• Korea Journal of Hospital Management
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• v.25 no.3
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• pp.29-37
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• 2020

Purposes: The purpose of this study was to identify the factors related to the long-stay hospitalization of dementia patients aged 65 years or older who had received inpatient care at geriatric hospitals according to the minute facility characteristics and patient features. Methodology: This study was conducted on 317,353 cases of 1,512 geriatric hospitals using the Health Insurance Review and Assessment Service dataset. The data collected were processed using the SAS Enterprise Guide 4.3 for descriptive statistics, the chi-square test, and the binary logistic regression analysis. Findings: As a result of the study, in the facility characteristics of geriatric hospitals, the long-stay hospitalization of the aged with dementia were found to be related to the type of facility establishment, the number of hospital beds, the number of medical specialists, the number of nursing personnel, and the number of geriatric hospitals by region and province. In the personal features of patients, the long-stay hospitalization was found to be associated with the gender, age, insurance, and the patient classification groups. Practical Implication: Considering the results of this study, it seems that securing the sufficient medical personnel in a geriatric facility, providing the good quality medical services, and preparing the appropriate discharge plan can reduce the unnecessary long-stay hospitalization and spend the medical expenses for the older patients.

• Journal of Environmental Health Sciences
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• v.31 no.2 s.83
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• pp.134-146
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• 2005

Environmental monitoring system has been adopted and supplemented as inspection measures for the quantitative and qualitative changes of environmental impact assessment (EIA). This study compares the results of environmental impact assessment with the results of post-environmental investigation using a correction and principal component analysis (PCA) in the housing development project. Correlation analysis showed that most of air quality variables including TSP, $PM_{10},\;NO_2$, CO were linearly correlated with each other in the environmental impact assessment and the post-environmental investigation. In the water quality, pH and BOD were well correlated with the DO and SS, respectively. As a result of correlation analysis in the noise and vibration, noise in day and night and vibration in day and night were related to each other between EIA and the post-environmental investigation. From the results of analysis of soil, Cu with Cd, Cu with Pb, and Cd with Pb were related to each other in EIA. Principal component analysis (PCA) showed a powerful pattern recognition that had attempted to explain the variance of a large dataset of inter-correlated variable with a smaller set of independent variables (principal components). Principal component (PC1) and principal component (PC2) were obtained with eigenvalues> 1 summing almost $90\%$ of the total variance in the all of the items(air, water, noise, vibration and soil) in EIA and post-environmental investigation.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.145-150
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• 2023

The subway is a public transportation that many people use every day. Line 2 especially has the most crowded stations during the day. However, the risk of crush accidents is increasing due to high congestion during rush hour and this reduces the safety and comfort of passengers. Subway congestion prediction is helpful to forestall problems caused by high congestion. Therefore, this study proposes machine learning classification models that predict subway congestion during commuting time. To predict congestion in Line 2 based in machine learning, we investigate variables that affect subway congestion through previous research and collect a dataset of subway congestion on Line 2 during rush hour from PUBLIC DATA PORTAL. The proposed model is expected to establish the subway operation plane to make passengers safe and satisfied.

• Korean Journal of Community Nutrition
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• v.28 no.5
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• pp.414-422
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• 2023

Objectives: This study evaluated usual dietary intakes of total fat and fatty acids among the Korean population based on the revised Dietary Reference Intakes for Koreans 2020 (2020 KDRIs). Methods: This study utilized data from the eighth Korea National Health and Nutrition Examination Survey (KNHANES 2019-2021). We included 18,895 individuals aged 1 year and above whose 1-day 24-hour dietary recall data were available. To calculate the external variability using the National Cancer Institute 1-day method, data from the U.S. NHANES 2017-March 2020 Pre-pandemic dataset were employed. The total fat and fatty acid intake were evaluated based on the Acceptable Macronutrient Distribution Ranges (AMDRs) and Adequate intake (AI) of 2020 KDRIs for each sex and age groups. Results: Approximately 86% of the Korean population obtained an adequate amount of energy from total fat consumption (within the AMDRs), indicating an appropriate level of intake. However, the percentage of individuals consuming saturated fatty acids below the AMDR was low, with only 12% among those under 19 years of age and 52% aged 19 years and older. On a positive note, approximately 70% of the population showed adequate consumption of essential fatty acids, exceeding the AI. Nevertheless, monitoring the intake ratio of omega 3 (n-3) to omega 6 (n-6) fatty acids is essential to ensure an optimum balance. Conclusions: This study explored the possibility of estimating the distribution of nutrient intake in a population by applying the external variability ratio. Therefore, if future KNHANES conduct multiple 24-hour recalls every few years-similar to the U.S. NHANES-even for a subset of participants, this may aid in the accurate assessment of the nutritional status of the population.

• Journal of information and communication convergence engineering
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• v.22 no.1
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• pp.33-43
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• 2024

Automated text summarization (ATS) systems rely on language resources as datasets. However, creating these datasets is a complex and labor-intensive task requiring linguists to extensively annotate the data. Consequently, certain public datasets for ATS, particularly in languages such as Thai, are not as readily available as those for the more popular languages. The primary objective of the ATS approach is to condense large volumes of text into shorter summaries, thereby reducing the time required to extract information from extensive textual data. Owing to the challenges involved in preparing language resources, publicly accessible datasets for Thai ATS are relatively scarce compared to those for widely used languages. The goal is to produce concise summaries and accelerate the information extraction process using vast amounts of textual input. This study introduced ThEconSum, an ATS architecture specifically designed for Thai language, using economy-related data. An evaluation of this research revealed the significant remaining tasks and limitations of the Thai language.

• Journal of Platform Technology
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• v.12 no.3
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• pp.3-15
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• 2024

Knowledge mining is a research field that applies various techniques such as data modeling, information extraction, analysis, visualization, and result interpretation to find valuable knowledge from diverse large datasets. It plays a crucial role in transforming raw data into useful knowledge across various domains like business, healthcare, and scientific research etc. In this paper, we propose analytical techniques for performing knowledge discovery and data mining from various data by extending the Formal Concept Analysis method. It defines algorithms for representing diverse formats and structures of the data to be analyzed, including models such as many-valued data table data and triadic data table, as well as algorithms for data processing (dyadic scaling and flattening) and the construction of concept hierarchies and the extraction of association rules. The usefulness of the proposed technique is empirically demonstrated by conducting experiments applying the proposed method to public open data.

• Korean Journal of Social Welfare
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• v.67 no.4
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• pp.279-299
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• 2015

This study examines the impact of Long-Term Care Insurance(LTCI) on family caregivers(especially focused on female household members) labor supply in South Korea. When public care and informal care are substitutes, LTCI will change allocation of time of family caregivers to spend more time to paid work. The impact of LTCI on labor supply depends on each country's institutional level of public care services. If public care can not substitute for informal care, labor supply of family caregivers will not rise significantly. The conclusions of vigorous empirical study from western countries' are incompatible and problem of endogeneity in terms of methodology has been raised consistently. The dataset of this study are used the third and ninth waves of Korea Welfare Panel. As a result, the introduction of LTCI had no effect on labor supply of household members. Robust findings suggest the positive effects of caregiving on labor market outcomes in simple comparison t-test, but not in fixed-effect regression. Compared with western countries, South Korea's public care services can be interpreted as a supplement to only part that remained at the level does not substitute informal care. These findings may suggest that if LTCI become much more prevalent in the future, senior citizens and family members will be able to choose the LTCI arrangement that best suits their needs.

• Journal of Technology Innovation
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• v.21 no.2
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• pp.199-223
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• 2013

Recently, R&D policy has importantly emphasized the creation of economic values added through the research performance developed by public research institutes. However, the research performance hasn't been still used and diffused effectively in Korea (Republic of Korea). This empirical study analyzes the effects of performance management & application capabilities and activities on technology transfer from public research institutes in Korea. Our dataset consists of total 84 Korean universities and government-funded research institutes in 2011. Performance management & application capabilities include dedicated organization, researcher-to-professional ratio, technology transfer and commercialization budget, and performance management & application activities include regular conduct of 3P analysis, pre-adjustment, post-management. The results show that performance management & application capabilities (except researcher-to-professional ratio) and activities are positively related to technology transfer. The results of this study contribute to the establishment of R&D policy to promote management & application of the research performance.

• Health Policy and Management
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• v.30 no.4
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• pp.479-492
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• 2020

Background: As the prevalence of hypertension is increasing in Korea, the government is seeking policy actions to manage patients with hypertension more efficiently. In this paper, we aimed to identify factors associated with the use of medical care at hospitals among outpatients with hypertension. Methods: We analyzed a total of 15,040 cases of 3,877 outpatients with hypertension obtained from the Korea Medical Panel database from 2010 to 2016. The dependent variable was whether a patient with hypertension visited a hospital or not; and independent variables were the patient's various socio-demographic, health-related, and heath-status characteristics. We conducted a generalized linear mixed model analysis with logit link for all the cases and then conducted it stratified by gender. Results: As a result of a multivariable analysis, women were less likely than to visit at a hospital (odds ratio [OR], 0.44; 95% confidence interval [CI], 0.32-0.61) and people aged 65 years and older than those aged less than 65 years (OR, 0.71; 95% CI, 0.57-0.89). Residents in Busan, Ulsan, and Gyeongnam were more likely than those in than Seoul, Gyeonggi, Incheon, and Jeju to visit a hospital (OR, 1.40; 95% CI, 1.05-1.86). The likelihood of visiting a hospital was high in people belonging to a group of: the highest level of annual household income (OR, 1.73; 95% CI, 1.30-2.29); Medical care aid recipients (OR, 1.94; 95% CI, 1.34-2.83); people having three or more complex chronic diseases (OR, 1.59; 95% CI, 1.19-2.11); people having diabetes (OR, 1.81; 95% CI, 1.41-2.32); or people having ischemic heart disease or cerebrovascular disease (OR, 6.80; 95% CI, 5.28-8.76). Also, we found that factors associated with the use of medical care at hospitals among outpatients with hypertension differed between genders. Conclusion: A variety of factors seem to be associated with the use of medical care at hospitals among outpatients with hypertension. Future research needs to find a way to help patients with hypertension visit an appropriate medical institution between clinics and hospitals.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.34 no.3
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• pp.202-213
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• 2024

Introduction: Acknowledging the global issue of diseases potentially caused by overwork, this study aims to develop an AI model to help workers understand the connection between cerebrocardiovascular diseases and their work environment. Materials and methods: The model was trained using medical and legal expertise along with data from the 2021 occupational disease adjudication certificate by the Industrial Accident Compensation Insurance and Prevention Service. The Polyglot-ko-5.8B model, which is effective for processing Korean, was utilized. Model performance was evaluated through accuracy, precision, sensitivity, and F1-score metrics. Results: The model trained on a comprehensive dataset, including expert knowledge and actual case data, outperformed the others with respective accuracy, precision, sensitivity, and F1-scores of 0.91, 0.89, 0.84, and 0.87. However, it still had limitations in responding to certain scenarios. Discussion: The comprehensive model proved most effective in diagnosing work-related cerebrocardiovascular diseases, highlighting the significance of integrating actual case data in AI model development. Despite its efficacy, the model showed limitations in handling diverse cases and offering health management solutions. Conclusion: The study succeeded in creating an AI model to discern the link between work factors and cerebrocardiovascular diseases, showcasing the highest efficacy with the comprehensively trained model. Future enhancements towards a template-based approach and the development of a user-friendly chatbot webUI for workers are recommended to address the model's current limitations.