• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.333-336
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• 2000

We discuss the direct methods (Gauss-Jordan and Gaussian eliminations) to solve linear systems on distributed memory parallel computers. It will be shown that the so-called row-cyclic storage gives rise to the best performance among the standard three (row-cyclic, column-cyclic and cyclic-cyclic) data storages. We also show that Gauss-Jordan elimination, rather than Gaussian elimination, is highly efficient for the direct solution of linear systems in parallel processing, though Gauss-Jordan elimination requires a larger number of arithmetic operations than Gaussian elimination. Numerical experiment is performed on HITACHI SR12201 with the standard libraries MPI and BLAS.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.5C
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• pp.384-392
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• 2012

Recently, much research on blind estimation of the interleaver parameters has been performed by using Gauss-Jordan elimination to find the linearity of the block channel code. When using Gauss-Jordan elimination, the input data to be calculated needs to run as long as the square multiple of the number of the interleaver period. Thus, it has a limit in estimating the interleaver parameters with insufficient input data. In this paper, we introduce and analyze an estimation algorithm which can estimate interleaver parameters by using only 15 percent of the input data length required in the above algorithm. The shorter length of input data to be calculated makes it possible to estimate the interleaver parameters even when limited data is received. In addition, a 80 percent reduction in the number of the interleaver period candidates increases the efficiency of analysis. It is also feasible to estimate both the type and size of the interleaver and the type of channel coding.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.8 no.12
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• pp.127-138
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• 1985

There are several methods which have been presented up to now in solving the simultaneous linear equations by computer. They are Gaussian Elimination Method, Gauss-Jordan Method, Inverse matrix Method and Gauss-Seidel iterative Method. This paper is not only discussed in their mechanisms compared with their algorithms, depicted flow charts, but also calculated the numbers of arithmetic operations and comparisons in order to criticize their availability. Inverse Matrix Method among em is founded out the smallest in the number of arithmetic operation, but is not the shortest operation time. This paper also indicates the many problems in using these methods and propose the new method which is able to applicate to even small or middle size computers.

• Proceedings of the Korea Institutes of Information Security and Cryptology Conference
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• 1991.11a
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• pp.40-48
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• 1991

McEliece 공개키 암호체계에 대한 새로운 암호해독적 공격이 제시되어진다. 기존의 암호해독 algorithm이 exponential-time의 complexity를 가지는 반면, 본고에서 제시되어지는 algorithm은 polynomial-time의 complexity를 가진다. 모든 linear codes에는 systematic generator matrix가 존재한다는 사실이 본 연구의 동기가 된다. Public generator matrix로부터, 암호해독에 사용되어질 수 있는 새로운 trapdoor generator matrix가 Gauss-Jordan Elimination의 역할을 하는 일련의 transformation matrix multiplication을 통해 도출되어진다. 제시되어지는 algorithm의 계산상의 complexity는 주로 systematic trapdoor generator matrix를 도출하기 위해 사용되는 binary matrix multiplication에 기인한다. Systematic generator matrix로부터 쉽게 도출되어지는 parity-check matrix를 통해서 인위적 오류의 수정을 위한 Decoding이 이루어진다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.5
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• pp.951-958
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• 2017

In an attack context, the adversary wants to retrieve the message from the intercepted noisy bit stream without any prior knowledge of the channel codes used. The process of finding out the code parameters such as code length, dimension, and generator, for this purpose, is called the blind recognition of channel codes or the reconstruction of channel codes. In this paper, we suggest an improved algorithm of the blind recovery of rate k/n convolutional encoders in a noisy environment. The suggested algorithm improves the existing algorithm by Marazin, et. al. by evaluating the threshold value through the estimation of the channel error probability of the BSC. By applying the soft decision method by Shaojing, et. al., we considerably enhance the success rate of the channel reconstruction.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2410-2413
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• 2005

Finite element method (FEM) has been widely used as a useful numerical method that can analyze complex engineering problems in electro-magnetics, mechanics, and others. CEMTool, which is similar to MATLAB, is a command style design and analyzing package for scientific and technological algorithm and a matrix based computation language. In this paper, we present new 3D FEM package in CEMTool environment. In contrast to the existing CEMTool 2D FEM package and MATLAB PDE (Partial Differential Equation) Toolbox, our proposed 3D FEM package can deal with complex 3D models, not a cross-section of 3D models. In the pre-processor of 3D FEM package, a new 3D mesh generating algorithm can make information on 3D Delaunay tetrahedral mesh elements for analyses of 3D FEM problems. The solver of the 3D FEM package offers three methods for solving the linear algebraic matrix equation, i.e., Gauss-Jordan elimination solver, Band solver, and Skyline solver. The post-processor visualizes the results for 3D FEM problems such as the deformed position and the stress. Consequently, with our new 3D FEM toolbox, we can analyze more diverse engineering problems which the existing CEMTool 2D FEM package or MATLAB PDE Toolbox can not solve.

• Research in Mathematical Education
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• v.8 no.2
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• pp.107-114
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• 2004

University teachers of linear algebra often feel annoyed and disarmed when faced with the inability of their students to cope with concepts that they consider to be very simple. Usually, they lay the blame on the impossibility for the students to use geometrical intuition or the lack of practice in basic logic and set theory. J.-L. Dorier [(2002): Teaching Linear Algebra at University. In: T. Li (Ed.), Proceedings of the International Congress of Mathematicians (Beijing: August 20-28, 2002), Vol. III: Invited Lectures (pp. 875-884). Beijing: Higher Education Press] mentioned that the situation could not be improved substantially with the teaching of Cartesian geometry or/and logic and set theory prior to the linear algebra. In East Asian countries, science-orientated mathematics curricula of the high schools consist of calculus with many other materials. To understand differential and integral calculus efficiently or for other reasons, students have to learn a lot of content (and concepts) in linear algebra, such as ordered pairs, n-tuple numbers, planar and spatial coordinates, vectors, polynomials, matrices, etc., from an early age. The content of linear algebra is spread out from grades 7 to 12. When the high school teachers teach the content of linear algebra, however, they do not concern much about the concepts of content. With small effort, teachers can help the students to build concepts of vocabularies and languages of linear algebra.

• School Mathematics
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• v.12 no.3
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• pp.323-335
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• 2010

Linear algebra is not only applied comprehensively in the branches of mathematics such as algebra, analytics, and geometry but also utilized for finding solutions in various fields such as aeronautical engineering, electronics, biology, geology, mechanics and etc. Therefore, linear algebra should be easy and comfortable for not only mathematics majors but also for general students as well. However, most find it difficult to learn linear algebra. Why is it so? It is because many studying linear algebra fail to achieve a correct understanding or attain erroneous concepts through misleading knowledge they already have. Such cases cause learning disability and mistakes. This research suggests more effective method of teaching by analyzing difficulty and errors made in learning system of linear equations.