• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2009년도 추계학술대회 논문집
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• pp.677-678
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• 2009

• 국제학술발표논문집
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• The 10th International Conference on Construction Engineering and Project Management
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• pp.1310-1310
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• 2024

• 한국방사성폐기물학회:학술대회논문집
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• 한국방사성폐기물학회 2005년도 추계 학술대회 논문집
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• pp.25-31
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• 2005

원자력연구시설에 대한 해체비용 산정은 해체계획 수립하는 데 중요한 작업이다. 해체비용 산정은 해체활동 단계와 해체 시설의 구설요소에 맞게 해체작업을 분류하여 계산을 해야 한다. 본 논문에서는 원자력연구시렁 해체비용 산정을 위하여 해체작업 활동을 분류하고 비용자료의 기준이 되는 비용항목을 계층적으로 세분화하여 구성하는 방법과 작업지연을 유발하는 비용영향 요인인 작업 난이도 인자에 대한 산출방법을 마련하였다. 이렇게 함으로써 해체활동 단계 및 작업에 대한 비용 항목별 분류 및 산정이 가능할 뿐만 아니라 원자력연구시설 해체비용 산정 방법론 및 프로그램을 개발하는데 활용할 예정이다.

• 품질경영학회지
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• 제42권4호
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• pp.747-756
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• 2014

Purpose: The purpose of this study is to apply the Bayesian estimation methodology for producing 'Korean Standard -Quality Excellence Index' model and prove the effectiveness of the new approach based on survey data by comparing the current index with the new index produced by Bayesian estimation method. Methods: The 'Korean Standard -Quality Excellence Index' was produced through the collected survey data by Bayesian estimation method and comparing the deviation with two results for confirming the effectiveness of suggested application. Results: The statistical analysis result shows that suggested estimator, that is, empirical Bayes estimator improves the effectiveness of the index with regard to reduce the error under specific loss function, which is suggested for checking the goodness of fit. Conclusion: Considering the Bayesian techniques such as empirical Bayes estimator for producing the quality excellence index reduces the error for estimating the parameter of interest and furthermore various Bayesian perspective approaches seems to be meaningful for producing the corresponding index.

• 경영과정보연구
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• 제7권
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• pp.427-450
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• 2001

This research suggests the estimation methodology of Logistics. This paper elucidates the main problems associated with estimation in the regression model. We review the methods for estimating the parameters in the model and introduce a modified procedure in which all models are fitted and combined to construct a combination of estimates. The resulting estimators are found to be as efficient as the maximum likelihood (ML) estimators in various cases. Our method requires more computations but has an advantage for large data sets. Also, it enables to detect particular features in the data structure. Examples of real data are used to illustrate the properties of the estimators. The backgrounds of estimation of logistic regression model is the increasing logistic environment importance today. In the first phase, we conduct an exploratory study to discuss 9 independent variables. In the second phase, we try to find the fittest logistic regression model. In the third phase, we calculate the logistic estimation using logistic regression model. The parameters of logistic regression model were estimated using ordinary least squares regression. The standard assumptions of OLS estimation were tested. The calculated value of the F-statistics for the logistic regression model is significant at the 5% level. The logistic regression model also explains a significant amount of variance in the dependent variable. The parameter estimates of the logistic regression model with t-statistics in parentheses are presented in Table. The object of this paper is to find the best logistic regression model to estimate the comparative accurate logistics.

• 전기학회논문지P
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• 제58권3호
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• pp.241-248
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• 2009

This paper presents stochastic methodology based fault detection algorithm for induction motor systems. We measure current of healthy induction motors by means of hall sensor systems and then establish its probability distribution. We propose online probability density estimation which is effective in real-time implementation due to its simplicity and low computational burden. In addition, we accomplish theoretical analysis of the proposed estimation to demonstrate its convergence property by using statistical convergence and system stability theories. We apply our fault detection approach to three-phase induction motors and achieve real-time experiment for evaluating its reliability and practicability in industrial fields.

• 한국자동차공학회논문집
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• 제11권5호
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• pp.1-6
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• 2003

The torque is an important measure that represents the performance of a particular engine. Furthermore the information of engine torque can be used as a primary feedback parameter in modem engine management system. In this paper, a methodology is proposed for torque estimation of SI-engine. Since the proposed method uses cylinder pressure sensor, the torque can be estimated in a simple manner. The indicated torque is estimated from the peak pressure and its location, and the load torque is observed by the state observer based on the estimated indicated torque. The proposed method is accurate and robust against the variations that affect the torque production such as spark timing, mass air flow and others. This torque estimation method may be an alternative solution to the use of engine torque maps in a modem torque-based engine management system.

• Communications for Statistical Applications and Methods
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• 제11권1호
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• pp.79-91
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• 2004

In this thesis, Bayesian parameter estimation procedure is discussed for the mean change model of multivariate normal random variates under the assumption of noninformative priors for all the parameters. Parameters are estimated by Gibbs sampling method. In Gibbs sampler, the change point parameter is generated by Metropolis-Hastings algorithm. We apply our methodology to numerical data to examine it.

• 대한안전경영과학회지
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• 제20권2호
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• pp.37-44
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• 2018

The Location Based Service is growing rapidly nowadays due to the universalization of the use for smartphone, and therefore the location determination technology has been placed in a very important position. This study suggests an algorithm that can provide the estimate of users' location by using smartphone sensors. And in doing so we will propose a methodology for the creation and update of indoor map through the more accurate position estimation using smartphone sensors such as acceleration sensor, gyroscope sensor, geomagnetic sensor and rotation sensor.

• Journal of the Korean Data and Information Science Society
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• 제26권3호
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• pp.755-762
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• 2015

One of the main objectives of the U.S. Census Bureau is the proper estimation of median household income for small areas. These estimates have an important role in the formulation of various governmental decisions and policies. Since direct survey estimates are available annually for each state or county, it is desirable to exploit the longitudinal trend in income observations in the estimation procedure. In this study, we consider Fay-Herriot type small area models which include time-specific random effect to accommodate any unspecified time varying income pattern. Analysis is carried out in a hierarchical Bayesian framework using Markov chain Monte Carlo methodology. We have evaluated our estimates by comparing those with the corresponding census estimates of 1999 using some commonly used comparison measures. It turns out that among three types of time-specific random effects the small area model with a time series random walk component provides estimates which are superior to both direct estimates and the Census Bureau estimates.