• Journal of Korean Public Health Nursing
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• v.36 no.3
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• pp.347-360
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• 2022

Purpose: The purpose of this study was to identify the risk perception, safety climate and preventive behaviors of COVID-19 infections, and to verify the factors influencing the adoption of preventive behaviors by health care workers. Methods: A mixed-method approach was used based on a survey carried out in a general hospital. Quantitative data (N=181) were collected through a questionnaire and analyzed using multiple regression. Qualitative data (N=8) were collected through individual interviews and analyzed through Colaizzi's phenomological research method. Results: The factors influencing adoption of preventive behaviors by health care workers were safety climate (β=.41, p<.001), education (β=-.20, p=.025), work unit (β=-.16, p=.032), and risk perception (β=.15, p=.020). The explanatory power was 28.3%, and they have shown that these health care workers felt 'the threat of a pandemic like a battlefield', experienced 'struggle with quarantine rules' and realized 'the reality of infection control and the reorganization for change'. Conclusion: The findings of this study indicate that to increase the adoption of infection control preventive behaviors by health care workers when faced with new infectious diseases in the future, it is necessary to establish organizational support and a safe climate. This study confirms the need for preemptive support and education.

• International Journal of Advanced Culture Technology
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• v.10 no.4
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• pp.316-321
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• 2022

Since 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread rapidly, infecting millions of people worldwide. On March 11, 2020, the World Health Organization declared coronavirus disease (COVID-19) a pandemic owing to the worldwide spread of SARS-CoV-2, which created an unprecedented burden on the global healthcare system. In this context, there are increasing concerns regarding co-infections with other respiratory viruses, such as the influenza virus. In this study, clinical data of patients infected with SARS-CoV-2 and other respiratory viruses were compared with patients infected with SARS-CoV-2 alone. The hematology and blood biochemistry results of 178 patients infected with SARS-CoV-2 , who were tested on admission, were retrospectively reviewed. In patients with SARS-CoV-2 and adenovirus co-infection, C-reactive protein levels were elevated on admission, whereas lactate dehydrogenase (LDH), prothrombin time, international normalized ratio, activated partial thromboplastin clotting time, and bilirubin values were all within the normal range. Moreover, patients with SARS-CoV-2 and human bocavirus co-infection had low LDH and high bilirubin levels on admission. These findings reveal the clinical features of respiratory virus and SARS-CoV-2 co-infections and support the development of appropriate approaches for treating patients with SARS-CoV-2 and other respiratory virus co-infections.

• Journal of Information Technology Services
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• v.21 no.6
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• pp.53-72
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• 2022

As a trend of modern service industry, self-service has been widely concerned by all walks of life, but there is a lack of literature on systematic management of the overall research in this field. Recently, people's lifestyle has been forced to change due to the influence of COVID-19, while there have been some changes in the field of self-service research. Based on the Web of Science data source, this study takes the literature of self-service field before and after the outbreak of COVID-19 as the research object, and summarizes the development process, research status and future research trend of self-service field through the Citespace visualization tool. The research shows that firstly, academic circles continue to be enthusiastic about self-service field research, cooperation between countries is becoming more and more diversified. Secondly, the communication between researchers is becoming more and more intensive, and the cooperation between different disciplines gradually becomes the mainstream. Third, related research gradually shifted to the practical application of technology, the research perspective gradually shifted from the initial traditional retail perspective industries such as tourism services. Finally, the role of customer experience and participation behavior in self-service process is gradually emphasized.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.352-358
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• 2022

In this paper, we study the relationship between infection rates of covid 19 and the precautionary measures and strict protocols taken by Saudi Arabia to combat the spread of the coronavirus disease and minimize the number of infected people. Based on the infection rates and the timetable of precautionary measures, the best framework of precautionary measures was identified by applying the traveling salesman problem (TSP) that relies on ant colony optimization (ACO) algorithms. The proposed algorithm was applied to daily infected cases data in Saudi Arabia during three periods of precautionary measures: partial curfew, whole curfew, and gatherings penalties. The results showed the partial curfew and the whole curfew for some cities have the minimum total cases over other precautionary measures. The gatherings penalties had no real effect in reducing infected cases as the other two precautionary measures. Therefore, in future similar circumstances, we recommend first applying the partial curfew and the whole curfew for some cities, and not considering the gatherings penalties as an effective precautionary measure. We also recommend re-study the application of the grouping penalty, to identify the reasons behind the lack of its effectiveness in reducing the number of infected cases.

• Journal of the Korean Society of School Health
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• v.35 no.2
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• pp.41-48
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• 2022

Purpose: The purpose of the study was to investigate the mediating effects of psychosocial well-being on the relationship between self-leadership and learning flow in nursing students. Methods: A total of 148 nursing students with online class experience participated in the study. The data were analyzed using the independent t-test, Pearson's correlation coefficient, PROCESS macro, and bootstrapping methods with SPSS Statistics 26.0. Results: The results showed that self-leadership, learning flow, and psychosocial well-being were significantly correlated, and self-leadership had a direct effect on learning flow. In other words, the higher the level of self-leadership, the higher the learning flow of nursing students. Psychosocial well-being was partially mediated by self-leadership and learning flow. Conclusion: It is necessary to develop and implement programs for self-leadership and psychosocial well-being enhancement as a strategy to enhance nursing students' learning flow.

• The Korean Journal of Emergency Medical Services
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• v.27 no.1
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• pp.79-90
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• 2023

Purpose: The study attempted to improve the health promotion behavior of university students by identifying the factors that affect health promotion behavior and by checking depression, anxiety, and stress levels of university students after the COVID-19 pandemic. Methods: We collected data using a structured questionnaire targeting 170 university students in C-province between December 1 and December 31, 2022. Results: Health promotion behavior had a significantly negative correlation with Depression (r=-.361, p<.001), Anxiety (r=-.191, p=.012), and Stress (r=-.301, p<.001), respectively. The influencing factors of health promotion behavior are gender (r=0.184, p<.001) and depression (r=-0.303, p<.001); the explanatory power is accounted for 15%. Conclusion: A practical method with counseling programs and mental health support services for early detection of risk groups by periodically monitoring the depression state of university students requires practicing health promotion behavior. Therefore, active support and attention should be provided to manage the mental health of university students.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.32-42
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• 2023

There are serious problems worldwide, such as a pandemic due to an unprecedented infection caused by COVID-19. On previous approaches, they invented medical vaccines and preemptive testing tools for medical engineering. However, it is difficult to access poor medical systems and medical institutions due to disparities between countries and regions. In advanced nations, the damage was even greater due to high medical and examination costs because they did not go to the hospital. Therefore, from a software engineering-based perspective, we propose a learning model for determining coronavirus infection through symptom data-based software prediction models and tools. After a comparative analysis of various models (decision tree, Naive Bayes, KNN, multi-perceptron neural network), we decide to choose an appropriate decision tree model. Due to a lack of data, additional survey data and overseas symptom data are applied and built into the judgment model. To protect from thiswe also adapt human normalization approach with traditional Korean medicin approach. We expect to be possible to determine coronavirus, flu, allergy, and cold without medical examination and diagnosis tools through data collection and analysis by applying decision trees.

• Biomedical Science Letters
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• v.28 no.4
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• pp.211-222
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• 2022

After more than two years of efforts to end the corona pandemic, a gradual recovery is starting in countries with high vaccination rates. Easing public health policies for a full-fledged post-corona era, such as lifting the mandatory use of outdoor mask and quarantine measures in entry have been considered in Korea. However, the continuous emergence of new variants of SARS-CoV-2 and limitations in vaccine efficacy still remain challenging. Fortunately, T cells and memory T cells, which are key components of adaptive immunity appear to contribute substantially in COVID-19 control. SARS-CoV-2 specific CD4⁺/CD8⁺ T cells are induced by natural infection or vaccination, and rapid induction and activation of T cells is mainly associated with viral clearance and attenuated clinical severity. In addition, T cell responses induced by recognition of a wide range of epitopes were minimally affected and conserved against the highly infectious subsets of omicron variants. Polyfunctional SARS-CoV-2 specific T cell memory including stem cell-like memory T cells were also developed in COVID-19 convalescent patients, suggesting long lasting protective T cell immunity. Thus, a robust T-cell immune response appears to serve as a reliable and long-term component of host protection in the context of reduced efficacy of humoral immunity and persistent mutations and/or immune escape.

• Journal of Distribution Science
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• v.20 no.3
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• pp.13-22
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• 2022

Purpose: Thisstudy aims to measure the attitudes of Generation Z in Jakarta towards advertisements containingCOVID-19 information. Research design, data and methodology: This study is a quantitative method with partial least square structural equation modeling (PLS-SEM) with SMART PLS as an analytical tool. The sample size is 216 participants was obtained randomly through a questionnaire distributed online. This study consisted of exogenous variables (advertising content, value, irritation, and economic benefits), endogenous variables (attitudes towards advertising), and some moderating roles. Results: The results of thi study explain that this generation's attitude towards advertising is affected by the content and value aspects embedded in advertisements. Value can be formed from creativity in making advertising content as interesting and informative as possible. Interestingly, this study also found that the irritation aspect and economic benefits had no effect on the audience's attitude towards the advertisement. Neither the irritating aspect of advertising nor the economic value that is formed acts as a moderator of the content and the value of the ad. Conclusions: The ongoing pandemic and periodic adjustments to government policies regarding COVID-19, these results can be compared with other advertisements for future studies, especially those using the same variables as this study.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.3
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• pp.217-227
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• 2022

Predicting return and volatility in the global Capital Market during a pandemic is challenging, and it is more difficult for a specific sector, particularly if that sector has a positive outlook. The goal of this research is to look at the impact of COVID-19 on the mean and volatility of the Information Technology Indexes of the best nine technology-driven countries based on return performance using an econometric GARCH model that is widely used. The daily returns of information technology indexes are evaluated for the same from November 2018 to February 2021. Data is taken from Yahoo Finance for CAC Tech (France), DAX Tech (Germany), FTSE All Tech (UK), KOPSI 200 IT (Korea), NIFTY IT (India), S&P 500 IT (US), S&P TSX (Canada), SSE_IT (China) and TOPIX17 (Japan). The results show daily positive mean returns for 8 countries' IT Indices and further, an uptrend in mean daily returns is observed in the crisis period for 6 countries' IT Indices. The exogenous variable COVID-19 which was taken as a regressor for the GARCH model was found to be positively significant for IT indices of all the countries. The overall results confirm the presence of the mean-reverting phenomenon for IT indices of all the countries.