• KOREAN JOURNAL OF CROP SCIENCE
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• v.51 no.4
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• pp.269-273
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• 2006

Multiple linear regression analysis was conducted to interpretate the relationship between sesame grain yield and its components under early sowing cropping condition. The t test showed that stem length, number of capsules per plant, 1000 seeds weight and seed weight per plant gave significant contribution to sesame grain yield, therefore those variables were assumed to mostly influenced components to grain yield of sesame. In the stepwise regression analysis, the predicted equation for sesame grain yield per square meter (Y) was Y = -7.900 + 0.150X1 + 0.461X5 + 15.553X6 + 8.543X7. Meanwhile, F value showed that stem length, number of capsules per plant and seed weight per plant gave significant contribution to sesame grain yield, while 1000 seeds weight did not significantly show. Based on the results, it is reasonable to assume that high yield. potential of sesame under early sowing cropping condition would be obtained by selecting breeding lines with long stem length, number of capsules per plant, and seed weight per plant, which was different result at the late sowing cropping condition in which days to flowering and maturity were assumed to be more affected factors to the sesame grain yield.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.9
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• pp.35-44
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• 2014

This study was to secure the safety of poor appearance distribution concrete poles effectively and to reduce the replacement costs of them by developing a soundness evaluation index. The researcher of this study investigated poor appearance types of concrete pole, collected 53 of test samples, and tested pole strength. As a result of strength test, only 17 percent of poor appearance concrete poles were below 2.0 of safety factor spec. As results of multiple regression analysis, it is verified that surface air void, horizontal crack, net-shaped crack, elapsed year, vertical crack, and deterioration in concrete compressive strength have statistically negative effects on safety factor of concrete poles in a significant level. The researcher set up a soundness evaluation index by using multiple regression equation, and suggested that poor appearance concrete poles should be replaced or reinforced only in case of soundness evaluation score of 150 or above.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.6 no.4
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• pp.57-64
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• 2007

In the recent years, development of machine tool with high speed feeding system have brought a rapid increase in productivity. Practically, thermal deformation problem due to high speed is, however, become a large obstacle to realize high precision machining. In this study, therefore, the construction of automatic error compensation system to control thermal deformation in high speed feeding system with real time is proposed. To attain this purpose, high speed feeding system with feeding speed 60mm/min is developed and experimental equation for relationship between thermal deformation and temperature of ball screw shaft using multiple regression analysis is established. Furthermore, in order to analyze thermal deformation error, compensation coefficient is determined and thermal deformation experiments is carried out. From obtained results, it is confirmed that automatic error compensation system constructed in this study is able to control thermal deformation error within $15{\sim}20{\mu}m$.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.851-856
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• 1997

This study is on the estimation of the tool temperature for different tool nose radius and cutting conditions in turning. The experiment has been performed in different cutting conditions such as cutting speed, feed rate, and depth of cut for the tool nose radius, 0.4R, 0.8R using SMC workpiece materials. Tool temperature is measured using thermo-couple which is embedded in the insert tip. Using a multiple linear regression method, the tool temperature can be determined as an exponential equation with cutting variables and tool nose diameters for different tool materials. The equations determined in this study show a good correlation for the cutting conditions and can be used for the tool temperature estimation. The result indicates that the tool temperature decreases for ~ncreasing the tool nose radius in general. Also, nose radius hardly influences on the tool temperature compared with cutting speed, feed rate and depth of cut.

• Transactions of Materials Processing
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• v.11 no.5
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• pp.394-404
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• 2002

The drawbead model for a three-dimensional a finite element analysis of sheet metal forming processes is developed. The mathematical models of the basic drawbeads like circular drawbead, stepped drawbead, and squared drawbaed are first derived using the bending theory, belt-pulley equation, and Coulomb friction law. Next, the experiments for finding the drawing characteristics of the drawbead are performed. Based on mathematical models and drawing test results, expert models of basic drawbeads are then developed employing a linear multiple regression method. For the expert models of combined drawbeads such as the double circular drawbead, double stepped drawbead, circular-and-stepped drawbead, etc., those of the basic drawbeads are summed. Finally, in order to verify the expert models developed, the drawing characteristics calculated by the expert models of the double circular drawbead and circular-and-stepped drawbead are compared with those obtained from the experiments. The predictions by expert models agree well with the measurements by experiments.

• Journal of Korean Society on Water Environment
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• v.25 no.4
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• pp.580-588
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• 2009

In this study daily flow rates and delivered pollutant loads of Nakdong river basin are simulated with modified TANK model and minimum variance unbiased estimator. Based on the simulation results, flow duration curves, load duration curves, and delivery ratio duration curves have been established. Then GIS analysis is performed to obtain several hydrological geomorphic characteristics such as watershed area, stream length, watershed slope and runoff curve number. Finally, multiple regression analysis is carried out to estimate empirical equations for pollutants delivery ratio. The results show that there is positive relation between the flow rates and delivery ratios, and the proposed empirical formulas for delivery ratio can predict well river pollutant loads.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.711-714
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• 2008

The objective of this study is to analyze the relationship between the watershed characteristics and the critical duration of design rainfall. For estimation of critical duration, adjustment Huff's method and ILLUDAS urban runoff model were applied to urban 21 areas. Watershed characteristics such as area, channel length, channel slope, shape factor, and pipe density were used to simulate correlation analysis. The conclusions of this study are as follows; it is revealed that critical duration is influenced by the watershed characteristics such as pipe density, area and channel length. Also, multiple regression analysis using watershed characteristics is carried out and the determination coefficient of multiple regression equation shows 0.972.

• The Journal of Engineering Geology
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• v.28 no.4
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• pp.673-686
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• 2018

The physical properties of rocks constituting the rock mass were analyzed by using various methods such as 7 kinds of physical properties of about 2,400 data. The correlation equation was derived from the correlation equation with the dependent variables by screening independent variables through the significance level using multiple regression analysis. In order to verify the reliability of this equation, verification was performed through comparison with actual data using artificial neural network learning. The analysis results by petrogenesis and strength confirmed that the elastic wave velocity (compressional wave) and elastic modulus as the main influence factors for the independent variables affecting the dependent variables. This proves that most of the correlation equations using the above items are found in existing studies. And through this study, it is confirmed whether the rock classification is based on the above items in various standards. In addition, the analysis results of representative rocks showed a high correlation as the equation for estimating unconfined compressive strength and elastic modulus exceeds the coefficient of determination 0.8.

• Journal of Family Resource Management and Policy Review
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• v.6 no.1
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• pp.103-115
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• 2002

The purpose of this study was to analyze which factor, influenced the business and family performance success. Data were obtained from 248 family households. Proxy variable of the business performance was gross business income and of the family performance was the Family AFGAR scores. The multiple regression analysis was conducted for both the business performance equation and family performance equation. The main results of this study were as followings: The results indicated the effects of various business and family characteristics on performance and their contributions to the business and family performance model. Nine explanatory variables such as sex, being home-based, number of hours worked per week, number of family employee, number of nonfamily employee, total asset, the presence of young child under 6, nonbusiness income, and role conflicts were statistically significant in the business performance equation and three explanatory variables such as the hours worked per week, family stress scores, and role conflicts were statistically significant in the family performance equation. The results indicated the need for a more comprehensive view of family business performance.

• Journal of the Korean Geotechnical Society
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• v.33 no.6
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• pp.27-36
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• 2017

Gravel compaction pile method has been widely used to improve the soft ground on the land or sea as one of the soft ground improvement technique. The ultimate bearing capacity of the ground reinforced by gravel compaction piles is affected by the soil strength, the replacement ratio of pile, construction conditions, and so on, and various prediction equations have been proposed to predict this. However, the prediction of the ultimate bearing capacity using the existing models has a very large error and variation, and it is not suitable for practical design. In this study, multiple regression analysis was performed using field loading test results to predict the ultimate bearing capacity of ground reinforced by gravel compaction pile, and the most efficient input variables are selected through evaluation of error by leave one out cross validation, and a multiple regression equation for the prediction of ultimate bearing capacity was proposed. In addition, the prediction error was evaluated by applying artificial neural network using the selected input variables, and the results were compared with those of the existing model.