• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.4
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• pp.327-335
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• 2019

This study develops a prediction model for toilet and laundry water end-uses based on surveyed data which measured housing and household characteristics of 140 households over 5 years in Korea. Classical regression model assuming a normal distribution was not appropriate and estimated parameters were biased, because the distribution of measured water-uses was left-skewed. As an alternative to this problem, we considered the distribution of weibull and lognormal for each water-uses, and three regression models were compared using log-likelihood and scale parameter. As a result, weibull regression were chosen to be appropriate for both water-uses and also presented the factors that affect each water-use. This results expect that an insight is provided on water resources utilization and theoretical support role for effective water resource management.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.7
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• pp.2159-2166
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• 1996

The stochastic properties of variation in fatigue crack growth are important in reliability and stability of structures. In this study,the stochastic model for the variation of fatigue crack growth rate was proposed in consideration of nonhomogeneity of materials. For this model, experiments were ocnducted on 7075-T6 aluminum alloy under the constant stress intensity factor range. The variation of fatigue crack growth rate was expressed by random variables Z and r based on the variation of material coefficients C and m in the paris-Erodogan's equation. The distribution of fatigue life with respect to the stress intensity factor range was evaluated by the stochastic Markov chain model based on the Paris-Erdogan's equation. The merit of proposed model is that only a small number of test are required to determine this this function, and fatigue crack growth life is easily predicted at the given stress intensity factor range.

• The Korean Journal of Applied Statistics
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• v.24 no.4
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• pp.567-573
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• 2011

This study develops a predictive model for household water end-uses based on data that have measured household characteristics, housing characteristics and other items, surveyed over 3 years in Korea. However, the measured data was left-skewed and it was not fitted to normal distribution. The parameter estimate were biased when using a multiple regression model. In addition, the results of the testing for the model were usually of significance due to the tiny residual from a large number of observations. In order to solve the problem, we suggested log-normal regression model and Weibull regression model as alternatives. The results of this study can be utilized in the planning stages of water and waste water facilities.

• Convergence Security Journal
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• v.6 no.3
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• pp.117-126
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• 2006

Bayesian inference and model selection method for software reliability growth models are studied. Software reliability growth models are used in testing stages of software development to model the error content and time intervals between software failures. In this paper, could avoid multiple integration using Gibbs sampling, which is a kind of Markov Chain Monte Carlo method to compute the posterior distribution. Bayesian inference for general order statistics models in software reliability with diffuse prior information and model selection method are studied. For model determination and selection, explored goodness of fit (the error sum of squares), trend tests. The methodology developed in this paper is exemplified with a software reliability random data set introduced by of Weibull distribution(shape 2 & scale 5) of Minitab (version 14) statistical package.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.6
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• pp.1997-2003
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• 2010

Mean Residual Life (MRL) function plays a very important role in the area of engineering, medical science, survival studies, social sciences, and many other fields. Specially, in the reliability study of technical systems, the MRL estimation of a component is very important because the sudden stop of a system brings a serious problem. So, many simulation studies of MRL estimation have been done considering various situation variables. In this paper, four estimators of MRL are proposed under random censoring and their performances re compared through bias and Mean Square Error (MSE) by Monte Carlo simulation.

• Korean journal of applied entomology
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• v.55 no.2
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• pp.119-128
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• 2016

This study was conducted to develop temperature-driven models for a population model of turnip aphid, Lipaphis erysimi: nymphal development rate models and apterious adult's oviposition (larviparous) model. Nymphal development and the longevity and fecundity of adults were examined on cabbage at six constant temperatures (10, 15, 20, 25, 30, $35{\pm}1^{\circ}C$, 16L:8D). L. erysimi nymphs did not survive at $10^{\circ}C$. Development time of nymphs increased with increasing temperature up to $30^{\circ}C$ and thereafter slightly decreased, ranging from 18.5 d at $15^{\circ}C$ to 5.9 d at $30^{\circ}C$. The lower threshold temperature and thermal constant were estimated as $7.9^{\circ}C$ and 126.3 degree days, respectively. The nonlinear model of Lactin 2 fitted well for the relationship between the development rate and temperature of small (1+2 instar), large (3+4 instar) and total nymph (all instars). The Weibull function provided a good fit for the distribution of development times of each stage. Temperature affected the longevity and fecundity of L. erysimi. Adult longevity decreased as the temperature increased and ranged from 24.4 d at $20^{\circ}C$ to 16.4 d at $30.0^{\circ}C$ with abnormal longevity 18.2 d at $15^{\circ}C$, which was used to estimate adult aging rate model for the calculation of adult physiological age. L. erysimi showed a maximum fecundity of 91.6 eggs per female at $20^{\circ}C$. In this study, we provided three temperature-dependent components for an oviposition model of L. erysimi: total fecundity, age-specific cumulative oviposition rate, and age-specific survival rate.