• Journal of the Korean Society of Manufacturing Process Engineers
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• v.15 no.4
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• pp.40-45
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• 2016

Interrupted cutting has different cutting characteristics compared with continuous cutting. In interrupted cutting, the workpiece has a groove that regularly impacts the cutting tool and workpiece. Therefore, tool damage occurs rapidly, and this increases the cutting force and surface roughness. In this study, we performed interrupted cutting of carbon steel for machine structure (SM45C) using a coated carbide tool (TT7100). To predict the cutting force, we analyzed the experimental results with a regression analysis. The results were as follows: We confirmed that the factors affecting the principal force and radial force were cutting speed, depth of cut, and feed rate. From the multi-regression analysis, we deduced regression equations, and their coefficients of determination were 89.6, 89.27, and 28.27 for the principal, radial, and feed forces, respectively. This means that the regression equations were significant for the principal and radial forces but not for the feed force.

• Journal of Korea Water Resources Association
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• v.55 no.4
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• pp.257-266
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• 2022

Inundation damage is increasing every year due to localized heavy rain and an increase of rainfall exceeding the design frequency. Accordingly, the importance of hydraulic structures for flood control and defense is also increasing. The hydraulic structures are designed according to its purpose and performance, and the amount of flood is an important calculation factor. However, in Korea, design rainfall is used as input data for hydrological analysis for the design of hydraulic structures due to the lack of sufficient data and the lack of reliability of observation data. Accurate probability rainfall and its temporal distribution are important factors to estimate the design rainfall. In practice, the regression equation of temporal distribution for the design rainfall is calculated using the cumulative rainfall percentage of Huff's quartile method. In addition, the 6^th order polynomial regression equation which shows high overall accuracy, is uniformly used. In this study, the optimized regression equation of temporal distribution is derived using the variable selection method according to the principle of parsimony in statistical modeling. The derived regression equation of temporal distribution is verified through the significance test. As a result of this study, it is most appropriate to derive the regression equation of temporal distribution using the stepwise selection method, which has the advantages of both forward selection and backward elimination.

• Tribology and Lubricants
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• v.23 no.4
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• pp.156-161
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• 2007

The friction test using disk-on-pad type was carried out and regression analysis with friction parameters was applied fur wear loss presumption of motorcycle break disk. The wear loss has an effect on the frictional factor such as applied load, sliding speed, and number of ventilated disk hole. However, it is difficult to know the mutual relation of these factors on wear loss of motorcycle break disk. From this study, the result was shown that the regression analysis equation containing 4 elements were constructed and this equation had a trust of 95% in wear loss presumption of motorcycle break disk. It is possible to apply for another automobile parts.

• 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 Korean Society on Water Environment
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• v.30 no.1
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• pp.8-15
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• 2014

In this study, regression equation was analyzed to estimate non-point source (NPS) pollutant loads in orchard area. Many factors affecting the runoff of NPS pollutant as precipitation, storm duration time, antecedent dry weather period, total runoff density, average storm intensity and average runoff intensity were used as independent variables, NPS pollutant was used as a dependent variable to estimate multiple regression equation. Based on the real measurement data from 2008 to 2012, we performed correlation analysis among the environmental variables related to the rainfall NPS pollutant runoff. Significance test was confirmed that T-P ($R^2=0.89$) and BOD ($R^2=0.79$) showed the highest similarity with the estimated regression equations according to the NPS pollutant followed by SS and T-N with good similarity ($R^2$ >0.5). In the case of regression equation to estimate the NPS pollutant loads, regression equations of multiplied independent variables by exponential function and the logarithmic function model represented optimum with the experimented value.

• Journal of Industrial Technology
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• v.28 no.B
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• pp.175-183
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• 2008

This study reviewed and compared the measured value with the calculated sediment loads value by the existing theory equation, after actually measuring the suspended load, focusing on locality river in Gangwon province. Next, it suggested the application problems of the existing sediment loads calculation equation in case of rivers in Gangwon province, and suggested the proper sediment loads calculation equation to rivers in Gangwon province, after implementing the statistical regression analysis by using the measured data for 5 rears, 2003 ~ 2007.

• Proceedings of the KIEE Conference
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• 2006.07a
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• pp.10-11
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• 2006

The fault location is obtained from the distance relay that detects the fault of the transmission line. In this time, transmission line crews track down the fault location and the reasons. However, because of having error at the fault location of the distance relay, there is a discordance between real and obtained fault location. As this reason, the inspection time for finding fault location can be longer. In this paper, we proposed the statistical (regression) analysis method based on each type of relay's the historical fault location data and the real fault distance data to improve the problems. With finding the regression equation based on the regression analysis, and putting the relay fault location into that equation, the real fault distance is calculated. As a result of the Prediction fault location, the inspection time of transmission line can be reduced.

• Journal of Animal Science and Technology
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• v.66 no.2
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• pp.374-386
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• 2024

To predict the apparent total tract digestibility (ATTD) of crude protein (CP) in dogs we developed an in vitro system using an in vitro digestion method and a statistical analysis. The experimental diets used chicken meat powder as the protein source, with CP levels of 20% (22.01%, analyzed CP value as dry-based), 30% (31.35%, analyzed CP value as dry-based), and 40% (41.34%, analyzed CP value as dry-based). To simulate in vivo digestive processes a static in vitro digestion was performed in two steps; stomach and small intestine. To analyze ATTD the total fecal samples were collected in eight neutered beagle dogs during the experimental period. CP digestibility was calculated by measuring CP levels in dog food, in vitro undigested fraction, and dog feces. In result, CP digestibility at both in vivo and in vitro was increased with increasing dietary CP levels. To estimate in vivo digestibility the co-relation of in vivo ATTD and in vitro digestibility was investigated statistically and a regression equation was developed to predict the CP ATTD (% = 2.5405 × in vitro CP digestibility (%) + + 151.8). The regression equation was evaluated its feasibility by using a commercial diet. The predicted CP digestibility which was calculated by the regression equation showed high index of similarity (100.16%) with that of in vivo in dogs. With that, it would be a feasible non-animal method to predict in vivo CP digestibility by using in vitro digestion method and the proposed linear regression equation in adult dogs.

• Culinary science and hospitality research
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• v.22 no.4
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• pp.143-155
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• 2016

This study conducted a survey and emperical analysis of SNS based consumer experience visits to eat out companies. A total of 350 questionnaires were collected of which 28 were deemed unreliable, leaving 322 responses to be used in the analysis. SPSS 22.0 was employed to carry out frequency analysis, factor analysis, and reliability analysis, correlation analysis, and regression analysis. First, choose eat out properties multiple regression analysis on the impact on customer satisfaction, overall explanatory power of the regression equation $R^2=.521$ (adjusted $R^2=.515$) and F values were analyzed statistically significant the influence of the positive (+) with 86.325 p=0.000 and the regression equation. Content type pursuit of independent variables (B=0.540, p<0.001), seeking safety type (B=0.292, p<0.001) were significantly appeared showed the influence of the positive (+), Pursuit convenience-type (B=0.071, p<0.001) and the pursuit of dignity type (B=0.002, p<0.001) the sub-showed the influence of (-). Second, the multiple regression analysis on the impact on customer satisfaction to others is recommended explanatory power is $R^2=.539$ (adjusted $R^2=.538$) and F values are analyzed by a statistical regression equation p=0.000 and 374.765 in significance showed that the model fit the regression line. Customer satisfaction is the independent variable was the influence of the positive (+) to (B=0.540, p<0.001).

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.1 no.1
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• pp.133-140
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• 2002

The object of this paper is to predict the surface roughness using the experiment equation of surface roughness, which is developed with a full factorial design in turning. $3^3$ full factorial design has been used to study main and interaction effects of main cutting parameters such as cutting speed, feed rate, and depth of cut, on surface roughness. For prediction of surface roughness, the arithmetic average (Ra) is used, and stepwise regression has been used to check the significance of all effects of cutting parameters. Using the result of these, the experimental equation of surface roughness, which consists of significant effects of cutting parameters, has been developed. The coefficient of determination of this equation is 0.9908. And the prediction ability of this equation was verified by additional experiments. The result of that, the coefficient of determination is 0.9718.