• Communications of the Korean Mathematical Society
• /
• v.16 no.4
• /
• pp.621-626
• /
• 2001

Let { $A_{>o}$ t= exp(M log t)} $_{t}$ be a dilation group where M is a real n$\times$n matrix whose eigenvalues has strictly positive real part, and let $\rho$be an $A_{t}$ -homogeneous distance function defined on ( $R^{n}$ ). Suppose that K is a function defined on ( $R^{n}$ ) such that /K(x)/$\leq$ (No Abstract.see full/text) for a decreasing function defined on (t) on R+ satisfying where wo(x)=│log│log (x)ll. For f$\in$ $L_{1}$ ( $R^{n}$ ), define f(x)=sup t>0 Kt*f(x)=t-v K(Al/tx) and v is the trace of M. Then we show that \ulcorner is a bounded operator of $L_{-{1}( $R^{n}$ ) into $L^1$,$\infty$( $R^{n}$).

• Journal of the Korean Institute of Telematics and Electronics C
• /
• v.35C no.5
• /
• pp.11-16
• /
• 1998

We analyze the software reliability growth models for the specified period from the viewpoint of theory of differential equations. we defien a genralized form of reliability growth models as follws: dN(t)/dt = b(t)f(N(t)), Where N(t) is the number of remaining faults and b(t) is the failure rate per software fault at time t. We show that the well-known three software reliability growth models - Goel - Okumoto, s-shaped, and Musa-Okumoto model- are special cases of the generalized form. We, also, extend the generalized form into an extended form being dN(t)/dt = b(t, .gamma.)f(N(t)), The genneralized form can be obtained if the distribution of failures is given. The extended form can be used to describe a software reliabilit growth model having weibull density function as a fault exposure rate. As an application of the generalized form, we classify three mentioned models according to the forms of b(t) and f(N(t)). Also, we present a case study applying the generalized form.

• Korean Journal of Mathematics
• /
• v.14 no.1
• /
• pp.1-5
• /
• 2006

We will introduce tensor product spectrums on the tensor product spaces. And we will show that ${\sigma}[P(T_1,T_2,{\ldots},T_n)]=P[({\sigma}(T_1),{\sigma}(T_2){\ldots},{\sigma}(T_n)]={\sigma}(T_1,T_2{\ldots},T_n)$.

• 한국생물공학회:학술대회논문집
• /
• 2003.04a
• /
• pp.343-347
• /
• 2003

Power of loess ball on nitrogen and phosphorous removal in wastewater treatment were investigated. flow line A ( anaerobic${\rightarrow}$oxic${\rightarrow}$anoxic(organic source methanol)${\rightarrow}$p-absorption) showed the results of T-P 0.5, T-N 1.0, and COD 10ppm bellow, and flow line B ( oxic${\rightarrow}$anoxic, organic source: methanol${\rightarrow}$p-absorption) showed the results of T-P 0.3, T-N 5.0, and COD 15 ppm bellow. flow line C ( anaerobic${\rightarrow}$oxic${\rightarrow}$anoxic, organic source: wastewater ${\rightarrow}$ p-absorption) showed the results of T-P 0.6, T-N 10, and COD 15 ppm bellow, and flow line D ( oxic${\rightarrow}$anoxic, organic source: methanol${\rightarrow}$p-absorption) showed the results of T-P 1, T-N 8m, and COD 20 ppm bellow. So the results of these experiments showed the probability of loess ball in wastewater treatment.

• Journal of applied mathematics & informatics
• /
• v.30 no.1_2
• /
• pp.289-304
• /
• 2012

In this paper, we study asymptotic behaviour of solutions of the following higher order nonlinear dynamic equations $$S_n^{\Delta}(t,x)+{\delta}p(t)f(x(g(t)))=0$$ and $$S_n^{\Delta}(t,x)+{\delta}p(t)f(x(h(t)))=0$$ on an arbitrary time scale $\mathbb{T}$ with sup $\mathbb{T}={\infty}$, where n is a positive integer, ${\delta}=1$ or -1 and $$S_k(t,x)=\{\array x(t),\;if\;k=0,\\a_k(t)S_{{\kappa}-1}^{\Delta}(t),\;if\;1{\leq}k{\leq}n-1,\\a_n(t)[S_{{\kappa}-1}^{\Delta}(t)]^{\alpha},\;if\;k=n,$$ with ${\alpha}$ being a quotient of two odd positive integers and every $a_k$ ($1{\leq}k{\leq}n$) being positive rd-continuous function. We obtain some sufficient conditions for the equivalence of the oscillation of the above equations.

• Journal of KIISE:Computer Systems and Theory
• /
• v.26 no.11
• /
• pp.1344-1352
• /
• 1999

본 논문에서는 두 단순 다각형의 교차 영역을 구하는 문제를 재구성메쉬(RMESH) 상에서 상수 시간에 해결하는 두 개의 알고리즘을 제시한다. 먼저, 두 다각형이 모두 볼록 다각형일 때, N$\times$N RMESH에서 상수 시간에 교차 영역을 구하는 알고리즘을 제시한다, 여기서 N은 두 다각형의 정점의 개수의 합이다. 그리고, 두 일반적인 단순 다각형의 교차 영역을 구하는 문제에 대해서 (N+T)$\times$(N+T)2 RMESH에서 수행되는 상수 시간 알고리즘을 제시한다, 여기서 T는 최악의 경우 두 다각형의 경계선 상의 교차점의 개수로서 두 다각형의 정점의 개수가 각각 n과 m일 때 n.m에 해당한다. 두 다각형 중 하나가 볼록 다각형인 경우는 T = 2.max{n, m}이다. 이 알고리즘은 두 다각형의 모든 교차 영역 조각들을 구한 후 RMESH의 0번째 열에 차례로 배치해 준다. Abstract In this paper, we consider two constant time algorithms for polygon intersection problems on a reconfigurable mesh(in short, RMESH). First, we present a constant time algorithm for computing the intersection of two convex polygons on an N$\times$N RMESH, where N is the total number of vertices in both polygons. Second, we present a constant time algorithm for computing the intersection of two simple polygons on an (N+T)$\times$(N+T)2 RMESH, where T is the worstcase number of intersection points between the boundaries of them. T = n m, where n and m are the numbers of vertices of two polygons respectively. If either of them is convex, then T = 2 max{n,m}. The algorithm computes the intersection of them, and then arranges each intersection component onto the 0-th column of the mesh.

• Journal of applied mathematics & informatics
• /
• v.14 no.1_2
• /
• pp.39-49
• /
• 2004

Let G be a simple graph and let $\={G}$ denotes its complement. We say that G is integral if its spectrum consists entirely of integers. If $\overline{aK_{a}\;{\bigcup}\;{\beta}K_{b}}$ is integral we show that it belongs to the class of integral graphs $[\frac{kt}{\tau}\;{x_0}\;+\;\frac{mt}{\tau}\;z}\;K_{(t+{\ell}n)+{\ell}m}\;\bigcup\;[\frac{kt}{\tau}\;{y_0}\;+\;\frac{(t\;+\;{\ell}n)k\;+\;{\ell}m}{\tau}\;z]n\;K_{em)$, where (i) t, k, $\ell$, m, $n\;\in\;\mathbb{N}$ such that (m, n) = 1, (n,t) = 1 and ($\ell,\;t$) = 1 ; (ii) $\tau\;=\;((t\;+\;{\ell}n)k\;+\;{\ell}m,\;mt)$ such that $\tau\;$\mid$kt$; (iii) ($x_0,\;y_0$) is a particular solution of the linear Diophantine equation $((t\;+\;{\ell}n)k\;+\;{\ell}m)x\;-\;(mt)y\;=\;\tau\;and\;(iv)\;z\;{\geq}\;{z_0}$ where $z_{0}$ is the least integer such that $(\frac{kt}{\tau}\;{x_0}\;+\;\frac{mt}{\tau}\;{z_0})\;\geq\;1\;and\;(\frac{kt}{\tau}\;{y_0}\;+\;\frac{(t+{\ell}n)k+{\ell}m}{\tau}\;{z_0})\;\geq\;1$.

• Bulletin of the Korean Mathematical Society
• /
• v.36 no.1
• /
• pp.63-78
• /
• 1999

Let $\mu$(x) be an increasing function on the real line with finite moments of all oeders. We show that for any linear operator T on the space of polynomials and any interger n $\geq$ 0, there is a constant $\gamma n(T)\geq0$, independent of p(x), such that $\parallel T_p\parallel\leq\gamma n(T)\parallel P\parallel$, for any polynomial p(x) of degree $\leq$ n, where We find a formular for the best possible value $\Gamma_n(T)\;of\;\gamma n(T)$ and estimations for $\Gamma_n(T)$. We also give several illustrating examples when T is a differentiation or a difference operator and $d\mu$(x) is an orthogonalizing measure for classical or discrete orthogonal polynomials.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.12 no.5
• /
• pp.129-139
• /
• 2012

Given digraph network $D=(N,A),n{\in}N,a=c(u,v){\in}A$ with source s and sink t, the maximum flow from s to t is determined by cut (S, T) that splits N to $s{\in}S$ and $t{\in}T$ disjoint sets with minimum cut value. The Ford-Fulkerson (F-F) algorithm with time complexity $O(NA^2)$ has been well known to this problem. The F-F algorithm finds all possible augmenting paths from s to t with residual capacity arcs and determines bottleneck arc that has a minimum residual capacity among the paths. After completion of algorithm, you should be determine the minimum cut by combination of bottleneck arcs. This paper suggests maximum adjacency merging and compute cut value method is called by MA-merging algorithm. We start the initial value to S={s}, T={t}, Then we select the maximum capacity $_{max}c(u,v)$ in the graph and merge to adjacent set S or T. Finally, we compute cut value of S or T. This algorithm runs n-1 times. We experiment Ford-Fulkerson and MA-merging algorithm for various 8 digraph. As a results, MA-merging algorithm can be finds minimum cut during the n-1 running times with time complexity O(N).

• Journal of Korean Society for Quality Management
• /
• v.26 no.3
• /
• pp.71-81
• /
• 1998

In reliability analysis, the time difference between the expected next failure time and the current failure time or the Mean Time Between Failure(MTBF) is of significant interest. Until recently, in reliability growth studies, the reciprocal of the intensity function at current failure time has been used as being equal to MTBE($t_n$)at the n-th failure time $t_n$. That is MTBF($t_n$)=l/$\lambda (t_n)$. However, such a relationship is only true for Homogeneous Poisson Process(HPP). Tsokos(1995) obtained the upper bound and lower bound for the MTBF($t_n$) and proposed an estimator for the MTBF($t_n$) as the mean of the two bounds. In this paper, we provide the estimator for the MTBF($t_n$) which does not depend on the value of the shape parameter. The result of the Monte Carlo simulation shows that the proposed estimator has better efficiency than Tsokos's estimator.