• 대한수학회지
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• 제47권5호
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• pp.947-965
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• 2010

The main purpose of this paper is using estimates for character sums and analytic methods to study the mean value involving the incomplete character sums, 2-th power mean of the inversion of Dirichlet L-function and general Kloosterman sums, and give four interesting asymptotic formulae for it.

• 대한수학회보
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• 제33권3호
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• pp.329-334
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• 1996

The notion of approximate derivative was introduced by Denjoy in 1916 [3]. Khintchine [5] proved that Rolle's theorem holds for approximate derivatives and Tolstoff [8] proved that every approximate derivative is of Baire class 1 and has Darboux property. Goffman and Neugebauer [4] proved the above results of Tolstoff [8] in a different and simplified method. Also they [4] proved indirectly (via Darboux property) that approximate derivatives possess mean value property.

• 대한기계학회논문집
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• 제12권3호
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• pp.599-606
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• 1988

본 연구에서는 공기와 물을 사용한 근사수평 반류성층유동에서의 계면파 구조 를 측정하였다. 3차원파 영역내의 유동조건하에서 탐침접촉법을 이용하여 계면파의 액막분포도를 구하였으며 Gauss 모델과 비교분석하였다. 또 이 분포도에서 파의 구 조와 관련된 통계치, 즉 평균액막두께, 파진폭, 파고 교란강도등을 계산하여 유동조건 에 따른 경향을 분석하였다. 본 연구와 병행하여 계면전단응력과 계면마찰계수에 관 한 실험을 수행하였는데 이 결과와 계면파 구조와의 상호연관성도 고찰하였다.

• 품질경영학회지
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• 제38권4호
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• pp.540-548
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• 2010

We consider the problem of selecting the most profitable initial process mean and length of production cycle for manufacturing processes subject to a constant linear trend during the same cycle that varies after resetting the processes. Assuming that the quality characteristic of interest is normally distributed, the optimum initial process mean and the length of production cycle are jointly obtained by minimizing the expected loss per unit time. We assume that the quality loss function due to the deviation from the target value is quadratic and resetting loss is constant. We consider both cases of symmetric and asymmetric quality loss function. An illustrative example is given and sensitivity analysis performed.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 학술대회 논문집 전문대학교육위원
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• pp.159-162
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• 2006

In this paper energy distribution function in $SiH_4$ has been analysed over the E/N range 0.5${\sim}$300Td and Pressure value 0.5, 1.0, 2.5 Torr by a two-term approximation Boltzmann equation method and by a Monte Carlo simulation. The motion has been calculated to give swarm parameters for the electron drift velocity, diffusion coefficient, electron ionization, mean energy and the electron energy distribution function. The electron energy distribution function has been analysed in $SiH_4$ at E/N=30, 50Td for a case of the equilibrium region in the mean electron energy and respective set of electron collision cross sections. The results show that the deduced electron drift velocities, the electron ionization or attachment coefficients, longitudinal and transverse diffusion coefficients and mean energy agree reasonably well with theoretical for a rang of E/N values.

• 대한수학회보
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• 제54권6호
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• pp.1981-1990
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• 2017

Let R be a root system in $\mathbb{R}^d$ with Coxeter-Weyl group W and let k be a nonnegative multiplicity function on R. The generalized volume mean of a function $f{\in}L^1_{loc}(\mathbb{R}^d,m_k)$, with $m_k$ the measure given by $dmk(x):={\omega}_k(x)dx:=\prod_{{\alpha}{\in}R}{\mid}{\langle}{\alpha},x{\rangle}{\mid}^{k({\alpha})}dx$, is defined by: ${\forall}x{\in}\mathbb{R}^d$, ${\forall}r$ > 0, $M^r_B(f)(x):=\frac{1}{m_k[B(0,r)]}\int_{\mathbb{R}^d}f(y)h_k(r,x,y){\omega}_k(y)dy$, where $h_k(r,x,{\cdot})$ is a compactly supported nonnegative explicit measurable function depending on R and k. In this paper, we prove that for almost every $x{\in}\mathbb{R}^d$, $lim_{r{\rightarrow}0}M^r_B(f)(x)= f(x)$.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1997년도 추계학술대회 논문집
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• pp.450-453
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• 1997

There are many studies about optimization using genetic algorithm and desirability function. It's very important to find the optimal value of something like response surface or regression model. In this study I ind~cate the problem using the old type desirability function, and suggest the new type desirabhty functton that can fix the problem better, and simulate the model. Then I'll suggest the form of desirability function to find the optimum value of response surfaces which are made by mean and standard deviation using genetic algorithm and new type desirability function.

• 응용통계연구
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• 제21권5호
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• pp.835-843
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• 2008

In this paper, we investigate a Bayesian inference for software reliability models based on mean value functions which take the form of the mixture of beta distribution functions. The posterior simulation via the Markov chain Monte Carlo approach is used to produce estimates of posterior properties. Its applicability is illustrated with two real data sets. We compute the predictive distribution and the marginal likelihood of various models to compare the performance of them. The model comparison results show that the model based on the beta-mixture performs better than other models.

• 품질경영학회지
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• 제26권3호
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• pp.141-149
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• 1998

It is of great practical interest to decide when to stop testing a software system in the development phase and transfer it to the user. This decision problemcalled an optimal software release one is discussed to specify the a, pp.opriate release time. In almost all studies, the software reliability models used are nonphomogenous Poisson process(NHPP) model with bounded mean value function. HNPP models with unbounded mean value function are more suitable in practice because of the possibility of introducing new faults when correcting or modifying the software. We discuss optimal software release policies which minimize a total average software cost under the constraint of satisfying a software reliability requirement. A numerical example illustrates the results.

• 경영과학
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• 제15권1호
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• pp.33-47
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• 1998

The facility location problem considered here is to determine facility location sites under future's uncertain demand. The objective of this paper is to propose a solution method and algorithm for a two-stage stochastic facility location problem. utilizing the Benders decomposition method. As a two-stage stochastic facility location problem is a large-scale and complex to solve, it is usually attempted to use a mean value problem rather than using a stochastic problem. Thus, the other objective is to study the relative error of objective function values between a stochastic problem and a mean value problem. The simulation result shows that the relative error of objective function values between two problems is relatively small, when a feasibility constraint is added to a facility location model.