• Journal of Food Hygiene and Safety
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• v.32 no.3
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• pp.193-198
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• 2017

Scutellaria baicalensis, Eleutherococcus senticosus, and Angelica sinensis have been used as raw materials for health functional foods. This study was conducted to develop a novel method to analyze levels of baicalin (Scutellaria baicalensis), eleutheroside E (Eleutherococcus senticosus), and ligustilide (Angelica sinensis) simultaneously in health functional foods. The methanol extracted samples were analyzed and quantified via liquid chromatography-tandem mass spectrometry (LC-MS/MS) in the positive ion mode and the negative ion mode using multiple reaction monitoring. Standard calibration curves confirmed linearity with the correlation coefficient ($r^2$) of > 0.99 at $100-2000{\mu}g/mL$ concentration range. The limits of detection (LODs) and limits of quantitation (LOQs) were in the range of $13.0{\sim}35.2{\mu}g/L$ and $39.3{\sim}106.7{\mu}g/L$, respectively. The recovery results ranged between 91.4~109.9% at 3 different concentration levels with relative standard deviations (RSDs) less than 5%. The proposed analytical method was characterized with high accuracy and acceptable precision. The new method would be an effective tool to analyze baicalin, eleutheroside E, and ligustilide simultaneously in raw materials of health functional foods.

• Ocean and Polar Research
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• v.27 no.1
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• pp.15-24
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• 2005

In order to investigate the structures and dynamics of phytoplankton communities, each physicochemical environmental factor, species composition, standing crop, and dominant species were examined in the marine ranching ground of Tongyeong coastal waters from April to October, 2000. During the studies, mean water temperature and salinity were $18.8^{\circ}C$ and 33.1 psu, respectively. DO, SS and transparency varied from 5.43 to 11.39 mg/l, 14.6 to 32.4mg/l and 3.5 to 9.0m, respectively. Light intensities varied from 0.02 to $966{\mu}E/m^2/s$, which decreased with depth. $NH_4-N,\;NO_3-N,\;NO_2-N,\;PO_4-P,\;and\;SiO_2-Si$ were fluctuated from 0.059 to 0.332 mg/l, 0.040 to 0.800 mg/l, 0.001 to 0.468 mg/l, 2.3 to $143.0{\mu}g/l$, and 0.007 to 0.600 mg/l, respectively. chlorophyll a concentrations were fluctuated from 0.7 to $8.9{\mu}g/l$. Among 130 taxa of phytoplankton communities observed. diatoms occupied more than 81.54% of the total species, and the others were dinoflagellates and silicoflagellates. Phytoplankton standing crops ranged from $4.6{\times}10^4\;to\;2.6{\times}10^6cells/l$. In October, the standing crops were at bloom level showing more than $10^6cells/lat$ all stations. Dominant species changed by month and station. Leptocylindrus danicus occupied 59.84% in April and 22.03% in June. Pseudo-nitzschia pungens in August and Chaetoceros socialis and Skeletonema costatum in October were predominant species. In order to investigate factors influencing the total phytoplankton standing crops the correlations between the standing crops of diatoms, dinoflagellates, all phytoplanktons occurred and environmental factors were calculated using a multiple regression analysis. The coefficient of determination $(R^2)$ for total standing crops was 0.63 which explained 63% of variance and that of $R^2$ for diatom was 0.82. In statistical analysis, the results showed that the environmental factors influencing the size of the communities were predominantly water temperature, salinity and silicate.

• Journal of the Korean GEO-environmental Society
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• v.10 no.7
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• pp.7-14
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• 2009

The correlation equation empirically proposed to obtain compression indexes has been proposed to conveniently obtain the value using the soil parameter that can be obtained through simple tests when the number of time of consolidation testing is low or the distribution is large but most of the analyzed regions are limited to certain regions abroad or in the country and multiple data were integrated for use in many cases, thus it is not very reasonable to apply it. Therefore, to establish a new design method considering the uncertainty of the ground, it was selected the Kwangyang port area of which the data have been collected recently thus are relatively more reliable as the subject region of the study in order to maximally reduce the uncertainty of test data. After performing the verification of the normality of the consolidation test data obtained from the selected region and the transformation of variables, a prediction formula was proposed through the regression model with the transformed variables and the proposed regression model with transformed variables was compared with existing empirical equations to verify the suitability of the proposed model formula. After analyzing, it was confirmed that the coefficient of determination was increased after the Box-Cox variable transformation, thus the explanatory power was being enhanced and through the root-mean-square-error method, it was confirmed that the proposed model formula showed the most closed value to the test value.

• Journal of Korean Society of Forest Science
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• v.102 no.2
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• pp.247-254
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• 2013

The objective of this study was to assess the canopy fuel characteristics of five major coniferous species in Korea. This study was also developed allometric equations for the canopy fuel load and canopy base height of the major coniferous species using the allomeric equations of biomass developed by the Korea Forest Research Institute and the data from the $5^{th}$ National Forest Inventory. Among the major coniferous fuel types, Pinus koraiensis stands had the highest mean canopy bulk density, 0.34 kg/$m^3$, followed by Gangwon region Pinus densiflora stands 0.28 kg/$m^3$, Pinus thunbergii stands 0.24 kg/$m^3$, Pinus rigida stands 0.15 kg/$m^3$, Central region Pinus densiflora stands 0.12 kg/$m^3$ and Larix leptolepis stands 0.09 kg/$m^3$. The adjusted multiple coefficient of determination of the developed models ranged from 0.6321 to 0.9950 for canopy fuel load and 0.6390 to 0.8539 for canopy base height.

• Journal of Ecology and Environment
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• v.48 no.2
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• pp.196-206
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• 2024

Background: Most of the biomass equations were developed using sample trees collected mainly from pan-tropical and tropical regions that may over- or underestimate biomass. Site-specific models would improve the accuracy of the biomass estimates and enhance the country's measurement, reporting, and verification activities. The aim of the study is to develop site-specific biomass estimation models and validate and evaluate the existing generic models developed for pan-tropical forest and newly developed allometric models. Total of 140 trees was harvested from each diameter class biomass model development. Data was analyzed using SAS procedures. All relevant statistical tests (normality, multicollinearity, and heteroscedasticity) were performed. Data was transformed to logarithmic functions and multiple linear regression techniques were used to develop model to estimate aboveground biomass (AGB). The root mean square error (RMSE) was used for measuring model bias, precision, and accuracy. The coefficient of determination (R² and adjusted [adj]-R²), the Akaike Information Criterion (AIC) and the Schwarz Bayesian information Criterion was employed to select most appropriate models. Results: For the general total AGB models, adj-R² ranged from 0.71 to 0.85, and model 9 with diameter at stump height at 10 cm (DSH₁₀), ρ and crown width (CW) as predictor variables, performed best according to RMSE and AIC. For the merchantable stem models, adj-R² varied from 0.73 to 0.82, and model 8) with combination of ρ, diameter at breast height and height (H), CW and DSH₁₀ as predictor variables, was best in terms of RMSE and AIC. The results showed that a best-fit model for above-ground biomass of tree components was developed. AGB_Stem = exp {-1.8296 + 0.4814 natural logarithm (Ln) (ρD²H) + 0.1751 Ln (CW) + 0.4059 Ln (DSH₃₀)} AGB_Branch = exp {-131.6 + 15.0013 Ln (ρD²H) + 13.176 Ln (CW) + 21.8506 Ln (DSH₃₀)} AGB_Foliage = exp {-0.9496 + 0.5282 Ln (DSH₃₀) + 2.3492 Ln (ρ) + 0.4286 Ln (CW)} AGB_Total = exp {-1.8245 + 1.4358 Ln (DSH₃₀) + 1.9921 Ln (ρ) + 0.6154 Ln (CW)} Conclusions: The results demonstrated that the development of local models derived from an appropriate sample of representative species can greatly improve the estimation of total AGB.

• Journal of the Korea Society for Simulation
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• v.23 no.1
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• pp.21-31
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• 2014

In this article, data mining simulation is applied to find a proper approach and results of analysis for study of variables related to organization. Also, turnover intention and organizational commitment are used as target (dependent) variables in this simulation. Classification and regression tree (CART) with ensemble methods are used in this study for simulation. Human capital corporate panel data of Korea Research Institute for Vocation Education & Training (KRIVET) is used. The panel data is collected in 2005, 2007, and 2009. Organizational commitment variables are analyzed with combined measure variables which are created after investigation of reliability and single dimensionality for multiple-item measurement details. The results of this study are as follows. First, major determinants of turnover intention are trust, communication, and talent management-oriented trend. Second, the main determining factors for organizational commitment are trust, the number of years worked, innovation, communication. CART with ensemble methods has two ensemble CART methods which are CART with Bagging and CART with Arcing. Comparing two methods, CART with Arcing (Arc-x4) extracted scenarios with very high coefficients of determination. In this study, a scenario with maximum coefficient of determinant and minimum error is obtained and practical implications are presented. Using one of data mining methods, CART with ensemble method. Also, the limitation and future research are discussed.

• Journal of Nutrition and Health
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• v.23 no.3
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• pp.170-178
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• 1990

The aim of the study was to investigate prevalence of obesity among housewives residing in apartments in Taegu city and any relationship of obesity with various factors. Hundred three housewives aged 30-49 years living in apartments (over 30 pyung) were interviewed for socio-economic status, food habit, food intake by a convenient questionnaire, and daily activity by the 24-hour recall. Their weight, height and triceps skinfold thickness were measured. The results were summarized as follows: 1) The percentages of subjects and their spouses with college and higher education were as much as 53.6% and 83.5%, respectively. The commonest family size was four members with two children. 2) The percentages of subjects classified as underweight, normal, overweight, and obesity according to relative body weight(RBW) were 4.9, 44.7, 24.3 and 26.2, respectively. Twenty four percent belonged to obese group according to body mass index(BMI$\geq$25). 3) Food habit score was 12.4 points in average and judged 'good'. The average of daily energy intake was 2247㎉ which corresponded to 112% of RDA and intakes of nutrients except iron exceeded RDA. The means of food habit score and energy intake were not significantly different among 4 groups. 4) Multiple regression analysis was tested to explain a relationship between fatness and various factors. The equation, BMI=25.216+(0.836$\times$family size)-(0.309$\times$education, years)-(0.00503$\times$household work time, minutes), indicates that fatness of housewives was related with family size(+), educational level(-) and household work time(-). These relationships were statistically significant(p<0.001) and R2 (coefficient of determination) was 0.237.

• Korean Journal of Veterinary Service
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• v.42 no.4
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• pp.289-296
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• 2019

A novel rapid procedure with liquid chromatography tandem mass spectrometry (LC-MS/MS) detection has been developed by changing various conditions including sample preparation such as QuEChERS (Quick, Easy, Cheap, Effective, Rugged and Safe) methodology. This work has been involved the optimization and validation of detection method for fluoroquinolones which are widespread used in livestock especially in the chicken. Five grams of homogenized chicken muscle were extracted with QuEChERS EN and acetonitrile containing 5% formic acid and cleaned with anhydrous magnesium sulfate and C₁₈ sorbent. The separation was performed on Acquity UPLC HSS T3 (2.1 mm×100 mm, 1.8 ㎛) column. The mobile phase A and B were composed of water containing 0.1% formic acid and acetonitrile containing 0.1% formic acid, respectively. Flow rate was 0.25 mL/min and column temperate was 40℃. LC-MS/MS with multiple reaction monitoring has been optimized for ten fluoroquinolones (ciprofloxacin, danofloxacin, difloxacin, enrofloxacin, marbofloxacin, norfloxacin, ofloxacin, orbifloxacin, pefloxacin and sarafloxacin). The method developed in this study has been presented good linearity with correlation coefficient (R²) of 0.9971~0.9998. LOD and LOQ values ranged from 0.09 to 0.76 ppb and from 0.26 to 2.29 ppb, respectively. The average recoveries were from 77.46 to 111.83% at spiked levels of 10.0 and 20.0 ㎍/kg. Relative standard deviation (%) ranged 1.28~11.90% on intra-day and 3.10~8.38 % on inter-day, respectively. This analysis method was applicable to the livestock residue laboratories and was expected to be satisfactory for the residue surveillance system.

• Journal of the korean academy of Pediatric Dentistry
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• v.34 no.3
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• pp.430-437
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• 2007

The probability table of Moyers and prediction equation of Tanaka and Johnston that have been the most frequently used, cannot produce accurate prediction when used in Korean because they are based on the Caucasian popularity of the Northern European race. The method of Moyers or Tanaka and Johnston predicts sizes of the unerupted canine and premolars on the basis of the sizes of mandibular incisors. However, some of the recent papers raise a question as to whether the mandibular incisors are the best combination to predict the sizes of the unerupted canine and premolars. The purpose of this study is to determine which sum or combination of sums of permanent tooth widths present the best prediction for the unerupted canine and premolars in a Korean sample, to calculate a specific linear regression equation for this population, and to evaluate the clinical significance. A new linear regression equation was calculated based on the data of 178 Korean young adults(70 women, 108 men, mean age 21.63 years) with complete permanent dentitions. Fifty three more children(28 girls, 25 boys, mean age 14.22 years) were used as a validation sample for the application of the multiple linear regression equation. The conclusions were as follows: 1. The combination of the sums of permanent upper central incisors, lower lateral incisors and upper first molars was the best predictor for the unerupted canine and premolars in this sample($r=0.65{\sim}0.80$). 2. The multiple linear regression equation was calculated including sex and arch as additional predictor variables. male, upper: $Y\;=\;0.332{\times}X_0\;+\;6.195$ male, lower: $Y\;=\;0.332{\times}X_0\;+\;5.269$ female, upper: $Y\;=\;0.332{\times}X_0\;+\;5.929$ female, lower: $Y\;=\;0.332{\times}X_0\;+\;5.003$. The determination coefficient of the equation was 64% and a standard error of the estimate was 0.71mm. 3. In about 97% of the validation sample, the estimation of the tooth width sums of unerupted canine and premolars using the new multiple linear regression equation was smaller than 1mm compaired with the actual values.

• Journal of Soil and Groundwater Environment
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• v.13 no.5
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• pp.57-73
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• 2008

Nitrate concentrations were measured up to 49 mg/L (as $NO_3$-N) and 22% of the samples exceeded drinking water standard in shallow and bedrock groundwater of the northern Nonsan area. Nitrate concentrations showed a significant difference among land use groups. To predict nitrate concentration in groundwater, multiple regression analysis was carried out using hydrogeologic parameters of soil media, topography and land use which were categorized as several groups, well depth and altitude, and field parameters of temperature, pH, DO and EC. Hydrogeologic parameters were quantified as area proportions of each category within circular buffers centering at wells. Regression was performed to all the combination of variables and the most relevant model was selected based on adjusted coefficient of determination (Adj. $R^2$). Regression using hydrogelogic parameters with varying buffer radii show highest Adj. $R^2$ at 50m and 300m for shallow and bedrock groundwater, respectively. Shallow groundwater has higher Adj. $R^2$ than bedrock groundwater indicating higher susceptibility to hydrogeologic properties of surface environment near the well. Land use and soil media was major explanatory variables for shallow and bedrock groundwater, respectively and residential area was a major variable in both shallow and bedrock groundwater. Regression involving hydrogeologic parameters and field parameters showed that EC, paddy and pH were major variables in shallow groundwater whereas DO, EC and natural area were in bedrock groundwater. Field parameters have much higher explanatory power over the hydrogeologic parameters suggesting field parameters which are routinely measured can provide important information on each well in assessment of nitrate contamination. The most relevant buffer radii can be applied to estimation of travel time of contaminants in surface environment to wells.