• Journal of Ocean Engineering and Technology
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• v.28 no.3
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• pp.254-259
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• 2014

The infrared signature of a ship is largely influenced by the ocean environment of the operating area, which has been known to cause large changes in the signature. As a result, the weather condition has to be clearly set for an analysis of the infrared signatures. It is necessary to analyze meteorological data for all the oceans where the ship is supposed to be operated. This is impossibly costly and time consuming because of the huge size of the data. Therefore, the creation of a standard environmental variable for an infrared signature research is necessary. In this study, we compared and analyzed sampling methods to represent ocean data close to the Korean peninsula. In order to perform this research, we collected ocean meteorological records from KMA (Korea Meteorological Administration), and sampled these in numerous ways considering five variables that are known to affect the infrared signature. Specifically, a simple random sampling method for all the data and 1-D, 2-D, and 3-D stratified sampling methods were compared and analyzed by considering the mean square errors for each method.

• Journal of Environmental Health Sciences
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• v.16 no.2
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• pp.1-10
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• 1990

This study was performed to evaluate a applicability of TCM(Texas Climatological Model) model to a industrial area sush as CUNSAN and a possibility to provide necessary informaitons for air quality management. The air pollutants were measured at 6 sampling sites of GUNSAN industrial area from june to july in 1989. The model was checked by comparing the observed data with estimated data. The meteorological data for wind direction and wind speed were obtained from the observatory station in GUNSAN. The results are summarized as follows. 1. Average concentrations of air pollutants at all sampling sites were SO$_{2}$ 0.011-0.019 ppm. NO$_{2}$ 0.012-0.017 ppm. CO 0.6-1.0 ppm. TSP 45.8-64.2 $\mu$g/m$^{3}$. 2. The emission amounts show that point source are in general higher than area source. 3. As a results of correlation analysis, relationship between SO$_{2}$ concentration in the observed value and estimated value showed positive significance.(r = 0.766) 4. The sulfer content of the 1.6% at present to 0.8%, which means a 53.3% reduction. By controlling stack height could be lowered 14.5%, but the effective way of emission control is use of the lower sulfer fuels than controlling stack height. 5. The ratio between SO$_{2}$ contration in the observed value and estimated value showed 1.05. There-fore, the TCM model was quite effective in predicting air quality in GUNSAN industrial area.

• Nuclear Engineering and Technology
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• v.54 no.1
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• pp.414-422
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• 2022

Presented in this paper is a methodology for combining a Bayesian statistical approach with Data Quality Objectives (a structured decision-making method) to provide increased levels of confidence in analytical data when approaching a waste boundary. Development of sampling and analysis plans for the characterisation of radioactive waste often use a simple, one pass statistical approach as underpinning for the sampling schedule. Using a Bayesian statistical approach introduces the concept of Prior information giving an adaptive sample strategy based on previous knowledge. This aligns more closely with the iterative approach demanded of the most commonly used structured decision-making tool in this area (Data Quality Objectives) and the potential to provide a more fully underpinned justification than the more traditional statistical approach. The approach described has been developed in a UK regulatory context but is translated to a waste stream from the Fukushima Daiichi Nuclear Power Station to demonstrate how the methodology can be applied in this context to support decision making regarding the ultimate disposal option for radioactive waste in a more global context.

• Journal of agricultural medicine and community health
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• v.34 no.2
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• pp.202-213
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• 2009

Objectives: The aim of this study was to compare health related behaviors among adolescents in the rural area with those in the urban area in Korea. Methods: The data source was the Korea Youth Risk Behavior Web-based Survey in 2005. With two stage cluster sampling, a total of 58,224 sample was selected from 799 middle and high schools nationwide. The area was classified into county area, small to medium city, and large city, and then the county area was considered as a rural area. Data was analyzed with STATA 9.0 using the method of complex survey data analysis considering sampling weight, strata, and primary sampling unit. Results: The prevalence of health related behaviors among adolescents in the rural area was higher than the city area as following health behaviors: smoking behaviors of smoking experience, smoking experience before entrance to middle school; drinking behaviors of frequent drinking, high risk behaviors with drinking; dietary behaviors of omitting of lunch or dinner, less intake of fruits or milk, more intake of cooky; oral hygiene of less tooth brushing, less preventive oral care, more oral symptoms and less dentist visit; safety behaviors of less wearing of safety belt or protective device; general hygiene of less hand washing before meal or after visiting rest room. Conclusions: The health behaviors among adolescents in the rural area were generally poorer than the city area. The results showed national health program for adolescents should be conducted primarily for those in rural areas. Further study is needed to explore the factors related with the discrepancy of health behaviors between the rural and urban area.

• The Korean Journal of Applied Statistics
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• v.28 no.3
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• pp.495-509
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• 2015

We study a classification problem of significant differences in the proportion of two groups known as the unbalanced classification problem. It is usually more difficult to classify classes accurately in unbalanced data than balanced data. Most observations are likely to be classified to the bigger group if we apply classification methods to the unbalanced data because it can minimize the misclassification loss. However, this smaller group is misclassified as the larger group problem that can cause a bigger loss in most real applications. We compare several classification methods for the unbalanced data using sampling techniques (up and down sampling). We also check the total loss of different classification methods when the asymmetric loss is applied to simulated and real data. We use the misclassification rate, G-mean, ROC and AUC (area under the curve) for the performance comparison.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.10C
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• pp.965-975
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• 2005

In this paper, we propose and evaluate joint carrier and sampling frequency offset estimation schemes based on the channel estimation sequences in PLCP (Physical Layer Convergence Procedure) preamble for the proper and effcient synchronization of the MB-OFDM WB (Multi-Band Orthogonal Frequency Division Multiplexing Ultra Wide Band) systems which have recently drawn explosive attention for future W-PAN (Wireless Personal Area Network) applications. In the joint estimation schemes, we first estimate the sampling frequency offset, and then estimate the carrier frequency offset using the estimated sampling frequency offset. Moreover, to improve the reliability of the estimated offset values, each process uses a combination scheme based on weighting factors. Simulation results using IEEE 802.15 Task Group 3a UWB channel models reveal that the estimation scheme using the simple weighting factors based on easily-measurable received signal power of each sub-channel shows favorably comparable performance to the ideal scheme using the weighting factors based on the perfectly-estimated frequency response of the channel.

• Asian Journal for Public Opinion Research
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• v.3 no.4
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• pp.156-175
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• 2016

This paper considers whether random sampling always produces more accurate survey results in the case of South Korea. We compare information from the 2010 census to the demographic variables of three public opinion surveys from South Korea: Gallup Korea's Omnibus Survey (Survey A) is conducted every two months by Gallup Korea; the annual Social Survey (Survey B) is conducted by Statistics Korea (KOSTAT); the Korean General Social Survey (KGSS or Survey C) is conducted annually by the Survey Research Center (SRC) at Sungkyunkwan University (SKKU). Survey A uses quota sampling after randomly selecting the neighborhood and initial addresses; Survey B uses random sampling, but allows replacements in some situations; Survey C uses simple random sampling. Data from more than one year was used for each survey. Our analysis suggests that Survey B is the most representative in most respects, and, in some respects, Survey A may be more representative than Survey C. Data from Survey C was the least stable in terms of representativeness by geographical area and age. Single-person households were underrepresented in both Surveys A and C, but the problem was more severe in Survey A. Four-person households and married persons were both over-represented in Survey A. Less educated people were under-represented in both Survey A and Survey C. There were differences in income level between Survey A and Survey C, but income data was not available for Survey B or the census, so it is difficult to ascertain which survey was more representative in this case.

• Journal of Korean Society of Forest Science
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• v.109 no.3
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• pp.291-299
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• 2020

The purpose of this study was to propose the most cost-effective sampling method, by analyzing the cost of forest resource investigation per sampling method for the planned harvesting area of in Chunyang-myeon, Byeonghwa-gun, Gyeongsangbuk-do, Korea. For this study, three sampling methods were selected: random sampling method, systematic sampling method, and line transect method. For each method, sample size, hourly wage, number of sample points, survey time, travel time, the sample error rate of the estimated average volume, and the desired sampling error rate were used to calculate the cost of forest resource inventories. Thus, 10 sampling points were extracted for each sampling method, and the factors required for cost analysis were calculated via a field survey. As a result, the field survey cost per ha using the random sampling method was found to be have the lowest cost, regardless of the desired sampling error rate, followed by the systematic sampling method, and the line transect method.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.16-41
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• 2020

Geospatial input setting to represent the reality of spatial distribution or quantitative property within model has become a major interest in earth system simulation. Many studies showed the variation of grid resolution could lead to drastic changes of spatial model results because of insufficient surface property estimations. Hence, in this paper, the authors proposed Monte Carlo Integration (MCI) to apply spatial probability (SP) in a spatial-sampling framework using a three-dimensional point cloud (3DPC) to keep the optimized spatial distribution and area/volume property of buildings in urban area. Three different decision rule based building identification results were compared : SP threshold, cell size, and 3DPC density. Results shows the identified building area property tend to increase according to the spatial sampling grid area enlargement. Hence, areal building property manipulation in the sampling frameworks by using decision rules is strongly recommended to increase reliability of geospatial modeling and analysis results. Proposed method will support the modeling needs to keep quantitative building properties in both finer and coarser grids.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.6
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• pp.527-534
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• 2017

The purpose of this study is to develop unmanned equipment that can automatically move to the desired point and measure water quality at the correct depth. For this purpose, we constructed a water sampling lift and water sampling container, an unmanned vessel equipped with a VRS-GPS, an acoustic echo sounder, and a water quality sensor. Also, we developed an automatic navigation algorithm and program, an automatic water sampling program, and a water quality map generation program. As a result of the experiment in the detention pond, the unmanned vessel sailed along the planned route with an accuracy of about 93% within the error range of 3m. In addition, the water quality sensor installed in the lift was able to acquire the water quality of the target area in real time and transmit it to the server via wireless Internet, and it was possible to monitor the water quality of each site in real time. Through field experiments, the water sampling lift was able to control the desired length with an accuracy of about 94%. The stretch length accuracy experiment of the water sampling lift was impossible to measure directly in the water, so it was replaced land-based experiment. We also found some unstable problems due to the weight of the water sampling lift and the weight of the air compressor to operate the water container. Except these two problems, we accomplished purpose of this study. An automated water quality measurement method using an unmanned vessel can be used to measure the quality of water in a difficult to access area and to secure the safety of the worker.