• Fashion & Textile Research Journal
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• v.24 no.5
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• pp.593-604
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• 2022

The purpose of this study is to analyze the flow of change in perception of metaverse before and after COVID-19 through big data analysis. This research method used Textom to collect all data, including metaverse for two years before COVID-19 (2018.1.1~2019.11.30) and after COVID-19 outbreak (2020.1.11~2021.12.31), and the collection channels were selected by Naver and Google. The collected data were text mining, and word frequency, TF-IDF, word cloud, network analysis, and emotional analysis were conducted. As a result of the analysis, first, hotels, weddings, and glades were commonly extracted as social issues related to metaverse before and after COVID-19, and keywords such as robots and launches were derived, so the frequency of keywords related to hotels and weddings was high. Second, the association of the pre-COVID-19 metaverse keywords was platform-oriented, content-oriented, economic-oriented, and online promotion-oriented, and post-COVID-19 clusters were event-oriented, ontact sales-oriented, stock-oriented, and new businesses. Third, positive keywords such as likes, interest, and joy before COVID-19 were high, and positive keywords such as likes, joy, and interest after COVID-19. In conclusion, through this study, it was found that metaverse has firmly established itself as a new platform business model that can be used in various fields such as tourism, travel, festivals, and education using smart technology and metaverse.

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.111-119
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• 2023

This study aimed to analyze the changes in news articles related to 'Elderly Living Alone' by comparing Big Data-based news articles related to 'Elderly Living Alone' reported before and after the outbreak of COVID-19. For this, 2018 to 2019 were selected before the outbreak of COVID-19, and 2020 to 2021 were selected after the outbreak, and news articles related to 'Elderly Living Alone' were collected and analyzed using BIGKinds. The main results are as follows. First, the number of related articles decreased after the outbreak of COVID-19 compared to before. Second, there was no significant difference in the analysis of related words. Third, in the relationship diagram analysis, 'Executives' before the outbreak of COVID-19 and 'Corona 19' after that showed the most weight. This study is expected to be used as basic data in preparing improvement plans for national policies and systems in the context of the spread of infectious diseases in relation to 'Elderly Living Alone'.

• Anxiety and mood
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• v.19 no.2
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• pp.61-68
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• 2023

Objective : The purpose of this study was to investigate the associations between psychosocial factors and the mask-wearing behavior after deregulation of COVID-19 quarantine guidelines among adults in Korea. Methods : We collected data (345 subjects) from online questionnaire survey. The questionnaire included the Korean version of the Patient Health Questionnaire-9, the Korean version of fear of COVID-19 Scale, the Korean version of the Patient Health Questionnaire-15, Korean versions of the Perceived Stress Scale, and measurement tools adapted from previous studies for COVID-19 risk perception, social stigma, and appearance interest of subjects. We analysed data using SPSS version 23.0 for descriptive statistics, chi-square test, and logistic regression analysis. Results : People with cohabitant or mask-wearing tendency before COVID-19 pandemic had a higher rate of mask-wearing than those who were not. Subjects reporting higher level of social stigma (OR=1.154, 95% CI 1.049-1.270) and COVID-19 anxiety (OR=1.072, 95% CI 1.007-1.141) were more likely to report maskwearing behavior. Conclusion : From the results, appropriate intervention to those who fear social stigma and are anxious to the infectious diseases will be needed. Additionally, providing policies and guidelines that consider cohabitants and offering continuous education with information of disease to the public are also expected to helpful for recovery of daily life from infectious diseases.

• Journal of Preventive Medicine and Public Health
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• v.53 no.2
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• pp.67-69
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• 2020

Controversy remains over whether the coronavirus disease 2019 (COVID-19) virus may have infectivity during the incubation period before the onset of symptoms. The author had the opportunity to examine the infectivity of COVID-19 during the incubation period by conducting an epidemiological survey on a confirmed patient who had visited Jeju Island during the incubation period. The epidemiological findings support the claim that the COVID-19 virus does not have infectivity during the incubation period.

• Molecules and Cells
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• v.44 no.6
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• pp.384-391
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• 2021

The recent appearance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has affected millions of people around the world and caused a global pandemic of coronavirus disease 2019 (COVID-19). It has been suggested that uncontrolled, exaggerated inflammation contributes to the adverse outcomes of COVID-19. In this review, we summarize our current understanding of the innate immune response elicited by SARS-CoV-2 infection and the hyperinflammation that contributes to disease severity and death. We also discuss the immunological determinants behind COVID-19 severity and propose a rationale for the underlying mechanisms.

• Journal of the Korea Convergence Society
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• v.13 no.5
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• pp.463-471
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• 2022

Purposes of this study were to identify the factors associated with behavioral Intention to social distancing (BItSD) in a loss versus gain advertising context. This study is a secondary analysis of data surveyed after randomly allocating one of the loss and gain message framing advertisements for the prevention of coronavirus disease-2019 (COVID-19) infection to 379 adults aged 19 and over living in Korea in early March 2021. Attitude toward advertisement (𝛽=.03, p<.001), involvement in COVID-19 (𝛽=.14, p=.006) and emotional stigma (𝛽=-0.17, p<.001) were associated with BItSD, and the explanatory power of these variables was 19% (Adjusted R²=.19). Therefore, when health care professionals communicate with the public, they should develop the strategies to increase public people's involvement in the information and to induce positive advertising attitudes, and provide the effective messages to prevent stigma by accurate information.

• Journal of Convergence for Information Technology
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• v.12 no.3
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• pp.66-74
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• 2022

This study identified the impact of information literacy, risk perception, crisis communication on preventive behaviors related to COVID-19 among nursing students. Data were collected from 187 nursing students from 25 June 2020 to 3 July 2020, and analyzed using the SPSS/WIN 26.0 program. As a result of regression analysis, the factors influencing prevention behaviors were crisis communication(β=0.30, p<.001), information literacy(β=0.29, p<.001), and risk perception(β=0.19, p=.004). The explanatory power of the model was 27%. This study suggests that the focus should be on improving the activating crisis communication process among individual, family and society, increasing information literacy and risk perception on crisis when developing program to improve COVID-19 preventive behaviors of nursing students experiencing clinical practice.

• Journal of Life Science
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• v.31 no.6
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• pp.603-608
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• 2021

The purpose of this perspective research is to discuss the potential role of exercise-interventions in COVID-19, terms of prevention and prognosis in the periods of the COVID-19 vaccine. SARCO-CoV-2. COVID-19 was detected as a new virus causing severe cardiovascular and respiratory complications. It emerged as a global public health emergency and national pandemic. It caused more than 1 million deaths in the first 6 months of the pandemic and resulted in huge social and economic fluctuations internationally. Unprecedented stressful situations, such as COVID-19 blue and COVID-19 red impact on many health problems. In healthy individuals, COVID-19 infection may induced no symptoms (i.e., asymptomatic), whereas others may experience flu-like symptoms, such as ARDS, pneumonia, and death. Poor health status, such as obesity and cardiovascular and respiratory complications, are high risk factors for COVID-19 prevention, occurrence, and prognosis. Several COVID-19 vaccines are currently in human trials. However, the efficacy and safety of COVID-19 vaccines, including potential side effects, such as anaphylaxis (a life-threatening allergic reaction) and rare blood clots, still need to be investigated. On the basis of direct and indirect evidence, it seems that regular and moderate physical exercise can be recommended as a nonpharmacological, efficient, and safe way to cope with COVID-19. Physical inactivity and metabolic abnormalities are directly associated with reduced immune responses, including reduced innate, CMI, and AMI responses. Due to prolonged viral shedding, quarantine in inactive, obese and disease people should likely be longer than physical active people. Multicomponent and systemic exercise should be considered for the obese, disease, and elderly people. More mechanism research is needed in this area.

• Journal of Internet Computing and Services
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• v.22 no.1
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• pp.65-77
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• 2021

COVID-19 has recently impacted the world with the large numbers of infected and deaths. The development of effective COVID-19 vaccine has not been successful. Hence, people have a high concern on the infection of this disease. The infection information from the governmantal public organizations are mainly based on simple summary statistics. Consequently, it is hard to assess the infection risks of individual person and the current location of the person. In this paper, we present a machine learning-based software system that analyzes COVID-19 infection risks and guidelines for safe activities.This paper proposes a suite of risk factors regarding COVID-19 infection and deaths and methods to quantitatively measure the individual and group risks using the proposed metrics. The proposed system utilizes a clustering algorithms and various software approaches that reflect the information and features of inviduals and their geograpical locations.

• Korea Journal of Hospital Management
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• v.25 no.4
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• pp.1-12
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• 2020

During the COVID-19 pandemic, most of the western countries with advanced medical technology failed to contain coronavirus. This fact triggered our research question of what factors influence the clinical outcomes like infection rates and case mortality rates. This study aims to identify the determinants of COVID-19 related infection rates and case mortality rates. We considered three sets of independent variables: 1) socio-demographic characteristics; 2) cultural characteristics; 3) healthcare system characteristics. For the analysis, we created an international dataset from diverse sources like World Bank, Worldometers, Hofstede Insight, GHS index etc. The COVID-19 related statistics were retrieved from Aug. 1. Total cases are from 95 countries. We used hierarchical regression method to examine the linear relationship among variables. We found that obesity, uncertainty avoidance, hospital beds per 1,000 made a significant influence on the standardized COVID-19 infection rates. The countries with higher BMI score or higher uncertainty avoidance showed higher infection rates. The standardized COVID-19 infection rates were inversely related to hospital beds per 1,000. In the analysis on the standardized COVID-19 case mortality rates, we found that two cultural characteristics(e.g., individualism, uncertainty avoidance) showed statistically significant influence on the case mortality rates. The healthcare system characteristics did not show any statistically significant relationship with the case mortality rates. The cultural characteristics turn out to be significant factors influencing the clinical outcomes during COVID-19 pandemic. The results imply that the persuasive communication is important to trigger the public commitment to follow preventive measures. The strategy to keep the hospital surge capacity needs to be developed.