• Environmental Analysis Health and Toxicology
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• v.17 no.2
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• pp.95-107
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• 2002

This study was designed to investigate the characteristics of atmospheric concentrations of toxic volatile organic compounds (VOCs) in Korea. Target compounds included 1,3-butadiene, aromatics such as BTEX, and a number of carbonyl compounds. In this paper, as the first part of the study, the performance of sampling and analytical methods was evaluated for the measurement of selected VOCs and carbonyl compounds in the ambient air. VOCs were determined by the adsorbent tube sampling and automatic thermal desorption coupled with GC/MSD analysis, while carbonyls by the DNPH-silica cartridge sampling with HPLC analysis. The methodology was investigated with a wide range of performance criteria such as repeatability, linearity. lower detection limits, collection efficiency, thermal conditioning, breakthrough volume and calibration methods using internal standards. In addition, the sampling and analytical methods established in this study were applied to real field samples duplicately collected in various ambient environments. Precisions for the duplicate samples appeared to be comparable with the performance criteria recommended by USEPA TO-17. The overall precision of the sampling and analytical methods was estimated to be within 20 ∼ 30% for major aromatic VOCs such as BTEX, whereas the precision for major carbonyl compounds such as formaldehyde and acetaldehyde was within 10 ∼ 20% for field samples. This study demonstrated that the adsorbent sampling and thermal desorption method can be reliably applied for the measurement of BTEX in ppb levels frequently occurred in common indoor and ambient environments.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.2
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• pp.294-302
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• 2008

In this paper, we present a new image up-sampling method which registers low resolution images to the high resolution grid when Bayesian super-resolution image processing is performed. The proposed up-sampling method interpolates high-resolution pixels using high-frequency data lying in all the low resolution images, instead of up-sampling each low resolution image separately. The interpolation is based on B-spline non-uniform re-sampling, adjusted for the super-resolution image processing. The experimental results demonstrate the effects when different up-sampling methods generally used such as zero-padding or bilinear interpolation are applied to the super-resolution image reconstruction. Then, we show that the proposed hybird up-sampling method generates high-resolution images more accurately than conventional methods with quantitative and qualitative assess measures.

• Communications for Statistical Applications and Methods
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• v.14 no.3
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• pp.667-677
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• 2007

In this paper, we propose a method for estimating the mean of a population which has a linear trend, when both n, the sample size, and k, the reciprocal of the sampling fraction, are odd numbers. The proposed method, not having the drawbacks of centered systematic sampling, centered modified sampling and centered balanced sampling, consists of selecting a sample by balanced systematic sampling and estimating the population mean by using interpolation. We compare the efficiency of the proposed method and existing methods under the criterion of the expected mean square error based on the infinite superpopulation model.

• ETRI Journal
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• v.23 no.3
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• pp.129-137
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• 2001

A random sampling or systematic sampling method is commonly used to assess the accuracy of classification results. In remote sensing, with these sampling methods, much time and tedious work are required to acquire sufficient ground truth data. So, a more effective sampling method that can represent the characteristics of the population is required. In this study, fractal analysis is adopted as an index for reference sampling. The fractal dimensions of the whole study area and the sub-regions are calculated to select sub-regions that have the most similar dimensionality to that of the whole area. Then the whole area's classification accuracy is compared with those of sub-regions, and it is verified that the accuracies of selected sub-regions are similar to that of whole area. A new kind of reference sampling method using the above procedure is proposed. The results show that it is possible to reduce sampling area and sample size, while keeping the same level of accuracy as the existing methods.

• The Korean Journal of Applied Statistics
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• v.30 no.5
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• pp.681-690
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• 2017

Various imbalanced binary classification problems exist such as fraud detection in banking operations, detecting spam mail and predicting defective products. Several sampling methods such as over sampling, under sampling, SMOTE have been developed to overcome the poor prediction performance of binary classifiers when the proportion of one group is dominant. In order to overcome this problem, several sampling methods such as over-sampling, under-sampling, SMOTE have been developed. In this study, we investigate prediction performance of logistic regression, Lasso, random forest, boosting and support vector machine in combination with the sampling methods for binary imbalanced data. Four real data sets are analyzed to see if there is a substantial improvement in prediction performance. We also emphasize some precautions when the sampling methods are implemented.

• Journal of Korean Society for Atmospheric Environment
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• v.14 no.1
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• pp.43-62
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• 1998

This study was carried out to investigate the influence of different sampling methods on the measured concentrations of polycyclic aromatic hydrocarbons (PAH) both in the vapor and particulate phases, and to evaluate the effects of ambient temperature and sampling duration on the losses of PAH associated with particle samples due to volatilization. The experimental protocol of this study is consisted of two parts. The first part is related to the comparison of PAH concentrations measured by 4 different sampling systems, each of which involves different sampling principles for comparison purposes, including a medium-volume sampler with XAD-2 adsorbent, a high-volume sampler with polyurethane foam (PUF), two identical low-volume samplers: one with XAD-2 and the other with PUF, respectively. The second part of this study is to quantitatively estimate the losses of particulate PAH samples by volatilization during sampling, using two identical low-volume samplers: one was used for changing the filters every 3 hrs, 6 hrs, 12 hrs, and 24 hrs sampling, while the other was maintained for continuous 48 hours sampling without changing the filter. The concentrations of volatile PAH including 2-3 rings appeared to be significantly affected by the type of adsorbent. Measured levels of these lower-molecular weight PAH by XAD-2 adsorbent were much higher than those by PUF for both high-volume and low-volume sampling. PUF was found to give rise to unknown components that interfered with the PAH analysis, even after extensive clean-up. In addition, the retention efficiency of PUF for lower molecular weight PAH was subject to a large variation, being significantly influenced by sampling conditions such as ambient temperature. However, the effect of sampling methods with different adsorbents on the measured levels of semi-volatile compounds including 4 rings PAH such as fluoranthene, pyrene, BaA and chrysene, was not so much significant as more volatile PAH compounds. It was also clear from this study that volatilization losses of the semi-volatile PAH collected on the filters were inevitably occurred during prolonged sampling, and hence the results obtained from conventional sampling methods may not be expected to yield an accurate distribution of PAH between the vapor and particulate phases.

• 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.

• Industry Promotion Research
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• v.8 no.1
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• pp.111-117
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• 2023

Sampling inspection methods for quality control have been proposed a lot in the industry. However, the sampling inspection method for reliability, which is a quality over time, has been relatively less presented, and there are not many literatures that are clearly summarized. Therefore, this paper focuses on the reliability conformity test to verify that the reliability evaluation scale value of the target is satisfied during the reliability test. To this end, first, we look at the conditions that both consumers and producers can satisfy in terms of the OC curve and find out what sampling methods satisfy the desired level of producer risk and consumer risk. Next, two methods of the reliability sampling methods such as attribute and variable reliability sampling methods are examined. Specifically, the attribute reliability sampling method is a form of sampling plan where n samples are tested for a certain period of T hours and the lot is accepted if the number of failures is less than or equal to a certain number c. On the other hand, the variable reliability sampling method is a form of sampling plan where the lot is accepted if the reliability evaluation scale such as MTBF satisfies a certain standard. Both sampling plans may also use inspection tables.

• Proceedings of the Korean Geotechical Society Conference
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• 2002.10a
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• pp.577-584
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• 2002

We have employed two methods to remove slime at the end of the sampler in clay layers. The first method is a sampling process that harnesses low pressure to clean up the ground around the sampler tip. The second method, in consideration of a disturbed layer, involves a technique of inserting the sampler 50 cm deep into the ground before cleaning up the verge of the sampler by using high pressure. Physical and mechanical properties of these two methods have been compared and analyzed to investigate how different sampling methods affect degree of disturbance. The first method shows little disturbance since the unconfined compression test results in quite greater E$\_$50//q$\_$u/ in the first method than in the second method. On the other hand, the consolidation test results in a slightly greater compression index in the second method than in the first method, when their indexes are compared in the same depth. This suggests that the second method demonstrates less disturbance than the first method does. It is assumed that the second method may reduce disturbance slightly, However, we suspect that choosing any of the two methods would not obtain a considerable difference in sampling.

• ALGAE
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• v.24 no.2
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• pp.111-120
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• 2009

Choosing an appropriate sample unit is a fundamental decision in the design of ecological studies. While numer-ous methods have been developed to estimate organism abundance, they differ in cost, accuracy and precision.Using both field data and computer simulation modeling, we evaluated the costs and benefits associated with twomethods commonly used to sample benthic organisms in temperatc kelp forests. One of these methods, theTargeted Sampling method, relies on different sample units, each "targeted" for a specific species or group ofspecies while the other method relies on coefficients that represent ranges of bottom cover obtained from visual esti-mates within standardized sample units. Both the field data and the computer simulations suggest that both meth-ods yield remarkably similar estimates of organisnm abundance and among-site variability, although the Coefficientmethod slightly underestimates variability armong sample units when abundances are low. In contrast, the twomethods differ considerably in the effort needed to sample these communities; the Targeted Sampling requiresmore time and twice the persormel to complete. We conclude that the Coeffident Sampling metliod may be bettcrfor environmental monitoring programs where changes in mean abundance are of central conccm and resources arelimiting, but that the Targeted sampling methods may be better for ecological studies where quantitative reIation-ships among species and small-scale variability in abundance are of central concern.