• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.4
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• pp.325-332
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• 2022

Determination of VLBI IVP (Very Long Baseline Interferometry Invariant Point) position with high accuracy is required to compute local tie vectors between the space geodetic techniques. In general, reflective targets are attached on VLBI antenna and slant distances, horizontal and vertical angles are measured from the pillars. Then, adjustment computation is performed by using the mathematical model which connects measurements and unknown parameters. This indicates that the accuracy of the estimated solutions is affected by the accuracy of the measurements. One of issues in local tie surveying, however, is that the reflective targets are not in favorable condition, that is, the reflective sheet target cannot be perfectly aligned to the instrument perpendicularly. Deviation from the line of sight of an instrument may cause different type of measurement errors. This inherent limitation may lead to incorrect stochastic modeling for the measurements in adjustment computation procedures. In this study, error characteristics by measurement types and pillars are analyzed, respectively. The analysis on the studentized residuals is performed after adjustment computation. The normality of the residuals is tested and then equal variance test between the measurement types are performed. The results show that there are differences in variance according to the measurement types. Differences in variance between distances and angle measurements are observed when F-test is performed for the measurements from each pillar. Therefore, more detailed stochastic modeling is required for optimal solutions, especially in local tie survey.

• Nuclear Engineering and Technology
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• v.40 no.7
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• pp.551-560
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• 2008

Radiation has stochastic aspects in its generation, its choice of interaction mode during traveling in media, and its impact on living bodies. In certain circumstances, like in high dose environments resulting from low-LET radiation, the variance in its impact on a target volume is negligible. On the contrary, in low dose environments, especially when they are attributed to high-LET radiation, the impact on the target carries with it a large variance. This variation is more significant for smaller target volumes. Microdosimetric techniques, which have been developed to estimate the distribution of radiation energy deposited to cellular and subcellular-sized targets, contrast with macrodosimetric techniques which count only the average value. Since cells and DNA compounds are the critical targets in human bodies, microdosimetry, or dose estimation by microscopic approach, helps one better analyze the biological effects of radiation on the human body. By utilizing microbeam systems designed for individual cell irradiation, scientists have discovered that human cells exhibit radiosensitive reactions without being hit themselves (bystander effect). During the past 10 or more years, a new therapeutic protocol using discontinuous multiple micro-slit beams has been investigated for its clinical application. It has been suggested that the beneficial bystander effect is the essence of this protocol.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.6
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• pp.573-580
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• 2017

Precise stochastic modeling for GPS measurements is one of key factors in adjustment computations for GPS positioning. To analyze the GPS measurement errors, Minimum Norm Quadratic Unbiased Estimators(MINQUE) approach is used in this study to estimate the variance components for measurement types with short-baseline GPS positioning model. The results showed the magnitudes of measurement errors for C1, P2, L1, L2 are 22.3cm, 27.6cm, 2.5mm, 2.2mm, respectively. To reduce the memory usage and computational burden, variance components are also estimated on epoch-by-epoch basis. The results showed that there exists slight differences between the solutions. However, epoch-by-epoch analysis may also be used for most of GPS applications considering the magnitudes of the differences.

• Proceedings of the Korean Geotechical Society Conference
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• 2003.03a
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• pp.123-130
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• 2003

The estimation of key soil properties and subsequent quantitative assessment of the associated uncertainties has always been an important issue in geotechnical engineering. It is well recognized that soil properties vary spatially as a result of depositional and post-depositional processes. The stochastic nature of spatially varying soil properties can be treated as a random field. A practical statistical approach that can be used to systematically model various sources of uncertainty is presented in the context of reliability analysis of slope stability Newly developed expressions for probabilistic characterization of soil properties incorporate sampling and measurement errors, as well as spatial variability and its reduced variance due to spatial averaging. Reliability analyses of the probability of slope failure using the different statistical representations of soil properties show that the incorporation of spatial correlation and conditional simulation leads to significantly lower probability of failure than obtained using simple random variable approach.

• The Korean Journal of Applied Statistics
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• v.14 no.2
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• pp.333-344
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• 2001

통계적 추론에 사용되는 많은 통계량들은 평균벡터의 평활함수의 형태로 표현이 가능하다. 본 연구에서는 이들 통계량들의 분포함수에 대한 안부점근사법을 제시하였다. 이 방법은 Na(1998)에서 제시된 일반적 통계량의 분포함수에 대한 안부점근사법이 평균벡터의 평활함수모형에 특히 유용하게 사용될 수 있음을 보인 것이다. 이 근사법은 정규근사에 비해 근사의 정도가 뛰어나며, 특히 통계량의 꼬리부분의 확률에 대해서도 정확도가 그대로 유지되는 장점이 있어 정밀한 추론이 요구되는 많은 문제에 효과적으로 사용될 수 있다. 모의 실험에 사용할 평균벡터의 평활함수 모형으로는 스튜던트화 분산을 고려하였다.

• Journal of the Korean earth science society
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• v.31 no.5
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• pp.437-447
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• 2010

Spatial estimation of environmental variables has been regarded as an important preliminary procedure for decision-making. A minimum variance criterion, which has often been adopted in traditional kriging algorithms, does not always guarantee the optimal estimates for subsequent decision-making processes. In this paper, a geostatistical framework is illustrated that consists of uncertainty modeling via stochastic simulation and risk modeling based on loss functions for the selection of optimal estimates. Loss functions that quantify the impact of choosing any estimate different from the unknown true value are linked to geostatistical simulation. A hybrid loss function is especially presented to account for the different impact of over- and underestimation of different land-use types. The loss function-specific estimates that minimize the expected loss are chosen as optimal estimates. The applicability of the geostatistical framework is demonstrated and discussed through a case study of copper mapping.

• Journal of the Korean Operations Research and Management Science Society
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• v.25 no.4
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• pp.67-80
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• 2000

Symbiotic evolutionary algorithms, also called cooperative coevolutionary algorithms, are stochastic search algorithms that imitate the biological coevolution process through symbiotic interactions. In the algorithms, the fitness evaluation of an individual required first selecting symbiotic partners of the individual. Several partner selection strategies are provided. The goal of this study is to analyze how much partnering strategies can influence the performance of the algorithms. With two types of test-bed problems: the NKC model and the binary string covering problem, extensive experiments are carried out to compare the performance of partnering strategies, using the analysis of variance. The experimental results indicate that there does not exist statistically significant difference in their performance.

• Journal of Korean Society for Quality Management
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• v.9 no.2
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• pp.10-14
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• 1981

Products are assumed to be spoiled and not recoverable when the raw material below the prescribed weight level is charged in the mold. The raw material is autoscaled and their weight is normally distributed with a given variance. This paper describes an appropriate stochastic model of determining the optimum weight allowance and the associated defective rate for auto scale system. The optimum weight allowance and the defective rate which minimizes the total loss of defective and the excess weight allowance is obtained. A numerical example for the existing rubber company is also presented and evaluated.

• Journal of the Korean Operations Research and Management Science Society
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• v.10 no.1
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• pp.9-13
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• 1985

This paper develops a decomposition method for stochastic programming with a block diagonal structure. Here we assume that the right-hand side random vector of each subproblem is differente each other. We first, transform this problem into a master problem, and subproblems in a similar way to Dantizig-Wolfe's Decomposition Princeple, and then solve this master problem by solving subproblems. When we solve a subproblem, we first transform this subproblem to a Deterministic Equivalent Programming (DEF). The form of DEF depends on the type of the random vector of the subproblem. We found the subproblem with finite discrete random vector can be transformed into alinear programming, that with continuous random vector into a convex quadratic programming, and that with random vector of unknown distribution and known mean and variance into a convex nonlinear programming, but the master problem is always a linear programming.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.3
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• pp.84-90
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• 2014

The partial discharge of Cast-resin Transformer has a difficulty to be analyzed, because it is an abnormal condition signal of which stochastic characteristics varies with time variance. In this study, background noise coming from the outside of the cast-resin transformers through ground wire can be removed and only a discharge signal of which defects are simulated can be obtained, using the wavelet transform method, which is a time-frequency domain analysis technique. As a result, it was confirmed that de-noising using the SWT technique is the best efficient among three methods of the wavelet transform techniques.