• Journal of the Korean Society of Tobacco Science
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• v.35 no.1
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• pp.7-12
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• 2013

A Solid-phase micro extraction(SPME) was evaluated as a tool for headspace sampling of tobacco samples. Several experimental parameters (sampling temperature, pH, and type of SPME fibers) were optimized to improve sampling efficiency in two aspects ; maximum adsorption and selective adsorption of volatile organic acids onto SPME fibers. Among four types of SPME fibers such as PDMS(Polydimethylsiloxane), PA(Polyacrylate), Car/PDMS (Carboxen/Polydimethylsiioxane) and PDMS/DVB(Polydimethylsiioxane/Divinylbenzene) which were investigated to determine the selectivity and adsorption efficiency. A variety of tobacco samples such as flue cured, burley and oriental were used in this study. The effect of these parameters was often dominated by the physical and chemical nature (volatility, polarity) of target compounds. This method allowed us to make important improvements in selectivity and sensitivity. The Car/PDMS fiber was shown to be the most efficient at extracting the 10 selected volatile organic acids. The parameters were optimized: $80^{\circ}C$ adsorption temperature, 30 min of adsorption time, $240^{\circ}C$ desorption temperature, 1 min of adsorption time.

• Structural Engineering and Mechanics
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• v.92 no.1
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• pp.111-120
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• 2024

Sampling methods are powerful approaches to solving the problems of structural reliability analysis and estimating the failure probability of structures. In this paper, a new sampling method is proposed offering lower variance and lower computational cost for complex and high-dimensional problems. The method is called Optimal Latinized partially stratified sampling (OLPSS) as it is based upon the Latinized Partially Stratified Sampling (LPSS) which itself is based on merging Stratified Sampling (SS) and Latin Hypercube Sampling (LHS) algorithms. While LPSS has a low variance, it may suffer from a lack of good space-filling of its generated samples in some cases. In the OLPSS, this issue has been resolved by employing a new columnwise-pairwise exchange optimization procedure for sample generation. The efficiency of the OLPSS has been tested and reported under several benchmark mathematical functions and structural examples including structures with a large number of variables (e.g., a structure with 67 variables). The proposed method provides highly accurate estimates of the failure probability of structures with a significantly lower variance relative to the Monte Carlo simulations, Latin Hypercube, and standard LPSS.

• Communications for Statistical Applications and Methods
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• v.22 no.5
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• pp.435-443
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• 2015

Two phase sampling design is useful to increase estimation efficiency using deep stratification, improved non-response adjustment and reduced coverage bias. The same sampling units are commonly used for the first and the second phases in complex two-phase sampling design. In this paper we consider a sampling scheme where the first phase sampling units are clusters and the second phase sampling units are list samples. Using selected clusters in first phase requires that we list up elements in the selected clusters from the first phase and then use the list as a secondary sampling frame for the second phase sampling design. Then we select second phase samples from the listed sampling frame. We suggest an estimator based on the complex two-phase sampling design with different sampling units of each phase. Also the estimated variances of the estimator obtained by using classic and replication variance methods are considered and compared using simulation studies. For real data analysis, 2010 Korea Farm Household Economy Survey (KFHES) and 2011 Korea Agriculture Survey (KAS) are used.

• 전기의세계
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• v.25 no.6
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• pp.89-96
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• 1976

In this paper we deal with that the performance indices by the three adaptive sampling control laws are computed and compared. It shows that the most effective control law is the integral input difference method. The techniques of simulation by Analog/Hybrid computer are presented and the results of the output illustrate that the maximum and minimum sampling interval can be applied to the time sharing of digital controller or computer.

• Journal of applied mathematics & informatics
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• v.3 no.1
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• pp.101-115
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• 1996

In this paper we extend the best choice of subsample size m in the 2-stage sampling which suggested by Mohammad(1986) to the 3-stage sampling in cases of known and of unknown cost and variance ratio. We find the subsample size m.k which ensures more than the relative efficiency 90% Also we see that the choice of 3-stage subsample size depends on the design parameters using in 2-stage sampling.

• Proceedings of the KSME Conference
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• 2007.05b
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• pp.3139-3143
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• 2007

The objective of this paper was to investigate the mixing characteristics of an three-stage inline coagulant mixing system experimentally. Wastewater samples of pH 8.5 and initial turbidity 1,000NTU were taken from a site of tunneling work. At the constant dosage, 0.36mL/L, of polymer as coagulant aids, the coagulation efficiency with the dosage of PAC as coagulant was about 4${\sim}$6% at 10 minutes after sampling. In the case of 2 different velocity gradient conditions, the efficiency of turbidity removal was increased about 6.5${\sim}$8% with increasing the dosage of coagulant while, the efficiency was increased about 20${\sim}$21.5% with increasing the dosage of coagulant aids. The efficiency of turbidity removal with the settling time after sampling was about 90% after 1 minute, and the efficiency was about 95% after 5 minutes.

• JSTS:Journal of Semiconductor Technology and Science
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• v.13 no.6
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• pp.608-616
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• 2013

This paper presents an adaptive sampling method for electrocardiogram (ECG) signal detection. First, by employing the strings matching process with compression dictionary, we recognize each segment of ECG with different characteristics. Then, based on the non-uniform sampling strategy, the sampling rate is determined adaptively. As the results of simulation indicated, our approach reconstructed the ECG signal at an optimized sampling rate with the guarantee of ECG integrity. Compared with the existing adaptive sampling technique, our approach acquires an ECG signal at a 30% lower sampling rate. Finally, the experiment exhibits its superiority in terms of energy efficiency and memory capacity performance.

• 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.

• Communications for Statistical Applications and Methods
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• v.14 no.3
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• pp.667-677
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• 2007

In this paper, we propose a method for estimating the mean of a population which has a linear trend, when both n, the sample size, and k, the reciprocal of the sampling fraction, are odd numbers. The proposed method, not having the drawbacks of centered systematic sampling, centered modified sampling and centered balanced sampling, consists of selecting a sample by balanced systematic sampling and estimating the population mean by using interpolation. We compare the efficiency of the proposed method and existing methods under the criterion of the expected mean square error based on the infinite superpopulation model.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.8 no.11
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• pp.85-95
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• 1985

This thesis is a study on the work sampling method which is one of the important parts in the fields of work measurement today. The primary objective of this study is to examine various methods of selecting observation times in work sampling studies, including simple random systematic, and stratified sampling and a new method called restricted random sampling. The attribute of these sampling methods are explained, particulary statistical efficiency, and the important advantages of stratification are analysed. A case study of work sampling was made in a manufacturing plant to show its practical application and the effectiveness of the stratified random sampling technique.