
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• 제30B권1호
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• pp.1-9
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• 1993

In recent days high perfermance graphic operation is needed, since computer graphics is widely used for computer-aided design and simulator using high resolution graphic card. In this paper a graphic accelerator is designd with the functions of graphic primitives generation and geometrical transformations. 1-D Systolic Array Processor for Matris Vector operation is designed and used in main ALU of a graphic accelerator, since these graphic algorithms have comonon operation of Matris Vector. Conclusively, in case that the resolution of graphic domain is 800$\times$600, and 33.3nsec operator is used in a graphic accelerator, 29732 lines per second and approximately 6244 circles per second is generated.

• 한국항행학회논문지
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• 제12권4호
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• pp.378-383
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• 2008

본 논문에서는 DCT 변환과 퍼지추론을 이용하여 영상을 분석하는 방법을 제안 한 바, 병해충 과실 등의 특성을 분석 할 수 있는 퍼지추론 알고리즘과 변환계수에 시각특성파라미터를 접목하는 방법에 중점을 두었다. 전처리 과정에서 이산코사인 변환계수로부터 엔트로피와 텍스처 등의 시각특징 파라미터들을 구하였고, 이 변수들을 이용하여 퍼지 추론의 입력 변수를 생성 하였다. 맘다니 연산자와 ${\alpha}$-cut 함수를 적용하여 영상 분석을 실험한 결과, 제안한 방법의 응용가능성을 입증하였다.

• Journal of the Korean Data and Information Science Society
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• 제24권5호
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• pp.1077-1088
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• 2013

High-dimensional data analysis arises from almost all scientific areas, evolving with development of computing skills, and has encouraged penalized estimations that play important roles in statistical learning. For the past years, various penalized estimations have been developed, and the least absolute shrinkage and selection operator (LASSO) proposed by Tibshirani (1996) has shown outstanding ability, earning the first place on the development of penalized estimation. In this paper, we first introduce a number of recent advances in high-dimensional data analysis using the LASSO. The topics include various statistical problems such as variable selection and grouped or structured variable selection under sparse high-dimensional linear regression models. Several unsupervised learning methods including inverse covariance matrix estimation are presented. In addition, we address further studies on new applications which may establish a guideline on how to use the LASSO for statistical challenges of high-dimensional data analysis.

• Kyungpook Mathematical Journal
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• 제56권4호
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• pp.1141-1160
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• 2016

In this paper, a symbolic algorithm for solving a regular initial value problem (IVP) for a system of linear differential-algebraic equations (DAEs) with constant coeffcients has been presented. Algebra of integro-differential operators is employed to express the given system of DAEs. We compute a canonical form of the given system which produces another simple equivalent system. Algorithm includes computing the matrix Green's operator and the vector Green's function of a given IVP. Implementation of the proposed algorithm in Maple is also presented with sample computations.

• Kyungpook Mathematical Journal
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• 제57권4호
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• pp.631-640
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• 2017

The aim of this paper is to introduce the binomial sequence spaces $b_0^{r,s}(\nabla)$, $b_c^{r,s}(\nabla)$ and $b_{\infty}^{r,s}(\nabla)$ by combining the binomial transformation and difference operator. We prove that these spaces are linearly isomorphic to the spaces $c_0$, c and ${\ell}_{\infty}$, respectively. Furthermore, we compute the Schauder bases and the ${\alpha}-$, ${\beta}-$ and ${\gamma}-duals$ of these sequence spaces.

• 대한수학회지
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• 제32권3호
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• pp.531-540
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• 1995

There is much literature on the study of matrices over a finite Boolean algebra. But many results in Boolean matrix theory are stated only for binary Boolean matrices. This is due in part to a semiring isomorphism between the matrices over the Boolean algebra of subsets of a k element set and the k tuples of binary Boolean matrices. This isomorphism allows many questions concerning matrices over an arbitrary finite Boolean algebra to be answered using the binary Boolean case. However there are interesting results about the general (i.e. nonbinary) Boolean matrices that have not been mentioned and they differ somwhat from the binary case.

• Bulletin of the Korean Chemical Society
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• 제28권10호
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• pp.1705-1708
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• 2007

Geometric manipulation of molecules is an essential elementary component in computational modeling programs for molecular structure, stability, dynamics, and design. The computational complexity of transformation of internal coordinates to Cartesian coordinates was discussed before.1 The use of rotation matrices was found to be slightly more efficient than that of quaternion although quaternion operators have been widely advertised for rotational operations, especially in molecular dynamics simulations of liquids where the orientation is a dynamical variable.2 The discussion on computational efficiency is extended here to a more general case in which bond angles and sidechain torsion angles are allowed to vary. The algorithm of Thompson3 is derived again in terms of quaternions as well as rotation matrices, and an algorithm with optimal efficiency is described. The algorithm based on rotation matrices is again found to be slightly more efficient than that based on quaternions.

• 한국생산제조학회지
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• 제9권2호
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• pp.144-150
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• 2000

Surface roughness is one of the most important parameters to estimate quality of products. As this reason so many studies were car-ried out through various attempts that were contact or non-contact using computer vision. Even through these efforts there were few good results in this research., however texture analysis making a important role to solve these problems in various fields including universe aviation living thing and fibers. In this study feature value of co-occurrence matrix was calculated by statistic method and roughness value of worked surface was classified, of it. Experiment was carried out using input vector of neural network with characteristic value of texture calculated from worked surface image. It's found that recognition rate of 74% was obtained when adapting texture features. In order to enhance recogni-tion rate combination type in characteristics value of texture was changed into input vector. As a result high recognition rate of 92.6% was obtained through these processes.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제14권1호
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• pp.35-42
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• 2010

A goal of Magnetic Resonance Imaging is reproducing a spatial map of the effective spin density from the measured Fourier coefficients of a specimen. The imaging procedure can be done by inverse Fourier transformation or backward fast Fourier transformation if the data are sampled on a regular grid in frequency space; however, it is still a challenging question how to reconstruct an image from a finite set of Fourier data on irregular points in k-space. In this paper, we describe some mathematical and numerical properties of imaging techniques from non-uniform MR data using the pseudo-inverse or the diagonal-inverse weight matrix. This note is written as an easy guide to readers interested in the non-uniform MRI techniques and it basically follows the ideas given in the paper by Greengard-Lee-Inati [10, 11].

• 대한수학회보
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• 제34권2호
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• pp.155-171
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• 1997

Let $M^n$ be a connected subminifold of a Euclidean space $E^m$, equipped with the induced metric. Denoty by $\Delta$ the Laplacian operator of $M^n$ and by x the position vector. A well-known T. Takahashi's theorem [13] says that $\delta x = \lambda x$ for some constant $\lambda$ if and only if $M^n$ is either minimal subminifold of $E^m$ or minimal submanifold in a hypersphere of $E^m$. In [9], O. Garay studied the hypersurfaces $M^n$ in $E^{n+1}$ satisfying $\delta x = Dx$, where D is a diagonal matrix, and he classified such hypersurfaces. Garay's condition can be seen as a generalization of T.