• Journal of KIISE:Computer Systems and Theory
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• v.32 no.1
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• pp.1-8
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• 2005

Image morphing to generate 2D transitions between images may be difficult even to express simple 3D transformations. In addition, previous view morphing method requires control points for postwarping, and is much affected by self- occlusion. This paper presents a new morphing algorithm that can generate automatically in-between scenes from un-calibrated images. Our algorithm rectifies input images based on the fundamental matrix, which is followed by linear interpolation with bilinear disparity map. In final, we generate in-between views by inverse mapping of homography between the rectified images. The proposed method nay be applied to photographs and drawings, because neither knowledge of 3D shape nor camera calibration, which is complex process generally, is required. The generated in-between views can be used in various application areas such as simulation system of virtual environment and image communication.

• Journal of the Chungcheong Mathematical Society
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• v.9 no.1
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• pp.175-181
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• 1996

We show that $\frac{{\partial}x}{{\partial}{\gamma}}(t,{\tau},{\gamma},{\lambda},{\varepsilon})$ is a fundamental matrix of the variational system $\dot{y}=fx(t,x(t,{\tau},{\gamma},{\lambda},{\varepsilon}),{\lambda},{\varepsilon})y$ corresponding to the solution $x(t,{\tau},{\gamma},{\lambda},{\varepsilon})$ of $\dot{x}=f(t,x,{\lambda},{\varepsilon})$.

• Proceedings of the KIEE Conference
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• 1979.08a
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• pp.138-141
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• 1979

The purpose of this paper is to develop an efficient model for the analysis of a John's Chopper Circuit. In the John's Chopper Circuit analysis, the open branches are removed from the associated graph to formulate the modified incidence matrix. An algorithm for the generation of a modified proper tree and fundamental cut set matrix from a network graph is developed, which utilizes much less computer storage space and computation time compared to the classical methods.

• Kyungpook Mathematical Journal
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• v.43 no.4
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• pp.503-512
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• 2003

In this paper, we first give an alternative description of the fundamental orthodox semigroup $\bar{A}$(1, 2). We then use this to represent the double four-spiral semigroup $DSp_4$ as a regular Rees matrix semigroup over $\bar{A}$(1, 2).

• Proceedings of the Korean Institute of Building Construction Conference
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• 2015.11a
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• pp.24-25
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• 2015

To secure fundamental materials for the performance change in concrete structure damaged by fire, this study analyzed SEM and XRD of hardened cement depending on high temperature conditions. As a result, at more than 200℃, SEM and XRD were not observed because of dehydration of Ettringite; at more than 500℃, calcium hydroxide was rapidly decomposed; at more than 700℃, calcium oxide was found; at 1000℃, the highest peak point appeared.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 1996.05a
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• pp.114-117
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• 1996

The wavelength selectivity in grating-assisted optical waveguide couplers is studied using a matrix method to analyse optical filter characteristics. The matrix method is extended to both 2-system modes and all guided system modes. The influence of fundamental design parameters on the performances of the optical filters by waveguide couplers is discussed.

• Proceedings of the KSR Conference
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• 2002.10a
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• pp.125-130
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• 2002

This paper investigates the dynamic characteristics of a beam axially moving over multiple elastic supports. The spectral element matrix is derived first for the axially moving beam element and then it is used to formulate the spectral element matrix for the moving beam element with an interim elastic support. The moving speed dependance of the eigenvalues is numerically investigated by varying the applied axial tension and the stiffness of the elastic supports. Numerical results show that the fundamental eigenvalue vanishes first at the critical moving speed to generate the static instability.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1362-1365
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• 1993

Fuzzy mathematics is used to elicit and evaluate human psychophysical responses in panel tests. The fundamental instrument used is a bar graph whose data is then converted to a paired comparison matrix. Form this matrix we use the theory of Perron and Froebenius to obtain an eigenvalue and eigenvector which indicates not only the panelist's comparitive responses but also the consistency of the responses from that panelist. Tests were done to evaluate the procedure.

• Journal of Institute of Convergence Technology
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• v.8 no.1
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• pp.15-20
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• 2018

Recently a GPU has acquired programmability to perform general purpose computation fast by running thousands of threads concurrently. This paper presents a parallel GPU computation algorithm for dense matrix-matrix addition and scalar multiplication using OpenGL compute shader. It can play a very important role as a fundamental building block for many high-performance computing applications. Experimental results on NVIDIA Quad 4000 show that the proposed algorithm runs 21 times faster than CPU algorithm and achieves performance of 16 GFLOPS in single precision for dense matrices with size 4,096. Such performance proves that our algorithm is practical for real applications.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.11
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• pp.1623-1629
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• 2022

Matrix multiplication is a fundamental operation widely used in science and engineering. There is an approximate matrix multiplication method as a way to reduce the amount of computation of matrix multiplication. Approximate matrix multiplication determines an appropriate probability distribution for selecting columns and rows of matrices, and performs approximate matrix multiplication by selecting columns and rows of matrices according to this distribution. Probability distributions are generated by considering both matrices A and B participating in matrix multiplication. In this paper, we propose a method to generate a probability distribution that selects columns and rows of matrices to be used for approximate matrix multiplication, targeting only matrix A. Approximate matrix multiplication was performed on 1000×1000 ~ 5000×5000 matrices using existing and proposed methods. The approximate matrix multiplication applying the proposed method compared to the conventional method has been shown to be closer to the original matrix multiplication result, averaging 0.02% to 2.34%.