• 근관절건강학회지
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• 제6권1호
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• pp.136-152
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• 1999

The purposes of this study were to identify the prevalence of fatigue. and factors influencing fatigue in women with rheumatoid arthritis. The subjects were 124 patients with rheumatoid arthritis. Most of all patients felt fatigue and mean score measured by Multidimensional Assessment of Fatigue was relatirely high. Fatigue was positively correlated with pain intensity, the number of pain sites, functional disability, depression. and sleep quality. A hierachical regression model was used to determine the variance which accounts for fatigue. Pain intensity, depression. sleep quality accounted for fatigue significantly. This finding indicates that pain influences fatigue through depression and sleep quality ; depression through sleep quality. The causative factors could be identified by further study of structural eqation model.

• 대한수학회지
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• 제43권2호
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• pp.357-371
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• 2006

Let $X\;=\;(X_t,\;t{\in}[0, T])$ be a generalized Brownian motion(gBm) determined by mean function a(t) and variance function b(t). Let $L^2({\mu})$ denote the Hilbert space of square integrable functionals of $X\;=\;(X_t - a(t),\; t {in} [0, T])$. In this paper we consider a class of nonlinear functionals of X of the form F(. + a) with $F{in}L^2({\mu})$ and discuss their analysis. Firstly, it is shown that such functionals do not enjoy, in general, the square integrability and Malliavin differentiability. Secondly, we establish regularity conditions on F for which F(.+ a) is in $L^2({\mu})$ and has its Malliavin derivative. Finally we apply these results to compute the price and the hedging portfolio of a contingent claim in our financial market model based on a gBm X.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 추계학술대회 논문집 전력기술부문
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• pp.393-395
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• 2006

In competitive market, it is important to establish a plan of transmission expansion considering uncertainty of future generation and load behavior. For this reason, revised transmission expansion model is proposed in this paper. In the proposed model, information of predictable future condition are included in a cost function of transmission expansion investment. Also, to reduce risk of the investment, mean-variance Markowitz approach is added to the objective function of cost. By optimization programming, the most robust and the minimum cost plan can be obtained.

• Journal of the Korean Data and Information Science Society
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• 제26권1호
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• pp.271-280
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• 2015

In this paper, the maximum likelihood estimators for parameters are derived under three step-stress accelerated life tests for Type-I hybrid censored data. The exponential distribution and the cumulative exposure model are considered based on the assumption that a log quadratic relationship exits between stress and the mean lifetime ${\theta}$. The test plan to search optimal stress change times minimizing the asymptotic variance of maximum likelihood estimators are presented. A numerical example to illustrate the proposed inferential procedures and some simulation results to investigate the sensitivity of the optimal stress change times by the guessed parameters are given.

• 대한교통학회지
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• 제9권1호
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• pp.47-56
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• 1991

With respect to stochastic delays at linked signals the solid quantitative information has not been available as yet. On the basis of field data the values of "I" (variance-mean ration of flow) were related with the rate of flow. The stochastic delays with specific "I" values were obtained from the distribution of overflow queue, which were calculated by the use of Markov chains. This examination of the results led to the derivation of a simple method for calculating stochastic dclays through the introduction of "I" into Miller's model. The good agreement was shown between the model and the field. The relationships between the cycle lengths and delays were examinated in a large number of conditions with regard to degree of saturation. signal split and link length. Within the practical range of cycle length uniform delays were dominant and no critical point was found in terms of minimum, delay. In highly saturated conditions however the weight of stochastic delay is noticeable.

• 대한산업공학회지
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• 제22권3호
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• pp.459-471
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• 1996

This paper considers ramp tests for exponential lifetime distribution when there are limitations on test stress and test time. The inverse power law and a cumulative exposure model are assumed. Maximum likelihood (ML) estimators of model parameters and their asymptotic covariance matrix are obtained. The optimum ramp test plans are also found which minimize the asymptotic variance of the ML estimator of the log mean life at design constant stress. For selected values of the design parameters, tables useful for finding optimal test plans are given. The effect of the pre-estimates of design parameters is studied.

• 품질경영학회지
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• 제30권4호
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• pp.106-119
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• 2002

The fatigue curve with estimated parameters represents the estimate of the median or mean life at a given applied stress But, in order to assist a designer in making decisions regarding the fatigue failure mode, it is common practice to construct a design curve on the lower or safe side of data. In this study, to overcome the limitations(i.e., no runout, equal variance, and quality of the approximation, etc) of Shen, Wirsching, and Cashman's method which suggested the approximate design curve for nonlinear models using tolerance interval constructed by Owen's method, an algorithm to find design curves under the fatigue model using a parametric bootstrap method, is proposed and illustrated with multiple fatigue data sets.

• 산업경영시스템학회지
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• 제36권1호
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• pp.36-43
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• 2013

Many retailer store managers are experiencing the situation where some customers balk at purchasing products if the stock is low. In this paper, we extend the single period newsvendor model in an environment of customer balking behavior occurring at double threshold inventory levels assuming the chance of sales during balking is a discrete function of inventory level. Our analysis is based on the assumption that only the mean and the variance of demand are known, without assuming any specific distributional form. We derive the explicit general expression of optimal order quantity with unknown distribution of demand with double threshold inventory levels of customer balking. Then, we illustrate the concepts developed here through simple numerical examples and conclude the future research topics under balking situation.

• 한국수학사학회지
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• 제35권1호
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• pp.1-18
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• 2022

This paper presents a statistical machine learning method that generates the implied volatility surface under the rareness of the market data. We apply the practitioner's Black-Scholes model and Gaussian process regression method to construct a Bayesian inference system with observed volatilities as a prior information and estimate the posterior distribution of the unobserved volatilities. The variance instead of the volatility is the target of the estimation, and the radial basis function is applied to the mean and kernel function of the Gaussian process regression. We present two types of Gaussian process regression methods and empirically analyze them.

• Computers and Concrete
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• 제32권6호
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• pp.607-613
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• 2023

The objective of this work is to determine the compressive strength of geopolymer concrete utilizing four distinct machine learning approaches. These techniques are known as gradient boosting machine (GBM), generalized linear model (GLM), extremely randomized trees (XRT), and deep learning (DL). Experimentation is performed to collect the data that is then utilized for training the models. Compressive strength is the response variable, whereas curing days, curing temperature, silica fume, and nanosilica concentration are the different input parameters that are taken into consideration. Several kinds of errors, including root mean square error (RMSE), coefficient of correlation (CC), variance account for (VAF), RMSE to observation's standard deviation ratio (RSR), and Nash-Sutcliffe effectiveness (NSE), were computed to determine the effectiveness of each algorithm. It was observed that, among all the models that were investigated, the GBM is the surrogate model that can predict the compressive strength of the geopolymer concrete with the highest degree of precision.