• Journal of Welding and Joining
• /
• v.17 no.4
• /
• pp.85-92
• /
• 1999

In GMAW, the spatter is generated because of the variation of the arc state. If the arc state is quantitatively assessed, the control method to make the spatter be reduced is able to develop. This study was attempted to develop the optimal model that could estimate the arc state quantitatively. To do this, the generated spatters was captured under the limited welding conditions, and the waveforms of the arc voltage and of the welding current were collected. From the collected waveforms, the waveform factors and their standard deviations were produced, and the linear and non-linear regression models constituted using the factors and their standard deviations are proposed to estimate the arc state. the performance test to the proposed models was practiced. Obtained results are as follow. From the results of correlation analysis between the factors and the amount of the generated spatters, the standard deviations of the waveform factors have more the multiple regression coefficients than the waveform factors. Because the correlation coefficient between T and {TEX}$T_{a}${/TEX}, and s[T] and s[{TEX}$T_{a}${/TEX}] was nearly one, it was found that these factors have the same effect to the spatter generation. In the regression models to estimate the arc state, it was fond that the linear and the non linear models were also consisted of similar factors. In addition, the linear regression model was assessed the optimal model for estimating the arc state because the variance of data was narrow and multiple regression coefficient was highest among the models. But in the welding conditions which the amount of the generated spatters were small, it was found that the non linear regression model had better the estimation performance for the spatter generation than the linear.

• Korean Journal of Soil Science and Fertilizer
• /
• v.31 no.4
• /
• pp.359-367
• /
• 1998

In order to determine the nitrogen supplying capabilities (NSC) of corn fields, 47 field experiments were performed in Pennsylvania over 3 year from 1986 and NSCs were estimated by the regression analysis with chemical properties and soil attributes. Although the content of $NO_3-N$ in soil showed the best correlation with NSC ($R^2=0.518$), the standardized partial regression coefficient of $NO_3-N$ for NSC was 0.52, with some variations over the years. This value was slightly higher than those of the other properties which ranged from 0.001 to 0.351. Multiple linear regression with soil attributes for the evaluation of NSC was better than simple regression with $NO_3-N$. The coefficient of determination ($R^2$) for the evaluation of NSC was gradually increased; 0.599 with selected chemical properties, 0.698 with quantitative attributes(chemical properties and depth of Ap horizon), and 0.839 with quantitative and selected qualitative soil attributes. Consequently, in order to evaluate NSC, analysis by multiple linear regression with soil attributes was more reliable and better model than by the simple regression model.

• Communications for Statistical Applications and Methods
• /
• v.4 no.2
• /
• pp.541-548
• /
• 1997

In regression model with nested error structure interval estimations on regression coefficients in different stages are proposed. Ordinary least square estimators and generalized least square estimators of the regression coefficients in this model are derived for between and within group model. The confidence intervals are dervied by using independent idstributional properties between regression coefficient estimators and quadratic froms obtained from the model.

• Journal of the Korean Institute of Gas
• /
• v.22 no.2
• /
• pp.52-58
• /
• 2018

The flash point is one of the most important properties to characterize fire and explosion hazard of flammable liquid mixture. In this paper, the flash points of ternary liquid mixture, n-nonane+n-decane+n-tridecane system, were measured using Seta flash closed cup tester. The measured values were compared with the calculated values using Raoult's law and multiple regression analysis. The absolute average errors(AAE) of the results calculated by Raoult's law is $0.6^{\circ}C$. The absolute average errors of the results calculated by multiple regression analysis is $0.4^{\circ}C$. As can be seen from AAE, the calculated values based on multiple regresstion analysis were found to be better than those based on Raoult's law.

• Journal of Korean Academy of Nursing
• /
• v.47 no.3
• /
• pp.357-366
• /
• 2017

Purpose: The aim of this study was to determine the influence of various factors on preterm labor symptoms (PLS) and preterm birth (PB). Methods: This prospective cohort study included 193 women in the second stage of pregnancy. Multiple characteristics including body mass index (BMI), smoking, and pregnancy complications were collected through a self-report questionnaire. Pregnancy stress and PLS were each measured with a related scale. Cervical length and birth outcome were evaluated from medical charts. Multiple regression was used to predict PLS and logistic regression was used to predict PB. Results: Multiple regression showed smoking experience, pregnancy complications and pregnancy specific stress were predictors of PLS and accounted for 19.2% of the total variation. Logistic regression showed predictors of PB to be twins (OR=13.68, CI=3.72~50.33, p<.001), shorter cervix (<25mm) (OR=5.63, CI=1.29~24.54, p<.05), BMI >25 ($kg/m^2$) (OR=3.50, CI=1.35~9.04, p<.01) and a previous PB (OR=4.15, CI=1.07~16.03, p<.05). Conclusion: The results of this study show that the multiple factors affect stage II pregnant women can result in PLS or PB. And preterm labor may predict PB. These findings highlight differences in predicting variables for pretrm labor and for PB. Future research is needed to develop a screening tool to predict the risk of preterm birth in pregnant women.

• Journal of Industrial Technology
• /
• v.22 no.A
• /
• pp.201-210
• /
• 2002

The object of this study is to evaluate the factors affecting the water quality and to propose the influence of dominant factor quantitatively. The correlation analysis was performed to know the correlationship among the water quality items As a result of partial correlation analysis, it was shown that the water quality items are affected by the rainfall item directly. The factor analysis was performed to grasp some number of factors on each point for deducing the items of similar variable characteristics. The four points were divided into different factor groups. It was grasped that $NH_3-N$ and $NO_3-N$ Items have different variable characteristics after comparing the items. The Multiple regression analysis can decrease the number of observation. In the deduced multiple regression formula, it was shown that the rate of T-N, $NH_3-N$ and $NO_3-N$ in the independent variable took about 60% among all the regression formulas.

• Computers and Concrete
• /
• v.26 no.2
• /
• pp.175-183
• /
• 2020

Fly ash has become an important component of concrete as supplementary cementitious material with the development of concrete technology. To make use of fly ash efficiently, four types of fly ash with particle size distributions that are in conformity with four functions, namely, S.Tsivilis, Andersen, Normal and F distribution, respectively, were prepared. The four particle size distributions as functions of the strength and pore structure of concrete were thereafter constructed and investigated. The results showed that the compressive and flexural strength of concrete with the fly ash that conforming to S.Tsivilis, Normal, F distribution increased by 5-10 MPa and 1-2 MPa, respectively, compared to the reference sample at 28 d. The pore structure of the concrete was improved, in which the total porosity of concrete decreased by 2-5% at 28 d. With regarding to the fly ash with Andersen distribution, it was however not conducive to the strength development of concrete. Regression model based on the grey multiple linear regression theory was proved to be efficient to predict the strength of concrete, according to the characteristic parameters of particle size and pore structure of the fly ash.

• Proceedings of the KSRS Conference
• /
• 2004.10a
• /
• pp.302-305
• /
• 2004

The aim of this study is to apply and crossvalidate a spatial logistic multiple-regression model at Boun, Korea, using a Geographic Information System (GIS). Landslide locations in the Boun area were identified by interpretation of aerial photographs and field surveys. Maps of the topography, soil type, forest cover, geology, and land-use were constructed from a spatial database. The factors that influence landslide occurrence, such as slope, aspect, and curvature of topography, were calculated from the topographic database. Texture, material, drainage, and effective soil thickness were extracted from the soil database, and type, diameter, and density of forest were extracted from the forest database. Lithology was extracted from the geological database and land-use was classified from the Landsat TM image satellite image. Landslide susceptibility was analyzed using landslide-occurrence factors by logistic multiple-regression methods. For validation and cross-validation, the result of the analysis was applied both to the study area, Boun, and another area, Youngin, Korea. The validation and cross-validation results showed satisfactory agreement between the susceptibility map and the existing data with respect to landslide locations. The GIS was used to analyze the vast amount of data efficiently, and statistical programs were used to maintain specificity and accuracy.

• Journal of Environmental Health Sciences
• /
• v.16 no.2
• /
• pp.11-20
• /
• 1990

To investigate ionic characteristics of acid rain by the succeeding rainfall. bulk precipitation was collected every each 5mm rainfall from march to october 1990 at Dae Jeon area. pH, sulfate nitrate, chloride, ammonium ion was measured and analyzed. The result was as follows: 1. The weighted average pH of rain was 5.1$\pm$ 0.72(4.15~7.6) and rain pH less than 5.5 was appeared 51.3% 2. Average ion concentrations of sulfate, nitrate, chloride and ammonium ion was 125.12 $\mu$eq/l, 62.38 $\mu$eq/l, 31.95 $\mu$eq/l, 66.6 $\mu$eq/l and rates of each anions was 57%, 28.4%, 14.6% and rate of sulfate by nitrate was 2 times. 3. There is no correlations time interval of rainfall and Ion concentration change. 4. From initial to 15mm rainfall, each ion concentrations were decreased. and average concentration of pH, SO$^{-2}_{4}$, Cl ion concentration was increased in the succeeding rainfall 5. Only sulfate ion was correlated by the simple regression analysis with pH except NO$^{-}_{3}$, Cl$^{-}$ and NH$_{4}^{+}$ Cl$^{-}$ correlation coefficient was very high at the multiple regression analysis with pH. 6. Simple & multiple correlation coefficient among anions and NH$^{+}_{4}$ was very high especially N$^{+}_{4}$ and SO$^{2-}_{4}$ at simple regression analysis and SO$^{-2}_{4}$ and NO$_{3}^{-}$, Cl$^{-}$, NH$_{4}^{-}$ at multiple regression analysis.

• Journal of Navigation and Port Research
• /
• v.27 no.2
• /
• pp.163-170
• /
• 2003

This empirical study takes the activation approach for the competitive power of Korean shipping companies in the Korea-China liner routes. Data for this study were collected from Korea/ China/ 3rd flag shipping companies through the 500 questionnaires. The data of 250 respondents were analyzed statistically to verify the hypotheses and to induce Regression Equation which could predicts the influencing level of the determinants to competitive advantage for Korean shipping companies on Korea-China Liner Shipping Routes. Factor Analysis/ Cronbach's Alpha/ Principal Analysis/ Multiple Regression Analysis were used in order to test the hypotheses for the empirical study.