• Journal of the Korean Statistical Society
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• v.35 no.4
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• pp.377-395
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• 2006

In this paper we have suggested a family of chain estimators of the population mean $\bar{Y}$ of a study variate y using two auxiliary variates in two phase (double) sampling assuming that the coefficient of variation of the second auxiliary variable is known. It is well known that chain estimators are traditionally formulated when the population mean $\bar{X}_1$ of one of the two auxiliary variables, say $x_1$, is not known but the population mean $\bar{X}_2$ of the other auxiliary variate $x_2$ is available and $x_1$ has higher degree of positive correlation with the study variate y than $x_2$ has with y, $x_2$ being closely related to $x_1$. Here the classes are constructed when the population mean $\bar{X}_1\;of\;X_1$ is not known and the coefficient of variation $C_{x2}\;of\;X_2$ is known instead of population mean $\bar{X}_2$. Asymptotic expressions for the bias and mean square error (MSE) of the suggested family have been obtained. An asymptotic optimum estimator (AOE) is also identified with its MSE formula. The optimum sample sizes of the preliminary and final samples have been derived under a linear cost function. An empirical study has been carried out to show the superiority of the constructed estimator over others.

• Journal of the Korean Statistical Society
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• v.35 no.3
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• pp.331-341
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• 2006

An approximate distribution of the plug-in estimator of the squared coefficient of variation ($CV^2$) is derived by using Edgeworth expansions under general population models. Also bias of the estimator is investigated for several important distributions. Under the normal distribution, we proposed the new estimator for $CV^2$ based on median of the sampling distribution of plug-in estimator.

• Journal of Ocean Engineering and Technology
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• v.34 no.5
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• pp.316-324
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• 2020

This paper presents comparative studies of reliability analysis and meta-modeling using the sampling method of Monte Carlo simulation for the structure design of an automatic ocean salt collector (AOSC). The thickness sizing variables of structure members are considered as random variables. Probabilistic performance functions are selected from strength performances evaluated via the finite element analysis of an AOSC. The sampling methods used in the comparative studies are simple random sampling and Sobol sequences with varied numbers of sampling. Approximation methods such as the Kriging model is applied to the meta-model generation. Reliability performances such as the probability failure and distribution are compared based on the variation of the sampling method of Monte Carlo simulation. The meta-modeling accuracy is evaluated for the Kriging model generated from the Monte Carlo simulation and Sobol sequence results. It is discovered that the Sobol sequence method is applicable to not only to the reliability analysis for the structural design of marine equipment such as the AOSC, but also to Kriging meta-modeling owing to its high numerical efficiency.

• Structural Engineering and Mechanics
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• v.82 no.3
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• pp.271-282
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• 2022

The active learning surrogate model based on adaptive sampling strategy is increasingly popular in reliability analysis. However, most of the existing sampling strategies adopt the trial and error method to determine the size of the Monte Carlo (MC) candidate sample pool which satisfies the requirement of variation coefficient of failure probability. It will lead to a reduction in the calculation efficiency of reliability analysis. To avoid this defect, a new method for determining the optimal size of the MC candidate sample pool is proposed, and a new structural reliability analysis method combining polynomial chaos-based Kriging model (PC-Kriging) with adaptive sampling region is also proposed (PCK-ASR). Firstly, based on the lower limit of the confidence interval, a new method for estimating the optimal size of the MC candidate sample pool is proposed. Secondly, based on the upper limit of the confidence interval, an adaptive sampling region strategy similar to the radial centralized sampling method is developed. Then, the k-means++ clustering technique and the learning function LIF are used to complete the adaptive design of experiments (DoE). Finally, the effectiveness and accuracy of the PCK-ASR method are verified by three numerical examples and one practical engineering example.

• 한국해양학회지
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• v.24 no.4
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• pp.165-171
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• 1989

To examine the sample variability of zooplankton, samples were collected at two stations in the nearshore off Anhung (Chungnam, Korea), using a NORPAC net (76 Cm diameter, 0.333 mm mesh size) for two days, April 5 and 6, 1989. The net was towed vertically to eliminate the source of variation due to vertical migration. During the period of 6 hours, triplicate sampling was done every one or two hour at each station. Species composition and abundances at two stations were not so different, but the abundances at each station varied greatly with respect to sampling time. Greater abundance at one sampling time ranged 2.3-8.7 times of smaller abundance at another sampling time. At the level of ${\alpha}=0.05$, however, mean abundances of different sampling time did not differ significantly from each other due to the large variance. It was believed that the large variance was caused by the time dependent effect of patchiness of which parameters were varied with time because of sea water movement. From the variation within the triplicate samples, it was considered that the abundance data obtained from single tow were not significantly different from the data in the range of 50-200% of those from single tow. From these results, the necessity for the replicate and time dependent sampling was indicated. In the nearshore like the sampling site of this study, it seemed to be better to reduce the number of stations for the replicate and time dependent sampling though the proper sampling scheme was to be decided based on the goal of the study.

• Journal of Korean Society for Atmospheric Environment
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• v.14 no.1
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• pp.43-62
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• 1998

This study was carried out to investigate the influence of different sampling methods on the measured concentrations of polycyclic aromatic hydrocarbons (PAH) both in the vapor and particulate phases, and to evaluate the effects of ambient temperature and sampling duration on the losses of PAH associated with particle samples due to volatilization. The experimental protocol of this study is consisted of two parts. The first part is related to the comparison of PAH concentrations measured by 4 different sampling systems, each of which involves different sampling principles for comparison purposes, including a medium-volume sampler with XAD-2 adsorbent, a high-volume sampler with polyurethane foam (PUF), two identical low-volume samplers: one with XAD-2 and the other with PUF, respectively. The second part of this study is to quantitatively estimate the losses of particulate PAH samples by volatilization during sampling, using two identical low-volume samplers: one was used for changing the filters every 3 hrs, 6 hrs, 12 hrs, and 24 hrs sampling, while the other was maintained for continuous 48 hours sampling without changing the filter. The concentrations of volatile PAH including 2-3 rings appeared to be significantly affected by the type of adsorbent. Measured levels of these lower-molecular weight PAH by XAD-2 adsorbent were much higher than those by PUF for both high-volume and low-volume sampling. PUF was found to give rise to unknown components that interfered with the PAH analysis, even after extensive clean-up. In addition, the retention efficiency of PUF for lower molecular weight PAH was subject to a large variation, being significantly influenced by sampling conditions such as ambient temperature. However, the effect of sampling methods with different adsorbents on the measured levels of semi-volatile compounds including 4 rings PAH such as fluoranthene, pyrene, BaA and chrysene, was not so much significant as more volatile PAH compounds. It was also clear from this study that volatilization losses of the semi-volatile PAH collected on the filters were inevitably occurred during prolonged sampling, and hence the results obtained from conventional sampling methods may not be expected to yield an accurate distribution of PAH between the vapor and particulate phases.

• Journal of Korean Society for Atmospheric Environment
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• v.1 no.1
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• pp.93-98
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• 1985

Mass size distribution of atmospheric particulates were measured using an Andersen using an Andersen sampler in urban air. The atmospheric particulates were fractionated in eight stages of an Andersen sampler operating at 28.4$\ell/min$ and collected on polyester sheets. A quartz filter was placed behind the last stage collect permeated partculates. The size distribution of atmospheric particulates were divided around 1-2 $\mu$m into two groups, coarse and fine particulates regardless of sampling times. The variation of course particulates concentration was higher than fine particulates among sampling times. Different meterorological conditions and natural phenomena brought high variation of course particulates' concentration. The rain caused removal of coarse particulates seriously and the yellow and may take part in a increase of the course particulates in spring. The average concentration of atmospheric particulates to be collected by Andersen sampler was 170.8 $\mug/m^3$ during 3 times of sampling. Among them the average concentration of atmospheric particulates which could penetrated under a bronchi and alveoli were 70.4$\mug/m^3$ and 36.6$\mug/m^3$ respectively.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.41 no.3
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• pp.31-38
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• 2004

The wavelength variation of a scanned fiber laser is analyzed using quadrature sampling technique. By time delayed sampling of a phase modulated Mach-Zender interferometer, the wavelength information can be precisely determined regardless of the nonlinearity in the Fabry-Perot wavelength filter which scanned the fiber laser. A wavelength readout resolution of ～20 pm was obtained at 2 KHz M-Z modulation frequency, and it was shown that the resolution could be improved in case of using an electro-optic phase modulator.

• The Korean Journal of Applied Statistics
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• v.32 no.4
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• pp.643-652
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• 2019

We propose a method for sample size determination using design effect formulas when a sample is resigned for a repeated survey. The proposed method enables the determination of the sample size by incorporating the impact of various design components to the sampling error through design effect formulas that are applicable under multistage sampling design and stratified multistage sampling designs.

• 전기의세계
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• v.21 no.2
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• pp.9-19
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• 1972

The transient characteristics of separately excited d-c motor driven by thyristor d-c chopper is studied in this paper. The armature controlled system is applied. As a result of theoretrical analysis the following conculsions were drawn: (1) For the transient analysis, it is recognized that the state transition analysis is a more general method and powerful tool than the state equation method or signal flow graph method, although it includes iterative matrix calculations. And the system is dealt with a finite width sampled-data system in the state transition analysis. (2) The transient characteristics of the motor angular velocity and its torque to the sampling duration variation are compared with those due to the amplitude variation of d-c chopper voltage as follows. The attenuation rate of the transient characteristics is equal in both cases, but the initial value of the transient characteristics in former case is greater than in latter case. (3) The roots of characteristics equation of the system lie inside the unit circle of the Z-plane. Therefor the system is stable. Further it is found that as the sampling duration is decreased the relative stability is lessened.