• Journal of Korean Society for Quality Management
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• v.21 no.2
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• pp.71-84
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• 1993

Currently the problem of air pollution caused by the motor vehicle emission is one of the most serious problems to be solved. Thus we needed the vehicle emissions audit procedure and technical innovation constraining the motor vehicle emission. The Korean Environmental Protection Agency currently audits automobiles for emissions compliance at assembly plants with multiple attribute multiple staged sampling plans. In order to establish the more reasonable audit procedure, the multiple staged sampling plan designed in this paper has been applied to the domestic vehicles by analyzing the statistic characteristics of the emission distribution. This paper summarizes the auditing procedure and develops methods for determining its statistical characteristics. Specifically, we consider how to evaluate a multiple staged sampling plan, give a procedure that efficiently estimates attribute-type probabilities from multivariate variables-type data, and quantify the effect of tightening the acceptable quality level of the sampling plan. As a result it can be proved that this audit procedure is the reasonable plan minimizing the AQL (Acceptable Quality Level) and is to be used effectively for the auditing procedure constraining the injurious gasses of the motor vehicles.

• Journal of Korean Institute of Industrial Engineers
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• v.5 no.1
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• pp.7-17
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• 1979

A procedure for constructing a double sampling plan with zero acceptance number for the first sample whose combined sample size does nat exceed that of the given single or double sampling plan is studied. Using this procedure a double sampling system is proposed that can be used in place of MIL-STD-105D system when the quality history is good, and its composite quality characteristics are tabulated and compared with those of MIL-STD-105D system. The study reveals that composite ASN's of the proposed double sampling system are considerably smaller than those of corresponding MIL-STD-105D system with no appreciable changes in other composite quality characteristics. The procedure is also applied to K SA 3102 plans with similar results. A cost model that can be used in comparing a given single sampling plan with the proposed double sampling plan is also developed.

• Communications for Statistical Applications and Methods
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• v.10 no.3
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• pp.1069-1086
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• 2003

This article presents the asymptotic theory of triple sampling procedure as pertain to estimating the shape parameter of Pareto distribution. Both point and confidence interval estimation are considered within the same inference unified framework. We show that this group sampling technique possesses the efficiency of Anscome (1953), Chow and Robbins (1965) purely sequential procedure as well as reduce the number of sampling operations by utilizing Stein (1945) two stages procedure. The analysis reveals that the technique performs excellent as far as the accuracy is concerned. The present problem differs from those considered by many authors, in multistage sampling, in that the final stage sample size and the parameter's estimate become highly correlated and therefore we adopted different approach.

• Communications for Statistical Applications and Methods
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• v.18 no.1
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• pp.147-153
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• 2011

In this paper a new sampling procedure for estimating the population mean is introduced. The performance of the new population mean estimator is discussed, along with its properties, and it is shown that the proposed method generates an unbiased estimator. The relative efficiency of the suggested estimator is computed, in regards to the simple random sample(SRS), and comparisons are made to the ranked set sampling(RSS) and extreme ranked set sampling(ERSS) estimators used for asymmetric distributions. The results indicate that the proposed estimator is more efficient than the estimators based on the ERSS. In addition, the folded ranked set sampling(FRSS) procedure has an advantage over the RSS and ERSS in that it reduces the number of unused sampling units.

• Journal of Korean Institute of Industrial Engineers
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• v.25 no.1
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• pp.8-20
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• 1999

In this paper, a design and estimation procedure for the stochastically dependent nonstationary multiple acceptance sampling plans is developed. At first, the rough-cut acceptance and rejection numbers are given as an initial solution from the corresponding sequential sampling plan. A Monte-Carlo algorithm is used to find the acceptance and rejection probabilities of a lot. The conditional probability formula for a sample path is found. The acceptance and rejection probabilities are found when a decision boundary is given. Several decision criteria and the design procedure to select optimal plans are suggested. The formula for measuring performance of these sampling plans is developed. Type I and II error probabilities are also estimated. As a special case, by setting the stage size as 1 in a dependent sampling plan, a sequential sampling plan satisfying type I and II error probabilities is more accurate and a smaller average sample number can be found. In a numerical example, a Polya dependent process is examined. The sampling performances are shown to compare the selection scheme and the effect of the change of the dependency factor.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.6 no.9
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• pp.1-5
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• 1983

This study takes over the application of survey sampling theory to activity sampling and the application of activity sampling to time standard estimation. Cluster, stratified, and multistage sampling are studied in conjunction with random and systematic sampling. Estimation procedures that will maximize the information obtained per cost expended on the study and specification of the procedure to be used to estimate the accuracy of the estimates for the adopted procedure are considered. The use of multiple regression md linear programming to estimate standard element performance time from typical job lot production data is also considered.

• Journal of applied mathematics & informatics
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• v.7 no.1
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• pp.237-245
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• 2000

In this paper, we consider to the adjustment weighting procedure in the two phase sampling scheme. In general, the unit nonresponses may be occured in the final survey operation. When the unit nonresponse be generated in survey, it is able to use the auxiliary variable for estimating of interest variable. In this viewpoint, we use the two kinds level of auxiliary variable, $X_{1k}$ and $X_{2k}$ for the calibration procedure. We proprose the two-step Newton's method in the calibration estimation procedure for the two phase sampling.

• Journal of Radiation Protection and Research
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• v.41 no.3
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• pp.291-300
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• 2016

Background: It is necessary to assess radiation dose to workers due to inhalation of airborne particulates containing naturally occurring radioactive materials (NORM) to ensure radiological safety required by the Natural Radiation Safety Management Act. The objective of this study is to develop an internal dose assessment procedure for workers at industries using raw materials containing natural radionuclides. Materials and Methods: The dose assessment procedure was developed based on harmonization, accuracy, and proportionality. The procedure includes determination of dose assessment necessity, preliminary dose estimation, airborne particulate sampling and characterization, and detailed assessment of radiation dose. Results and Discussion: The developed dose assessment procedure is as follows. Radioactivity concentration criteria to determine dose assessment necessity are $10Bq{\cdot}g^{-1}$ for $^{40}K$ and $1Bq{\cdot}g^{-1}$ for the other natural radionuclides. The preliminary dose estimation is performed using annual limit on intake (ALI). The estimated doses are classified into 3 groups ( < 0.1 mSv, 0.1-0.3 mSv, and > 0.3 mSv). Air sampling methods are determined based on the dose estimates. Detailed dose assessment is performed using air sampling and particulate characterization. The final dose results are classified into 4 different levels ( < 0.1 mSv, 0.1-0.3 mSv, 0.3-1 mSv, and > 1 mSv). Proper radiation protection measures are suggested according to the dose level. The developed dose assessment procedure was applied for NORM industries in Korea, including coal combustion, phosphate processing, and monazite handing facilities. Conclusion: The developed procedure provides consistent dose assessment results and contributes to the establishment of optimization of radiological protection in NORM industries.

• Journal of Industrial Technology
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• v.9
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• pp.51-56
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• 1989

A methodology for determining optimal sampling plans for Bayesian multiattribute curtailed inspection models is proposed, whereby sampling inspection is terminated as soon as the disposition of the inspection lot is determined. An iterative solution procedure is developed for obtaining optimal multiattribute acceptance sampling plans under cuntailed sampling inspection.

• Structural Engineering and Mechanics
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• v.38 no.1
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• pp.125-140
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• 2011

This study presents an innovative method to estimate the reliability sensitivity based on the low-discrepancy sampling which is a new technique for structural reliability analysis. Two advantages are contributed to the method: one is that, by developing a general importance sampling procedure for reliability sensitivity analysis, the partial derivative of the failure probability with respect to the distribution parameter can be directly obtained with typically insignificant additional computations on the basis of structural reliability analysis; and the other is that, by combining various low-discrepancy sequences with the above importance sampling procedure, the proposed method is far more efficient than that based on the classical Monte Carlo method in estimating reliability sensitivity, especially for problems of small failure probability or problems that require a large number of costly finite element analyses. Examples involving both numerical and structural problems illustrate the application and effectiveness of the method developed, which indicate that the proposed method can provide accurate and computationally efficient estimates of reliability sensitivity.