• Asia-Pacific Journal of Business
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• v.13 no.1
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• pp.247-262
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• 2022

Purpose - The purpose of this study is to examine the impact of the Pandamic Declaration on 'untact firms' listed in KOSPI and KOSDAQ market in order to verify Investor Mania Hypothesis. Design/methodology/approach - This study collected financial data for 44 untact firms in KOSPI and KOSDAQ market. Then, we employed ESM(Event Study Methodology), EGARCH model and DID(Difference-In-Difference) for analysis. Findings - First, in contrast with the benchmarking index, KOSPI 200 which shows a negative (-) abnormal return trend, the untact firms have positive abnormal return trend consistently. Second, after the Pandemic Declaration, the variability of abnormal return for the untact firms is found to be significantly positive. Third, we find that the cumulative abnormal return and volatility of the untact firms significantly increase after the Pandemic Declaration. Research implications or Originality - Based on the Investor Mania Hypothesis, we confirm that the market potential of untact firms after the Pandemic Declaration is observed when compared with the KOSPI 200.

• Journal of Trauma and Injury
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• v.37 no.1
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• pp.60-66
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• 2024

Purpose: This study investigated changes in interpersonal violence and utilization of trauma recovery services during the COVID-19 pandemic. At an urban level I trauma center, trauma recovery services (TRS) provide education, counseling, peer support, and coordination of rehabilitation and recovery to address social and mental health needs. The COVID-19 pandemic prompted considerable changes in hospital services and increases in interpersonal victimization. Methods: A retrospective analysis was conducted between September 6, 2018 and December 20, 2020 for 1,908 victim-of-crime patients, including 574 victims of interpersonal violence. Outcomes included length of stay associated with initial TRS presentation, number of subsequent emergency department visits, number of outpatient appointments, and utilization of specific specialties within the year following the initial traumatic event. Results: Patients were primarily female (59.4%), single (80.1%), non-Hispanic (86.7%), and Black (59.2%). The mean age was 33.0 years, and 247 patients (49.2%) presented due to physical assault, 132 (26.3%) due to gunshot wounds, and 76 (15.1%) due to sexual assault. The perpetrators were primarily partners (27.9%) or strangers (23.3%). During the study period, 266 patients (mean, 14.9 patients per month) presented before the declaration of COVID-19 as a national emergency on March 13, 2020, while 236 patients (mean, 25.9 patients per month) presented afterward, representing a 74.6% increase in victim-of-crime patients treated. Interactions with TRS decreased during the COVID-19 period, with an average of 3.0 interactions per patient before COVID-19 versus 1.9 after emergency declaration (P<0.01). Similarly, reductions in length of stay were noted; the pre-COVID-19 average was 3.6 days, compared to 2.1 days post-COVID-19 (P=0.01). Conclusions: While interpersonal violence increased, TRS interactions decreased during the COVID-19 pandemic, reflecting interruption of services, COVID-19 precautions, and postponement/cancellation of elective visits. Future direction of hospital policy to enable resource and service delivery to this population, despite internal and external challenges, appears warranted.

• Health Policy and Management
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• v.20 no.1
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• pp.64-86
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• 2010

Korea has had problems with the price and supply of essential drugs such as Gleevec for leukemia, Fuzeon for HIV/AIDS, and Tamiflu for both avian flu and swine flu. The shortage or refusal of patented drugs supply is imposing a heavy burden in not only developing countries but also developed countries. Thinking over the serious results, we need to concern about the limited access to patented drugs by multinational drug companies' patent monopoly especially for pandemic and life threatening diseases. The effective response regarding to pandemic and life threatening diseases. The effective response regarding to pandemic situation requests collaborative and unbiased provisions of all countries in the world, however, sometimes patent monopoly may hinder the efforts. Compulsory licensing has been considered to be a useful alternative to the abuse of patent rights. However, the Korean experiences of compulsory licensing have left some controversial issues in connection with the availability of it in Korea. 'Flexibility' allowed in TRIPS and Doha Declaration has not come into effect in Korea for several reasons. Although the situation shows the limitations of compulsory licensing as a pharmaceutical supply policy, it is clear that compulsory licensing still has the possibilities of enhancing the access to medicines of all countries in need. Through searching the institutionalization process and experiments of compulsory licensing in Korea, this article explores the possibilities and the limits.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.5
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• pp.1377-1393
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• 2023

Social media is used for various purposes including entertainment, communication, information search, and voicing their thoughts and concerns about a service, product, or issue. The social media data can be used for information mining and getting insights from it. The World Health Organization has listed COVID-19 as a global epidemic since 2020. People from every aspect of life as well as the entire health system have been severely impacted by this pandemic. Even now, after almost three years of the pandemic declaration, the fear caused by the COVID-19 virus leading to higher depression, stress, and anxiety levels has not been fully overcome. This has also triggered numerous kinds of discussions covering various aspects of the pandemic on the social media platforms. Among these aspects is the part focused on vaccines developed by different countries, their features and the advantages and disadvantages associated with each vaccine. Social media users often share their thoughts about vaccinations and vaccines. This data can be used to determine the popularity levels of vaccines, which can provide the producers with some insight for future decision making about their product. In this article, we used Twitter data for the vaccine popularity detection. We gathered data by scraping tweets about various vaccines from different countries. After that, various machine learning and deep learning models, i.e., naive bayes, decision tree, support vector machines, k-nearest neighbor, and deep neural network are used for sentiment analysis to determine the popularity of each vaccine. The results of experiments show that the proposed deep neural network model outperforms the other models by achieving 97.87% accuracy.

• Biomedical Science Letters
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• v.26 no.3
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• pp.127-135
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• 2020

Coronavirus is generally known to cause minor respiratory diseases in animals and humans. However, some coronavirus genus is reported to cause animal-to-human interspecies infection. Since the end of 2019, a new type of coronavirus (COVID-19) infection is spreading rapidly throughout the world, leading to the declaration of the pandemic by the World Health Organization (WHO). Despite various clinical studies to counter COVID-19 infection, the total confirmed cases and death rates are still accumulating. To break down this new threat, we should pay attention to newly revealed information based on scientific facts. In this review, we introduced the clinical characteristics, diagnostic methods, and treatment of patients infected with COVID-19. Moreover, we highlighted the correlation between COVID-19 severity and patients with underlying diseases. Potential risks associated with COVID-19 can be differed depending on the condition of patients and can cause pulmonary complications. Therefore, lung capacity exams are expected to help predict the progression of the disease along with previously established detection methods such as molecular diagnostics and immunoassay. Although physiological research hasn't yet been emphasized to evaluate COVID-19 infection, this review is expected to be valuable to give new inspiration to deal with COVID-19 which might strike again in the future.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.32 no.4
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• pp.161-188
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• 2021

Libraries are experiencing numerous modifications to multifunctional spaces in response to the declaration of WHO pandemic. Most libraries throughout the globe have reported their closures, including national libraries in every country, and most established facing services have been transformed to untact services. However, the breadth of the service varies by local autonomous entity and library, making it difficult for librarians to act according to their conviction, and also users are feeling inconvenienced. As a result, this study used a user perception survey to determine the extent of non-face-to-face services in the library and to suggest the direction of operation of non-face-to-face services in a pandemic condition. To that purpose, beginning February 12, 2020, an online survey of library customers in 37 public libraries was performed for about three weeks, and the 117 replies were examined using the SPSS statistics tool to perform frequency analysis, regression analysis, correlation analysis, and reliability analysis. By the survey and data survey results, it was recommended that library services be re-established in the direction of non-face-to-face library service operation, that library non-face-to-face services be expanded, that user education be conducted, that non-face-to-face services be promoted, and that user opinions be collected.

• Journal of the Korea Convergence Society
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• v.11 no.9
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• pp.7-13
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• 2020

With the recent World Health Organization (WHO) Declaration of Pandemic for Coronavirus Disease-19 (COVID-19), COVID-19 is a global concern and many deaths continue. To overcome this, there is an increasing need for sharing information between countries and countermeasures related to COVID-19. However, due to linguistic boundaries, smooth exchange and sharing of information has not been achieved. In this paper, we propose a Neural Machine Translation (NMT) model specialized for the COVID-19 domain. Centering on English, a Transformer based bidirectional model was produced for French, Spanish, German, Italian, Russian, and Chinese. Based on the BLEU score, the experimental results showed significant high performance in all language pairs compared to the commercialization system.

• Journal of Preventive Medicine and Public Health
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• v.54 no.4
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• pp.238-244
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• 2021

Objectives: Previous pandemics have demonstrated that several demographic, geographic, and socioeconomic factors may play a role in increased infection risk. During this current coronavirus disease 2019 (COVID-19) pandemic, our aim was to examine the association of timing of lockdown at the county level and aforementioned risk factors with daily case rate (DCR) in the United States. Methods: A cross-sectional study using publicly available data was performed including Americans with COVID-19 infection as of May 24, 2020. The United States counties with >100 000 population and >50 cases per 100 000 people were included. The independent variable was the days required from the declaration of lockdown to reach the target case rate (50/100 000 cases) while the dependent (outcome) variable was the DCR per 100 000 on the day of statistical calculation (May 24, 2020) after adjusting for multiple confounding socio-demographic, geographic, and health-related factors. Each independent factor was correlated with outcome variables and assessed for collinearity with each other. Subsequently, all factors with significant association to the outcome variable were included in multiple linear regression models using stepwise method. Models with best R² value from the multiple regression were chosen. Results: The timing of mandated lockdown order had the most significant association on the DCR per 100 000 after adjusting for multiple socio-demographic, geographic and health-related factors. Additional factors with significant association with increased DCR include rate of uninsured and unemployment. Conclusions: The timing of lockdown order was significantly associated with the spread of COVID-19 at the county level in the United States.

• Journal of Environmental Health Sciences
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• v.47 no.3
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• pp.292-301
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• 2021

Objectives: Wearing medical masks has been recommended since the declaration of coronavirus disease-19 (COVID-19) as a pandemic disease. Certified medical masks are evaluated according to filtration efficiency and facial inhalation resistance. However, some people use non-certified common masks. This study aimed to evaluate various non-certified commercial masks based on the certification criteria for medical masks. Methods: Twenty mask products (three anti-droplet, three disposable dental, eight fashion, three cotton, and three children's masks) were selected. For performance evaluation, filtration efficiency and facial inhalation resistance tests were conducted. The evaluation method followed the certification method for KF-certified masks of the Ministry of Food and Drug Safety (MFDS) and the N95 respirator of the National Institute for Occupational Safety and Health (NIOSH). Results: None of the 20 masks met the KF94 certification standard set by the MFDS. Four and three masks respectively met the KF80 certification standard and the N95 standard of NIOSH. Filtration efficiency was significantly higher in three-layer masks than in single layer masks. Pleated-type masks had higher filtration efficiency than cone-type masks. There was no correlation between the structure of masks and facial inhalation resistance. Conclusion: While no masks complied with the KF94 certification standard, a few masks met the KF80 and the N95 certification standards of NIOSH. Although some people wear non-certified commercial masks, protection from aerosols is not guaranteed by such masks. Evaluation of the protection efficiency of non-certified mask against microbiological infection is needed for the prevention of infectious disease.

• Journal of Service Research and Studies
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• v.12 no.4
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• pp.50-71
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• 2022

After the declaration of the Covid-19 pandemic impacted most of the industries resulting economic fallout. Firms sought for solutions of governments regulations to prevent spread of infectious diseases. This led to demand rise of digital layer and spectrums of virtual reality. Replacing the reality in to virtual and interactions with the digital contents by augmented reality, the consequences were decrement of human-to-human contact. Concerns of Covid-19 and public interests of digital solutions has led to significant amounts of research and developments of Virtual/Augment Reality resulted to driven up new terms of extended reality. However, the uses in industries and the characteristics of the extended reality are currently not defined. In this paper the goal is to define and classify the uses and characteristics of extended reality based on previous researches suggested by research institute. By developing a new classification models of extended realities core technology, uses of industries and utility to analyze trends of extended reality. Two separate classification models of uses of industries and utility will be used as a tool by creating a linkage matrix. The x-axis is divided by utiliy classification model of extended reality. The y-axis are divided into classification model of uses in industries. This matrix will be used as a tool to present a guideline for industry-utility development where extended reality can be served as a service