• Asia-Pacific Journal of Business
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• v.11 no.3
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• pp.63-77
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• 2020

Purpose - The purpose of this study is to examine the effects of personal characteristics, loan characteristics, and interest rate characteristics of 2,653 borrowers on the delinquency possibility. In doing so, this study applies both multiple regression and logistic regression models to the data of credit unions in the city of Daegu. Design/Methodology/Approach - The major results of multiple regression analysis using SPSS are as follows. Findings - As for the results of testing the significance of the regression coefficients, it has been found that among the personal characteristics variables membership, credit rating, credit rating changes, and LTV have significant positive (+) effects on the delinquency possibility. Also it has been shown that among the loan characteristics variables loan amount, loan balance, total debt amount, collateral type, collateral amount, and repayment method have significant positive (+) effects on the delinquency possibility. Furthermore it has been found that among the interest rate characteristics variables both overdue interest rate and interest rate spread have positive (+) effects on the delinquency possibility. However, it has been shown that among the personal characteristics variables equity and membership do not have significant effects on the delinquency possibility, and that normal interest rate among the interest rate characteristics variables also do not have a significant effect on the delinquency possibility. Research Implications - By systematically analyzing the variables affecting delinquency possibility based on the results of this study, credit unions might get positive help in improving the system of managing receivables. Furthermore, the results of this study could be extended and applied to other types of financial institutions, so that financial institutions in general will also get some help to systematically manage the delinquency possibility.

• Geomechanics and Engineering
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• v.30 no.1
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• pp.11-26
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• 2022

One of the most important issues in tunneling, is the squeezing phenomenon. Squeezing can occur during excavation or after the construction of tunnels, which in both cases could lead to significant damages. Therefore, it is important to predict the squeezing and consider it in the early design stage of tunnel construction. Different empirical, semi-empirical and theoretical-analytical methods have been presented to determine the squeezing. Therefore, it is necessary to examine the ability of each of these methods and identify the best method among them. In this study, squeezing in a part of the Alborz service tunnel in Iran was estimated through a number of empirical, semi- empirical and theoretical-analytical methods. Among these methods, the most robust model was used to obtain a database including 300 data for training and 33 data for testing in order to develop a machine learning (ML) method. To this end, three ML models of Gaussian process regression (GPR), artificial neural network (ANN) and support vector regression (SVR) were trained and tested to propose a robust model to predict the squeezing phenomenon. A comparative analysis between the conventional and the ML methods utilized in this study showed that, the GPR model is the most robust model in the prediction of squeezing phenomenon. The sensitivity analysis of the input parameters using the mutual information test (MIT) method showed that, the most sensitive parameter on the squeezing phenomenon is the tangential strain (ε_θ^α) parameter with a sensitivity score of 2.18. Finally, the GPR model was recommended to predict the squeezing phenomenon in tunneling projects. This work's significance is that it can provide a good estimation of the squeezing phenomenon in tunneling projects, based on which geotechnical engineers can take the necessary actions to deal with it in the pre-construction designs.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.10
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• pp.1633-1641
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• 2020

Objective: The objective of this study was to develop a model for estimating the carcass weight of Hanwoo cattle as a function of body measurements using three different modeling approaches: i) multiple regression analysis, ii) partial least square regression analysis, and iii) a neural network. Methods: Data from a total of 134 Hanwoo cattle were obtained from the National Institute of Animal Science in South Korea. Among the 372 variables in the raw data, 20 variables related to carcass weight and body measurements were extracted to use in multiple regression, partial least square regression, and an artificial neural network to estimate the cold carcass weight of Hanwoo cattle by any of seven body measurements significantly related to carcass weight or by all 19 body measurement variables. For developing and training the model, 100 data points were used, whereas the 34 remaining data points were used to test the model estimation. Results: The R² values from testing the developed models by multiple regression, partial least square regression, and an artificial neural network with seven significant variables were 0.91, 0.91, and 0.92, respectively, whereas all the methods exhibited similar R² values of approximately 0.93 with all 19 body measurement variables. In addition, relative errors were within 4%, suggesting that the developed model was reliable in estimating Hanwoo cattle carcass weight. The neural network exhibited the highest accuracy. Conclusion: The developed model was applicable for estimating Hanwoo cattle carcass weight using body measurements. Because the procedure and required variables could differ according to the type of model, it was necessary to select the best model suitable for the system with which to calculate the model.

• Restorative Dentistry and Endodontics
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• v.37 no.3
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• pp.155-159
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• 2012

Objectives: To investigate the effect of dentin moisture degree and air-drying time on dentin-bond strength of two different one-step self-etching adhesive systems. Materials and Methods: Twenty-four human third molars were used for microtensile bond strength testing of G-Bond and Clearfil $S^3$ Bond. The dentin surface was either blot-dried or air-dried before applying these adhesive agents. After application of the adhesive agent, three different air drying times were evaluated: 1, 5, and 10 sec. Composite resin was build up to 4 mm thickness and light cured for 40 sec with 2 separate layers. Then the tooth was sectioned and trimmed to measure the microtensile bond strength using a universal testing machine. The measured bond strengths were analyzed with three-way ANOVA and regression analysis was done (p = 0.05). Results: All three factors, materials, dentin wetness and air drying time, showed significant effect on the microtensile bond strength. Clearfil $S^3$ Bond, dry dentin surface and 10 sec air drying time showed higher bond strength. Conclusions: Within the limitation of this experiment, air drying time after the application of the one-step self-etching adhesive agent was the most significant factor affecting the bond strength, followed by the material difference and dentin moisture before applying the adhesive agent.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.6
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• pp.848-859
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• 2004

Mechanical testing methods to determine the material constants for large deformation nonlinear finite element analysis were demonstrated for natural rubber. Uniaxial tension, uniaxial compression, equi-biaxial tension and pure shear tests of rubber specimens are performed to achieve the stress-strain curves. The stress-strain curves are obtained after between 5 and 10 cycles to consider the Mullins effect. Mooney and Ogden strain-energy density functions, which are typical form of the hyperelastic material, are determined and compared with each other. The material constants using only uniaxial tension data are about 20% higher than those obtained by any other test data set. The experimental equations of shear elastic modulus on the hardness and maximum strain are presented using multiple regression method. Large deformation finite element analysis of automotive transmission mount using different material constants is performed and the load-displacement curves are compared with experiments. The selection of material constant in large deformation finite element analysis depend on the strain level of component in service.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.2
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• pp.515-524
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• 2013

For the development of reliable software, Software testing is the most important. Recently small changes of the software according to the importance of regression testing is growing. To verify Application of a large number of nodes, Network simulator environment is required. This paper proposed interface module between network framework for sensor network application and co-simulator to unit test sensor network application. To conclude, developer can focus on sensor network application implementation only, so the improved integrated simulator contributes to increase development productivity.

• Journal of the Korean Society for Nondestructive Testing
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• v.28 no.3
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• pp.279-284
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• 2008

The firmness of fruit is one of the most important quality factors and is highly correlated to the elastic modulus. In this study, the ultrasonic transmission method was applied to evaluate the elastic modulus of the apple. In order to transmit and receive the ultrasonic wave through the whole apple, the ultrasonic measurement setup consisted of ultrasonic pulser, two specially fabricated ultrasonic transducers for fruit and digital storage oscilloscope. Ultrasonic parameters such as ultrasonic wave velocity, apparent attenuation, and peak frequencies were analyzed. The elastic modulus of apple was measured by using compression test apparatus. The correlations between ultrasonic parameters and elastic modulus were analyzed. A multiple linear regression model describing the relationship between elastic modulus and ultrasonic parameters was proposed.

• Journal of Korean Academy of Nursing
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• v.42 no.2
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• pp.217-225
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• 2012

Purpose: This study was conducted to examine the factors associated with HPV (Human Papillomavirus) related stigma, shame and intent to have HPV test among adult women. Methods: Data were collected from December 1, 2009 to January 31, 2010, and participants were 324 women who visited an obstetric gynecologic clinic. They anticipated testing positive for HPV. Then HPV related stigma, shame, intent to have HPV testing and HPV knowledge were measured. Descriptive statistics, Mann-Whitney U test, Kruskal Wallis test and multivariate adjusted logistic regression were used for data analysis. Results: The levels of stigma and shame were higher than average. Intent to have HPV test was high and HPV knowledge was low. Women who answered that HPV is not sexually transmitted had lower HPV stigma than did women who answered they didn't know (OR=0.20, 95%CI 0.06-0.68). Women with lower stigma showed lower intent to have HPV test than women with higher stigma (OR=0.46, 95%CI 0.26-0.82). Conclusion: Basic HPV information should be fully understood for women especially prior to HPV test. Normalizing HPV stigma is necessary for women who perceive HPV as sexually transmitted and women intending to have HPV test.

• Journal of Biosystems Engineering
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• v.38 no.3
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• pp.192-198
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• 2013

Purpose: Methods for non-destructive estimation of product quality have been reported in various industrial fields, but the application of ultrasonic techniques for the agricultural products of potatoes, pears, apples, watermelons, kiwis and tomatoes etc. have been rarely reported since the application of a contact-type ultrasonic transducer in agricultural products is very difficult. Therefore, this study sought to determine the firmness of apples using non-contact ultrasonic techniques. Methods: For this experiment, an ultrasonic experimental tester using a non-contact ultrasonic transducer was created, and a signal processing program was used to analyze the acquired ultrasonic reflected signal. Also, a universal testing machine was used to measure firmness parameters of the apples such as bioyield strength, a firmness factor, after the ultrasonic tests had been performed. Results: Six distance correction factors were calculated to obtain consistent values of ultrasonic properties regardless of the distance between the transducer and the surface of the subject. We developed prediction models of the bioyield strength using the distance correction factors. Conclusions: The optimum prediction model of the bioyield strength of apples using a non-contact ultrasonic technique was a multiple regression model ($R^2=0.9402$).

• Journal of the Korean Society of Clothing and Textiles
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• v.22 no.3
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• pp.417-427
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• 1998

Price, one of the marketing 4p's, is a key decision variable affecting market share and the profitability of individual products. For consumers, since price is almost always known to and can be compared, it is one of the most important criteria when they make a purchase decision making. With the consumers' increasing consciousness for price due to economic recession, and the saturation of domestic apparel market, it is expected that the effect of price on consumers' decision making would be greater than ever. This study, the first in two part series, focuses on testing the validity of dimensions of clothing price using Lichtenstein et. at. (1993)'s suggestion. In addition, the effect of demographic variables on the perception of each price dimension was investigated. The subjects were 264 college students living in Seoul, Korea. The data were collected by self -administered questionnaires and analyzed by t-test, ANOVA, regression analysis and Lisrel confirmatory factor analysis. The result supported Lichtenstein et. al. (1993)'s suggestion. That is, consumers' perception of clothing price is not mini-dimensional, but has six dimensions: sale proneness, price mavenism, value consciousness, price consciousness, price -quality schema and prestige sensitivity. Demographic variables partially effect on the consumers' perception of each clothing price dimension. The level of monthly pocket money, however, has influence on all price dimensions. Based on these results, marketing implications for apparel manufacturers were suggested.