• Journal of Internet Computing and Services
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• v.21 no.5
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• pp.139-148
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• 2020

Infectious diseases have long plagued mankind, and predicting and preventing them has been a big challenge for mankind. For this reasen, various studies have been conducted so far to predict infectious diseases. Most of the early studies relied on epidemiological data from the Centers for Disease Control and Prevention (CDC), and the problem was that the data provided by the CDC was updated only once a week, making it difficult to predict the number of real-time disease outbreaks. However, with the emergence of various Internet media due to the recent development of IT technology, studies have been conducted to predict the occurrence of infectious diseases through web data, and most of the studies we have researched have been using single Web data to predict diseases. However, disease forecasting through a single Web data has the disadvantage of having difficulty collecting large amounts of learning data and making accurate predictions through models for recent outbreaks such as "COVID-19". Thus, we would like to demonstrate through experiments that models that use multiple Web data to predict the occurrence of infectious diseases through LSTM models are more accurate than those that use single Web data and suggest models suitable for predicting infectious diseases. In this experiment, we predicted the occurrence of "Malaria" and "Epidemic-parotitis" using a single web data model and the model we propose. A total of 104 weeks of NEWS, SNS, and search query data were collected, of which 75 weeks were used as learning data and 29 weeks were used as verification data. In the experiment we predicted verification data using our proposed model and single web data, Pearson correlation coefficient for the predicted results of our proposed model showed the highest similarity at 0.94, 0.86, and RMSE was also the lowest at 0.19, 0.07.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.728-739
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• 2020

Using webometric big data, this study examines the diversity of online information sources about the novel coronavirus causing the COVID-19 pandemic. Specifically, it focuses on some 28 countries where confirmed coronavirus cases occurred in February 2020. In the results, the online visibility of Australia, Canada, and Italy was the highest, based on their producing the most relevant information. There was a statistically significant correlation between the hit counts per country and the frequency of visiting the domains that act as information channels. Interestingly, Japan, China, and Singapore, which had a large number of confirmed cases at that time, were providing web data related to the novel coronavirus. Online sources were classified using an N-tuple helix model. The results showed that government agencies were the largest supplier of coronavirus information in cyberspace. Furthermore, the two-mode network technique revealed that media companies, university hospitals, and public healthcare centers had taken a positive attitude towards online circulation of coronavirus research and epidemic prevention information. However, semantic network analysis showed that health, school, home, and public had high centrality values. This means that people were concerned not only about personal prevention rules caused by the coronavirus outbreak, but also about response plans caused by life inconveniences and operational obstacles.

• Journal of Christian Education in Korea
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• v.62
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• pp.285-311
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• 2020

Many people are suffering from the economic crisis and poverty that are deepening due to the recent spread of the COVID-19 epidemic. In this situation, this study focuses on the biblical Jubilee in order to seek how "Jubilee justice" can be realized in the modern context. The Law of Jubilee consists of four contents: the liberation of slaves, debt remission, land return and fallow. Ultimately it aims to prevent human slavery and preserve equality. Nevertheless, the thought of Jubilee has been distorted theologically and situationally, and as a result, it has been overlooked in the field of Christian education, and there is a limit in Christian practice for social justice. The thought of Jubilee, however, can be an alternative to overcome various problems of modern society such as the issue of the privatization of Christianity or the deepening of polarization caused by neoliberal globalization and can contribute positively to the practice of social justice. In other words, the thought of Jubilee can act as a biblical initiative in reforming wrong laws and establishing institutions for the poor on the institutional level; on the personal level, it can be a great motive in terms of the change of perception and the practice of the sharing economy. Jubilee education, which aims for Jubilee justice, helps to break the misconceptions and change the existing meaning perspectives on the basis of various interdisciplinary knowledge and supports social behavior for transforming social structure through activation of public opinion and fund raising at the practical level. Therefore, the learners of Christian education can play a public role in transforming the unjust society.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.6
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• pp.181-190
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• 2021

Sports activities conducted by multiple people are difficult to proceed in a situation where a widespread epidemic such as COVID-19 is spreading, and this causes a lack of physical activity in modern people. This problem can be overcome by using online exercise contents, but it is difficult to check detailed postures such as during face-to-face exercise. In this study, we present a model that detects posture and tracks movement using IT system for better non-face-to-face exercise content management. The proposed motion tracking model defines a body model with reference to motion analysis methods widely used in physical education and defines posture and movement accordingly. Using the proposed model, it is possible to recognize and analyze movements used in exercise, know the number of specific movements in the exercise program, and detect whether or not the exercise program is performed. In order to verify the validity of the proposed model, we implemented motion tracking and exercise program tracking programs using Azure Kinect DK, a markerless motion capture device. If the proposed motion tracking model is improved and the performance of the motion capture system is improved, more detailed motion analysis is possible and the number of types of motions can be increased.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.5
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• pp.157-166
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• 2022

Exercise is necessary for a healthy life, but it is recommended that it be conducted in a non-face-to-face environment in the context of an epidemic such as COVID-19. However, in the existing non-face-to-face exercise content, it is possible to recognize exercise movements, but the process of interpreting and providing feedback information is not automated. Therefore, in this paper, to solve this problem, we propose a method of creating a formalized rule to track the contents of exercise and the motions that constitute it. To make such a rule, first make a rule for the overall exercise content, and then create a tracking rule for the motions that make up the exercise. A motion tracking rule can be created by dividing the motion into steps and defining a key frame pose that divides the steps, and creating a transition rule between states and states represented by the key frame poses. The rules created in this way are premised on the use of posture and motion recognition technology using motion capture equipment, and are used for logical development for automation of application of these technologies. By using the rules proposed in this paper, not only recognizing the motions appearing in the exercise process, but also automating the interpretation of the entire motion process, making it possible to produce more advanced contents such as an artificial intelligence training system. Accordingly, the quality of feedback on the exercise process can be improved.

• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.432-438
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• 2021

This dissertation's object is to confirm the drastic popularity of La Peste of Albert Camus in Korea post-corona society using big data as the mean of inductive research. Analyzing news articles concerning Camus and investigating word frequency of the book La Peste will affirm the implications La Peste has on current Korea society as the outbreak spreads. As an analysis tool, Bigkinds of Korea Press Foundation and Nuagedemots, the French version of Word Cloud were used. For the past 30 years, Albert Camus has been known in Korea as the writer of L'étranger, but after the epidemic, he earned more reputation with La Peste. Compared to L'étranger that rebelled against the world's absurdity with ennui, La peste emphasizes the importance of resistance accompanied by solidarity. La peste conveys hope by depicting disastrous situations of citizens who confront the plague by organizing a health college. The novel delivers a lot of ethical inspiration to humanity in this exceptional circumstance of COVID-19.

• Journal of Korean Medical classics
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• v.37 no.2
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• pp.49-76
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• 2024

Objectives : The purpose of this paper is to examine the mechanism and treatment of the Zangfu warm disease in the Beijiqianjinyaofang. Methods : This study examined the Zangfu warm disease content in the Beijiqianjinyaofang, Shanghanzongbinglun, Saninfang, based on the Neijing explanation of the pathological mechanism. Treatment was analyzed among the three texts in terms of their similarity and difference. Results & Conclusions : 1. Zangfu warm disease is caused by seasonally inappropriate qi, which is infectious, epidemic, and seasonal. 2. While the Qingjinqian disease pattern was explained in terms of the relationship between Shaoyin and Shaoyang, the actual disease pattern happened more in the Taiyang channel, and partly in the Shaoyang channel. For treatment of Fu deficiency pattern, the Chaihudihuangtang was listed in the Qianjinyaofang and the Shanghanzongbinglun, while in the Sanyinfang, the formula was modified to extinguish heat and thin phlegm, while reinforcing healthy qi. 3. The Chimaifei disease pattern was explained in terms of the relationship between Shaoyin and Taiyang that is deeply associated with Wei qi. For treatment of Fu deficiency the Qianjinyaofang and Shanghanzongbinglun used the Shigaodihuangtang, while the Sanyinfang reinforced healthy qi and eliminated pathogenic qi. 4. The Huangrousui disease pattern was explained as being caused by problems in the Taiyin and Yangming, in which the Triple Burner fails to control and manage cold dampness. In treating Zang excessiveness, the Qianjinyaofang and Shanghanzongbinglun used the Xuanshenhanshuishitang, while the Sanyinfang instructed to reinforce healthy qi and eliminate pathogenic qi. In treating Fu deficiency, the Sanyinfang instructed to warm the center and dry dampness, tonifying the Spleen and reinforcing qi. 5. The Baiqili disease pattern was explained within the relationship between Taiyin and Taiyang. In treating Fu deficiency, the Qianjinyaofang and Shanghanzongbinglun used the Shigaoxingrentang, while the Sanyinfang instructed to reinforce healthy qi and eliminate pathogenic qi. In treating Zang excessiveness, the Qianjinyaofang and Shanghanzongbinglun used the Shigaocongbaitang, while the Sanyinfang instructed to reinforce healthy qi and eliminate pathogenic qi. 6. The Heiguwen disease pattern was explained as being caused by stagnation and obstruction in the Triple Burner due to clash between Taiyang and Shaoyin. In treating Zang excessiveness, the Qianjinyaofang and Shanghanzongbinglun used the Kushenshigaotang, while the Sanyinfang instructed to reinforce healthy qi and eliminate pathogenic qi. The Zangfu Warm Disease is a infectious disease concept which is based on the Five Zang that integrates the meridian aspect together with the Six Fu with which there is an external/internal relationship. This concept and treatment could be considered in dealing with COVID-19.