• Archives of Pharmacal Research
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• v.28 no.5
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• pp.598-603
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• 2005

The purpose of this study was to determine the influence of weight with gentamicin assay error on the Bayesian and nonlinear least squares regression analysis in 12 Korean appen dicitis patients. Gentamicin was administered intravenously over 0.5 h every 8 h. Three specimens were collected at 48 h after the first dose from all patients at the following times, just before regularly scheduled infusion, at 0.5 h and 2 h after the end of 0.5 h infusion. Serum gentamicin levels were analyzed by fluorescence polarization immunoassay technique with TDxFLx. The standard deviation (SD) of the assay over its working range had been determined at the serum gentamicin concentrations of 0, 2, 4, 8, 12, and 16 ${\mu}g$/mL in quadruplicate. The polynominal equation of gentamicin assay error was found to be SD (${\mu}g$/mL) = 0.0246-(0.0495C)+ (0.00203C$^2$). There were differences in the influence of weight with gentamicin assay error on pharmacokinetic parameters of gentamicin using the nonlinear least squares regression analysis but there were no differences on the Bayesian analysis. This polynominal equation can be used to improve the precision of fitting of pharmacokinetic models to optimize the process of model simulation both for population and for individualized pharmacokinetic models. The result would be improved dosage regimens and better, safer care of patients receiving gentamicin.

• Journal of the Korean Society of Safety
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• v.34 no.1
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• pp.34-39
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• 2019

Flash point is the important indicator to determine fire and explosion hazards of liquid solutions. In this study, flash points of n-propanol+n-hexanol and n-butanol+n-hexanol systems were obtained by Seta flash tester. The methods based on UNIFAC equation and multiple regression analysis were used to calculate flash point. The calculated flash point was compared with the experimental flash point. Absolute average errors of flash points calculated by UNIFAC equation are $2.9^{\circ}C$ and $0.6^{\circ}C$ for n-propanol+n-hexanol and n-butanol+n-hexanol, respectively. Absolute average errors of flash points calculated by multiple regression analysis are $0.5^{\circ}C$ and $0.2^{\circ}C$ for n-propanol+ n-hexanol and n-butanol+n-hexanol, respectively. As can be seen from AAE, the values calculated by multiple regression analysis are noticed to be better than the values by the method based on UNIFAC eauation.

• Journal of agricultural medicine and community health
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• v.7 no.1
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• pp.80-89
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• 1982

In order to observe the endemic status of Clonrchis sinensis infection in Samrangjin eup, Milyang gun, Kyongsang nam do, a total number of 294 stool specimens were collected from the inhabitants who lived in the basin of the Nakdong river. The specimens were examined by cellophane thick smear technique and Stoll's egg dilution technique during the period from May to June 1983. The epidemiological status was analysed statistically by the regression equation and catalytic curv with the results obtained from this area. The results are as follows : 1) The infestation rate of Clonorchis sinensis in 294 was 49.0%. 2) No remarkable difference was observed between male (52.5%) and female (44.8%). 3) Average E.P.G. by Stoll's egg dilution technique in this area was 9,597. 4) The degree of the intensity of Clonorchis infection by E.P.G. count was distributed as 10.5% in very heavy infection, 14.7% in heavy infection, 47.4% in moderate infection, and 29.3% in light infection. 5) The intensity of endemicity in this area was represented with the regression equation calculated with the cumulative percentages of E.P.G. counts. Regression equation was y=3.40+1.23 log x and Cs. $D._{50}$ was 19.99. 6) The two stage catalytic model was applied and the calculation lead to the equation $y=1296(e^{-0.008t}-e^{-0.035t})$ ; a=0.035 > b=0.008 in this surveyed area. 7) Other helminthic infection rate in this area was 7.1% in A. lumbricoides, 9.5% in T. trichiura and 4.1% in E. vermicularis respectively.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.4
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• pp.109-118
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• 2011

In this research estimated accuracies that were results in all the area of filtering of the plane equation that was used by whole data set, and regional of filtering that was driven by the plane equation for each vertual Grid. All of this estimates were based by all the area of filtering that deduced the plane equation by multiple linear regression analysis that was used by ground data set. Therefore, accuracy of all the area of filtering that used whole data set has been dropped about 2~3% when average of accuracy of all the area of filtering was based on ground data set while accuracy of Regional of filtering dropped 2~4% when based on virtual Grid. Moreover, as virtual Grid which was set 3~4 cm was difference about 2% of accuracy from standard data. Thus, it leads conclusion of set 3~4 times bigger size in virtual Grid filtering over LiDAR scan gap will be more appropriated. Hence, the result of this research allow us to conclude that there was difference in average accuracy has been noticed when we applied each different approaches, I strongly suggest that it need to research more about real topography for further filtering accuracy.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.57 no.3
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• pp.296-300
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• 2012

Discrimination of geographic origin of agricultural products is a important issue in Korea because the price difference between Korean domestic and imported cereals is a key among some reasons. NIRS (Near Infrared Reflectance Spectroscopy) has been applied to classify the geographical origin of soybeans. Total 135 samples (Korean domestic 92 and foreign 43) were used to obtain calibration equation through 400~2,500 nm wavelength. The math treatment with 1st derivative and 4 nm gap and the modified partial least squares(MPLS)regression was outstanding for calibration equation. The standard error of calibration and determination coefficient in calibration set(n=115) was 6.65 and 0.98, respectively. And it showed that the extra 20 samples for validation equation were identified their authentication correctly. This study describes that the application of NIRS would be possible for discrimination of geographical origin between Korean domestic and imported soybeans.

• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.5
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• pp.125-130
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• 2009

Storage function method which considers the non-linearity of the relationship between rainfall and runoff has been frequently used to predict runoff in a basin and a flood pattern. However, it is time-consuming to estimate appropriate parameters of every basin and rainfall event, which requires the empirical parameter equation applicable in Korea. In this study, multiple regression analysis is used to develop empirical equations to estimate parameters of Storage Function method using basin characteristics. The basin area, maximum stream length, and stream slope are considered as the basin characteristics as the result of the regression analysis. Collinearity is removed and trial-and-error method is used to choose the most descriptive parameters to the dependent variables in Han River basin which is divided into 30 subbasins. The developed equations are validated using the rainfall events in MunMak gauging station and named as 'Han River equation'. The equation could provide the useful information about Storage Function method parameter to calculate runoff from a basin and predict river stage.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.9
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• pp.4323-4326
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• 2016

Background: The cancer mortality-to-incidence ratio (MIR) has been established as an important measure of health disparities in local and global circumstances. Past work has corroborated a linkage between the colorectal cancer MIR and the World Health Organization (WHO) Health System ranking. The literature further documents many Asian countries having incomplete cancer registries and a lack of comprehensive colorectal cancer screening guidelines. Materials and Methods: The colorectal cancer MIR values for 23 Asian countries were calculated from data obtained from the 2012 GLOBOCAN database. The 2000 World Health Organization (WHO) Health System rankings were used as a proxy for health system infrastructure and responsiveness. A regression equation was calculated with the MIR as the dependent variable and the WHO Health System ranking as the independent variable. Predicted MIR values were next calculated based on the regression results. Actual MIR values that exceeded 0.20 from the predicted MIR were removed as 'divergent' points. The regression equation was then re-plotted. Goodness-of-fit for both regressions was assessed by the R-squared test. Results: Asian countries have a relatively wide colorectal cancer MIR range, from a minimum of 0.24 to a maximum of 0.86. For the full dataset, the adjusted R-squared value for this regression was 0.53. The equation was then used to calculate a predicted MIR, whereby two data points were identified as 'divergent' and removed. The adjusted R-squared for the edited dataset increased to 0.66. Conclusions: Asian countries have a marked range in their colorectal cancer MIR values and there is a strong correlationwith the WHO Health System ranking. These results corroborate the contribution of the MIR as a potentially robust tool in monitoring changes in colorectal cancer care for Asian nations.

• International Journal of Highway Engineering
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• v.14 no.6
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• pp.121-129
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• 2012

PURPOSES : Traffic accidents at intersections have been increased annually so that it is required to examine the causations to reduce the accidents. However, the current existing accident models were developed mainly with non-linear regression models such as Poisson methods. These non-linear regression methods lack to reveal complicated causations for traffic accidents, though they are right choices to study randomness and non-linearity of accidents. Therefore, to reveal the complicated causations of traffic accidents, this study used structural equation methods(SEM). METHODS : SEM used in this study is a statistical technique for estimating causal relations using a combination of statistical data and qualitative causal assumptions. SEM allow exploratory modeling, meaning they are suited to theory development. The method is tested against the obtained measurement data to determine how well the model fits the data. Among the strengths of SEM is the ability to construct latent variables: variables which are not measured directly, but are estimated in the model from several measured variables. This allows the modeler to explicitly capture the unreliability of measurement in the model, which allows the structural relations between latent variables to be accurately estimated. RESULTS : The study results showed that causal factors could be grouped into 3. Factor 1 includes traffic variables, and Factor 2 contains turning traffic variables. Factor 3 consists of other road element variables such as speed limits or signal cycles. CONCLUSIONS : Non-linear regression models can be used to develop accident predictions models. However, they lack to estimate causal factors, because they select only few significant variables to raise the accuracy of the model performance. Compared to the regressions, SEM has merits to estimate causal factors affecting accidents, because it allows the structural relations between latent variables. Therefore, this study used SEM to estimate causal factors affecting accident at urban signalized intersections.

• Journal of Forest and Environmental Science
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• v.24 no.3
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• pp.155-158
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• 2008

Site index is the essential tool for forest management to estimate the productivity of forest land Generally, site index equation is developed and used by relationship between stand age and dominant tree heights. However, there is a limit to use the site index equation in the application of variable ages, environmental influence, and estimation of site index for unstocked land. Therefore, it was attempted to develop a new site index equations based on various environmental factors including site and topographical variables. This study was conducted to develop regional site index equations based on the relationship between site index and soil factors for Pinus densiflora. Environmental factors that obtained from GIS application, were selected by stepwise-regression. Site index Equation was estimated by multiple regression from selected factors. Four environmental factors were selected in the final site index equations by stepwise regression. It was observed that coefficients of determination for site index equations were ranged from 0.34 which seem to be relatively low but good enough for estimation of forest stand productivity. The site index equations developed in this study were also verified to be useful by three evaluation statistics such as model's estimation bias, model's precision and mean square error type of measure.

• Journal of the Korean GEO-environmental Society
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• v.11 no.12
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• pp.63-74
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• 2010

Normally consolidated and slightly overconsolidated soft clay layer is widely distributed in the south coast of Korea. To ensure the efficient and economical construction design of any structure to be built on this soft soil, exhaustive studies related to geotechnical and physical engineering properties are required. In this study, the relationship of the physical properties of southern Gwangyang marine clay in the Korea Peninsula were examined, including natural water content, specific gravity, total unit weight, initial void ratio, liquid limit, plastic limit, and physical properties of activity and soil parameters. For the parameter relationship analysis, the latest relatively reliable data on the large harbor construction work were used, optimum values were deducted with linear regression and non-linear regression between soil parameters, water content or initial void ratio appears to be very large. Moreover, in the linear and involution pattern regression, equal coefficient of determination appeared. The relationship of the different parameters was shown to be excellent in the non-linear regression of involution equation and exponential equation pattern compared with the findings of linear regression analysis.