• 한국식품과학회지
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• 제51권3호
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• pp.227-236
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• 2019

Antioxidant activity in water and ethanol extracts of dried Lycium chinense fruit, as a result of the total phenolic and tannin content, was measured using a number of chemical and biochemical assays for radical scavenging and inhibition of lipid peroxidation, with the analysis being extended by applying a bootstrapping statistical method. Previous statistical analyses mostly provided linear correlation and regression analyses between antioxidant activity and increasing concentrations of phenolics and tannins in a concentration-dependent mode. The present study showed that multiple component or multivariate analysis by applying multiple regression analysis or regression planes proved more informative than linear regression analysis of the relationship between the concentration of individual components and antioxidant activity. In this paper, we represented the multivariate analysis of antioxidant activities of both phenolic and tannin contents combined in the water and ethanol extracts, which revealed the hidden observations that were not evident from linear statistical analysis.

• Earthquakes and Structures
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• 제24권6호
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• pp.429-437
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• 2023

This paper studied the prediction of structural damage indices to buildings after earthquake occurrence using Multiple Linear Regression (MLR) and Fuzzy Linear Regression (FLR) methods. Particularly, the structural damage degree, represented by the Maximum Inter Story Drift Ratio (MISDR), is an essential factor that ensures the safety of the building. Thus, the seismic response of a steel building was evaluated, utilizing 65 seismic accelerograms as input signals. Among the several response quantities, the focus is on the MISDR, which expresses the postseismic damage status. Using MLR and FLR methods and comparing the outputs with the corresponding evaluated by nonlinear dynamic analyses, it was concluded that the FLR method had the most accurate prediction results in contrast to the MLR method. A blind prediction applying a set of another 10 artificial accelerograms also examined the model's effectiveness. The results revealed that the use of the FLR method had the smallest average percentage error level for every set of applied accelerograms, and thus it is a suitable modeling tool in earthquake engineering.

• Geomechanics and Engineering
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• 제29권3호
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• pp.219-228
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• 2022

The most widely used parameter to represent rock abrasiveness is the Cerchar abrasivity index (CAI). The CAI value can be applied to predict wear in TBM cutters. It has been extensively demonstrated that the CAI is affected significantly by cementation degree, strength, and amount of abrasive minerals, i.e., the quartz content or equivalent quartz content in rocks. The relationship between the properties of rocks and the CAI is investigated in this study. A database comprising 223 observations that includes rock types, uniaxial compressive strengths, Brazilian tensile strengths, equivalent quartz contents, quartz contents, brittleness indices, and CAIs is constructed. A linear model is developed by selecting independent variables while considering multicollinearity after performing multiple regression analyses. Machine learning-based regression methods including support vector regression, regression tree regression, k-nearest neighbors regression, random forest regression, and artificial neural network regression are used in addition to multiple linear regression. The results of the random forest regression model show that it yields the best prediction performance.

• 한국농업기계학회:학술대회논문집
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• 한국농업기계학회 2000년도 THE THIRD INTERNATIONAL CONFERENCE ON AGRICULTURAL MACHINERY ENGINEERING. V.II
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• pp.188-195
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• 2000

This study was conducted to measure the moisture content of powdered food using RF impedance spectroscopic method. In frequency range of 1.0 to 30㎒, the impedance such as reactance and resistance of parallel plate type sample holder filled with wheat flour and red-pepper powder of which moisture content range were 5.93∼-17.07%w.b. and 10.87 ∼ 27.36%w.b., respectively, was characterized using by Q-meter (HP4342). The reactance was a better parameter than the resistance in estimating the moisture density defined as product of moisture content and bulk density which was used to eliminate the effect of bulk density on RF spectral data in this study. Multivariate data analyses such as principal component regression, partial least square regression and multiple linear regression were performed to develop one calibration model having moisture density and reactance spectral data as parameters for determination of moisture content of both wheat flour and red-pepper powder. The best regression model was one by the multiple linear regression model. Its performance for unknown data of powdered food was showed that the bias, standard error of prediction and determination coefficient are 0.179% moisture content, 1.679% moisture content and 0.8849, respectively.

• 한국환경과학회지
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• 제23권3호
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• pp.387-397
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• 2014

This study is carried out to propose an empirical equation which can promptly predict the aircraft noise level at a specific point (a receptor) near Jeju international airport by using the information of the flight path data. For this purpose, Analyses of multiple linear regression with the slant distances (SD) calculated from the gate analyses of the flight path data, aircraft noise certification levels with unit of EPNL(effective perceived noise level) and noise levels measured at receptors are performed by SPSS package. From these regression analyses for approach and departure of aircraft, we can propose empirical equations which is statistically significant. The noise levels predicted by these empirical equations are highly correlated the measured data.

• Annals of Occupational and Environmental Medicine
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• 제35권
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• pp.51.1-51.15
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• 2023

Background: Recently, there has been increasing worldwide concern about outdoor air pollution, especially particulate matter (PM), which has been extensively researched for its harmful effects on the respiratory system. However, sufficient research on its effects on cardiovascular diseases, such as hypertension, remains lacking. In this study, we examine the associations between PM levels and hypertension and hypothesize that higher PM concentrations are associated with elevated blood pressure. Methods: A total of 133,935 adults aged ≥ 40 years who participated in the Korean Genome and Epidemiology Study were analyzed. Multiple linear regression analyses were conducted to investigate the short- (1-14 days), medium- (1 and 3 months), and long-term (1 and 2 years) impacts of PM on blood pressure. Logistic regression analyses were conducted to evaluate the medium- and long-term effects of PM on blood pressure elevation after adjusting for sex, age, body mass index, health-related lifestyle behaviors, and geographic areas. Results: Using multiple linear regression analyses, both crude and adjusted models generated positive estimates, indicating an association with increased blood pressure, with all results being statistically significant, with the exception of PM levels over the long-term period (1 and 2 years) in non-hypertensive participants. In the logistic regression analyses on non-hypertensive participants, moderate PM₁₀ (particulate matter with diameters < 10 ㎛) and PM_2.5 (particulate matter with diameters < 2.5 ㎛) levels over the long-term period and all high PM₁₀ and PM_2.5 levels were statistically significant after adjusting for various covariates. Notably, high PM_2.5 levels of the 1 year exhibited the highest odds ratio of 1.23 (95% confidence interval: 1.19-1.28) after adjustment. Conclusions: These findings suggest that both short- and long-term exposure to PM is associated with blood pressure elevation.

• 대한치과교정학회지
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• 제51권1호
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• pp.15-22
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• 2021

Objective: The aim of this study was to evaluate the correlation between the vertical position of maxillary first molar and vertical skeletal measurements in lateral cephalograms by using new linear measurements on the vertical axis of coordinates with calibration. Methods: The vertical position of maxillary first molar (U6-SN), and the conventionally used variables (ConV) and the newly derived linear variables (NwLin) for vertical skeletal patterns were measured in the lateral cephalograms of 103 Korean adults with normal occlusions. Pearson correlation analyses and multiple linear regression analyses were performed with and without calibration using the anterior and posterior cranial base (ACB and PCB, respectively) lengths to identify variables related to U6-SN. Results: The PCB-calibrated statistics showed the best power of explanation. ConV indicating skeletal hyperdivergency was significantly correlated with U6-SN. Six NwLin regarding the position of palatal plane were positively correlated with U6-SN. Each multiple linear regression analysis generated a two-variable model: sella and nasion to palatal plane. Among the three models, the PCB-calibrated model yielded highest adjusted R2 value, 0.880. Conclusions: U6-SN could be determined by the vertical position of the maxilla, which could then be used to plan the amount of molar intrusion and estimate its clinical stability. Cephalometric calibration on the vertical axis of coordinates by using PCB for vertical linear measurements could strengthen the analysis itself.

• 산업기술연구
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• 제25권A호
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• pp.57-65
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• 2005

In this paper, for the highly plastic marine soft clay distributed in west and southern coast of Korean peninsula of Kwangyang and Busan New Port areas, correlation between compression index and other indices representing geotechnical engineering properties such as liquid limit, void ratio and natural water content were analyzed. Appropriate empirical equations of being able to estimate the compressibility of clays in the specific areas were proposed and compared with other existing empirical ones. For analyses of the data and test results, data for marine clays were used from areas of the South Container Port of the Busan New Port, East Breakwater, Passenger Quay, Jungma Reclamation and Reclamation Containment in the 3rd stage in Kwangyang. In order to find the best regression model by using the commercially available software, MS EXCEL 2000, results obtained from the simple linear regression analysis, using the values of liquid limit, initial void ratio and natural water content as independent variables, were compared with the existing empirical equations. Multiple linear regression was also performed to find the best fit regression curves for compression index and other soil properties by combining those independent variables. On the other hands, another software of SPSS for non-linear regression was used to analyze the correlations between compression index and other soil properties.

• 운동영양학회지
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• 제14권2호
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• pp.81-86
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• 2010

The purpose of this study was to identify the factors associated with child's Body Mass Index (BMI) and physical activity. The participants (n = 133) were Korean juveniles (3^rd and 4^th graders) and their parents. They completed a questionnaire packet including the SPARK (Sports, Play, and Active Recreation for Kids) survey and the parent equivalent survey. Correlation, multiple linear regression and binary logistic regression analyses were applied to identify the association between child's BMI and 10 factors of SPARK as predict or variables. 25.6% of the participants were classified as overweight (21.1%) or obesity (4.5%). 3 parental factors including mother's BMI and frequency of mother's and father's physical activity were identified as significant predictors of children's BMI. The 10 variables accounted for 28% of the variance (p<.01) in the linear regression model. These results provide insight into parental factors which are related to a child's BMI and physical activity. Parental role modeling which refers to parents' efforts to model an active lifestyle for children plays an important role.

• 대한가정학회지
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• 제28권1호
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• pp.57-66
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• 1990

The purpose of this study was to investigate the analytical model of the implicit price according to objective and subjective characteristics of housing. The hedonic price regression was used for estimating the implicit price. The subjectives of this study were 1,143 dwellers who live in Seoul metropolitan area. Taejeon, and Jeonju. Satistical analyses were conducted using frequencies, percentiles, mean, and multiple regression. The major findings were as follows: 1. There was a significant difference in the implict price of the apartment between owners and renters. 2. There was a sginificant difference in the implicit price of the apartment among Seoul metropolitan area, Taejeon, and Jeonju. 3. Using a stepwise multiple regression method, the order of variables as they were entered in the model were different between tenure types (owner/renter), and regions(Seoul metroplitan area/Taejeon/Jeonju). 4. The linear model was the most appropriate noe which explained the housing price. 5. Subjective characteristics of housing in Taejeon and Jeonju had an effect on the housing price more than those in Seoul metropolitan area.