• Journal of Periodontal and Implant Science
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• v.26 no.3
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• pp.689-699
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• 1996

The purpose of this research is to determine elements affecting the out-of-pocket cost of woman. The sample consisted of 1907 women living Iksan city. The survey was conducted by means of questionnaires. The model used in the analysis of out-of-pocket cost was the Andersen-Newman model, while the analysis techniques used were stepwise multiple regression and path analysis. The number of independent variables used in the analysis was 28 in total, ie 19 predisposing components, 6 enabling components, and 3 need components. In this study, the amount of variance by the model was 17 percent. Number of restricted activity days caused by oral disease, perceived susceptibility of dental disease, having a regular dental care, dental treatment costs, education level and income were found to have significant major effects on out-of-pocket cost. Number of restricted activity days caused by oral disease was the most important variable affecting out-of-pocket cost of woman. Also out-of-pocket cost shows larger effect due to enabling components than frequency of dental utilization.

• Journal of the Korean Operations Research and Management Science Society
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• v.26 no.4
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• pp.55-70
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• 2001

Artificial neural network(ANN) models have been widely used for the classification problems in business such as bankruptcy prediction, credit evaluation, etc. Although the application of ANN to classification of consumers＇ choice behavior is a promising research area, there have been only a few researches. In general, most of the researches have reported that the classification performance of the ANN models were better than conventional statistical model Because the survey data on consumer behavior may include much noise and missing data, ANN model will be more robust than conventional statistical models welch need various assumptions. The purpose of this paper is to study the potential of the ANN model for forecasting consumers＇ choice behavior based on survey data. The data was collected by questionnaires to the shoppers of department stores and discount stores. Then the correct classification rates of the ANN models for the training and test sample with that of multiple discriminant analysis(MDA) and logistic regression(Logit) model. The performance of the ANN models were betted than the performance of the MDA and Logit model with respect to correct classification rate. By using input variables identified as significant in the stepwise MDA, the performance of the ANN models were improved.

• Journal of the Earthquake Engineering Society of Korea
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• v.23 no.2
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• pp.119-129
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• 2019

Many reinforced concrete (RC) buildings constructed prior to 1980's lack important features guaranteeing ductile response under earthquake excitation. Structural components in such buildings, especially columns, do not satisfy the reinforcement details demanded by current seismic design codes. Columns with deficient reinforcement details may suffer significant damage when subjected to cyclic lateral loads. They can also experience rapid lateral strength degradation induced by shear failure. The objective of this study is to accurately simulate the load-deformation response of RC columns experiencing shear failure. In order to do so, model parameters are calibrated to the load-deformation response of 40 RC column specimens failed in shear. Multivariate stepwise regression analyses are conducted to develop the relationship between the model parameters and physical parameters of RC column specimens. It is shown that the proposed predictive equations successfully estimated the model parameters of RC column specimens with great accuracy. The proposed equations also showed better accuracy than the existing ones.

• Asia Pacific Journal of Business Review
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• v.6 no.1
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• pp.21-48
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• 2021

Promoting low carbon transportation adoption is important for energy saving. Some prior studies have discussed on environmental values affect low carbon transportation commuting is inconclusive. This study has constructed the environmental values, utility value, and social influence-based low-carbon transportation adoption model through the theory of the technology acceptance model and VBN model and the IS success model. Through the SEM model and stepwise regression analysis, we have found that environmental values positively affect utility value, and utility value also positively affects the behavior adoption of low carbon transportation. The utility value as mediating effect in the relationship between environmental values and low carbon transportation commuting behavior. Besides, we also have found that social influence positively impacts the behavior adoption of low carbon transportation. It better enhances the level of household residents' environmental values and utility values, and social influence for promoting the adoption of low carbon transportation. This present research provides theoretical guidance and suggestions for promoting the development of low-carbon transportation innovation.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.6
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• pp.219-225
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• 2019

There is a problem with the existing method of selecting the difficulty levels of Hanja characters. Some Hanja characters selected by the existing methods are different from Sino-Korean words used in real life and it is impossible to know how many times the Hanja characters are used. To solve this problem, we measure the difficulty of Hanja characters using the multiple regression analysis with the frequency as the features. Based on the elementary textbooks, FWS and FHU are counted. A questionnaire is written using the two frequencies and stroke together to answer the appropriate timing of learning the Hanja characters and use them as target variables for regression. Use stepwise regression to select the appropriate features and perform multiple linear regression. The R² score of the model was 0.1105 and the RMSE was 0.1105.

• Asian-Australasian Journal of Animal Sciences
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• v.23 no.4
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• pp.417-424
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• 2010

The purpose of this study was to detect significant SNPs for carcass quality traits using DNA chips of high SNP density in Hanwoo populations. Carcass data of two hundred and eighty nine steers sired by 30 Korean proven sires were collected from two regions; the Hanwoo Improvement Center of National Agricultural Cooperative Federation in Seosan, Chungnam province and the commercial farms in Gyeongbuk province. The steers in Seosan were born between spring and fall of 2006 and those in Gyeonbuk between falls of 2004 and 2005. The former steers were slaughtered at approximately 24 months, while the latter steers were fed six months longer before slaughter. Among the 55,074 SNPs in the Illumina bovine 50K chip, a total of 32,756 available SNPs were selected for whole genome association study. After adjusting for the effects of sire, region and slaughter age, phenotypes were regressed on each SNP using a simple linear regression model. For the significance threshold, 0.1% point-wise p value from F distribution was used for each SNP test. Among the significant SNPs for a trait, the best set of SNP markers were selected using a stepwise regression procedure, and inclusion and exclusion of each SNP out of the model was determined at the p<0.001 level. A total of 118 SNPs were detected; 15, 20, 22, 28, 20, and 13 SNPs for final weight before slaughter, carcass weight, backfat thickness, weight index, longissimus dorsi muscle area, and marbling score, respectively. Among the significant SNPs, the best set of 44 SNPs was determined by stepwise regression procedures with 7, 9, 6, 9, 7, and 6 SNPs for the respective traits. Each set of SNPs per trait explained 20-40% of phenotypic variance. The number of detected SNPs per trait was not great in whole genome association tests, suggesting additional phenotype and genotype data are required to get more power to detect the trait-related SNPs with high accuracy for estimation of the SNP effect. These SNP markers could be applied to commercial Hanwoo populations via marker-assisted selection to verify the SNP effects and to improve genetic potentials in successive generations of the Hanwoo populations.

• Food Science and Preservation
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• v.6 no.1
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• pp.29-36
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• 1999

Using Fuji apple fruits cultivated in Kyungpook prefecture, the calibration model for firmness evaluation of fruits by near infrared(NIR) reflectance spectroscopy was developed, and the various influence factors such as instrument variety, measuring method, sample group, apple peel and selection of firmness point were investigated. Spectra of sample were recorded in wavelength range of 1100∼2500nm using NIR spectrometer (InfraAlyzer 500), and data were analyzed by stepwise multiple linear regression of IDAS program. The accuracy of calibration model was the highest when using sample group with wide range, and the firmness mean values obtained in graph by texture analyser(TA) were used as standard data. Chemometrics models were developed using a calibration set of 324 samples and an independent validation set of 216 samples to evaluate the predictive ability of the models. The correlation coefficients and standard error of prediction were 0.84 and 0.094kg, respectively. Using developed calibration model, it was possible to monitor the firmness change of fruits during storage frequently. Time, which was reached to firmness high value in graph by TA, is possible to use as new parameter for freshness of fruit surface during storage.

• Journal of the korean academy of Pediatric Dentistry
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• v.24 no.1
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• pp.195-203
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• 1997

The purpose of this study is to provide framework for understanding women's preventive dental utilization. In this paper Andersen-Newman's model is applied to the use of dental visits. This model consists of predisposing, enabling, and need components that describe a person's decision to use preventive health services. The sample consisted of 1907 women living Iksan city. Models are operationalized using stepwise multiple regression analysis and path analysis. The number of independent variables used in the analysis was 27 in total, i.e. 20 predisposing components, 6 enabling components, and 1 need component. Preventive dental utilization was measured based on the number of visits. The data collected by means of a questionnaire survey. In this study, the amount of variance by the model was 11 percent. Number of restricted activity days caused by oral disease, perceived threat of dental disease, having a regular dental care, and income were found to have significant major effects on preventive dental utilization of women. Number of restricted activity days caused by oral disease was the most important variable affecting preventive dental utilization of women.

• Journal of Environmental Health Sciences
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• v.46 no.1
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• pp.96-102
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• 2020

Objectives: This study identified factors impacting radiation knowledge among aircrew, who are affected by cosmic radiation exposure due to their occupational environment. Methods: In September 2019 we conducted an online survey of aircrew through a Google link. We evaluated the level of radiation knowledge using a ten-item (10 points) questionnaire. The following exploratory variables were evaluated in relationship with the level of radiation knowledge using univariable linear regression models: sex, age, duration of employment, position level, company, marriage, education level, personal/family history of disease, and the number of times acquiring information on radiation through various channels (internet searching, watching television, reading newspaper, conversation about radiation with aircrew/non-aircrew, in-house training). With a p of 0.2 in univariable models, we built a multivariable linear regression model using a stepwise selection method. Results: The average radiation knowledge score of the 356 respondents was 7.22. Univariable linear regression analysis showed that radiation knowledge of the aircrew was associated with their company, position level, age, and number of conversations with other aircrew members. Our multivariable model showed that the radiation knowledge level of aircrew decreased as they had more conversations about radiation with other aircrew members and as their age increased. Conclusions: Korean air crew showed a lower level of radiation knowledge as their age and the number of conversations with colleagues increased. The study suggests that more education is needed in order for aircrew to gain accurate radiation knowledge.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.9
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• pp.3900-3914
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• 2012

This study examined the background of the recent global financial crisis and the concept of one of the financial derivatives such as the credit default swap(CDS) or synthetic CDO(collateral debt obligations), given the rapid growing and changing the over-the-counter derivative markets in their volume and structures. In comparison with the previous literature such as the study of Park & Kim (2011), this research empirically performed more thorough and comprehensive investigations to find any financial characteristics or attributes to determine the CDS spreads. Regarding the results obtained from the multiple regression models, the explanatory variables such as STYIELD3, SLOPE, INASSETS, and VOLATILITY, showed their statistically significant effects on all the tested dependent variables(DVs). Another procedure such as the principle component analysis(PCA), was also performed to account for additional IDVs as possible determinants of the dependent variables. Subsequent to this analysis, larger coefficients of each corresponding eigenvector such as BETA, PFT2, GROWTH, STD, and BLEVERAGE were found to be possible financial determinants. For robustness, all the IDVs were employed to be tested in the 'full' regression model with stepwise procedure. As a result, STYIELD3, SLOPE, and VOLATILITY, and BETA showed their statistically significant relationship with all the dependent variables of the CDS spreads.