• Journal of Venture Innovation
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• v.6 no.3
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• pp.165-184
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• 2023

Since municipal welfare institutions operate for different purposes from general companies or public enterprises, ESG practice items and model construction should be conducted through various and comprehensive social welfare studies. Since there are not many studies available in domestic welfare institutions yet and there are no suitable ESG management utilization indicators, the Cheonan Welfare Foundation's strategy and management strategy system were established to spread the model to other welfare institutions and become a leading foundation through education and training. The foundation and front-line welfare institutions selected issues identification and key issues through the foundation's empirical analysis and criticality analysis, focusing on understanding ESG management and ways to establish a practice model that positively affects institutional image and business performance. Based on this, the promotion system was examined by establishing a performance management plan after deriving appropriate strategies and establishing a strategic system for social welfare institutions. Environmental and social responsibility, transparent management, safety management system establishment, emergency and prevention, user (customer) satisfaction system establishment, anti-corruption prevention and integrity ethics monitoring and evaluation, responsible supply chains, and community contribution programs. This study attempted to specifically present efforts to settle ESG management through the consideration of the Cheonan Welfare Foundation. Therefore, it is considered to be useful data for developing ESG management by referring to the systematic development process of the Cheonan City Restoration Foundation to develop ESG measurement indicators.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.155-166
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• 2023

This study was conducted with 50 elderly people each (5) participating in the cognitive rehabilitation treatment program at the Dementia Care Center in D City to derive the development direction and contents of a multidimensional therapeutic recreation program and a revitalization plan through analysis of the current status and actual conditions of the cognitive rehabilitation program at the Dementia Care Center. aperture) was selected, and 9 people were selected as the subject of expert group opinion collection. The collected data was SPSS ver. Using the 18.0 statistical program, descriptive statistics and the importance and priority of each component were analyzed by hierarchical structure analysis. First, unlike the needs of users, the cognitive rehabilitation support programs currently being provided are not sufficient and require considerable experience. It was found to be low, and the areas for improvement were the expansion of care and protection facilities and the development of various programs to meet the needs of users. Second, the importance and priority of each component of therapeutic recreation were categorized into 6 major categories: exercise therapy , middle category (16 items) behavior-centered approach to exercise therapy, small category (47 items) strength and brain gymnastics, and silver health gymnastics were the highest. This result shows that a multidimensional program plan that considers the priorities of each area must be made when developing a therapeutic recreation program.

• Korean Journal of Culture and Social Issue
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• v.8 no.1
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• pp.41-59
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• 2002

The present study explored the major behavior patterns of drivers and the environmental settings having an effect on traffic accident using the data collected from drivers and traffic police. Drivers and traffic police read questionnaire which contain the passible causes of traffic accident and selected the major causes on the basis of their latest accidents. Unexperienced drivers were forced to answer the questionnaire by referring to their friends and neighborhoods. The results showed that the major causes of traffic accident were connected with the driver's factors. The most important cause of traffic accidents was inattention/incautiousness. The next were lack of competence, skill, and experience. One interesting fact was that drivers and traffic police attributed differently. Drivers pointed out the lack of ability coping with an emergency and the insufficient skill of defensive driving as causes of the traffic accident. On the other hand, traffic polices indicated the intentional violations such as the disregard for traffic rules, trespassing on the central line of the roadway, speed limit violation, and breaking into the vehicle's line. The implications for appling the this results to driver education institutions were discussed.

• Journal of Korea Water Resources Association
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• v.56 no.12
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• pp.939-953
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• 2023

Shallow water equations (SWE) serve as fundamental equations governing the movement of the water. Traditional numerical approaches for solving these equations generally face various challenges, such as sensitivity to mesh generation, and numerical oscillation, or become more computationally unstable around shock and discontinuities regions. In this study, we present a novel approach that leverages the power of physics-informed neural networks (PINNs) to approximate the solution of the SWE. PINNs integrate physical law directly into the neural network architecture, enabling the accurate approximation of solutions to the SWE. We provide a comprehensive methodology for formulating the SWE within the PINNs framework, encompassing network architecture, training strategy, and data generation techniques. Through the results obtained from experiments, we found that PINNs could be an accurate output solution of SWE when its results were compared with the analytical method. In addition, PINNs also present better performance over the Artificial Neural Network. This study highlights the transformative potential of PINNs in revolutionizing water resources research, offering a new paradigm for accurate and efficient solutions to the SVE.

• Quality Improvement in Health Care
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• v.30 no.1
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• pp.120-131
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• 2024

Purpose: This study aimed to evaluate the impact of implementing a clinical pathways (CPs) on the clinical outcomes and costs of patients undergoing breast cancer surgery. Methods: This retrospective cohort study included patients who were newly diagnosed with primary breast cancer at the Samsung Medical Center between 2014 and 2019 (N=8482; 2931 patients in the pre-path and 5551 patients in the post-path). Clinical outcomes included reoperation during hospitalization, readmission, and emergency room visits within 30 days of discharge. The cost data for each unit were obtained from an activity-based management accounting system. We performed an interrupted time series analysis. Results: The post-path period showed a significantly shorter hospital length of stay (LOS) than the pre-path period (6.3 days in pre-path vs. 5.0 days in post-path; -1.3 days' difference; p=.001), and fewer reoperations during hospitalization and within 30 days after discharge than the pre-path period. After adjusting for inflation rates and relative value scores, the model demonstrated savings of $146 per patient in the post-path for total costs, and $537 per patient for patient out-of-pocket costs (p=.001). Conclusion: CPs can help reduce costs without compromising the quality of care by reducing the number of reoperations, readmissions, and complications.

• Korean Journal of Radiology
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• v.21 no.1
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• pp.88-100
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• 2020

Objective: We aimed to develop and validate a deep learning system for fully automated segmentation of abdominal muscle and fat areas on computed tomography (CT) images. Materials and Methods: A fully convolutional network-based segmentation system was developed using a training dataset of 883 CT scans from 467 subjects. Axial CT images obtained at the inferior endplate level of the 3rd lumbar vertebra were used for the analysis. Manually drawn segmentation maps of the skeletal muscle, visceral fat, and subcutaneous fat were created to serve as ground truth data. The performance of the fully convolutional network-based segmentation system was evaluated using the Dice similarity coefficient and cross-sectional area error, for both a separate internal validation dataset (426 CT scans from 308 subjects) and an external validation dataset (171 CT scans from 171 subjects from two outside hospitals). Results: The mean Dice similarity coefficients for muscle, subcutaneous fat, and visceral fat were high for both the internal (0.96, 0.97, and 0.97, respectively) and external (0.97, 0.97, and 0.97, respectively) validation datasets, while the mean cross-sectional area errors for muscle, subcutaneous fat, and visceral fat were low for both internal (2.1%, 3.8%, and 1.8%, respectively) and external (2.7%, 4.6%, and 2.3%, respectively) validation datasets. Conclusion: The fully convolutional network-based segmentation system exhibited high performance and accuracy in the automatic segmentation of abdominal muscle and fat on CT images.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.111-124
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• 2018

This study aims to develop a classification model for predicting the occurrence of hyperlipidemia, one of the chronic diseases. Prior studies applying data mining techniques for predicting disease can be classified into a model design study for predicting cardiovascular disease and a study comparing disease prediction research results. In the case of foreign literatures, studies predicting cardiovascular disease were predominant in predicting disease using data mining techniques. Although domestic studies were not much different from those of foreign countries, studies focusing on hypertension and diabetes were mainly conducted. Since hypertension and diabetes as well as chronic diseases, hyperlipidemia, are also of high importance, this study selected hyperlipidemia as the disease to be analyzed. We also developed a model for predicting hyperlipidemia using SVM and meta learning algorithms, which are already known to have excellent predictive power. In order to achieve the purpose of this study, we used data set from Korea Health Panel 2012. The Korean Health Panel produces basic data on the level of health expenditure, health level and health behavior, and has conducted an annual survey since 2008. In this study, 1,088 patients with hyperlipidemia were randomly selected from the hospitalized, outpatient, emergency, and chronic disease data of the Korean Health Panel in 2012, and 1,088 nonpatients were also randomly extracted. A total of 2,176 people were selected for the study. Three methods were used to select input variables for predicting hyperlipidemia. First, stepwise method was performed using logistic regression. Among the 17 variables, the categorical variables(except for length of smoking) are expressed as dummy variables, which are assumed to be separate variables on the basis of the reference group, and these variables were analyzed. Six variables (age, BMI, education level, marital status, smoking status, gender) excluding income level and smoking period were selected based on significance level 0.1. Second, C4.5 as a decision tree algorithm is used. The significant input variables were age, smoking status, and education level. Finally, C4.5 as a decision tree algorithm is used. In SVM, the input variables selected by genetic algorithms consisted of 6 variables such as age, marital status, education level, economic activity, smoking period, and physical activity status, and the input variables selected by genetic algorithms in artificial neural network consist of 3 variables such as age, marital status, and education level. Based on the selected parameters, we compared SVM, meta learning algorithm and other prediction models for hyperlipidemia patients, and compared the classification performances using TP rate and precision. The main results of the analysis are as follows. First, the accuracy of the SVM was 88.4% and the accuracy of the artificial neural network was 86.7%. Second, the accuracy of classification models using the selected input variables through stepwise method was slightly higher than that of classification models using the whole variables. Third, the precision of artificial neural network was higher than that of SVM when only three variables as input variables were selected by decision trees. As a result of classification models based on the input variables selected through the genetic algorithm, classification accuracy of SVM was 88.5% and that of artificial neural network was 87.9%. Finally, this study indicated that stacking as the meta learning algorithm proposed in this study, has the best performance when it uses the predicted outputs of SVM and MLP as input variables of SVM, which is a meta classifier. The purpose of this study was to predict hyperlipidemia, one of the representative chronic diseases. To do this, we used SVM and meta-learning algorithms, which is known to have high accuracy. As a result, the accuracy of classification of hyperlipidemia in the stacking as a meta learner was higher than other meta-learning algorithms. However, the predictive performance of the meta-learning algorithm proposed in this study is the same as that of SVM with the best performance (88.6%) among the single models. The limitations of this study are as follows. First, various variable selection methods were tried, but most variables used in the study were categorical dummy variables. In the case with a large number of categorical variables, the results may be different if continuous variables are used because the model can be better suited to categorical variables such as decision trees than general models such as neural networks. Despite these limitations, this study has significance in predicting hyperlipidemia with hybrid models such as met learning algorithms which have not been studied previously. It can be said that the result of improving the model accuracy by applying various variable selection techniques is meaningful. In addition, it is expected that our proposed model will be effective for the prevention and management of hyperlipidemia.

• Child Health Nursing Research
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• v.8 no.1
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• pp.32-43
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• 2002

The purpose of this study was to provide basic data on elementary school children's lifestyle and to contribute to developing on the health education program in elementary schools. The subjects were 1,412 children in 4 elementary schools in Gangwon-Do and Chonrabuk-Do area. Data collection was done from September to November 2001 by questionnaire and school health documents. The questionnaire corrected for the purpose of this study which had been developed by Bronson School of Nursing(1991), 'Lifestyle Questionnaire for School-age Children'. The questionnaire consists of 3 categories; 'Activities that promote health', 'Injury prevention', 'Feeling'. Cronbach coefficient alpha for the 29 items was .68. The data analyzed to obtain frequency, mean, percentage, t-test, ANOVA and Pearson correlation coefficient by SPSS Win program. The results of this study were as follows. 1. Females(50.2%) of gender, 6th grade(24.2%) of grade, nuclear family(82.0%) of family type, beyond college graduate(54.5%) of father's school career, under high school graduate(58.1%) of mother's school career, first of birth order(47.1%) were majority. Mean of father's age was 41.2 and mother's age was 38.1. 2. The mean of lifestyle was 66.4, feeling was 73.3, activities that promote health was 60.3 and injury prevention was 64.0. The highest degree of activities that promote health was 「I eat fruits」and injury prevention was 「I look both ways when crossing streets」and feeling was 「I enjoy my family」. The lowest degree of activities that promote health was 「I visit the dentist every tear」 and injury prevention was 「I wear a helmet when I go on bike trips」 and feeling was 「I think it is okay to cry」. 3. There were significant differences in lifestyle of gender(t=4.309, p=.000), grade(F=6.299, p=.000), father's age(t=2.534, p=.011), father's education(t=-4.933, p=.000), mother's education(t=-3.360, p=.001), birth order (t=5.363, p=.000). There were significant differences in activities that promote health of gender(t=-2.462, P=.014), grade(F=4.893, p=.000), father's education(t=-4.480, p=.000), birth order(t=4.343, p=.000), in injury prevention of gender(t=-4.452, p=.000), grade(F=8.636, p=.000), father's age(t=3.386, p=.001), mother's age(t=2.059, p=.040), father's education(t=-6.051, p=.000), mother's education(t=-5.173, p=.000), birth order(t=4.417, p=.000) and in feeling of gender (t=-3.285, p=.001), grade(F=7.526, p=.000), mother's age(t=-3.268, p=.001). 4. Activities that promote health was positively correlated with injury prevention(r=.432, p=.000), feeling(r=.210, p=.000), lifestyle (r=.785, p=.000). Injury prevention was positively correlated with feeling(r=.256, p=.000), lifestyle(r=.854, p=.000) also feeling was positively correlated with lifestyle(r=.504, p=.000). These findings suggest the need to develop nursing strategy to promote elementary school children's health. Because helmet use score in injury prevention marked the lowest score, it is necessary to encourage helmet use when planning injury prevention and health promotion.

• The Korean Society of Law and Medicine
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• v.21 no.1
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• pp.223-259
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• 2020

With COVID-19 spreading rapidly around the world, research and development issues on treatments and vaccines for the virus are of high interest. Among them, Remdesivir was the first to show noticeable therapeutic effects and began clinical trials, with each country authorizing the use of the drug through emergency approval. However, Gilead Co., Ltd., the developer of Remdesivir, received a lot of criticism from civic groups for submitting the application for the marketing authorization as an orphan drug. This is because when a new drug got a marketing authorization as an orphan drug could be granted an exclusive status for seven year. The long-term exclusive status of an orphan drug comes from the policy purpose of motivating pharmaceutical companies to develop treatment opportunities for patients suffering from rare diseases, which was not appropriate to apply to infectious disease treatments. This paper provides a review of the problems and improvement directions of the domestic system through comparative legal consideration against the United States, Europe and Japan for the statutes which give exclusive status to medicines. The domestic system has a fundamental problem that it does not have explicit provisions in the statute in the manner of granting exclusive status, and that it uses the review system to give it exclusive status indirectly. In addition, in the case of orphan drugs, the "Rare Diseases Management Act" and the "Regulations on Examination of Items Permission and Reporting of Drugs" provide overlapping review periods, and despite the relatively long monopoly period, there seems to be no check clause to recover exclusive status in the event of a change in circumstances. Given that biopharmaceuticals are difficult to obtain patents, the lack of such provisions is a pity of domestic legislation, although granting exclusive rights may be a great motivation to induce drug development. In the United States, given that the first biosimilar also has a one-year monopoly period, it can be interpreted that domestic legislation is quite strictly limited to granting exclusive status to biopharmaceuticals. The need for improvement of the domestic system will be recognized in that it could undermine local pharmaceutical companies' willingness to develop biopharmaceuticals in the future, and in that it is also necessary to harmonize international regulations. Taking advantage of the emergence of COVID-19 as an opportunity, we look again at the problems of the domestic system that grants exclusive rights to medicines and hope that an overall revision of the relevant legislation will be made to establish a unified legal basis.

• Journal of Internet Computing and Services
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• v.22 no.4
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• pp.83-98
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• 2021

The purpose of this study to find the factors influencing the fire alarms using IoT firefighting facility management system data of Seoul Fire & Disaster Headquarters, and to present academic implications for establishing an effective prevention system of fire situation. As the number of high and complex buildings increases and former bulidings are advanced, the fire detection facilities that can quickly respond to emergency situations are also increasing. However, if the accuracy of the fire situation is incorrectly detected and the accuracy is lowered, the inconvenience of the residents increases and the reliability decreases. Therefore, it is necessary to improve accuracy of the system through efficient inspection and the internal environment investigation of buildings. The purpose of this study is to find out that false detection may occur due to building characteristics such as usage or time, and to aim of emphasizing the need for efficient system inspection and controlling the internal environment. As a result, it is found that the size(total area) of the building had the greatest effect on the fire alarms, and the fire alarms increased as private buildings, R-type receivers, and a large number of failure or shutoff days. In addition, factors that influencing fire alarms were different depending on the main usage of the building. In terms of time, it was found to follow people's daily patterns during weekdays(9 am to 6 pm), and each peaked around 10 am and 2 pm. This study was claimed that it is necessary to investigate the building environment that caused the fire alarms, along with the system internal inspection. Also, it propose additional recording of building environment data in real-time for follow-up research and system enhancement.