• Communications for Statistical Applications and Methods
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• v.6 no.1
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• pp.107-116
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• 1999

We propose a sample design which minimize Bayes risk for cluster smpling in sampling inspection. We treat a pilot sample and an additional sample size as random variable. In addition we compute an appropriate cluster size for handling over-dispersion.

• Communications for Statistical Applications and Methods
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• v.7 no.1
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• pp.211-224
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• 2000

The Bayes estimation of the proportion in successive occasions sampling with randomized response model is discussed by means of Acceptance Rejection sampling. Bayesian estimation of transition probabilities in two successive occasions is suggested via Markov Chain Monte Carlo algorithm and its applicability is represented in a numerical example.

• Journal of Soil and Groundwater Environment
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• v.22 no.6
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• pp.57-65
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• 2017

Six soil subsampling methods were evaluated with explosive compounds-contaminated soils to quantify the variance associated with each method. The methods include modified grab sampling, simplified ripple splitting, fractional shoveling, coning & quatering, degenerate fractional shoveling, and rolling & quatering. All the methods resulted in significantly lower CV (coefficient of variation) of 1~5%, compared to common grab sampling that gave 8~98% of CV, possibly due to the reduction of grouping and segregation errors described by Gy sampling theory. Among the methods, simplified ripple splitting tends to result in lower explosive compounds concentrations, while the rolling & quatering gave the opposite result. Fractional shoveling method showed the least variance and the highest reproducibility in the analysis.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.76-78
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• 2019

Sampling-based algorithms are one of the most commonly approaches which give good results in robot path planning with many degree of freedom. So that many proposed methods as well as their improvement based on these approaches have been proposed. The purpose of this paper is to survey some current algorithms using for path planning, the original proposed methods as well as their improvement. Some advantages and disadvantages of these algorithms will be also mentioned, how the improved version of the proposed methods overcome the original proposed methods' drawback.

• Communications for Statistical Applications and Methods
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• v.26 no.2
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• pp.103-129
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• 2019

The main goal of a case-control study is to learn the association between various risk factors and a primary outcome (e.g., disease status). Particularly recently, it is also quite common to perform secondary analyses of the case-control data in order to understand certain associations between the risk factors of the primary outcome. It has been repeatedly documented with case-control data, association studies of the risk factors that ignore the case-control sampling scheme can produce highly biased estimates of the population effects. In this article, we review the issues of the naive secondary analyses that do not account for the biased sampling scheme, and also the various methods that have been proposed to account for the case-control ascertainment. We additionally compare the results of many of the discussed methods in an example examining the association of a particular genetic variant with smoking behavior, where the data were obtained from a lung cancer case-control study.

• 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.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.563-566
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• 1997

In this paper, several bandwidth sampling methods were compared in which contains "multi-order sampling", which was proposed or envelope detections in RF ultrasonic signals by a computer simulation and on experiment quadrature sampling method. The second-order sampling method were compared with it. As a conclusion, a multi-order sampling method, especially 5th order sampling method showed quite good envelope detection property. This means that more economical and quite good performance digital beamforming system can be built by adopting this new bandwidth sampling method.

• Transactions on Electrical and Electronic Materials
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• v.7 no.4
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• pp.210-214
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• 2006

In this paper, two sampling methods which are Latin hypercube sampling (LHS) and simple random sampling were. compared to improve the modeling speed of neural network model. Sampling method was used to generate initial weights and bias set. Electrical characteristic data for $HfO_2$ thin film was used as modeling data. 10 initial parameter sets which are initial weights and bias sets were generated using LHS and simple random sampling, respectively. Modeling was performed with generated initial parameters and measured epoch number. The other network parameters were fixed. The iterative 20 minimum epoch numbers for LHS and simple random sampling were analyzed by nonparametric method because of their nonnormality.

• The Journal of the Acoustical Society of Korea
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• v.11 no.4
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• pp.36-44
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• 1992

To reduce the redundancy within samples that resulted from uniform sampling method, nonuniform sampling or nonredundant-sample coding methods can be considered. But it is well-known that when conventional nonuniform sampling methods are applied directly to speech signal, the amount of data required is comparable to or more than that required by uniform sampling method like PCM. To overcome this problem, we consider properties of speech signal in the sense of perception, and suggest a nonuniform sampling method at the maxima and minima of speech wave. To analyze the performance of the suggested method, compression ratio is considered. We show that compression ratio can be improved by silence detection, which can't be implemented by conventional methods based on uniform sampling. As experimental results, compression ratios of 1.54 without silence detection and 2.88 with silence detection for 8kHz 8-bit PCM signals are obtained.

• Journal of Electrical Engineering and Technology
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• v.8 no.4
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• pp.872-878
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• 2013

In industrial control systems, flow measurement is a very important issue. It is frequently needed to calculate how much total fluid or gas flows through a cross-section. Flow volume measurement tools use simple sampling or rectangle methods. Actually, flow volume measurement process is an integration process. For this reason, measurement systems using instantaneous sampling technique cause considerably high errors. In order to make more accurate flow measurement, numerical integration methods should be used. Literally, for numerical integration method, Rectangular, Trapezoidal, Simpson, Romberg and Gaussian Quadrature methods are suggested. Among these methods, trapezoidal rule method is quite easy to calculate and is notably more accurate and contains no restrictive conditions. Therefore, it is especially convenient for the portable flow volume measurement systems. In this study, the volume measurement of air which is flowing through a cross-section is achieved by using PLC ladder diagram. The measurements are done using two different approaches. Trapezoidal rule method is proposed to measure the flow sensor signal to minimize measurement errors due to the classical sampling method as a different approach. It is concluded that the trapezoidal rule method is more effective than the classical sampling.