• Journal of Korean Clinical Nursing Research
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• v.19 no.3
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• pp.357-368
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• 2013

Purpose: The purpose of this study was to investigate risk factors related to delirium and to develop screening model on delirium occurrence in MICU (Medical Intensive Care Unit) patients. Methods: For developing a preliminary tool for delirium, the data of 166 patients were collected and analyzed. In order to estimate the accuracy and discriminating power for the developed screening model, 98 patients were enrolled. The data used in this study were collected by EMR (Electronic Medical Record) review from January to September in 2012. The collected data were analyzed using SPSS/PC Win 18.0 program. Results: Screening model on delirium in MICU patients was developed using the results of logistic regression. The total score of screening model was 24 point and measuring point was 10 point. When the measuring point is over 10 point, it means that the risk of delirium occurrence is high. The discriminating power and the validity of screening model showed AUC .908 (p <.001) and .935 (p <.001) respectively. This result showed that the screening model on delirium which developed in this study was an appropriate model for screening the delirium risk group in MICU. The sensitivity of the screening model was 83%, specificity 89% and accuracy 84%. Conclusion: The developed screening model on delirium occurrence in MICU should be combined with EMR for screening and preventing delirium in a high risk group.

• Journal of Navigation and Port Research
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• v.48 no.2
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• pp.109-115
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• 2024

To develop a shipping company insolvency prediction model, we sampled shipping companies that closed between 2005 and 2023. In addition, a closed company and a normal company with similar asset size were selected as a paired sample. For this study, data of a total of 82 companies, including 42 closed companies and 42 general companies, were obtained. These data were randomly divided into a training set (2/3 of data) and a testing set (1/3 of data). Training data were used to develop the model while test data were used to measure the accuracy of the model. In this study, a prediction model for Korean shipping insolvency was developed using financial ratio variables frequently used in previous studies. First, using the LASSO technique, main variables out of 24 independent variables were reduced to 9. Next, we set insolvent companies to 1 and normal companies to 0 and fitted logistic regression, LDA and QDA model. As a result, the accuracy of the prediction model was 82.14% for the QDA model, 78.57% for the logistic regression model, and 75.00% for the LDA model. In addition, variables 'Current ratio', 'Interest expenses to sales', 'Total assets turnover', and 'Operating income to sales' were analyzed as major variables affecting corporate insolvency.

• Journal of Information Technology Applications and Management
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• v.31 no.1
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• pp.1-9
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• 2024

Predicting the spread of COVID-19 remains a challenge due to the complexity of the disease and its evolving nature. This study presents an integrated approach using the classic SIR model for infectious diseases, enhanced by the chemical master equation (CME). We employ a Monte Carlo method (SSA) to solve the model, revealing unique aspects of the SARS-CoV-2 virus transmission. The study, a first of its kind in Korea, adopts a step-by-step and complementary approach to model prediction. It starts by analyzing the epidemic's trajectory at local government levels using both basic and stochastic SIR models. These models capture the impact of public health policies on the epidemic's dynamics. Further, the study extends its scope from a single-infected individual model to a more comprehensive model that accounts for multiple infections using the jump SIR prediction model. The practical application of this approach involves applying these layered and complementary SIR models to forecast the course of the COVID-19 epidemic in small to medium-sized local governments, particularly in Gangnam-gu, Seoul. The results from these models are then compared and analyzed.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.3
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• pp.129-144
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• 2013

Recognizing a limits on quantitative evaluation of cultural contents' and for its betterment, study aims developing a qualitative evaluation model. For this study, Reception Theory, Semiotics and Psychology were derived for epistemological dimension to contemplate culture contents' essential attribute. To be concrete, cultural contents was examined as experiential products, emotional products, rememberable products and texts. Also, codes of fun, emotion and culture were discussed as intrinsic attributes for cultural contents and how those attributes were expressed or composed in cultural contents was discussed as well. Evaluation items were extracted based on final discussion at the epistemic level, set up the final evaluation model by taking experts' advices on each items. With all those outcomes, qualitative evaluation model for cultural contents was developed. For the importance of each index in the model, priority was granted by weighting on each index. Lastly, evaluation scale was developed for each index. The culture contents' evaluation model developed in study is meaningful not only in drawing qualitative evaluation items of video(image) contents and developing the index and model for the first time, but also its possibility of wide use for other genres.

• Journal of the Korean Institute of Landscape Architecture
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• v.28 no.1
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• pp.19-28
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• 2000

The purposes of this study are two folds: a) to introduce conjoint choice model to research the choice behavior of theme park users, and b) to suggest the strategies to strengthen the competitiveness of theme parks. The major four theme parks in Seoul metropolitan areas were selected as study areas. A leading polling agency was employed to select 432 respondents by probability sampling and to conduct face-to-face interview. Both alternative generating and choice set generating fractional factorial design were conducted simultaneously to meet the necessary and sufficient conditions for calibration of the conjoint choice model. Dummy coding was used to represent the attribute levels, and the alternative-specific model was calibrated. The goodness-of-fit of the model was quite satisfactory($\rho$$^2$=0.47950), and most parameters values had to expected sign and magnitude. Car was preferred transport mode to shuttle bus for visiting theme parks ; however the most ideal attribute levels only were estimated significantly. Most attribute levels of shuttle bus were estimated significantly except the Dream Land, which is the least attractive park among study areas. Simulation results showed that the shuttle bus was a mode worth providing to switch the current car dominant visiting pattern of theme parks, which will be one the effective strategies to attract more patrons, especially for potential users adjacent to parks. Several ideals were suggested for future researches, in terms of utilization of more general utility function and new base alternative, and inclusion of more salient attributes such as constraints in the model.

• Journal of Information Technology Applications and Management
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• v.22 no.2
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• pp.149-169
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• 2015

This study tried to find out how to overcome multicollinearity problems in the structural equation model by creating a hierarchical construct model about the repurchase intention of social commerce. This study selected, as independent variables, price, quality, service, and social influence, based on literature review about social commerce, and then, as detailed variables of independent variables, selected system quality, information quality, transaction safety, order fulfillment and after-sales service, communication, subjective norms, and reputation. As results of empirical analysis about hierarchical construct model, all the independent variables were accepted having a significant impact on repurchase intention of social commerce. Next, this study analyzed the competition model that eight independent variables of price, system quality, information quality, transaction safety, order fulfillment and after-sales service, communication, subjective norm, and reputation directly influence the repurchase intention of social commerce. As results of empirical analysis, system quality, information quality, transaction safety, communication appeared to be insignificant. This study showed that hierarchical construct model is useful to overcome the multicollinearity problem in structural equational model and to increase explanatory power.

• Communications of Mathematical Education
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• v.29 no.2
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• pp.197-214
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• 2015

This study is to design Flipped Learning classrooms of learner-centered education on the pre-service math teachers education. The study aims to explore the feasibility of teaching and learning method. To achieve the objectives of the study was to explore the teaching and learning model. Flipped learing classroom design includes a main step of a typical process of teaching system. And we designed the model based on the ADDIE Model. This model contains the design steps and the Flipped learning component of the teaching and learning design model. Designed classroom presented in three steps that are before classroom, during classroom and after classroom.

• Journal of the Korea Safety Management & Science
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• v.8 no.3
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• pp.1-9
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• 2006

Recently data mining techniques have been used for analysis and classification of data related to industrial accidents. The main objective of this study is to compare algorithms for data analysis of industrial accidents and this paper provides an optimal predicting model of 5 kinds of algorithms including CHAID, CART, C4.5, LR (Logistic Regression) and NN (Neural Network) with ROC chart, lift chart and response threshold. Also, this paper provides an approximation model for an optimal predicting model based on NN. The approximation model provided in this study can be utilized for easy interpretation of data analysis using NN. This study uses selected ten independent variables to group injured people according to a dependent variable in a way that reduces variation. In order to find an optimal predicting model among 5 algorithms, a retrospective analysis was performed in 67,278 subjects. The sample for this work chosen from data related to industrial accidents during three years ($2002\;{\sim}\;2004$) in korea. According to the result analysis, NN has excellent performance for data analysis and classification of industrial accidents.

• East Asian Journal of Business Economics (EAJBE)
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• v.4 no.2
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• pp.1-11
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• 2016

This study investigated commercial power theory of traditional market through the analysis of literature review. Consumers' store selection models are made up a theory based on normative hypothesis, theory of mutual reaction, utility function estimation model, and cognitive-behavioral model. Detailed models are as follows. Normative hypothesis based theory is divided into Reilly's retail gratification theory and Converse's revised retail g ratification theory. Interaction theory is composed of Huff's probability gratification theory, MCI model and Multi-nominal Logit Model (MNL model). There are four models in retail organization position theory such as central place theories, single store position theory, multi store position - assign model, and retail growth potential model. In case of single store position theory, theoretical and empirical techniques have developed for a decision to optimum single store position. Those are like these, a check list, the most simple and systematic method, analogy, and microanalysis technique. Aforementioned models are theoretical and mathematical commercial power measurement and/or model. The study has rather limitations because the variation factors included in formula are only a part of actual commercial power. Therefore, further study shall be made continuously to commercial power areas and variables.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.49-49
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• 2016

The impact of land cover changes on streamflow of the Akaki catchment will be assessed using Soil and Water Assessment Tool (SWAT) model. The study will analyze the historical land cover changes (1993 to 2016) that have taken place in the catchment and its effect on the streamflow of the study area. Arc GIS will be used to analysis the satellite images obtained from the United States Geological Survey (USGS). To investigate the impact of land cover change on streamflow the model set up will be done using readily available spatial and temporal data, and calibrated against measured discharge. Two third of the data will be used for model calibration (1993?2000) and the remaining one-third for model validation (2001?2004). Model performance will be evaluated by using Nash and Sutcliff efficiency (NS) and coefficient of determination (R2). The calibrated model will be used to assess two land cover change (2002 and 2016) scenarios and its likely impacts of land use changes on the runoff will be quantified. The evaluation of the model response to these changes on streamflow will be presented properly. The study will contribute a lot to understand land use and land cover change on streamflow. This enhances the ability of stakeholder to implement sound policies to minimize undesirable future impacts and management alternatives which have a significant role in future flood control of the study area.