• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.06a
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• pp.36-37
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• 2014

기존에 영상 내에 원형 검출 방법으로 가장 널리 사용되는 방법은 허프 변환에 기초한다. 허프 변환은 해석적 곡선의 각 점을 원의 중심 좌표와 반지름으로 매핑 시키는 과정을 포함한다. 이러한 과정은 실행시간을 매우 많이 필요로 하고 또한 응용에 따라서 최적인 원 근사화 방법을 찾는데 문제점을 야기하기도 한다. 본 논문에서는 원형 모양인 광 연결 소자 장치로 제한된 응용환경에 대해 원 검출을 빠른 속도로 탐색하는 방법과 최적인 원 근사화 방법을 제안한다. 제안한 방법은 에지 검출과 검출된 에지를 이용한 중심좌표 및 반지름 탐색 그리고 최적화된 원 근사화 방법으로 구성된다. 모의실험을 통하여 제안한 방법은 기존의 오픈라이브러리로 제공되는 OpenCV의 허프 변환에 의한 방법에 비해 원 검출 및 근사화 방법에 있어 성능을 개선할 수 있음을 보인다.

• Journal of the Chungcheong Mathematical Society
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• v.34 no.1
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• pp.1-15
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• 2021

In the recent papers, S'anchez-Reyes [Appl. Math. Model. 40 (2016), 1676-1682] described the method for finding a minimal surface through a geodesic, and Li et al. [Appl. Math. Model. 37 (2013), 6415-6424] studied the approximation of minimal surfaces with a geodesic from Dirichlet function. In the present article, we consider an isoparametric surface generated by Frenet frame of a curve introduced by Wang et al. [Comput. Aided Des. 36 (2004), 447-459], and give the necessary and sufficient condition to satisfy both geodesic of the curve and minimality of the surface. From this, we construct minimal surfaces in terms of constant curvature and torsion of the curve. As a result, we present a new approach for constructions of the minimal surfaces from a prescribed closed geodesic and unclosed geodesic, and show some new examples of minimal surfaces with a circle and a helix as a geodesic. Our approach can be used in design of minimal surfaces from geodesics.

• Communications of the Korean Mathematical Society
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• v.38 no.2
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• pp.431-450
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• 2023

The basic goal of quantization for probability distribution is to reduce the number of values, which is typically uncountable, describing a probability distribution to some finite set and thus to make an approximation of a continuous probability distribution by a discrete distribution. It has broad application in signal processing and data compression. In this paper, first we define the uniform distributions on different curves such as a line segment, a circle, and the boundary of an equilateral triangle. Then, we give the exact formulas to determine the optimal sets of n-means and the nth quantization errors for different values of n with respect to the uniform distributions defined on the curves. In each case, we further calculate the quantization dimension and show that it is equal to the dimension of the object; and the quantization coefficient exists as a finite positive number. This supports the well-known result of Bucklew and Wise [2], which says that for a Borel probability measure P with non-vanishing absolutely continuous part the quantization coefficient exists as a finite positive number.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.1
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• pp.36-41
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• 2011

Configuration space(C-space) including configuration obstacle(C-obstacle) is one of the most important concepts in mobile robot path planning. Using C-space and C-obstacles, the robot with different shapes and moving mechanisms can be considered as a point in the C-space. And, as a result, the collision-free path for the robot can be easily achieved. To make C-space including C-obstacle, many researchers used circular approximation method for the efficient caluculation time. This method can help us to save our time by approximating the shape of a robot as the minimum sized circle which can cover all the area of robot. But, by using the circle larger than the robot, more space are considered as the part of robot and, as a result, some obstacles which are very near each other may be considered as a combined one obstacle. To solve this problem, multi-level configuration space is proposed by this paper. This multi-level method also use the circular approximation method as the initial step. But, after finding the initial path, it will check how many obstacles are combined. And then, for each combined obstacle, more accurate C-space generation will be continued. To check the efficiency of the proposed algorithm, time for c-space generation are compared with the well-known accurate C-space generation method using various types of robot shape.

• Journal of Educational Research in Mathematics
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• v.27 no.4
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• pp.811-831
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• 2017

The purpose of this study is to analyze the contents of pi of Chosun-sanhak and organize the teaching and learning activities to help to understand the concept of pi deeply using the analysis results. The results of this study are as follows. First, Chosun-sanhak used various approximate values of pi and those were represented as the form to reveal the meaning of the ratio of radius and circumference. Second, There were the freedom of selection of the approximate values of pi suitably. Lastly, the enriched leaning about pi need to draw a distinction pi from approximate values of pi, choose the suitable approximate values of pi and compare the method of calculation of circumference and the area of circle of Chosun-sanhak and today's mathematics. In conclusion, I proposed several issues which is worth exploring further in relation to pi and Chosun-Sanhak.

• Journal of the Korean Data and Information Science Society
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• v.28 no.4
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• pp.831-841
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• 2017

The irrational number ${\pi}$ is defined as the ratio of circumference of a circle to its radius and always becomes constant. This article does Monte Carlo approximation of its value using the famous Buffon's needle experiment and shows that its convergence is not always proportional to the sample size. We also do Monte Carlo simulations to see the convergence of the computed ${\pi}$ values from the random walk series with independent normal increment. Finally we apply the theoretical derivation to various financial time series data such as KOSPI, stock prices of Korean big firms, global stock indices and major foreign exchange rates. The historical data shows that log transformed data random walk process but most of their first lagged data don't follow a normal distribution. More importantly the computed value from the ratio of the regression coefficient ${\pi}$ tend to converge a constant, unfortunately not ${\pi}$. Using this result we could doubt on the efficient market hypothesis, and relate the degree of the hypothesis with the amount of deviation of the estimated ${\pi}$ values.