• BMB Reports
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• v.55 no.9
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• pp.465-471
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• 2022

Understanding and monitoring virus-mediated infections has gained importance since the global outbreak of the coronavirus disease 2019 (COVID-19) pandemic. Studies of high-throughput omics-based immune profiling of COVID-19 patients can help manage the current pandemic and future virus-mediated pandemics. Although COVID-19 is being studied since past 2 years, detailed mechanisms of the initial induction of dynamic immune responses or the molecular mechanisms that characterize disease progression remains unclear. This study involved comprehensively collected biospecimens and longitudinal multi-omics data of 300 COVID-19 patients and 120 healthy controls, including whole genome sequencing (WGS), single-cell RNA sequencing combined with T cell receptor (TCR) and B cell receptor (BCR) sequencing (scRNA(+scTCR/BCR)-seq), bulk BCR and TCR sequencing (bulk TCR/BCR-seq), and cytokine profiling. Clinical data were also collected from hospitalized COVID-19 patients, and HLA typing, laboratory characteristics, and COVID-19 viral genome sequencing were performed during the initial diagnosis. The entire set of biospecimens and multi-omics data generated in this project can be accessed by researchers from the National Biobank of Korea with prior approval. This distribution of large-scale multi-omics data of COVID-19 patients can facilitate the understanding of biological crosstalk involved in COVID-19 infection and contribute to the development of potential methodologies for its diagnosis and treatment.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.457-467
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• 2021

This paper aims to analyze changes in urban space use due to social distancing measures for COVID-19 using de facto population data in Seoul during daytime, which is estimated by Seoul Metropolitan Government and telecommunication company of KT using public big data and LTE signal data. The result of kernel density estimation and spatial autocorrelation analysis shows that the distribution patterns of de facto population in 2019 and 2020 were generally similar. This is a result of showing that the government's social distancing measures enabled a certain level of normal activities while suppressing the spread of COVID-19. However, analyzing de facto population subtracting 2019 from 2020 showed different results at the micro level. De facto population decreased in commercial areas but increased in residential areas. This means that COVID-19 social distancing measures had spatially uneven effect. The results of analyzing the effect of regional, land use, economic, educational, and accessibility characteristics on the changes of de facto population using spatial regression analysis are as follows. The higher the density of commercial facilities, the more businesses subject to regulations and schools and universities that require non-face-to-face classes, the more de facto population decreased. Conversely, it was found that de facto population increased in areas with many houses and parks due to telecommuting.

• The Journal of Information Systems
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• v.32 no.4
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• pp.211-227
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• 2023

Purpose In the contemporary landscape, marked by the enduring impact of COVID-19 and the recent disruptions stemming from the conflict in Ukraine, the purpose of this study is to navigate the era characterized by pervasive risk and uncertainty. Specifically, the study aims to dissect the impact of the COVID-19 outbreak on digital transformation, exploring the factors influencing this process and considering the multifaceted dynamics at play. The focus extends to the post-COVID-19 landscape, scrutinizing the implications and meanings of digital transformation both before and after the pandemic. Additionally, the study delves into future digital trends, with particular attention to climate and environmental issues, emphasizing corporate responsibilities in averting crises similar to COVID-19. The overarching goal is to provide a holistic perspective, shedding light on both positive and negative facets of digital transformation, and advocating for regulatory enhancements and legal frameworks conducive to a balanced and resilient digital future. Design/methodology/approach This study employs a comprehensive approach to analyze the impact of the COVID-19 outbreak on digital transformation. It considers various facets, such as smart devices reshaping daily routines, transformative changes in corporate ecosystems, and the adaptation of government institutions to the digital era within the broader context of the Fourth Industrial Revolution. The analysis extends to the post-COVID-19 landscape, examining the implications and meanings of digital transformation. Future digital trends, especially those related to climate and environmental issues, are prognosticated. The methodology involves a proactive exploration of challenges associated with digital transformation, aiming to advocate for regulatory enhancements and legal frameworks that contribute to a balanced and resilient digital future. Findings The findings of this study reveal that the digital economy has gained momentum, accelerated by the proliferation of non-face-to-face industries in response to social distancing imperatives during the COVID-19 pandemic. Digital transformation, both preceding and succeeding the onset of the pandemic, has precipitated noteworthy shifts in various aspects of daily life. However, challenges persist, and the study highlights factors that either bolster or hinder the transformative process. In the post-COVID-19 era, corporate responsibilities in averting crises, particularly those resembling the pandemic, take center stage. The study emphasizes the need for a holistic perspective, acknowledging both positive and negative facets of digital transformation. Additionally, it calls for proactive measures, including regulatory enhancements and legal frameworks, to ensure a balanced and resilient digital future.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.3
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• pp.141-156
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• 2023

Due to the unprecedented worldwide pandemic of the new Covid-19 infection, business trends of companies have changed significantly. Therefore, it is strongly required to monitor the rapid changes of innovation trends to design and plan future businesses. Since the pandemic, many studies have attempted to analyze business changes, but they are limited to specific industries and are insufficient in terms of data objectivity. In response, this study aims to analyze business trends after Covid-19 using Crunchbase, a global startup data. The data is collected and preprocessed every two years from 2018 to 2021 to compare the business trends. To capture the major trends, a network analysis is conducted for the industry groups and industry information based on the co-occurrence. To analyze the minor trends, LDA-based topic modelling and word2vec-based clustering is used. As a result, e-commerce, education, delivery, game and entertainment industries are promising based on their technological advances, showing extension and diversification of industry boundaries as well as digitalization and servitization of business contents. This study is expected to help venture capitalists and entrepreneurs to understand the rapid changes under the impact of Covid-19 and to make right decisions for the future.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.163-171
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• 2021

This study aimed to investigate the main characteristics of the COVID-19 vaccine-related videos spread on YouTube and differences in user responses in the infodemic situation caused by COVID-19. As a result of content analysis of 579 videos related to the COVID-19 vaccine, it was found that all of the false information was written by individual channels. Institutions, organizations, media companies, and government channels reported spread of false information as well as fact-oriented reporting. The progressive channel had a high percentage of positive sentiment in favor of vaccination, and the conservative channel had a high percentage of negative emotion against vaccination. After the vaccination started, the number of videos on government channels increased, and it was found that the number of videos with positive emotions increased. Results of regression analysis of video characteristics that affect the number of likes indicated that personal expert videos and videos from progressive channels received more likes. Combining the research results, we propose a plan to promote government policies regarding the COVID-19 vaccine using social media.

• Journal of the Korea Convergence Society
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• v.13 no.4
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• pp.531-540
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• 2022

This study is a descriptive survey study attempted to find out the difference in stress by occupation before and after responding to COVID-19 among care facility for the elderly. In this study, a survey was conducted on workers in care facility for the elderly in Chungcheongnam-do and Gyeonggi-do from March 22 to April 25, 2021. Of a total of 220 questionnaires, 206 were collected, and the data were analyzed through t-test, one way ANOVA, and chi-square test. According to the research results, the difference in the sub-areas of job stress before and after the COVID-19 response of nursing home workers shows that nurses have job demands(t=-3.90, p<.001), job instablity(t=-3.30, p=.002), the nursing assistant has job demands(t=-2.45, p=.018), nursing care workers have job autonomy(t=-3.34, p=.001) showed a significant difference. Therefore, in order to effectively solve job stress according to the occupation of workers in care facility for the elderly in the COVID-19 era, stress relief programs for each occupation must be customized.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.2
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• pp.306-312
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• 2022

During the unprecedented COVID-19 outbreak, the public's information needs created an environment where they overwhelmingly consume information on the chronic disease. Given that news media affect the public's emotional well-being, the pandemic situation highlights the importance of paying particular attention to how news stories frame their coverage. In this study, COVID-19 news speech emotion from mainstream broadcasters in South Korea and the United States (US) were analyzed using convolutional neural networks. Results showed that neutrality was detected across broadcasters. However, emotions such as sadness and anger were also detected. This was evident in Korean broadcasters, whereas those emotions were not detected in the US broadcasters. This is the first quantitative vocal emotion analysis of COVID-19 news speech. Overall, our findings provide new insight into news emotion analysis and have broad implications for better understanding of the COVID-19 pandemic.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.2
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• pp.117-123
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• 2022

Currently the number of COVID-19 cases is increasing rapidly around the world. One way to restrict the spread of COVID-19 infection is to find confirmed cases using rapid diagnosis. The previously proposed group testing problem assumed without measurement noise, but recently, false positive and false negative cases have occurred during COVID-19 testing. In this paper, we define the noisy group testing problem and analyze how much measurement noise affects the performance. In this paper, we show that the group testing system should be designed to be less susceptible to measurement noise when conducting group testing with a low positive rate of COVID-19 infection. And compared with other developed reconstruction algorithms, our proposed algorithm shows superior performance in noisy group testing.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.33-39
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• 2023

Although COVID-19 has transitioned to a level 4 infectious disease in 2023 and has entered a stable trend, in special education settings, the importance of supporting the academic and social development gaps of students with disabilities caused by non-face-to-face learning situations such as remote classes during the COVID-19 period is emerging. there is. Accordingly, in this study, in order to identify and support the educational status and academic deficits of students with disabilities after COVID-19, we conducted a survey targeting 2,214 special education teachers in 17 cities and analyzed the results. As a result of the study, due to COVID-19, the developmental delay and educational gap in students with disabilities in terms of academics, emotions, and behavior deepened, and there was a high demand for manpower support, psychological counseling, and medical support for emotional behavior as a way to support this. Based on the results of this study, follow-up results were proposed.

• Korean Journal of Clinical Pharmacy
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• v.30 no.3
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• pp.169-176
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• 2020

Background: Most meta-analyses of risk factors for severe or critical outcomes in patients with COVID-19 only included studies conducted in China and this causes difficulties in generalization. Therefore, this study aimed to systematically evaluate the risk factors in patients with COVID-19 from various countries. Methods: PubMed, Embase, and Web of Science were searched for studies published on the mortality risk in patients with COVID-19 from January 1 to May 7, 2020. Pooled estimates were calculated as odds ratio (OR) with 95% confidence interval (CI) using the random-effects model. Results: We analyzed data from seven studies involving 26,542 patients in total in this systematic review and meta-analysis. Among the patients, 2,337 deaths were recorded (8.8%). Elderly patients and males showed significantly higher mortality rates than young patients and females; the OR values were 3.6 (95% CI 2.5-5.1) and 1.2 (95% CI 1.0-1.3), respectively. Among comorbidities, hypertension (OR 2.3, 95% CI 1.1-4.6), diabetes (OR 2.2, 95% CI 1.2-3.9), cardiovascular disease (OR 3.1, 95% CI 1.5-6.3), chronic obstructive pulmonary disease (OR 4.4, 95% CI 1.7-11.5), and chronic kidney disease (OR 4.2, 95% CI 2.0-8.6) were significantly associated with increased mortalities. Conclusion: This meta-analysis, involving a huge global sample, employed a systematic method for synthesizing quantitative results of studies on the risk factors for mortality in patients with COVID-19. It is helpful for clinicians to identify patients with poor prognosis and improve the allocation of health resources to patients who need them most.