• 대한수학회보
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• 제45권3호
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• pp.427-435
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• 2008

In this paper we consider the problem of whether certain homogeneous or non-homogeneous differential polynomials in f(z) necessarily have infinitely many zeros. Particularly, this extends a result of Gopalakrishna and Bhoosnurmath [3, Theorem 2] for a general differential polynomial of degree $\bar{d}$(P) and lower degree $\underline{d}$(P).

• 한국산학기술학회논문지
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• 제7권6호
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• pp.1421-1424
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• 2006

본 논문은 맨델브로트 집합을 9차 복소 다항식에 확장시켜 새로운 프랙탈 도형을 나타내는 9차 분기집합을 정의하고, 2주기 성분의 경계방정식을 매개함수로 표현한다. 또한, 2주기 성분을 작도하는 알고리즘을 고안하고, 매스매티카를 활용하여 2주기 성분의 기하학적 구조에 관한 결과를 제시하고자 한다.

• East Asian mathematical journal
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• 제28권5호
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• pp.605-615
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• 2012

In this paper, we show that any definite lattice over $\mathbb{F}_q[x]$ is universal if and only if it is quaternary and its discriminant is of degree 2, where $ch(\mathbb{F}_q){\neq}2$. The Four Conjecture follows as an immediate consequence.

• 대한수학회보
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• 제50권3호
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• pp.929-934
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• 2013

In this short note we discuss degrees of twisted Alexander polynomials and demonstrate an explicit example of a closed 3-manifold which is related to the degree formula due to Friedl, Kim and Kitayama.

• 호남수학학술지
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• 제29권2호
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• pp.299-305
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• 2007

We prove that the bounded attracting basin of the origin for a complex homogeneous polynomial of degree larger than two is Carath$\'{e}$odory finitely compact.

• Communications for Statistical Applications and Methods
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• 제3권1호
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• pp.51-59
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• 1996

A measure that quantifies the amount of slope retatability for the second degree Scheffe polynomial model for mixture experiments is proposed and used to compare the several mixture designs which met the symmetric momemts conditions in this article.

• 한국광학회:학술대회논문집
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• 한국광학회 1988년도 광학 및 양자전자학 워크샵
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• pp.68-75
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• 1988

The imporance and technique of sudtrating the background intensity of the interferogram in digital interferometry is discussed. Also the way of determinating the polynomial and its degree to fit the wavefront is discussed.

• 한국컴퓨터정보학회논문지
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• 제18권11호
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• pp.159-165
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• 2013

본 논문은 NP-완전 문제인 간선 색칠과 그래프 부류 결정 문제를 동시에 해결하는 O(E)의 다항시간 알고리즘을 제안하였다. 제안된 알고리즘은 최대차수-최소차수 정점 쌍 간선을 단순히 선택하는 방법으로 간선 채색수 ${\chi}^{\prime}(G)$를 결정하였다. 결정된 ${\chi}^{\prime}(G)$는 ${\Delta}(G)$ 또는 ${\Delta}(G)+1$을 얻는다. 결국, 알고리즘 수행 결과 얻은 ${\chi}^{\prime}(G)$로부터 ${\chi}^{\prime}(G)={\Delta}(G)$이면 부류 1, ${\chi}^{\prime}(G)={\Delta}(G)+1$이면 부류 2로 분류할 수 있다. 또한, 미해결 문제로 알려진 "최대차수가 6인 단순, 평면 그래프는 부류 1이다."라는 Vizing의 평면 그래프 추정도 증명하였다.

• Journal of Information Processing Systems
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• 제10권3호
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• pp.395-411
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• 2014

Temporal medical data is often collected during patient treatments that require personal analysis. Each observation recorded in the temporal medical data is associated with measurements and time treatments. A major problem in the analysis of temporal medical data are the missing values that are caused, for example, by patients dropping out of a study before completion. Therefore, the imputation of missing data is an important step during pre-processing and can provide useful information before the data is mined. For each patient and each variable, this imputation replaces the missing data with a value drawn from an estimated distribution of that variable. In this paper, we propose a new method, called Newton's finite divided difference polynomial interpolation with condition order degree, for dealing with missing values in temporal medical data related to obesity. We compared the new imputation method with three existing subspace estimation techniques, including the k-nearest neighbor, local least squares, and natural cubic spline approaches. The performance of each approach was then evaluated by using the normalized root mean square error and the statistically significant test results. The experimental results have demonstrated that the proposed method provides the best fit with the smallest error and is more accurate than the other methods.

• Journal of the Korean Statistical Society
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• 제7권1호
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• pp.3-10
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• 1978

Let $X_i,...,X_n$ be a random sample from a distribution with cumulants $K_1, K_2,...$. The statistic $t = \frac{\sqrt{x}(\bar{X}-K_1)}{S}$ has the well-known 'student' distribution with $\nu = n-1$ degrees of freedom if the $X_i$ are normally distributed (i.e., $K_i = 0$ for $i \geq 3$). An Edgeworth series expansion for the distribution of t when the $X_i$ are not normally distributed is obtained. The form of this expansion is Prob $(t