• Journal of the Korea Convergence Society
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• v.10 no.9
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• pp.141-151
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• 2019

Purpose: This study aimed to identify the type of Sanhujori subjectivity experienced by husbands of pregnant women, and analyzed the characteristics of each type. Method: Q-methodology was used and 207 statements were extracted. Finally, 37 Q-samples were derived and 40 P-samples used the 9-point scale to distribute statements. Data were collected from March-May 2018 and analyzed using PC-QUANL program. Results: The analysis of factor weights and variables showed that 48.0% of the total variance was explained by three types of subjectivity, namely, 'couple-centered pursuit of women's health', 'expecting emotional recovery and requiring social support', and 'each family makes their own family system' for which the explanatory powers were 38.1%, 5.8%, and 4.1%, respectively. Conclusion: This study is meaningful as it explores Sanhujori from the viewpoint of husbands; its findings can be used to both evaluate Sanhujori service in Korea and provide basic data to develop convergent services for Sanhujori.

• The Journal of Korean Medical History
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• v.31 no.2
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• pp.91-101
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• 2018

Over the past 100 years, since the establishment of the modern medical education system in the early 1900s, the results of extensive field research and practice in North American medical schools and professional education have led the flow of medical education around the world. In this study, the direction of medical education in North America over the past 100 years were examined through major literature review, leading to implications and suggestions for Korean medicine education. The "Medical Education in the United States and Canada" published by the Carnegie Educational Foundation in 1910, which is considered to have laid the foundation for modern health care education, was reviewed. Next, "Educating physician: A Call for Reform of Medical School and Residency", published in 2010, which is known to have proposed a future-oriented goal for the training of medical professionals has been analyzed. The results of this study are as follows: 1) Acquisition and utilization of biomedical knowledge which is the basis of clinical competence, is a basic competency that should be provided to future medical professionals. 2) Beyond education to cultivate clinical competence of individuals directly affecting the medical treatment, various professionalism education programs that capture the specificity of Korean Medicine doctors should be established and strengthened.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.363-366
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• 2019

Blockchain technology is a new paradigm that will change existing business processes and has a significant impact on all industries, not just on specific industries. The medical industry also expects the impact of blockchain technology to be very significant. I think blockchain technology should be applied in the medical industry because the medical industry has the problem of information asymmetry due to the structural characteristics of a centralized system composed of hospitals. However, no one can be sure that the value of blockchain technology is absolutely right, and absolute trust should be avoided. Blockchain technology provides many limitations to the process in which blockchain technology is applied in the medical industry, as it can be seen as still immature in terms of security and scalability. Therefore, we analyze the application cases of blockchain technology in the medical field, current problems in the medical field, solutions and issues through Blockchain.

• Journal of Convergence for Information Technology
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• v.11 no.5
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• pp.259-266
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• 2021

This paper sought to help north Korean women understand their lives and seek to integrate the in-house between North and South Korea by organizing the overall reality of north Korea's fashionable hairstyles and beauty industry. The research method looks at the appearance management activities of North Koreans in north Korean media, media outlets, and testimonies of north Koreans who have been on the outstay since Kim Jong-un's ruling, among other things, and analyzed their hair activities. C. Studies have shown that some improvements have been made since the Kim Regime through the smuggling of foreign goods by yusists. In addition, it was confirmed that beauty education is being systematically edied out through a beauty training institute in North Korea, and that it has changed from a fixed salary system to an ability-based allowance. This study shows a limitation that north Korea has failed to study. It is believed to be a boon to future research on North Korean hair.

• Journal of Family Relations
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• v.21 no.4
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• pp.51-74
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• 2017

Objectives: This study observes how providing family support - financial, emotional, and instrumental - is related to depression in babyboom women. Method: I analysed data from the Korean Longitudinal Survey of Women and Families 5th wave, collected by the Korean Women's Development Institute. The analysis was conducted using regression, t-test, Chi-square test, frequency analysis, and Pearson's correlation analysis. Results: Financial support for grown-up children, either married or unmarried, increases depression in babyboom women. In the dimension of instrumental support, caring for grandchildren reduces babyboom women's depression. It implies that contact with grandchildren is perceived as an emotional support rather than a physical burden. The results of this study also show that babyboom women are comforted by living with their own parents, but not by living with parents-in-law. The most impressive observation, however, is in the dimension of emotional support, which showed that the conversation with elderly parents reduces baby-boom women's depression, but that the conversation with married children increases it. The opposite directions in the effects seem to be related to the subjects of the conversations. The subjects of the conversation with children are mostly about problems and agenda of the children, while those with elderly parents are mainly about parents' health and care for each other. Conclusions: The results of the analyses suggest that babyboom women should become less involved with their grown-up children's lives. It also calls for the societal efforts to be put into building up the support system, especially for eco-boom generation, to reduce babyboomer's burden of supporting the children.

• Oral Biology Research
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• v.42 no.4
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• pp.208-215
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• 2018

The purpose of this study was to identify the risk of dysphagia among patients that visited prosthodontics department, and evaluate the difference in risks arising from oral conditions and disease in order to preliminarily intervene the various influencing factors of dysphagia. A questionnaire was given to patients that were aged 65 years or older who visited the prosthodontics department between September to December 2017. The data was collected and analyzed using the t-test, $x^2-test$ and logistic regression analysis. The mean age of the patients was 75 years. Out of 300 patients, 206 patients (68.7%) had a risk of dysphagia. There were statistically significant differences between the -non-risk and risk groups, which included the number of natural teeth, total number of teeth including prosthesis, denture use, denture discomfort, number of tooth brushing, oral dryness, digestive system diseases, and musculoskeletal diseases. Among these, oral dryness was a risk factor while the total number of teeth, including natural teeth and prostheses, served as a protective factor. More than half of the elderly patients were at risk of dysphagia. Oral dryness is influenced by many factors and it should continuously be managed. Patients should fully recover their masticatory function by preserving the remaining teeth and compensating for the missing teeth. A dental practitioner should be fully aware of the risk of dysphagia in elderly patients and be able to intervene and offer proper patient health care in advance through treatment guidelines and education.

• Design & Manufacturing
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• v.14 no.4
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• pp.17-24
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• 2020

Products for heating indoors in low temperature and dry winter are largely divided into products using fossil fuels and products using electricity. The fossil fuels can warm the entire space by convection, but there is a high risk of fire and the frequent ventilation due to the increase in carbon monoxide and carbon dioxide. Heaters using electricity are mainly used because they are convenient to use and are cheap. However, these products can not efficiently warm the air because they use radiation energy. In other words, only the front part exposed to the heater is warm, and the rear part has no heating effect at all. Also, because it emits a large amount of light, fatigue of the eyes is very high. Another problem is that when using electric heaters, the room tends to be dry by high heat. Indoor humidity maintenance is a very important factor in the prevention and treatment of respiratory diseases. Especially, it is essential for health care for infants, bronchial organs and people with weak respiratory because humidity is low in winter. In this study, we conducted a study to develop a product that can improve heating efficiency while maintaining proper indoor humidity by combining heat energy and moisture particles. The concept of humidification and heating at the same time, moisture particles generated in the humidifier pass through the heater, include thermal energy, and the moisture particles with thermal energy are diffused into the space by forced convection, thereby warming the entire space. In addition, the heating time is shortened as the feeling temperature is increased with the high relative humidity, and this has the effect that the heating cost in winter is reduced.

• Journal of International Academy of Physical Therapy Research
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• v.12 no.1
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• pp.2261-2266
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• 2021

Background: Deep learning related research works on website medical images have been actively conducted in the field of health care, however, articles related to the musculoskeletal system have been introduced insufficiently, deep learning-based studies on classifying orthopedic manual therapy images would also just be entered. Objectives: To create a deep learning model that categorizes cervical mobilization images and establish a web application to find out its clinical utility. Design: Research and development. Methods: Three types of cervical mobilization images (central posteroanterior (CPA) mobilization, unilateral posteroanterior (UPA) mobilization, and anteroposterior (AP) mobilization) were obtained using functions of 'Download All Images' and a web crawler. Unnecessary images were filtered from 'Auslogics Duplicate File Finder' to obtain the final 144 data (CPA=62, UPA=46, AP=36). Training classified into 3 classes was conducted in Teachable Machine. The next procedures, the trained model source was uploaded to the web application cloud integrated development environment (https://ide.goorm.io/) and the frame was built. The trained model was tested in three environments: Teachable Machine File Upload (TMFU), Teachable Machine Webcam (TMW), and Web Service webcam (WSW). Results: In three environments (TMFU, TMW, WSW), the accuracy of CPA mobilization images was 81-96%. The accuracy of the UPA mobilization image was 43~94%, and the accuracy deviation was greater than that of CPA. The accuracy of the AP mobilization image was 65-75%, and the deviation was not large compared to the other groups. In the three environments, the average accuracy of CPA was 92%, and the accuracy of UPA and AP was similar up to 70%. Conclusion: This study suggests that training of images of orthopedic manual therapy using machine learning open software is possible, and that web applications made using this training model can be used clinically.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1075-1080
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• 2020

The development of computing technology and networking is developing as the fundamental technology of the 4th industrial revolution. AR and VR technologies, which are dual realistic media fields, are developing into many application areas, especially! The potential for development in the medical field is very high. As for the development potential of the health care field, the 4th industrial revolution such as AR/VR to solve problems, such as the increase of various chronic diseases due to the aging of the population, the limitation of infrastructure that can deal with them, and the lack of specialized personnel. It is adopting services in the healthcare field using representative technologies. Accordingly, AR/VR in the healthcare field occupies about 17% of the total industrial market. Therefore, in this study, cognitive judgment technology using AR applies cognitive evaluation through a computing system to the mild cognitive impairment, and based on the results, researches to utilize cognitive rehabilitation contents using augmented reality, and hardware necessary for cognitive judgment technology. Also, software design to help in the field of cognitive judgment technology and healthcare using AR.

• Journal of Biomedical Engineering Research
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• v.42 no.4
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• pp.175-185
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• 2021

Purpose: Vital sign are used to help assess the general physical health of a person, give clues to possible diseases, and show progress toward recovery. Researchers are using vital sign data and AI(artificial intelligence) to manage a variety of diseases and predict mortality. In order to analyze vital sign data using AI, it is important to select and extract vital sign data suitable for research purposes. Methods: We developed a method to visualize vital sign and early warning scores by processing retrospective vital sign data collected from EMR(electronic medical records) and patient monitoring devices. The vital sign data used for development were obtained using the open EMR big data MIMIC-III and the wearable patient monitoring device(CareTaker). Data processing and visualization were developed using Python. We used the development results with machine learning to process the prediction of mortality in ICU patients. Results: We calculated NEWS(National Early Warning Score) to understand the patient's condition. Vital sign data with different measurement times and frequencies were sampled at equal time intervals, and missing data were interpolated to reconstruct data. The normal and abnormal states of vital sign were visualized as color-coded graphs. Mortality prediction result with processed data and machine learning was AUC of 0.892. Conclusion: This visualization method will help researchers to easily understand a patient's vital sign status over time and extract the necessary data.