• Korean System Dynamics Review
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• v.9 no.2
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• pp.5-25
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• 2008

This paper analysed the impact of return policy as a coordination mechanism for decentralized supply chain with one capacitated supplier and two competing retailers under random demand distribution. In this study, Shortage gaming also considered to reflect a competing environment of two retailers. System dynamics approach was used to model the baseline two echelon supply chain and return policy on it. Given each of 4 experiment settings being used for 100 simulations with different random seeds, 400 random samples were used in a t-test. The result show that return policy significantly enhance the supply chain profits and fillrates. The analysis suggest that the supply chain performance can be build up by implementing a return policy even though under consideration of a capacitated supplier and competing retailers.

• Asian-Australasian Journal of Animal Sciences
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• v.14 no.12
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• pp.1655-1658
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• 2001

Bovine genome samples were collected from meat of three different beef breeds (Hanwoo, Holstein and imported beef breed) that are commercially merchandized in Korean beef market. Operon B (OPB)-kits were used as random primers (3, 7, 10, 11, 12, 14) in random amplified polymorphic DNA (RAPD) method on whole genome. Each primer provided characteristic bands that were highly polymorphic. Each single primer could provide relatively efficient polymorphic band patterns among breeds. However, use of two or more primers in combination is recommended to improve resolution of experiments with higher molecular weight bands of DNA. In our experiments, OPB-11 resolved well between beef cattle breeds and Holstein. And OPB-7, 12 and 14 could be combined with OPB-11 to identify Hanwoo beef from the other two kinds of beef.

• Communications for Statistical Applications and Methods
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• v.8 no.1
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• pp.137-145
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• 2001

There are many situations in which the well-known tests such as log-rank test and Gehan-Wilcoxon test fail to detect the survival differences. Assuming large samples, these tests are developed asymptotically normal properties. Thus, they shall be called asymptotic tests in this paper, Several asymptotic tests sensitive to some specific types of survival differences have been recently proposed. This paper compares by simulations the test levels and the powers of the conventional asymptotic tests and their random permutation versions. Simulation studies show that the random permutation tests possess competitive powers compared to the corresponding asymptotic tests, keeping exact test levels even in the small sample case. It also provides the guidelines for choosing the valid and most powerful test under the given situation.

• Elastomers and Composites
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• v.56 no.4
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• pp.217-222
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• 2021

In this study, random polypropylene (rPP) was compounded with two of monoglycerides, namely, glyceryl monolaurate (GML) and glyceryl monostearate (GMS), as antifogging agents to improve its antifogging performance. rPP film samples were prepared by a film-casting method using a three-roll casting machine after melt blending through a twin screw extruder. With an increase in the monoglyceride content, the melt flow index for rPP films with GML and GMS increased, and their yield strength decreased. The incorporation of GMS in rPP was proven to be more effective in improving its physical properties than was rPP with GML. When GML and GMS were separately added to the rPP film at contents of more than 1 phr and more than 5 phr, respectively, the film exhibited antifogging performance.

• Communications for Statistical Applications and Methods
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• v.31 no.1
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• pp.65-85
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• 2024

The tail probability of a function of a multivariate random variable is not easy to estimate by the crude Monte Carlo simulation. When the occurrence of the function value over a threshold is rare, the accurate estimation of the corresponding probability requires a huge number of samples. When the explicit form of the cumulative distribution function of each component of the variable is known, the inverse transform likelihood ratio method is directly applicable scheme to estimate the tail probability efficiently. The method is a type of the importance sampling and its efficiency depends on the selection of the importance sampling distribution. When the cumulative distribution of the multivariate random variable is represented by a copula and its marginal distributions, we develop an iterative algorithm to find the optimal importance sampling distribution, and show the convergence of the algorithm. The performance of the proposed scheme is compared with the crude Monte Carlo simulation numerically.

• Journal of the Korean Statistical Society
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• v.30 no.4
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• pp.667-678
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• 2001

The asymptotic behavior and distribution for quantiles estimators using ranked samples are introduced. Applications of quantiles estimation on finding the normal ranges (2.5% and 97.5% percentiles) and the median of some medical characteristics and on finding the Hodges-Lehmann estimate are discussed. The conclusion of this study is, whenever perfect ranking is possible, the relative efficiency of quantiles estimation using ranked samples relative to SRS is high. This may translates to large savings in cost and time. Also, this conclusion holds even if the ranking is not perfect. Computer simulation results are given and real data from lows 65+ study is used to illustrate the method.

• Korean Journal of Veterinary Research
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• v.34 no.1
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• pp.55-62
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• 1994

This study was carried out to determine the sulfamethazine residues in liver and kidney of chickens. For this experiment total 80 samples of livers and kidneys were collected at random 4 points(east area 2, west area 2) meat markets in Kyong-nam area 2 and were analysed by HPLC system. The results were as follows : 1. The average concentration of sulfamethazine residues in liver and kidney were 0.056 ppm and 0.035 ppm, respectively, the sulfamethazine residues in chicken tissue was higher in liver than kidney. 2. The sulfamethazine residues of livers were exceed 0.1 ppm in three samples and no samples were exceed than 0.1 ppm in kidney. 3. No sulfamethazine residues in liver and kidney were 14 and 25 samples respectively.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.901-905
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• 2005

Monte Carlo localization is known to be one of the most reliable methods for pose estimation of a mobile robot. Much research has been done to improve performance of MCL so far. Although MCL is capable of estimating the robot pose even for a completely unknown initial pose in the known environment, it takes considerable time to give an initial estimate because the number of random samples is usually very large especially for a large-scale environment. For practical implementation of the MCL, therefore, a reduction in sample size is desirable. This paper presents a novel approach to reducing the number of samples used in the particle filter for efficient implementation of MCL. To this end, the topological information generated off- line using a thinning method, which is commonly used in image processing, is employed. The topological map is first created from the given grid map for the environment. The robot scans the local environment using a laser rangefinder and generates a local topological map. The robot then navigates only on this local topological edge, which is likely to be the same as the one obtained off- line from the given grid map. Random samples are drawn near the off-line topological edge instead of being taken with uniform distribution, since the robot traverses along the edge. In this way, the sample size required for MCL can be drastically reduced, thus leading to reduced initial operation time. Experimental results using the proposed method show that the number of samples can be reduced considerably, and the time required for robot pose estimation can also be substantially decreased.

• Geomechanics and Engineering
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• v.17 no.1
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• pp.31-45
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• 2019

In this study the spatial variability of soils is substantiated physically and numerically by using random field theory. Heterogeneous samples are fabricated by combining nine homogeneous soil clusters that are assumed to be elements of an adopted random field. Homogeneous soils are prepared by mixing different percentages of kaolin and bentonite at water contents equivalent to their respective liquid limits. Comprehensive characteristic laboratory tests were carried out before embarking on direct shear experiments to deduce the basic correlations and properties of nine homogeneous soil clusters that serve to reconstitute the heterogeneous samples. The tests consist of Atterberg limits, and Oedometric and unconfined compression tests. The undrained shear strength of nine soil clusters were measured by the unconfined compression test data, and then correlations were made between the water content and the strength and stiffness of soil samples with different consistency limits. The direct shear strength of heterogeneous samples of different stochastic properties was then evaluated by physical and numerical modelling using FISH code programming in finite difference software of $FLAC^{3D}$. The results of the experimental and stochastic numerical analyses were then compared. The deviation of numerical simulations from direct shear load-displacement profiles taken from different sources were discussed, potential sources of error was introduced and elaborated. This study was primarily to explain the mathematical and physical procedures of sample preparation in stochastic soil mechanics. It can be extended to different problems and applications in geotechnical engineering discipline to take in to account the variability of strength and deformation parameters.

• Geomechanics and Engineering
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• v.22 no.3
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• pp.207-217
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• 2020

Slope reliability analysis and risk assessment for spatially variable soils under rainfall infiltration are important subjects but they have not been well addressed. This lack of study may in part be due to the multiple and diverse evaluation indexes and the low computational efficiency of Monte-Carlo simulations. To remedy this, this paper proposes a highly efficient computational method for investigating random field problems for slopes. First, the probability density evolution method (PDEM) is introduced. This method has high computational efficiency and does not need the tens of thousands of numerical simulation samples required by other methods. Second, the influence of rainfall on slope reliability is investigated, where the reliability is calculated from based on the safety factor curves during the rainfall. Finally, the uncertainty of the sliding mass for the slope random field problem is analyzed. Slope failure consequences are considered to be directly correlated with the sliding mass. Calculations showed that the mass that slides is smaller than the potential sliding mass (shallow surface sliding in rainfall). Sliding mass-based risk assessment is both needed and feasible for engineered slope design. The efficient PDEM is recommended for problems requiring lengthy calculations such as random field problems coupled with rainfall infiltration.