• Journal of Preventive Medicine and Public Health
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• v.20 no.2 s.22
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• pp.261-269
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• 1987

In order to investigate working conditions of underground coal mines, this work was undertaken to evaluate the respirable dust and the concentration of quartz in Taeback and Kangneung areas. The concentration of quartz was determined by Fourier Transform Infrared Spectrophotometry. The results were as follows; 1) The concentration of respirable dust of drilling and coal face in Taeback and Kangneung areas were as followed; Arithmetic $Mean{\pm}S.D.(mg/m^3)$ Taeback Drilling: $2.00{\pm}1.56$ Taeback Coal Face: $3.74{\pm}3.14$ Kangneung Drilling: $4.55{\pm}4.51$ Kangneung Coal Face: $5.77{\pm}4.53$ Geometric $Mean{\pm}S.D.(mg/m^3)$ Taeback Drilling: $1.34{\pm}2.81$ Taeback Coal Face : $2.55{\pm}2.61$ Kangneung Drilling : $2.44{\pm}3.63$ Kangneung Coal Face: $4.24{\pm}2.37$ 2) Distribution of respirable dust was well fitted to the log-normal distribution and geometric mean value was $log^{-1}\;0.37{\pm}log^{-1}\;0.47(2.34{\pm}2.95)mg/m^3$. 3) The difference of respirable dust concentrations in Taeback and Kangneung areas was not significant statistically (p>0.05). 4) The concentration of quartz of drilling and coal face in Taeback and Kangneung areas were as followed; Arithmetic $Mean{\pm}S.D.(%)$ Taeback Drilling: $6.18{\pm}5.52$ Taeback Coal Face: $1.89{\pm}1.54$ Kangneung Drilling: $3.54{\pm}2.12$ Kangneung Coal Face: $2.05{\pm}3.37$ Geometric $Mean{\pm}S.D.(%)$ Taeback Drilling: $4.24{\pm}2.59$ Coal Face: $1.39{\pm}2.22$ Kangneung Drilling : $2.55{\pm}3.08$ Kangneung Coal Face : $1.24{\pm}2.33$ 5) Distribution of quartz concentrations was well fitted to the log-normal distribution and geometric mean value was $log^{-1}\;0.33{\pm}log^{-1}\;0.45(2.14{\pm}2.82)%$. 6) The difference of quartz concentrations in Taeback and Kangneung areas was not significant (p>0.05), but significant at drilling sites and coal faces (p<0.05).

• Journal of Korean Society for Atmospheric Environment
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• v.2 no.3
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• pp.34-44
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• 1986

Particle size distribution of airborne suspended particulate concentrations according to particle size in the events of yellow sand phenomena, have been measured and analyzed by using Andersen air sampler for four years, January 1982 through December 1985. The conclusions are as follows: 1. Yellow sand phenomena, generally, occur between March and May. 2. The frequent occurrences of yellow sand were observed during March and April and airborne suspended particulate concentrations in the cases of yellow sand appeared to be 2 $\sim$ 3.4 times higher than those of normal conditions. 3. Geometric mean particle diameter and its geometric mean standard deviation by logarithmic normal distribution sheet, were quite close to each other and log-distribution curves showed similar shapes. 4. Analysis by particle size distribution curve showed bi-modal distribution. 5. Concentrations of coarse particles in normal conditions were 1.2 $\sim$ 2 times higher than those of fine particles and, similarly, coarse particle concentrations in yellow sand cases were 1.3 $\sim$ 2.5 times higher than those of fine particles. 6. Concentrations of coarse particles in yellow sand cases were 2 $\sim$ 3.6 times higher than those in normal conditions and those of fine particles were 1.7 $\sim$ 3.5 times higher.

• Asian Journal of Atmospheric Environment
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• v.6 no.4
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• pp.304-313
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• 2012

In this study, the ${\AA}$ngstrom exponent for polydispersed aerosol during dynamic processes was investigated. Log-normal aerosol size distribution was assumed, and a sensitivity analysis of the ${\AA}$ngstrom exponent with regards the coagulation and condensation process was performed. The ${\AA}$ngstrom exponent is expected to decrease because of the particle growth due to coagulation and condensation. However, it is difficult to quantify the degree of change. In order to understand quantitatively the change in the ${\AA}$ngstrom exponent during coagulation and condensation, different real and imaginary parts of the refractive index were considered. The results show that the ${\AA}$ngstrom exponent is sensitive to changes in size distribution and refractive index. The total number concentration decreases and the geometric mean diameter of aerosols increase during coagulation. On the while, the geometric standard deviation approaches monodispersed size distribution during the condensation process, and this change in size distribution affects the ${\AA}$ngstrom exponent. The degree of change in the ${\AA}$ngstrom exponent depends on the refractive index and initial size distribution, and the size parameter changes with the ${\AA}$ngstrom exponent for a given refractive index or chemical composition; this indicates that the size distribution plays an important role in determining the ${\AA}$ngstrom exponent as well as the chemical composition. Subsequently, this study shows how the ${\AA}$ngstrom exponent changes quantitatively during the aerosol dynamics processes for a log-normal aerosol size distribution for different refractive indices; the results showed good agreement with the results for simple analytic size distribution solutions.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.5B
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• pp.431-438
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• 2011

This study investigated the problem of mean-field bias correction under the assumption that the radar and rain gauge rainfall data follow the log-normal distribution. Regression curves for the average, median and mode of the radar and rain gauge rainfall were derived and evaluated for their usefulness. Additionally, these regression curves were compared with those derived under the assumption that the radar and rain gauge data follow the normal distribution. This study investigated the regression results for the Typhoon Meami occurred in 2003 as an example. As results, three regression lines with the radar rainfall as the independent variable were found to underestimate the rainfall, while those with the rain gauge rainfall as the independent variable to overestimate. Among three types of regression curves considered, the result for the average was most appropriate. However this case was found to be inferior to the regression line passing the origin under the assumption of the normal distribution with the rain gauge rainfall as its independent variable. So it was hard to conclude that the consideration of the log-normality on the correction of radar rainfall is beneficial.

• The Korean Journal of Physiology and Pharmacology
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• v.13 no.5
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• pp.367-371
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• 2009

The estimation of 90% parametric confidence intervals (CIs) of mean AUC and Cmax ratios in bioequivalence (BE) tests are based upon the assumption that formulation effects in log-transformed data are normally distributed. To compare the parametric CIs with those obtained from nonparametric methods we performed repeated estimation of bootstrap-resampled datasets. The AUC and Cmax values from 3 archived datasets were used. BE tests on 1,000 resampled data sets from each archived dataset were performed using SAS (Enterprise Guide Ver.3). Bootstrap nonparametric 90% CIs of formulation effects were then compared with the parametric 90% CIs of the original datasets. The 90% CIs of formulation effects estimated from the 3 archived datasets were slightly different from nonparametric 90% CIs obtained from BE tests on resampled datasets. Histograms and density curves of formulation effects obtained from resampled datasets were similar to those of normal distribution. However, in 2 of 3 resampled log (AUC) datasets, the estimates of formulation effects did not follow the Gaussian distribution. Bias-corrected and accelerated (BCa) CIs, one of the nonparametric CIs of formulation effects, shifted outside the parametric 90% CIs of the archived datasets in these 2 non-normally distributed resampled log (AUC) datasets. Currently, the 80~125% rule based upon the parametric 90% CIs is widely accepted under the assumption of normally distributed formulation effects in log-transformed data. However, nonparametric CIs may be a better choice when data do not follow this assumption.

• Communications for Statistical Applications and Methods
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• v.10 no.2
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• pp.607-617
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• 2003

This paper offers a practical comparison of efficiency between local likelihood approach and conventional kernel approach in density estimation. The local likelihood estimation procedure maximizes a kernel smoothed log-likelihood function with respect to a polynomial approximation of the log likelihood function. We use two types of data driven bandwidths for each method and compare the mean integrated squares for several densities. Numerical results reveal that local log-linear approach with simple plug-in bandwidth shows better performance comparing to the standard kernel approach in heavy tailed distribution. For normal mixture density cases, standard kernel estimator with the bandwidth in Sheather and Jones(1991) dominates the others in moderately large sample size.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.1B
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• pp.55-64
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• 2008

The evidence of changes in the climate system is obvious in the world. Nevertheless, at the current techniques for flood frequency analysis, the flood distribution can not reflect climate change or long-term climate cycles. Using a linear regression and a Mann-Kendall test, trends in annual maximum precipitation and flood data for several major gauging sites were evaluated. Moreover, this research considered incorporating flood trends by climate change effects in flood frequency analyses. For five rainfall gauging sites (Seoul, Incheon, Ulleungdo, Jeonju, and Gangneung), upward trends were observed in all gauged annual maximum precipitation records but they were not statistically significant. For three streamflow gauging sites (Andong Dam, Soyanggang Dam, and Daecheong Dam), upward trends were also observed in all gauged annual maximum flood records, but only the flood at Andong Dam was statistically significant. A log-normal trend model was introduced to reflect the observed linear trends in annual maximum flood series and applied to estimate flood frequency and risk for Andong Dam and Soyanggang Dam. As results, when the target year was 2005, 50-year floods of the log-normal trend model were 41% and 21% larger then those of a log-normal model for Andong Dam and Soyanggang Dam, respectively. Moreover, the estimated floods of the log-normal trend model increases as the target year increases.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.50 no.3
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• pp.130-135
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• 2001

In this paper, the distribution characteristics of salt contaminants with the distance from sea in East coast, from Sokcho to Pusan of Korea peninsula were investigated to evaluate the design standard of KEPCO. To get the equivalent salt deposit density(ESDD), conventional brush wiping method was used. As the measuring period is comparatively short, and the measuring interval is long to check the maximum value, acquired ESDD data is very lower than the recommended value in the standard. The measured data didn't follow normal distribution, so it should take the statistical treatment. Through normalizing method, we could get a reliable probability data. In the past investigation, the accumulation characteristics of Japan is consulted to set the criterion, but the climatic condition of Korea is different to Japan. With the comparison of precipitation data and some measured data for long tern accumulation, we could set appropriate accumulation factor.

• The Journal of the Korean life insurance medical association
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• v.3 no.1
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• pp.103-141
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• 1986

The present study was undertaken to establish the decision standard of builds for the insured by using the ratio of weight-for-height as build index. Materials being examined were the ratio of weight-for-height being calculated from the actually measured heights and weights of a total of 15,838 insured persons who were examined medically at Honam Medical Department of Dong Bang Life Insurance Company, Ltd. from June, 1979 to September, 1985. The ratio of weight-for-height is calculated by the following formula. The ratio of weight-for-height(%)=$\frac{weight(kg){\times}100}{\{height(cm)-100\}{\times}0.9(kg)$ The results were as follows: 1. The distribution of the ratio of weight. for-height of the 15,838 insureds follows Log normal distribution being skewed to the left(the direction of underweight). 2. The ratio of weight-for-height were Log transformed to lead to a sym metrical pattern of distribution in which statistical rules are known to be applied more exactly. Thereafter, the establishment of dicision standard of builds was undertaken by using the log of the ratio of weight-for-height as build index. Through all ages in male, the ratio of weight-for-height indicating the range of standard lives including slight overweighted and underweighted lives besides normal lives is 80-130%, and corresponds to $"M-2{\delta}"-"M+1.5{\delta}"$ and to $M{\pm}20%$ ; in female, 85-135%, and corresponds to $"M-2{\delta}"-"M+1.5{\delta}"$ and to $M{\pm}20%$. Through all ages in male, the ratio of weight-for-height indicating the initial level of super-overweighted and super-underweighted lives is 130-150% and 75-80%,and corresponds to $M+3{\delta}\;and\;M-3{\delta}$ and to M+40% and M-25% respectively;in female, 140-160% and 75-80%, and corresponds to $M+3{\delta}\;and\;M-3{\delta}$ and to M+40%-+50% and M-25% respectively. 3. Author's rating table model for builds(a table of weight per height) is proposed. On the table, the ratings for builds, i. e. standard, super-weighted and super-underweighted lives, are listed.

• Proceedings of the Korean Magnestics Society Conference
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• 2007.12a
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• pp.80-81
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• 2007