• Journal of the Korean Society of Safety
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• v.24 no.1
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• pp.1-6
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• 2009

In machining of ceramic materials, they are very difficult-to cut materials because of there high strength and hardness. Machining of ceramics are characterized by cracking and brittle fracture. Generally, ceramics are machined using conventional method such as grinding and polishing. However these processes are generally costly and have low MRR(material removal rate). This paper focuses on machinability evaluation of machinable ceramics for products with CNC machining center. Thus, in this paper, experiment applying cutting parameters is performed based on experimental design method. A design and analysis of experiments is conducted to study the effects of these parameters on the surface roughness by using the S/N ratio, analysis of ANOVA, and F-test. And multiple linear regression analysis is applied to compare experimental with predicted data in consideration of surface roughness. Cutting parameters, namely, feed, cutting speed and depth of cut are used to accomplish purpose of this paper. Required experiments are performed, and the results are investigated.

• Journal of the Korean Geographical Society
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• v.45 no.6
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• pp.806-819
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• 2010

Population data has been essential and fundamental in spatial analysis and commonly aggregated into political boundaries. A conventional method for population distribution estimation was a regression model with land use data, but the estimation process has limitation because of spatial autocorrelation of the population data. This study aimed to improve the accuracy of population distribution estimation by adopting a Regression-Kriging method, namely RK Model, which combines a regression model with Kriging for the residuals. RK Model was applied to a part of Seoul metropolitan area to estimate population distribution based on the residential zones. Comparative results of regression model and RK model using RMSE, MAE, and G statistics revealed that RK model could substantially improve the accuracy of population distribution. It is expected that RK model could be adopted actively for further population distribution estimation.

• Journal of ILASS-Korea
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• v.20 no.4
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• pp.247-253
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• 2015

Recently, the engine calibration technique has been much more complicated than that of the past engine case in order to satisfy the strict emission regulations. The current calibration method for the diesel engine which has an increasing market is both costly and time-consuming. New engine calibration method is required to develop for high-quality diesel engines with low cost and release it at the appropriate time. This study provides the optimal calibrating technique for complex engine systems using statistical modeling and numerical optimization. Firstly, it design a test plan based on Design of Experiments, a V-optimality methodology which is suitable looking for set-points, and determine the shape of test engine response. Secondly, it uses functions to make linear regression model for data analysis and optimization to fit the models of engines behavior. Finally, it generates the optimal calibrations obtained directly from empirical engine models using Grey Relational Analysis and compares the calibrations with data. This method can develop a process for systematically identifying the optimal balance of engine emissions.

• Asia-Pacific Journal of Business
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• v.13 no.1
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• pp.213-230
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• 2022

Purpose - The purpose of this study is to find out any potential factors for explanatory variables when calculating the virtual successful bid rate in case of no collusion. Design/methodology/approach - An empirical analysis was conducted in this study with a regression analysis that included 725 bid samples under the public construction technical type bidding. Findings - The result of the basic analysis showed that there are several factors affecting the successful bid rate. First, collusion variable; second, government variable; third, successful bidder design score variable and the number of bidder variable among bidding features; fourth, turnkey variable based on the alternative method; fifth, civil works variable and plant works variable based on building work; sixth, asset variable and the fourth-quarter performance difference variable. However, the technical proposal method variable among bidding features was found to be statistically insignificant in column(4). Research implications or Originality - The significance of this research is that new variable such as the government variable and the fourth-quarter performance difference variable were added in the regression model, which showed statistically significant research results.

• Journal of Korea Multimedia Society
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• v.7 no.7
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• pp.877-885
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• 2004

In this paper, we propose an enhancement shot change detection method using the neural net and the robust feature selection out of multiple features. The previous shot change detection methods usually used single feature and fixed threshold between consecutive frames. However, contents such as color, shape, background, and texture change simultaneously at shot change points in a video sequence. Therefore, in this paper, we detect the shot changes effectively using robust features, which are supplementary each other, rather than using single feature. In this paper, we use the typical CART (classification and regression tree) of data mining method to select the robust features, and the backpropagation neural net to determine the threshold of the each selected features. And to evaluation the performance of the robust feature selection, we compare the proposed method to the PCA(principal component analysis) method of the typical feature selection. According to the experimental result. it was revealed that the performance of our method had better that than the PCA method.

• Journal of the Korean Statistical Society
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• v.19 no.2
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• pp.151-159
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• 1990

Regression diagnostics often involves assesment of the changes that result from deleting multiple cases. Diagnostic mehtodology based on global influence measure, however, needs prohibitive computing time. As an alternative, Cook (1986) developed influence approach in which it is checked whether a minor modification of specifiation influences key results of an analysis. In line with Cook's development, we propose and study an inflence derivative method that yields both the magnitude and direction of case influences. The utility of our methodology is highlighted when case influence derivatives are plotted in a lower demensional space. Such plots are especially effective in unmasking "masked" observations in least squares regression and in robust regression also. We give several illustrations.strations.

• Computers and Concrete
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• v.21 no.3
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• pp.291-298
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• 2018

In this study, the flexural fatigue performance of concrete beams made with 100% Coarse Recycled Concrete Aggregates (RCA) and 100% Coarse Natural Aggregates (NA) were statistically commanded. For this purpose, the experimental fatigue test results of earlier researcher were investigated using two parameter Weibull distribution. The shape and scale parameters of Weibull distribution function was evaluated using seven numerical methods namely, Graphical method (GM), Least-Squares (LS) regression of Y on X, Least-Squares (LS) regression of X on Y, Empherical Method of Lysen (EML), Mean Standard Deviation Method (MSDM), Energy Pattern Factor Method (EPFM) and Method of Moments (MOM). The average of Weibull parameters was used to incorporate survival probability into stress (S)-fatigue life (N) relationships. Based on the Weibull theory, as single and double logarithm fatigue equations for RCA and NA under different survival probability were provided. The results revealed that, by considering 0.9 level survival probability, the theoretical stress level corresponding to a fatigue failure number equal to one million cycle, decreases by 8.77% (calculated using single-logarithm fatigue equation) and 6.62% (calculated using double logarithm fatigue equation) in RCA when compared to NA concrete.

• Journal of the Society of Disaster Information
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• v.17 no.2
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• pp.306-318
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• 2021

The dispatch law has a negative impact on safety management at construction sites as the command and command relationship to safety assistants of the original contractor are applied to the dispatch law. Purpose: The purpose is to study the importance and impact of safety management according to the dispatch law, and to propose a direction for safety management so that safety assistants can actively and proactively prevent accidents. In this study, we used AHP analysis techniques for experts to achieve the final goal and verified the suitability through logistic regression. Method: AHP analysis technique is used for experts and workers and logistic regression analysis is conducted. Result: The result of analyzing scenario data where the dispatch method can be applied showed the importance in the order of education (SkillUp education), management (work-time management) and direct instructions (feedback instruction). In logistic regression analysis, feedback is the factor that affects direct instruction, and in education management, the ratio of education management is 3.42 times lower than that of other groups when only the team leader of the company gives work instructions. Conclusion: The management of feedback and education is more important than anything else within the range in which the dispatch method is not applied, and the expansion of non-face-to-face online education is judged to avoid the violation of dispatch method because the expansion of non-face-to-face online education due to covid 19 recently has brought more various target for safety education.

• Korean Journal of Community Nutrition
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• v.4 no.2
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• pp.157-165
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• 1999

This study was conducted to identify the determinants of regional body fat distribution of obesity(upper body obesity and lower body obesity) for adolescents. The macronutrient consumption pattern utilized the most important variables to test for potential determinants. A total of 726 adolescents living in rural areas in Korea had been observed for four years from 1992 to 1996 about their diet, sexual maturation, serum components and physical growth. The study design was similar to that of a case control study. Logistic regression analysis were used as an analytical method to identify the determinants of upper body obesity and lower body obesity. Odd ratios were estimated from the regression to identify the determinants of upper body obesity and lower body obesity. Odd ratios were estimated from the regression to identify the risk factors. Fat consumption pattern was the most frequent one among the three macronutrient consumption pattern of carbohydrate, fat and protein. Prevalence of obesity for the subjects was 9.5%. Prevalence of upper body obesity was higher in malestudents than in female students. On the other had, prevalence of lower body obesity was higher in females. The results of the logicstic regression analysis showed that the risk factor for upper body obesity was sexual maturity rather than dietary factors. None of the factors included in the analysis for lower body obesity appear to be the risk factor. The result may suggest that to develop a determinant model for obesity of adolescents, the model should include a wider range of variables other than diet, sexual maturity and changes in blood serum.

• Journal of Microbiology and Biotechnology
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• v.10 no.4
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• pp.476-481
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• 2000

A linear correlation, by the stepwise multiple regression analysis, was found between the sensory test of Sigumjang aroma and the gas chromatographic data which were transformed with logarithm. GC data is the most objective method to evaluate Sigumjang aroma. A multiple correlation coefficient and a determination coefficient of more than 0.9 were obtained at the 9th and 13th steps, respectively. At step 31, the coefficient of determination level of 0.95 was attained. The accuracy of its estimation became higher as the number of the variables entered into the regression model increased. Over 90% of the Sigumjang aroma was explained by 13 compounds indentified on GC. The contributing proportion of the peak 26 was the highest followed by peaks 57 (9.27%), 29 (7.51%), 54 (6.01%), 8 (5.99%), 49 (4.97%), and 13 (4.11%).