• Nuclear Engineering and Technology
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• v.55 no.11
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• pp.4228-4237
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• 2023

The Improved Deterministic Truncation of Monte Carlo (iDTMC) is a powerful acceleration and variance reduction scheme in the Monte Carlo analysis. The concept of the iDTMC method and correlated sampling-based real variance estimation are briefly introduced. Moreover, the application of the iterative scheme to the correlated sampling is discussed. The iDTMC method is utilized in a 3-dimensional small modular reactor (SMR) model problem. The real variances of burnup-dependent criticality and power distribution are evaluated and compared with the ones obtained from 30 independent iDTMC calculations. The impact of the inactive cycles on the correlated sampling is also evaluated to investigate the consistency of the correlated sample scheme. In addition, numerical performances and sensitivity analysis on the real variance estimation are performed in view of the figure of merit of the iDTMC method. The numerical results show that the correlated sampling accurately estimates the real variances with high computational efficiencies.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.4
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• pp.793-802
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• 1997

A sampling plan is presented for situations where sampling inspection is based on the quality characteristic of interest and items in rejected lots are screened based on a correlated variable. A cost model is constructed which involves the costs of misclassification errors, sampling and screening inspections. A method of finding optimal values of sample size, acceptance number and cutoff value on the correlated variable is presented, and numerical studies are given.

• Journal of the Korean Statistical Society
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• v.35 no.4
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• pp.441-452
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• 2006

Here an efficient regression type estimator for a stratified population mean is proposed under the two-phase sampling scheme. While constructing the proposed estimator, it is assumed that the first auxiliary variable x is directly and highly correlated with the study variable y, and the second auxiliary variable z is directly and highly correlated with the first auxiliary variable x. However the variable z is not directly correlated with the variable y, but they are just correlated with each other only due to their direct and high correlation with the variable x. The proposed regression type estimator is found to be always more efficient than the existing estimators defined under the same situation.

• International Journal of Contents
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• v.3 no.1
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• pp.1-8
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• 2007

The distributions of the minimum correlated F-variable arises in many applied statistical problems including simultaneous analysis of variance (SANOVA), equality of variance, selection and ranking populations, and reliability analysis. In this paper, negative binomial sampling technique is employed to derive the distributions of the minimum of chi-square variables and hence the distributions of the minimum correlated F-variables. The work presented in this paper is divided in two parts. The first part is devoted to develop some combinatorial identities arised from the negative binomial sampling. These identities are constructed and justified to serve important purpose, when we deal with these distributions or their characteristics. Other important results including cumulants and moments of these distributions are also given in somewhat simple forms. Second, the distributions of minimum, chisquare variable and hence the distribution of the minimum correlated F-variables are then derived within the negative binomial sampling framework. Although, multinomial theory applied to order statistics and standard transformation techniques can be used to derive these distributions, the negative binomial sampling approach provides more information regarding the nature of the relationship between the sampling vehicle and the probability distributions of these functions of chi-square variables. We also provide an algorithm to compute the percentage points of the distributions. The computation methods we adopted are exact and no interpolations are involved.

• Journal of Ecology and Environment
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• v.36 no.1
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• pp.65-71
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• 2013

The concentration of airborne pollen is related to meteorological parameters. The main purpose of this study was to determine the correlation between airborne pollen and meteorological parameters in Ulsan based on sampling from 2010 to 2011. The primary factors of interest were differences in the pollen scattering start date, end date, and peak date, and the fluctuations in pollen concentration. The meteorological parameters that affected the start and peak dates of the pollen season were as follows. For Pinus and Alnus, the dates were correlated with sunshine and an increase in temperature, whereas for Quercus, the dates were correlated with increasing temperature. During the pollen season, Alnus peaked when the temperature was highest and Pinus peaked when the relative humidity was lowest. The concentration of airborne pollen was correlated with meteorological parameters during the sampling period as follows: Pinus, Alnus, and Humulus pollen concentrations were positively correlated with increasing temperature and negatively correlated with rainfall and relative humidity; Humulus pollen concentration was positively correlated with sunshine; and Quercus and Humulus pollen concentrations were positively correlated with wind speed.

• Journal of Sensor Science and Technology
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• v.21 no.1
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• pp.7-12
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• 2012

In this paper, we propose a 4-transistor active pixel sensor(APS) with a novel correlated double sampling(CDS) circuit for the purpose of extending dynamic range. Dual sampling techniques can overcome low-sensitivity and temporal disparity problems at low illumination. To accomplish this, two images are obtained at the same time using different sensitivities. The novel CDS circuit proposed in this paper contains MOS switches that make it possible for the capacitance of a conventional CDS circuit to function as a charge pump, so that the proposed APS exhibits an extended dynamic range as well as reduced noise. The designed circuit was fabricated by using $0.35{\mu}m$ 2-poly 4-metal standard CMOS technology and its characteristics have been evaluated.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2009.06a
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• pp.7-8
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• 2009

In the presence of infrared light, a CMOS Readout IC (ROIC) for a microbolometer typed infrared sensor detects the voltage or current that is caused by the changing in resistance in the bolometer sensor. A serious problem in designing the ROIC is how the value of the bolometer and reference resistors vary because of variations in manufacturing process. Since different pixel have different, resistance values, sensor operations must contend with fixed pattern noise (FPN) problems. In this paper, we propose a novel technique to compensate for the fluctuation in reference resistance by tiling into account the process variation. By using constant current source basing and correlated double sampling, we solved FPN.

• Journal of Korean Society for Quality Management
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• v.25 no.3
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• pp.39-50
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• 1997

Markov chain method to evaluate the properties of control charts with variable sampling intervals(VSI0 for simultaneously monitoring several correlated quality characteristics under multivariate normal process are investigated. For comparing the efficiencies and properties of multivariate control charts, we consider multivariate Shewhart, CUSUM and EWMA charts in terms of average time to signal(ATS) and average number of samples to signal(ANSS). We obtained stabilized numerical results with Markov chain method when the number of transient state is greater than 100.

• Communications for Statistical Applications and Methods
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• v.6 no.3
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• pp.755-760
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• 1999

In multivariate stratified sampling surveys it is general to use a few stratification variables which are highly correlated with the important variables at design stage. But there might be some secondary study variables which are not so highly correlated with those stratification variables. In that case it is not efficient to use the same type of estimator due to the secondary variables as the one base on the important variables. A post-stratified estimation is proposed to increase the efficiency of the estimator with existence of secondary variables. The proposed method is illustrated with a set of fishery household population survey data.

• International Journal of Contents
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• v.2 no.2
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• pp.17-24
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• 2006

The work presented in this paper is divided into two parts. The first part presents finite urn problems which generate truncated negative binomial random variables. Some combinatorial identities that arose from the negative binomial sampling and truncated negative binomial sampling are established. These identities are constructed and serve important roles when we deal with these distributions and their characteristics. Other important results including cumulants and moments of the distributions are given in somewhat simple forms. Second, the distributions of the maximum of two chi-square variables and the distributions of the maximum correlated F-variables are then derived within the negative binomial sampling scheme. Although multinomial theory applied to order statistics and standard transformation techniques can be used to derive these distributions, the negative binomial sampling approach provides more information and deeper insight regarding the nature of the relationship between the sampling vehicle and the probability distributions of these functions of chi-square variables. We also provide an algorithm to compute the percentage points of these distributions. We supplement our findings with exact simple computational methods where no interpolations are involved.