• Journal of the Korean Geotechnical Society
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• v.26 no.12
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• pp.71-79
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• 2010

The reliable evaluation of the coefficient of variation (COV) of soil properties is required for the determination of adequate design values and the application of a probabilistic method for the design of geotechnical structures. In this paper, the applicability of methods for estimating the standard deviation, such as the. Three-Sigma Rule and a statistical method, is evaluated by using site investigation data of the Songdo area. It is found that the Three-Sigma Rule provides similar results to those of a statistical method when using $N_{\sigma}$=6 for the property with small variability and $N_{\sigma}$=4.2~5.3 for the property with large variability. It is also observed that, for the undrained shear strength that has an increasing trend with depth, a $N_{\sigma}$ value of 4 is adequate for the evaluation of the variability by the Three-Sigma Rule. The COVs of soil properties determined in this paper could be used in the estimation of the confidence interval and characteristic values of soil properties.

• Journal of the Korean Institute of Landscape Architecture
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• v.30 no.4
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• pp.28-36
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• 2002

The main purpose of this study was to estimate a new regression model to explain the relationship between urban forest and air temperature in summer, 2001. This study consists of two parts: correlation coefficient analysis and regression analysis. According to correlation coefficient analysis, thermal infra-red radiations of the major land use categories found significant difference in each category. However there were no significant relationship between the data (thermal infra-red radiation and NDVI) derived from Landsat-7 ETM+ image and air temperature at Automatic Weather Stations(AWSs). After estimating various regression models for summer air temperature, the final models were chosen. The final regression models consisted of two variables such as forest m and traffic facilities area. The regression models explained over 78% of the variability in air temperatures. The regression models with variables of forest area and traffic facilities area showed that the coefficient of the first variable was even more significant than the second one. However, the negative impact of the traffic facilities area was slightly greater than the positive impact of the forest area. Consequently, the effects of forest area and traffic facilities area were apparent to explain summer air temperature in Seoul. Therefore two policies have the most important implications to mitigate the summer air temperature in Seoul: to expand and to conserve the urban forest; and to change the Oafnc facilities'characteristics. The results from this study are expected to be useful not merely in informing the public that urban forest mitigates summer air temperahne, but in urging the necessity of budgets for trees and managing urban forests. It is recommended that field swey of summer air temperature be Performed for the vadidation of the models. The main purpose of this study was to estimate a new regression model to explain the relationship between urban forest and air temperature in summer, 2001. This study consists of two parts: correlation coefficient analysis and regression analysis. According to correlation coefficient analysis, thermal infra-red radiations of the major land use categories found significant difference in each category. However there were no significant relationship between the data (thermal infra-red radiation and NDVI) derived from Landsat-7 ETM+ image and air temperature at Automatic Weather Stations(AWSs). After estimating various regression models for summer air temperature, the final models were chosen. The final regression models consisted of two variables such as forest m and traffic facilities area. The regression models explained over 78% of the variability in air temperatures. The regression models with variables of forest area and traffic facilities area showed that the coefficient of the first variable was even more significant than the second one. However, the negative impact of the traffic facilities area was slightly greater than the positive impact of the forest area. Consequently, the effects of forest area and traffic facilities area were apparent to explain summer air temperature in Seoul. Therefore two policies have the most important implications to mitigate the summer air temperature in Seoul: to expand and to conserve the urban forest; and to change the traffic facilities'characteristics. The results from this study are expected to be useful not merely in informing the public that urban forest mitigates summer air temperature, but in urging the necessity of budgets for trees and managing urban forests. It is recommended that field survey of summer air temperature be Performed for the vadidation of the models.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.9
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• pp.1340-1349
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• 2012

Increasing the oxidation of fat through exercise is the recommendable method for weight control. Preceding researches have proposed increase in the usage of fat during exercise in stabilized state and under maximum exertion through aerobic training. However, such researches require additional equipment for gas analysis in order to measure the caloric value or gas exchange of subjects during exercise. Such equipments become highly restrictive for those exercise and cause substantially higher cost. According to this, we have presented the method of estimating the maximal fat oxidation point through changes in LF & HF which reflects changes in heart rate and the autonomic nervous system in order to induce exercise for a less restrictive and efficient fat oxidation than existing methods. We have conducted exercise stress test on subject with similar exercise abilities, and have detected the changes in heart rate and changes in LF & HF by measuring changes in fat oxidation and measuring ECG signals at the same time through a gas analyzer. Changes in heart rate and HRV of the subjects during exercising was detected through only the electrocardiographic signals from exercising and detected the point of maximum fat oxidation that differs from person to person. The experiment was carried out 16 healthy males, and used Modified Bruce Protocol, which is one of the methods of exercise stress test methods that use treadmill. The fat oxidation amount during exercise of all the subjects showed fat oxidation of more than 4Fkcal/min in the exercise intensity from about 5 minutes to 10 minutes. The correlation between the maximal fat oxidation point obtained through gas analysis and the point when 60% starts to be relevant in the range from -0.01 to 0.01 seconds for values of R-R interval from changes in heart rate had correlation coefficients of 0.855 in Kendall's method and in Spearman's rho, it showed significant results of it being p<0.01 with 0.950, respectively. Furthermore, in the changes in LF & HF, we have determined the point where the normalized area value starts to become the same as the maximal fat oxidation point, and the correlation here showed 0.620 in Kendall and 0.780 in Spearma of which both showed significant results as p<0.01.

• Journal of Ecology and Environment
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• v.32 no.2
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• pp.67-73
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• 2009

Soil $CO_2$ efflux can vary markedly in magnitude over both time and space, and understanding this variation is crucial for the correct measurement of $CO_2$ efflux in ecological studies. Although considerable research has quantified temporal variability in this flux, comparatively little effort has focused on its spatial variability. To account for spatial heterogeneity, we must be able to determine the number of sampling points required to adequately estimate soil $CO_2$ efflux in a target ecosystem. In this paper, we report the results of a study of the number of sampling points required for estimating soil $CO_2$ efflux using a closed-dynamic chamber in young and old Japanese cedar plantations in central Japan. The spatial heterogeneity in soil $CO_2$ efflux was significantly higher in the mature plantation than in the young stand. In the young plantation, 95% of samples of 9 randomly-chosen flux measurements from a population of 16 measurements made using 72-$cm^2$ chambers produced flux estimates within 20% of the full-population mean. In the mature plantation, 20 sampling points are required to achieve means within $\pm$ 20% of the full-population mean (15 measurements) for 95% of the sample dates. Variation in soil temperature and moisture could not explain the observed spatial variation in soil $CO_2$ efflux, even though both parameters are a good predictor of temporal variation in $CO_2$ efflux. Our results and those of previous studies suggest that, on average, approximately 46 sampling points are required to estimate the mean and variance of soil $CO_2$ flux in temperate and boreal forests to a precision of $\pm$ 10% at the 95% confidence level, and 12 points are required to achieve a precision of $\pm$ 20%.

• Journal of Korean Society of Water and Wastewater
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• v.29 no.4
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• pp.469-479
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• 2015

This study have been conducted to analyze the feasibility of establishing Contamination Warning System(CWS) that is capable of monitoring early natural or intentional water quality accidents, and providing active and quick responses for domestic C_water supply system. In order to evaluate the water quality data set, pH, turbidity and free residual chlorine concentration data were collected and each statistical value(mean, variation, range) was calculated, then the seasonal variability of those were analyzed using the independent t-test. From the results of analyzing the distribution of outliers in the measurement data using a high-pass filter, it could be confirmed that a lot of lower outliers appeared due to data missing. In addition, linear filter model based on autoregressive model(AR(1) and AR(2)) was applied for the state estimation of each water quality data set. From the results of analyzing the variability of the autocorrelation coefficient structure according to the change of window size(6hours~48hours), at least the window size longer than 12hours should be necessary for estimating the state of water quality data satisfactorily.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.50 no.4
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• pp.268-275
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• 2005

Early predictions of crop yields call provide information to producers to take advantages of opportunities into market places, to assess national food security, and to provide early food shortage warning. The objectives of this study were to identify the most useful parameters for estimating yields and to compare two model selection methods for finding the 'best' model developed by multiple linear regression. This research was conducted in two 65ha corn/soybean rotation fields located in east central South Dakota. Data used to develop models were small temporal variability information (STVI: elevation, apparent electrical conductivity $(EC_a)$, slope), large temporal variability information (LTVI : inorganic N, Olsen P, soil moisture), and remote sensing information (green, red, and NIR bands and normalized difference vegetation index (NDVI), green normalized difference vegetation index (GDVI)). Second order Akaike's Information Criterion (AICc) and Stepwise multiple regression were used to develop the best-fitting equations in each system (information groups). The models with $\Delta_i\leq2$ were selected and 22 and 37 models were selected at Moody and Brookings, respectively. Based on the results, the most useful variables to estimate corn yield were different in each field. Elevation and $EC_a$ were consistently the most useful variables in both fields and most of the systems. Model selection was different in each field. Different number of variables were selected in different fields. These results might be contributed to different landscapes and management histories of the study fields. The most common variables selected by AICc and Stepwise were different. In validation, Stepwise was slightly better than AICc at Moody and at Brookings AICc was slightly better than Stepwise. Results suggest that the Alec approach can be used to identify the most useful information and select the 'best' yield models for production fields.

• Journal of the Korean Geotechnical Society
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• v.24 no.5
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• pp.27-35
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• 2008

Geotechnical characteristic values for reliability-based design were analyzed using domestic marine clays. Analysis results indicate that there were close to mean values in oder of Student/Ovesen, Schneider and EN 1990's approach. However, it was found that the EN 1990's approach is inappropriate far estimating geotechnical characteristic value due to low reliability of estimation results. Four approaches had a trend of evaluating characteristic value conservatively with increasing of soil variability. Also, stability and settlement of breakwater subjected to nominal stress with unimproved soft grounds were computed to investigate the effects of estimated characteristic values. In case of using the Schneider's approach, the ratio of allowable bearing capacity/acting loads suggested 65% of that obtained from using the arithmetic mean approach, and showed underestimated value of 13.6% of the settlement obtained from the latter. The comparison of case designs using a representative value from arithmetic mean approach with the proposed approaches, using characteristic value showed that the former was mostly overestimated.

• Journal of Korea Water Resources Association
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• v.51 no.2
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• pp.89-98
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• 2018

Satellite data have attracted attention on research such as natural disaster and climate changes because satellite data is very advantageous for observing a wide range of variability. However, there are still limited spatial and temporal resolutions in satellite data. To overcome these limitations, fusion of various sensors and combination of primary products are used. In this study, surface temperature data of 500 m spatial resolution was produced by fusion of GOCI and MI data of COMS. Also these LST are used with NDVI for estimating TVDI. Soil moisture condition of the Korean peninsula was evaluated by these TVDI and it was compared with SSMI derived from ASCAT surface soil moisture data. As a result, COMS TVDI and ASCAT SSMI showed similar spatial distribution and suggested the possibility of observing the soil moisture using COMS. Therefore, the TVDI estimations can be used as a basis for estimating the high resolution soil moisture, and the application of the COMS can be expanded for various studies.

• Geotechnical Engineering
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• v.3 no.2
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• pp.17-28
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• 1987

Reliability of the cone penetration test (CPT) for estimating shear strength of marine soils is investigated in this paper. For sands, the uncertainty about the angle of internal friction is analyzed. It includes the spatial variation of the soil and the model error in the equation used for interpretation. The most serious uncertainty encountered was the error in the interpretative models. Different methods of interpretation gave quite different values. Subjective opinion was introduced to combine all the interpretative models in a systematic manner. For clays, the undrained Shear Strength from the CPT results is usually =derived by empirical correlations between cone resistance and untrained shear strength from laboratory tests or field vane tests, expressed in terms of cone factor and function of overburden pressure. The uncertainty of the undrained shear strength is caused by data scatter of the cone factor in the correlation, model error of the cone factor, effect of anisotropy, and spatial variability of cone resistance. Among these uncertainties, the most serious one was the data scatter of the cone factor in the .correlation. Between the laboratory test and the field vane test used for correlation, the field vane test was more reliable.

• Journal of Radiation Protection and Research
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• v.41 no.2
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• pp.149-154
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• 2016

Background: Any real application of Bayesian inference must acknowledge that both prior distribution and likelihood function have only been specified as more or less convenient approximations to whatever the analyzer's true belief might be. If the inferences from the Bayesian analysis are to be trusted, it is important to determine that they are robust to such variations of prior and likelihood as might also be consistent with the analyzer's stated beliefs. Materials and Methods: The robust Bayesian inference was applied to atmospheric dispersion assessment using Gaussian plume model. The scopes of contaminations were specified as the uncertainties of distribution type and parametric variability. The probabilistic distribution of model parameters was assumed to be contaminated as the symmetric unimodal and unimodal distributions. The distribution of the sector-averaged relative concentrations was then calculated by applying the contaminated priors to the model parameters. Results and Discussion: The sector-averaged concentrations for stability class were compared by applying the symmetric unimodal and unimodal priors, respectively, as the contaminated one based on the class of ${\varepsilon}$-contamination. Though ${\varepsilon}$ was assumed as 10%, the medians reflecting the symmetric unimodal priors were nearly approximated within 10% compared with ones reflecting the plausible ones. However, the medians reflecting the unimodal priors were approximated within 20% for a few downwind distances compared with ones reflecting the plausible ones. Conclusion: The robustness has been answered by estimating how the results of the Bayesian inferences are robust to reasonable variations of the plausible priors. From these robust inferences, it is reasonable to apply the symmetric unimodal priors for analyzing the robustness of the Bayesian inferences.