• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.354-357
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• 2013

The filtering algorithm is used very frequently in the preprocessing stage of many image processing algorithms in computer vision processing. Because video signals are two-dimensional signals, computaional complexity is very high. To reduce the complexity, separable filters and the factorization theorem is applied to the filtering operation. As a result, it is shown that a significant reduction in computational complexity is achieved, although the experimental results could be slightly different depending on the condition of the image.

• Communications of Mathematical Education
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• v.29 no.1
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• pp.111-130
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• 2015

The purpose of the study was to investigate the differences between two groups of students according to information recognition styles such as visual learners and linguistic learners. Two instructional methods, algeblocks and factorization formula, were utilized to introduce the factorization. Four students were participated for the study, and two of them were visual learners and the other two were linguistic learners based on learning style test. Interviews and the diagnostic tests were implemented before the instructions which were lasted for 6 sessions. After the instructions all the participants were interviewed and the researchers also interviewed them 5 days later. The results of the study were the followings: 1. All the participants regardless of their learning style revealed that algeblocks were helpful in understanding the factorization. 2. Visual learners were more likely using algeblocks, while the linguistic learners were more enthusiastic and proficient in using formula to solve the problems. 3. Five days later, two types of learning style students revealed different tendencies. Visual learners mainly used algeblocks, and linguistic learners were not enthusiastic about using algeblocks and one of them did not use them at all. 4. Five days later, two visual learners could not remember the formula, but linguistic learners could remember the formula in somewhat different level.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.5_6
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• pp.324-329
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• 2003

The public-key cryptosystems such as Diffie-Hellman Key Distribution and Elliptical Curve Cryptosystems are built on the basis of the operations defined in GF(2$^{m}$ ):addition, subtraction, multiplication and multiplicative inversion. It is important that these operations should be computed at high speed in order to implement these cryptosystems efficiently. Among those operations, as being the most time-consuming, multiplicative inversion has become the object of lots of investigation Formant's theorem says $\beta$$^{-1}$ =$\beta$$^{2}$sup m/-2/, where $\beta$$^{-1}$ is the multiplicative inverse of $\beta$$\in$GF(2$^{m}$ ). Therefore, to compute the multiplicative inverse of arbitrary elements of GF(2$^{m}$ ), it is most important to reduce the number of times of multiplication by decomposing 2$^{m}$ -2 efficiently. Among many algorithms relevant to the subject, the algorithm proposed by Itoh and Tsujii[2] has reduced the required number of times of multiplication to O(log m) by using normal basis. Furthermore, a few papers have presented algorithms improving the Itoh and Tsujii's. However they have some demerits such as complicated decomposition processes[3,5]. In this paper, in the case of 2$^{m}$ -2, which is mainly used in practical applications, an efficient algorithm is proposed for computing the multiplicative inverse at high speed by using both the factorization formula x$^3$-y$^3$=(x-y)(x$^2$＋xy＋y$^2$) and normal basis. The number of times of multiplication of the algorithm is smaller than that of the algorithm proposed by Itoh and Tsujii. Also the algorithm decomposes 2$^{m}$ -2 more simply than other proposed algorithms.

• East Asian mathematical journal
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• v.36 no.2
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• pp.291-315
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• 2020

In this study, the geometric model of 11 factorization formulas presented in the 2015 revised national curriculum was constructed and the necessary mathematical conditions were derived in the process. As a result of the study, all of the 11 factorization formulas are geometrically modeled and 12 conditions are derived in the process. However, the basic method of directly cutting and attaching a given shape was limited to not being able to make a rectangle or rectangular parallelepiped. Therefore, the problem was solved by changing the perspective and focusing on whether rectangle or rectangular parallelepiped with the same area or volume could be constructed.