• Journal of the Korean Dietetic Association
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• v.28 no.2
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• pp.143-159
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• 2022

This study was undertaken to assess levels of job stress, self-efficacy, job satisfaction, and job involvement as perceived by school dietitians/nutrition teachers during the early stage of the COVID-19 pandemic and to determine the effects of these three factors. An online survey was sent from May 18 to May 26, 2021, to school dietitians/nutrition teachers in Seoul with experience of foodservice operations during 2020; 250 responses were used for this analysis. Job demands contributed most to job stress, whereas human relations contributed most to job satisfaction. Job stress caused by COVID-19 had a negative impact on self-efficacy (P<0.01) and job satisfaction (P<0.01), but a positive impact on job involvement (P<0.05). Self-efficacy positively impacted job involvement (P<0.01) but did not significantly influence job satisfaction. However, job satisfaction during early COVID-19 positively impacted job involvement (P<0.05). In conclusion, job stress associated with job requirements was greater during the early stage of the COVID-19 pandemic than before the pandemic guidelines are needed that enable school dietitians/nutrition teachers to better cope with the job pressures generated by infectious diseases.

• Korean Journal of Culture and Social Issue
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• v.28 no.3
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• pp.483-512
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• 2022

This study examined the patterns of coping strategies among Koreans during the early stage of the COVID-19 pandemic, explored the influence of demographic information (gender, age, economic level, household type), along with the unusual experiences due to COVID-19 (fear, stress of COVID, constraints of routine, income risk) on the classification of subclasses, and analyzed the latent profile differences in psychological wellbeing (life satisfaction, depression, and anxiety). An online survey was conducted among Korean Adults(n=600) between April 13, 2020 and 21, when WHO declared COVID-19 a global pandemic and Daegu as well as Gyeongsangbuk-do was nominated as a special disaster zone. First, Latent Profile Analysis (LPA) was used to identify subclasses of coping strategies and results suggested that the 4-class model had the best fit. Second, Class memberships were predicted by gender, age, economic level, as well as fear, stress, constraints of routine, and income risk, among the unusual experiences due to COVID-19. Finally, there are differences in psychological wellbeing among latent profiles. 'High level of adaptive coping group 3' showed the highest level of life satisfaction, 'Adaptive-maladaptive coping group 4' showed the highest level of depression, anxiety. Implications and suggestions are discussed based on the study results.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.913-921
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• 2021

The objective of the study is to investigate the impact of the COVID-19 pandemic on Saudi Arabia stock market. The study relied on the data of the daily closing stock market price index Tadawul All Share Index (TASI), and the number of daily cases infected with COVID-19 during the period from March 15, 2020, to August 10, 2020. The study employs the Vector Auto-Regressive (VAR) model, the Impulse Response Function (IRF) and Autoregressive Conditional Heteroscedasticity (ARCH) models. The results of the correlation matrix and the Impulse Response Function (IRF) show that stock market returns responded negatively to the growth in COVID-19 infected cases during the pandemic. The results of ARCH model confirmed the negative impact of COVID-19 pandemic on KSA stock market returns. The results also showed that the negative market reaction was strong during the early days of the COVID-19 pandemic. The study concluded that stock market in KSA responded quickly to the COVID-19 pandemic; the response varies over time according to the stage of the pandemic. However, the Saudi government's response time and size of the stimulus package have played an important role in alleviating the impacts of the COVID-19 pandemic on Saudi Arabia Stock Market.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.539-541
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• 2023

COVID-19 is a viral pandemic disease that spreads widely all around the world. The only way to identify COVID-19 patients at an early stage is to stop the spread of the virus. Different approaches are used to diagnose, such as RT-PCR, Chest X-rays, and CT images. However, these are time-consuming and require a specialized lab. Therefore, there is a need to develop a time-efficient diagnosis method to detect COVID-19 patients. The proposed machine learning (ML) approach predicts the presence of coronavirus based on clinical symptoms. The clinical dataset is collected from the Israeli Ministry of Health. We used different ML classifiers (i.e., XGB, DT, RF, and NB) to diagnose COVID-19. Later, classifiers are optimized with the Bayesian hyperparameter optimization approach to improve the performance. The optimized RF outperformed the others and achieved an accuracy of 97.62% on the testing data that help the early diagnosis of COVID-19 patients.

• Journal of Gastric Cancer
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• v.23 no.4
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• pp.574-583
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• 2023

Purpose: Gastric cancer (GC) is among the most prevalent and fatal cancers worldwide. National cancer screening programs in countries with high incidences of this disease provide medical aid beneficiaries with free-of-charge screening involving upper endoscopy to detect early-stage GC. However, the coronavirus disease 2019 (COVID-19) pandemic has caused major disruptions to routine healthcare access. Thus, this study aimed to assess the impact of COVID-19 on the diagnosis, overall incidence, and stage distribution of GC. Materials and Methods: We identified patients in our hospital cancer registry who were diagnosed with GC between January 2018 and December 2021 and compared the cancer stage at diagnosis before and during the COVID-19 pandemic. Subgroup analyses were conducted according to age and sex. The years 2018 and 2019 were defined as the "before COVID" period, and the years 2020 and 2021 as the "during COVID" period. Results: Overall, 10,875 patients were evaluated; 6,535 and 4,340 patients were diagnosed before and during the COVID-19 period, respectively. The number of diagnoses was lower during the COVID-19 pandemic (189 patients/month vs. 264 patients/month) than before it. Notably, the proportion of patients with stages 3 or 4 GC in 2021 was higher among men and patients aged ≥40 years. Conclusions: During the COVID-19 pandemic, the overall number of GC diagnoses decreased significantly in a single institute. Moreover, GCs were in more advanced stages at the time of diagnosis. Further studies are required to elucidate the relationship between the COVID-19 pandemic and the delay in the detection of GC worldwide.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.3
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• pp.327-335
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• 2022

The purpose of this study is to examine the Kuwaiti Stock Exchange's (KDE) response to the COVID-19 pandemic and the precautions taken by Kuwaiti authorities to protect their citizens and other residents. To achieve this objective, daily data from four different indexes published by the Kuwait Stock Exchange (KSE) for the period between 24 February and 30 June 2020, as well as daily data on the number of people infected with COVID-19, the daily number of recovered people, the daily number of deaths, lockdown days, and days the country was under curfew. The findings show a significant positive association between the daily recovery of persons infected by COVID-19 and all indexes published by the KSE except for the Boursa Kuwait Main Market 50, where the association was positive but insignificant. A negative and significant association was also found between the closure of the country and each of the four indexes. Although the curfew imposed by the Kuwaiti authorities at an early stage of the pandemic appeared to have a negative effect on the four indexes, the level of association was statistically significant only in the cases of the Main Market index and Boursa Kuwait Main Market 50 index.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.7
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• pp.463-474
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• 2020

This study aims to investigate the impact of COVID-19 pandemic on the stock markets of sixteen countries. Pooled OLS regression, conventional t-test and Mann-Whitney test are used to estimate the results of the study. We construct a weekly panel data of COVID-19 new cases and stock returns. Pooled OLS estimation result shows that the growth rate of weekly new cases of COVID-19 negatively predicts the return in stock market. Next, the returns on leading stock indices of these countries during the COVID-19 outbreak period are compared with returns during the non-COVID period. We use a t-test and Mann-Whitney test to compare the returns. The results reveal that investors in these countries do not react to the media news of COVID-19 at the early stage of the pandemic. However, once the human-to-human transmissibility had been confirmed, all of the stock market indices negatively reacted to the news in the short- and long-event window. Interestingly, we noticed that the Shanghai Composite Index, which was severely affected during the short-event window, bounced back during the long-event window. This indicates that the Chinese government's drastic measures to contain the spread of the pandemic regained the confidence of investors in the Shanghai Stock Market.

• The Research Journal of the Costume Culture
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• v.28 no.3
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• pp.285-298
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• 2020

This study aimed at examining fashion consumers' awareness during the COVID-19 pandemic. Big data analysis methods, such as text mining, social network analysis, and regression analysis, were applied to user posts about fashion on Korean portal websites and social media during COVID-19. R 3.4.4, UCINET 6, and SPSS 25.0 software were used to analyze the data. The results were as follows. In researching the popular fashion-related topics during COVID-19, the prevention of infection and prophylaxis were significant concerns in the early stage (Jan 1 to Jan 31, 2020), and changed to online channels and online fashion platforms. Then, various topics and fashion keywords appeared with COVID-19-related keywords afterwards. Fashion-related subjects concerned prophylaxis, home life, digital and beauty products, online channels, and fashion consumption. In comparing fashion consumers' awareness during COVID-19 with SARS and MERS, "face masks" was the common keyword for all three illnesses; yet, the prevention of infection was a major consumer concern in fashion-related subjects during COVD-19 only. As COVD-19 cases increased, the search volume for face masks, shoes, and home clothes also increased. Consumer awareness about face masks shifted from blocking yellow dust and micro-dust to the sociocultural significance and short supply. Keywords related to performance turned out to be the major awareness as to shoes, and home clothes were repurposed with an expanded range of use.

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.1-13
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• 2021

With the global pandemic of COVID-19, it is pointed out that exposure to false information to the public could cause serious problems. However, in pandemic situations, there is also an positive effect for the public to share private-led information rather than centralized unilateral delivery of information. This study analyzes the role of private-led information provision in infectious disease situations. To this end, topic modeling and sentiment analysis is carried out on online reviews of all COVID-19-related applications in Google Playstore provided by the Korean government and the private. The results showed that the user's evaluation of private apps, which were used from the early stage of COVID-19, was much higher than the apps provided by the government. In particular, users responded more positively to private apps than government apps in all aspects such as reliability of information, risk avoidance, timeliness, usefulness, and stability. Based on these results, a post-monitoring system is recommended rather than a pre-block of all private apps.

• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.4
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• pp.197-207
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• 2021

The threat of COVID-19 pandemic put many universities in Korea to develop and implement various types of non-face-to-face on-line classes, such as on-line real time class and on-line recorded video class. Online education has been recognized as one of the effective educational methods because of its ubiquitous and flexible educational environments. Even though COVID-19 led to many problems such as faculty's burden and stress during the early stage of COVID-19, both students and faculties have gradually become familiar with on-line environment. As students have got accustomed to the online environment, on-line recorded lectures are shown to be more preferred rather than on-line real time class. Researches regarding the learner's satisfaction of on-line classes during the COVID-19 indicate that systematic and good quality contents and interaction by instructor are important factors. This study, therefore, investigate the learner's satisfaction of online classes in Liberal Arts course using recorded video contents in terms of contents and interaction. The results of empirical analysis reveal that systematic and good quality contents are likely to predict learner's satisfaction and interaction plays a great role in providing those contents. These findings provide insights that preparing systematic contents and interaction are key to enhancing learner's satisfaction of on-line classes in Liberal Arts course.