• Journal of Information Technology Services
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• v.21 no.3
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• pp.63-72
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• 2022

The extinction crisis of local cities, caused by a population density increase phenomenon in capital regions, directly causes the increase of vacant houses in local cities. According to population and housing census, Gunsan-si has continuously shown increasing trend of vacant houses during 2015 to 2019. In particular, since Gunsan-si is the city which suffers from doughnut effect and industrial decline, problems regrading to vacant house seems to exacerbate. This study aims to provide a foundation of a system which can predict and deal with the building that has high risk of becoming vacant house through implementing a data driven vacant house prediction machine learning model. Methodologically, this study analyzes three types of machine learning model by differing the data components. First model is trained based on building register, individual declared land value, house price and socioeconomic data and second model is trained with the same data as first model but with additional POI(Point of Interest) data. Finally, third model is trained with same data as the second model but with excluding water usage and electricity usage data. As a result, second model shows the best performance based on F1-score. Random Forest, Gradient Boosting Machine, XGBoost and LightGBM which are tree ensemble series, show the best performance as a whole. Additionally, the complexity of the model can be reduced through eliminating independent variables that have correlation coefficient between the variables and vacant house status lower than the 0.1 based on absolute value. Finally, this study suggests XGBoost and LightGBM based machine learning model, which can handle missing values, as final vacant house prediction model.

• Journal of The Korean Society of Integrative Medicine
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• v.12 no.2
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• pp.187-195
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• 2024

Purpose : Many studies have confirmed the relationship between physical exercise, chronic diseases, and quality of life, but few of those studies were limited to aerobic exercise. Above all, no research has confirmed the relationship between aerobic exercise and the oral health. This study is significant because it is the first study to confirm the relationship between aerobic exercise, which is practiced more frequently than other exercises, and oral health in adults. Through this study, we hoped to confirm the complex impacts of aerobic exercise on health-related quality of life, oral health-related behavior, and oral health status in adults and to use these impacts as basic data on the importance of aerobic exercise. Methods : In this study, the following analysis was conducted based on a complex sample design that applied stratification variables, cluster variables, and weights using SPSS version 21.0. Complex sample cross-analysis was conducted to identify general characteristics according to aerobic physical activity practice, and oral health-related characteristics according to the aerobic physical activity practice rate. Then, complex sample logistic regression analysis was conducted to determine the effect of aerobic physical activity practice on oral health-related characteristics. During the statistical analysis, missing values were treated as valid values, and the statistical significance level was set at .05. Results : Aerobic physical activity practice was 1.39 times higher among the respondents who brushed their teeth after lunch (p<.001), 1.43 times higher among those who used dental floss (p<.001), 1.24 times higher among those who used mouthwash (p=.040), and 1.37 times higher was among those who had not experienced dental treatment (p=.040), which were statistically significant differences. Conclusion : This study found that when an individual's health status is maintained, positive oral health behavior can be achieved by paying attention to oral health, and this appears to contribute to improving oral health.

• 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.

• The Korean Journal of Applied Statistics
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• v.24 no.3
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• pp.547-557
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• 2011

In this paper we developed a statistical model for traffic volume data which collected from a spot of specific local state road. One peculiar property of daily traffic data is that it has bimodal shape which have two peaks on times of both going to office and coming back to home. So, various mixture models of circular distribution are suggested for bimodal traffic data and EM algorithms are applied to estimate the parameters of the suggested models. To compare the accuracy of the suggested models, classical regressions with dummy variables are also considered. The suggested models for traffic volumn data can be effectively used to estimate missing values due to measuring instrument disorder.

• Asian Journal of Innovation and Policy
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• v.7 no.2
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• pp.310-337
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• 2018

Adoption of mobile learning (m-learning) is not new in Malaysian oil and gas industry, with heavy investment into research and development to train the workers. Nevertheless, the low application of learnt skills on the job remains an emergent research area where there is a missing link on the effects of m-learning and effective organisational learning and implication on its training transfer. The result of this quantitative research revealed that all variables in m-learning were found to have a positive relationship with the effective organisational learning, and there is evidence of training transfer as a mediator of the relationship between self-directed learning, training design, work environment and effective organisational learning. However, there were some discrepancies in the extend of training transfer between trainee characteristics and organisational learning. As such, some important issues emerged which challenge the importance of evaluating workers' readiness and transfer for a successful implementation of m-learning towards developing effective organisational learning.

• The Journal of Advanced Prosthodontics
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• v.9 no.6
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• pp.409-415
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• 2017

PURPOSE. Accurate information is essential in dentistry. The image information of missing teeth is used in optically based medical equipment in prosthodontic treatment. To evaluate oral scanners, the standardized model was examined from cases of image recognition errors of linear discriminant analysis (LDA), and a model that combines the variables with reference to ISO 12836:2015 was designed. MATERIALS AND METHODS. The basic model was fabricated by applying 4 factors to the tooth profile (chamfer, groove, curve, and square) and the bottom surface. Photo-type and video-type scanners were used to analyze 3D images after image capture. The scans were performed several times according to the prescribed sequence to distinguish the model from the one that did not form, and the results confirmed it to be the best. RESULTS. In the case of the initial basic model, a 3D shape could not be obtained by scanning even if several shots were taken. Subsequently, the recognition rate of the image was improved with every variable factor, and the difference depends on the tooth profile and the pattern of the floor surface. CONCLUSION. Based on the recognition error of the LDA, the recognition rate decreases when the model has a similar pattern. Therefore, to obtain the accurate 3D data, the difference of each class needs to be provided when developing a standardized model.

• Journal of Korean society of Dental Hygiene
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• v.13 no.6
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• pp.961-967
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• 2013

Objectives : The purpose of this study is to establish the regular scaling checkup service and to improve oral health care on the basis of knowledge, attitude, and belief by Dental Prophylaxis Practice Lab in A university. Methods : Subjects were 324 patients who visited Dental Prophylaxis Practice Lab in A university for the preventive removal of tartar from April to June 8, 2012. Data were analyzed using SPSS version 18.0 through the frequency analysis, chi-test, and logistics regression analysis. Results : In relation to scaling experience by age, 65.3% had experienced scaling checkup and those between 20 to 29 (34.7%) did not receive the scaling therapy. Smokers tended to have received more scaling experience than nonsmokers. Second, the number of untreated dental caries and missing teeth due to dental caries were important because the variables of oral health condition affected the scaling experience. Conclusions : It is necessary to increase the scaling experience and regular dental checkup by providing the education to improve dental clinics visit based on the knowledge and belief towards the scaling.

• The Korean Journal of Health Service Management
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• v.8 no.2
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• pp.187-195
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• 2014

To improve oral hygiene management, the effects of toothbrush training on general oral hygiene based on the simplified oral hygiene index(S-OHI) and degree of knowledge about toothbrushing were examined. Pre-and post-training changes in the S-OHI (lower score = better oral health status) showed a significant decrease in score in all variables (gender, age, marital status, occupation, and level of education).Pre- and post-training changes in the degree of knowledge about toothbrushing showed a significant increase. Negative correlations between the S-OHI, oral health status, and degree of knowledge about toothbrushing and the S-OHI and the Decayed, Missing, Filled (DMF) index (the better the oral cavity environment, the lower the DMF index) were observed. Positive effects of repeated toothbrush training on the maintenance of healthy oral cavity environment and continuous oral health management were observed, as reflected by the correct toothbrushing-related knowledge and skills.

• Korean Management Science Review
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• v.31 no.3
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• pp.1-12
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• 2014

This study suggests the two types DEA models such as DEA CCR model and Super Efficiency model to evaluate the value of a company and to apply them for the investments. 14 kinds of real data of companies such as EV/EBITDA, EPS growth rate, PCR, PER, dividend yield, PBR, stock price/net current asset, debt ratio, current ratio, ROE, operating margin, inventory turnover, accounts receivable turnover, and sales growth ratio were used as input variables of DEA models. 12 year data from December 30, 2000 up to December 30, 2012 were collected, and the data with negative, missing and 0 values were removed reflecting the characteristics of the DEA. In order to verify the effectiveness of the models, we compared the historical variability and rate of return of both models those of the market. Study results are as follows. First, two DEA models are more stable than market in terms of rate of return because the historical variability of both models are less than that of market. Second, Super Efficiency model is more stable than CCR model. Lastly, the cumulative rate of return of Super Efficiency model (434%) is greater than that of the CCR model (420%) and that of the market (269%).

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.1021-1031
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• 2020

This study aims to invest in empirical relationships in a model that becomes the process of Team-Performance due to participation in practical training through causality between Training Effectiveness variables, soft-skill competence, Employee-Creativity, and team performance. This study uses a quantitative approach. The analytical tool used is structural equation modeling (SEM) using AMOS version 23 software. Accidental sampling technique is used to collect the sample. As many as 202 respondents filled up a survey questionnaire with complete and valid answers. This study's results significantly contribute to fill the gap of inadequate empirical evidence that can answer critical questions about the missing link between training and employee-performance, more specifically between training-effectiveness and team-performance. The results showed that practical training would encourage employees' soft-skill competence, improve Employee-Creativity, and improve Team-Performance. Furthermore, training-effectiveness also plays a significant role in enhancing employee-creativity and helping in optimal team-performance. This study also found that the relationship between employee-creativity and team-performance did not show positive and significant results; therefore, empirically, it did not support the hypothesis built in this study. Practical training targeted towards increasing soft-skills and creativity is a fundamental reason which not only aims to contribute toward organizational performance but also provides personal feedback for self-development.