• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.865-868
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• 1999

In this paper, indoor propagation characteristics are analyzed for various environments such as corridors, walls and corners. In order to present the statistical model for indoor environments the loss factors of each case are obtained by linear regression analysis method with the function of logarithmic distance between transmitter and receiver.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 1997.11a
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• pp.11-15
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• 1997

This study deals with the method for modeling relationship between human sensibility and design dldments of a product for applying human sensibility to product development, Inorder to extract sensibility characteeristics concerning a product, we figured out the relationship between xensibilith and design elements using corrdlation analysis and multiple regression analysis, and then modeled the realtionship between then through multiple objective linert programming. The results of this study can be effectively applied to develop a product based on human sensibility

• Journal of the Korea Safety Management & Science
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• v.6 no.4
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• pp.123-137
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• 2004

It is an important and hot issue how to improve the competitiveness concerned on product, company and industry. It is necessary to develop the strategy of competitiveness for an efficient operation as well as improving the competitiveness in view of product, system, industry, price, quality and so on. This paper aims at proposing a model to choose dominating factors of competitiveness including a method o( resources allocation which can be applied to all products. And we show its empirical application on tile-industry.

• Computational Structural Engineering
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• v.7 no.1
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• pp.109-116
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• 1994

In this paper, various reliability analysis methods for calculating a probability of failure are investigated for their accuracy and efficiency. Crude Monte Carlo method is used as a basis for the comparison of various numerical results. For the sampling methods, Importance Sampling method and Directional Simulation method are considered for overcoming a drawback of Crude Monte Carlo method. For the approximate methods, conventional Rackwitz-Fiessler method. 3-parameter Chen-Lind method, and Rosenblatt transformation method are compared on the basis of First order reliability method. As a Second-order reliability method, Curvature-Fitting paraboloid method, Point-fitting paraboloid method, and Log-likelihood function method are explored in order to verify the accuracy of the reliability calculation results. These methods mentioned above would have some difficulty unless the limit state equation is expressed explicitly in terms of random design variables. Thus, there is a need to develop some general reliability methods for the case where an implicit limit state equation is given. For this purpose, Response surface method is used where the limit state equation is approximated by regression analysis of the response surface outcomes resulted from the structural analysis. From the application of these various reliability methods to three examples, it is found that Directional Simulation method and Response Surface method are very efficient and recommendable for the general reliability analysis problem cases.

• The Korean Journal of Applied Statistics
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• v.32 no.4
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• pp.607-618
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• 2019

A new and interesting task in statistics is to effectively analyze functional data that frequently comes from advances in modern science and technology in areas such as meteorology and biomedical sciences. Functional linear regression with scalar response is a popular functional data analysis technique and it is often a common problem to determine a functional association if a functional predictor variable affects the scalar response in the models. Recently, Kong et al. (Journal of Nonparametric Statistics, 28, 813-838, 2016) established classical testing methods for this based on functional principal component analysis (of the functional predictor), that is, the resulting eigenfunctions (as a basis). However, the eigenbasis functions are not generally suitable for regression purpose because they are only concerned with the variability of the functional predictor, not the functional association of interest in testing problems. Additionally, eigenfunctions are to be estimated from data so that estimation errors might be involved in the performance of testing procedures. To circumvent these issues, we propose a testing method based on fixed basis such as B-splines and show that it works well via simulations. It is also illustrated via simulated and real data examples that the proposed testing method provides more effective and intuitive results due to the localization properties of B-splines.

• Transactions of the Korean hydrogen and new energy society
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• v.32 no.6
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• pp.636-641
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• 2021

Using numerical analysis, various factors influencing the performance development of high-pressure pumps for Dimethyl Ether (DME) engines were identified and the impact of each factor was evaluated using Taguchi method. DME fuels are more compressive than diesel fuels and have the lower heat generation, so it is necessary to increase the size of the plunger and speed (RPM) of the pump as well. In addition, it is necessary to change the shape and design of control valve to control the discharge flow and pressure. In this study, various variables affecting the performance and flow rate increase of high-pressure pumps for DME engines are planned using Taguchi method, and the best design method is proposed using correlation of the most important variables. As a result, we were able to provide the design value needed for a six-liter engine and provide optimal conditions. The best combination factors to optimize the flow rate at RPM 2,000 and diameter plunger with 20 mm. The regression equation can also be used to optimize the flow rate; -8, 13+0, 2552 RPM +54, 17 diam. Plunger.

• Tunnel and Underground Space
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• v.33 no.6
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• pp.594-609
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• 2023

TBM (Tunnel Boring Machine) method is gaining popularity in urban and underwater tunneling projects due to its ability to ensure excavation face stability and minimize environmental impact. Among the prominent models for predicting disc cutter life, the NTNU model uses the Cutter Life Index(CLI) as a key parameter, but the complexity of testing procedures and rarity of equipment make measurement challenging. In this study, CLI was predicted using multiple linear regression analysis and tree-based machine learning techniques, utilizing rock properties. Through literature review, a database including rock uniaxial compressive strength, Brazilian tensile strength, equivalent quartz content, and Cerchar abrasivity index was built, and derived variables were added. The multiple linear regression analysis selected input variables based on statistical significance and multicollinearity, while the machine learning prediction model chose variables based on their importance. Dividing the data into 80% for training and 20% for testing, a comparative analysis of the predictive performance was conducted, and XGBoost was identified as the optimal model. The validity of the multiple linear regression and XGBoost models derived in this study was confirmed by comparing their predictive performance with prior research.

• Journal of the Korean Institute of Landscape Architecture
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• v.30 no.3
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• pp.64-72
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• 2002

The purpose of this paper is to examine the effects of interior landscape that influence preference at a department store in order to answer the research question; What are the effective factors of interior landscape that affect preference at a department store. After review of the effect of interior landscape, and the interior landscape at a department store, we constructed a literature framework and have formulated the hypothesis of this research. We have analyzed the data which surveyed 108 visitors about the interior landscape in a department store, using factor analysis, Pearson's correlation analysis, and the multiple linear regression method. We found that; 1) eleven variables can be selected for the effects of interior landscape at department store: accessibility, image, stay, distinction, comfort, complexity, cleanness, mystery, purification of atmosphere, noise and harmony. Among the 11 independent variables used to study the effect of interior landscape at a department store, the image and purification of atmosphere highly affect preference. 2) These 11 variables are grouped by factor analysis as effects of amenity, attractiveness and identity. 3) As a result of multiple regression analysis, independent variables influencing preference were proved statistically significant at one percent level. 4) Regarding their relative contribution of interior landscape effect at a department store, the effects of amenity was the most important and it showed a level of importance 1.4 times higher than the effect of identity, and 1.25 times higher than the effect of attractiveness. The research results suggest the need for guidelines for the creation of interior landscape at department stores. The approach and analysis method adopted by this research is highly useful for the evaluation of interior landscape criteria at a department store. It is recommended that more practical study on factors affecting user's preference be performed in the future.

• Journal of the Semiconductor & Display Technology
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• v.22 no.1
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• pp.134-138
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• 2023

This study focuses on the analysis of the results of computational fluid dynamics simulations of mist-chemical vapor deposition for the growth of an epitaxial wafer in power semiconductor technology using artificial intelligence techniques. The conventional approach of predicting the uniformity of the deposited layer using computational fluid dynamics and design of experimental takes considerable time. To overcome this, artificial intelligence method, which is widely used for optimization, automation, and prediction in various fields, was utilized to analyze the computational fluid dynamics simulation results. The computational fluid dynamics simulation results were analyzed using a supervised deep neural network model for regression analysis. The predicted results were evaluated quantitatively using Euclidean distance calculations. And the Bayesian optimization was used to derive the optimal condition, which results obtained through deep neural network training showed a discrepancy of approximately 4% when compared to the results obtained through computational fluid dynamics analysis. resulted in an increase of 146.2% compared to the previous computational fluid dynamics simulation results. These results are expected to have practical applications in various fields.

• International Journal of Advanced Culture Technology
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• v.11 no.4
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• pp.223-232
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• 2023

The purpose of this study is to determine the impact of social network sports community consciousness on loyalty and sports attitude. In order to achieve this research purpose, the population of the study was selected as adult men and women over the age of 20 who are active in the social network sports community in 2022. The sampling method used cluster random sampling to select a total of 300 people, 150 men and 150 women, as research subjects. The survey tool used was the questionnaire method, and the questionnaire whose reliability and validity had been verified in previous studies at home and abroad was used by requoting, modifying, or supplementing it to suit the purpose of this study. It was also structured on a 5-point scale. Frequency analysis, factor analysis, reliability analysis, simple regression analysis, and multiple regression analysis were performed on the collected data using the statistical program SPSS Windows 20.0 Version. The results obtained through this process are as follows. First, social network sports community consciousness was found to have a partial effect on loyalty. Second, social network sports community consciousness was found to have a partial effect on sports attitudes. Third, social network sports community loyalty was found to have a partial effect on sports attitudes. Considering these results, various activities such as decision-making process, relationship formation, and opinion expression of modern people are carried out by the O-line community. In addition, while in the past it was a format that led from offline activities to online activities, currently, there are more and more formats that lead from online activities to offline activities. Therefore, modern people's SNS sports community activities provide many experiences, which creates a sense of community and sports attitudes are formed based on this. This can be said to lead to loyal activities.