• Journal of Soil and Groundwater Environment
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• v.16 no.6
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• pp.1-9
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• 2011

A bibliographical review of Gy sampling theory for particulate materials was conducted to provide readers with useful means to reduce errors in soil contamination investigation. According to the Gy theory, the errors caused by the heterogeneous nature of soil include; the fundamental error (FE) caused by physical and chemical constitutional heterogeneity, the grouping and segregation error (GE) aroused from gravitational force, long-range heterogeneous fluctuation error ($CE_2$), the periodic heterogeneity fluctuation error ($CE_3$), and the materialization error (ME) generated during physical process of sample treatment. However, the accurate estimation of $CE_2$ and $CE_3$ cannot be estimated easily and only increasing sampling locations can reduce the magnitude of the errors. In addition, incremental sampling is the only method to reduce GE while grab sampling should be avoided as it introduces uncertainty and errors to the sampling process. Correct preparation and operation of sampling tools are important factors in reducing the incremental delimitation error (DE) and extraction error (EE) which are resulted from physical processes in the sampling. Therefore, Gy sampling theory can be used efficiently in planning a strategy for soil investigations of non-volatile and non-reactive samples.

• Journal for History of Mathematics
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• v.11 no.1
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• pp.68-77
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• 1998

There are two approach methods widely in statistical inferences. First is sampling theory methods and the other is Bayesian methods. In this paper, we will introduce the most basic differences of the two approach methods. Especially, we investigate and introduce the historical origin of Bayesian methods in Statistical inferences which is currently used. Also, we introduce the some characteristics of sampling theory method and Bayesian methods.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.9 no.2
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• pp.141-146
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• 2009

Support vector machine is a classification algorithm based on statistical learning theory. It has shown many results with good performances in the data mining fields. But there are some problems in the algorithm. One of the problems is its heavy computing cost. So we have been difficult to use the support vector machine in the dynamic and online systems. To overcome this problem we propose to use stratified sampling of statistical sampling theory. The usage of stratified sampling supports to reduce the size of training data. In our paper, though the size of data is small, the performance accuracy is maintained. We verify our improved performance by experimental results using data sets from UCI machine learning repository.

• Fisheries and Aquatic Sciences
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• v.21 no.8
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• pp.24.1-24.9
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• 2018

The Korean bottom trawl survey has been deployed on a regular basis for about the last decade as part of groundfish stock assessments. The regularity indicates that they sample groundfish once per grid cell whose sides are half of one latitude and that of one longitude, respectively, and whose inside is furthermore divided into nine nested grids. Unless they have a special reason (e.g., running into a rocky bottom), their sample location is at the center grid of the nine nested grids. Given data collected by the survey, we intended to show how to appropriately estimate not only the survey index of a fish stock but also its uncertainty. For the regularity reason, we applied the systematic sampling theory for the above purposes and compared its results with a reference, which was based on the simple random sampling. When using the survey data about 11 fish stocks, collected by the spring and fall surveys in 2014, the survey indices of those stocks estimated under the systematic sampling were overall more precise than those under the simple random sampling. In estimates of the survey indices in number, the standard errors of those estimates under the systematic sampling were reduced from those under the simple random sampling by 0.23~27.44%, while in estimates of the survey indices in weight, they decreased by 0.04~31.97%. In bias of the estimates, the systematic sampling was the same as the simple random sampling. Our paper is first in formally showing how to apply the systematic sampling theory to the actual data collected by the Korean bottom trawl surveys.

• Journal of the Korean School Mathematics Society
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• v.26 no.1
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• pp.21-47
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• 2023

This study examines the activity system of teaching and learning about informal statistical inference using sampling simulation, based on cultural-historical activity theory. The research explores what contradictions arise in the activity system and how the system changes as a result of these contradictions. The participants were 20 elementary school students in the 5th to 6th grades who received classes on informal statistical inference using sampling simulations. Thematic analysis was used to analyze the data. The findings show that a contradiction emerged between the rule and the object, as well as between the mediating artifact and the object. It was confirmed that visualization of empirical sampling distribution was introduced as a new artifact while resolving these contradictions. In addition, contradictions arose between the subject and the rule and between the rule and the mediating artifact. It was confirmed that an algorithm to calculate the mean of the sample means was introduced as a new rule while resolving these contradictions.

• Korean Journal of Optics and Photonics
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• v.7 no.4
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• pp.322-327
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• 1996

Unlike holograms of real objects, holographic stereograms(HS) are made using a relatively small number of synthesized 2D images. The influence of aliasing artifacts caused by insufficient or improper sampling is presented, and a new sampling theory is proposed, which is used to making holographic stereograms. Also, the optical system for extension of viewing distance and viewing zone is proposed. Results of this analysis can be applied to design normal holographic stereograms and computer based holographic stereograms.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.524-528
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• 1996

Quality information is known to have the characteristic of continuous distribution in many manufacturing processes. It is difficult to describe the process condition by classifying the distribution into discrete ranges which is based on the set concept. Fuzzy control chart has been developed for the control of linguistic data but it still utilizes the dichotomous notion of classical set theory. In this paper, the fuzzy sampling method is studied in order to manage the ambiguous data properly and incorporated for generating fuzzy control chart. The method is based on the fuzzy set concept and considered to be appropriate for the realization of a complete fuzzy control chart. The fuzzy control chart was compared with the conventional generalized p-chart in the sensitivity for quality distribution and robustiness against the noise. The fuzzy control chart with the fuzzy sampling method showed better characteristics.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.6 no.9
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• pp.1-5
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• 1983

This study takes over the application of survey sampling theory to activity sampling and the application of activity sampling to time standard estimation. Cluster, stratified, and multistage sampling are studied in conjunction with random and systematic sampling. Estimation procedures that will maximize the information obtained per cost expended on the study and specification of the procedure to be used to estimate the accuracy of the estimates for the adopted procedure are considered. The use of multiple regression md linear programming to estimate standard element performance time from typical job lot production data is also considered.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.9C
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• pp.913-921
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• 2005

A complex bandpass sampling technique can provide a more flexible architecture for designing a software- defined radio(SDR) system, because it has several advantageous features of larger sampling range and lower minimum sampling frequency than a real bandpass sampling method. In spite of the potential advantages of the complex bandpass sampling, solid investigation for the direct downconversion of multiple signals by the complex sampling theory has not been reported yet. Thus, we propose in this paper a novel scheme for the downconversion of multiple signals using the complex bandpass sampling, and develop the formulae related to the complex bandpass sampling for practical usage, such as the valid sampling range, the intermediate frequency (If), and the minimum sampling frequency of the downconversion of multiple RE signals. Such derived formulae are verified from simulations.

• Honam Mathematical Journal
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• v.38 no.3
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• pp.613-623
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• 2016

As a generalization of the Fourier transform, the fractional Fourier transform plays an important role both in theory and in applications of signal processing. We present a new approach to reach a uniform sampling theorem in the shift-invariant spaces associated with the fractional Fourier transform domain.