• Journal of muscle and joint health
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• v.27 no.3
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• pp.255-267
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• 2020

Purpose: The purpose of this study is to compare topics through keywords related to nurses in internet portals and social media Pre coronavirus disease (COVID-19) era and during the COVID-19 era. Methods: For six months before and during the outbreak of COVID-19 in Korea, "nurse" was searched on the internet. For data collection, we implemented web crawlers in programming languages such as Python and collected keywords. The keywords collected were classified into three domains of topic Modeling. Results: The keyword 'nurse' increased by 15% during COVID-19 era. Keywords that ranked high in Term Frequency - Inverse Document Frequency (TF-IDF) values were before COVID-19, such as "nurse" and "C-section". during COVID-19, however, they were not only "nurse" but also "emergency" and "gown" related to pandemics. Conclusion: Various topics were being uploaded into the internet media. Nursing professionals should be interested in the text that is revealed in the internet media and try to continuously identify and improve problems.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.149-158
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• 2022

The pandemic of Covid-19 (Coronavirus Disease 19) has devastated the world, affected millions of people, and disrupted the world economy. The cause of the Covid19 epidemic has been identified as a new variant known as Severe Acute Respiratory Syndrome Coronavirus 2(SARS-CoV2). It motives irritation of a small air sac referred to as the alveoli. The alveoli make up most of the tissue in the lungs and fill the sac with mucus. Most human beings with Covid19 usually do no longer improve pneumonia. However, chest x-rays of seriously unwell sufferers can be a useful device for medical doctors in diagnosing Covid19-both CT and X-ray exhibit usual patterns of frosted glass (GGO) and consolidation. The introduction of deep getting to know and brand new imaging helps radiologists and medical practitioners discover these unnatural patterns and pick out Covid19-infected chest x-rays. This venture makes use of a new deep studying structure proposed to diagnose Covid19 by the use of chest X-rays. The suggested model in this work aims to predict and forecast the patients at risk and identify the primary COVID-19 risk variables

• Journal of the Korean Society of Radiology
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• v.81 no.6
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• pp.1334-1347
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• 2020

Coronavirus disease (COVID-19) has threatened public health as a global pandemic. Chest CT and radiography are crucial in managing COVID-19 in addition to reverse transcription-polymerase chain reaction, which is the gold standard for COVID-19 diagnosis. This is a review of the current status of the use of chest CT and radiography in COVID-19 diagnosis and management and anㄷ introduction of early representative studies on the application of artificial intelligence to chest CT and radiography. The authors also share their experiences to provide insights into the future value of artificial intelligence.

• Genomics & Informatics
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• v.19 no.3
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• pp.23.1-23.7
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• 2021

Currently, coronavirus disease 2019 (COVID-19) literature has been increasing dramatically, and the increased text amount make it possible to perform large scale text mining and knowledge discovery. Therefore, curation of these texts becomes a crucial issue for Bio-medical Natural Language Processing (BioNLP) community, so as to retrieve the important information about the mechanism of COVID-19. PubAnnotation is an aligned annotation system which provides an efficient platform for biological curators to upload their annotations or merge other external annotations. Inspired by the integration among multiple useful COVID-19 annotations, we merged three annotations resources to LitCovid data set, and constructed a cross-annotated corpus, LitCovid-AGAC. This corpus consists of 12 labels including Mutation, Species, Gene, Disease from PubTator, GO, CHEBI from OGER, Var, MPA, CPA, NegReg, PosReg, Reg from AGAC, upon 50,018 COVID-19 abstracts in LitCovid. Contain sufficient abundant information being possible to unveil the hidden knowledge in the pathological mechanism of COVID-19.

• Journal of Convergence for Information Technology
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• v.10 no.12
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• pp.75-81
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• 2020

The purpose of this study was to investigate whether there is a relationship between COVID-19 of feelings, work values, and employment preparation behaviors of nursing student and to prepare plans for the curriculum and activities of nursing students. The subject of the study was a questionnaire for 130 students 4th grade, who are graduating grades in one region. Data analysis was performed with the SPSS Win 19.0 program and correlation was analyzed by Pearson's correlation. As a result of the study, the average score for emotions from COVID-19 was 3.61±0.62. There was significant correlation between feelings and extrinsicl values from COVID-19. There was a significant repayment relationship with intrinsic work values and job preparation behavior. Based on these studies, it is meaningful to provide an effective way to prepare for employment programs and provide educational programs related to COVID-19.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.4
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• pp.495-500
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• 2021

This paper is to identify the recent growing crisis from coronavirus infections-19, using domestic news big data. This paper analyzed media articles related to the crisis caused by COVID-19 using the Korea Press Foundation's news big data analysis system 'BIGKinds'. In this paper, a total of 54 media articles were extracted around the keywords 'Corona' and 'Crisis', after a period of about 10 months. We want to understand the correlation coefficient between the two keywords "Corona" and "Crisis" and to understand what kind of crisis the COVID-19 is facing for each representative category of economy, society, international and cultural. As the COVID-19 crisis is taking a heavy toll on the economy, society and any other categories, this research using big data is expected to be used as a basic data to overcome the crisis of COVID-19.

• Journal of Korean Home Economics Education Association
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• v.36 no.2
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• pp.1-13
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• 2024

This study used TEXTOM for a total of 4 years, 2 years before and after, as of January 19, 2020, when the domestic confirmed cases of COVID-19 were officially announced, targeting Naver, Daum, Google, YouTube, and Twitter. By analyzing changes in adolescents' interest and awareness of their dietary habits, we aimed to create an opportunity to develop a dietary education program to provide proper dietary education. The results obtained through this study are as follows. First, the keywords with the highest co-occurrence before COVID-19 were 'nutrition' and 'counseling', and the next keywords were 'nutrition' and 'education'. After COVID-19, the order was 'nutrition', 'education', 'food' and 'safety'. Second, the results of co-occurrence frequency network analysis showed that there was high interest in nutrition and counseling regardless of COVID-19, and that interest in safety and health increased further after COVID-19. Third, through cluster formation through CONCOR analysis, before COVID-19, it was categorized into 'diet and physical activity', 'skin and disease', 'health and food', and 'nutrition and intake', and after COVID-19, it was categorized into 'nutrition, intake and COVID-19', 'diet and physical activity', 'skin and disease', and 'circadian rhythm imbalance and disease'. Fourth, as a result of the diet-related keyword cluster analysis network, before COVID-19, keywords in the 'eating and physical activity' group were strongly connected to keywords in the 'health and food' and 'nutrition and intake' groups, and after COVID-19, 'diet' Keywords in the 'and physical activity' group were strongly connected to keywords in the 'nutrition, intake, and COVID-19' group.

• Korea Trade Review
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• v.48 no.1
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• pp.127-163
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• 2023

The objective of this study is to investigate the volatility spillover effects among BDI, CCFI and SCFI. This paper will divide the empirical analysis section into two periods to analyze and compare the differences in volatility spillover effect between shipping freight indices before and after the outbreak of COVID-19 separately. First, in order to compare the mean spillover impact and index lead-lag correlations in BDI and CCFI indices, along with BDI and SCFI indices before and after COVID-19, the co-integration analysis and the test of Granger causality built on the VAR model were utilized. Second, the impulse response and variance decomposition are employed in this work to investigate how the shipping freight index responds to shocks experienced by itself and other freight indices in a short period. Before the COVID-19 epidemic, the results demonstrated that the BDI freight index is the Granger cause of the variable CCFI freight index. But the BDI and CCFI freight indices have no apparent lead-lag relationships after COVID-19, and this empirical result echoes the cointegration test result. After the COVID-19 epidemic, the SCFI index leads the BDI index. This study employs the VAR-BEKK-GARCH joint model to explore the volatility spillover results between dry bulk and container transport markets before and after COVID-19. The empirical results demonstrate that after COVID-19, fluctuations in the BDI index still affect the CCFI index in the maritime market. However, there is no proof of a volatility spillover relationship between the BDI and SCFI after the COVID-19 epidemic. This study will provide an insight into the volatility relationship among BDI, CCFI and SCFI before and after the the COVID-19 epidemic occurred.

• Pediatric Infection and Vaccine
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• v.29 no.1
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• pp.37-45
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• 2022

Purpose: During the coronavirus disease 2019 (COVID-19) pandemic, we conducted a Delphi survey that included the experts from the field of COVID-19 immunization in children aged 5-11 years. The aim was to organize collective expert opinions on COVID-19 vaccination in young children in the Republic of Korea, and so thus assist the vaccination policy. Methods: The panels included pediatric infectious disease specialists, preventive medicine experts, infectious disease physicians, and COVID-19 vaccine experts consulting the Ministry of Health and Welfare. The Delphi survey was conducted online using a questionnaire from February 14 to February 27, 2022. Results: The Delphi panels agreed that children were vulnerable to COVID-19, and the severity of illness was modest. Furthermore the panels reported that children with chronic illness were more susceptible to a worsening clinical course. There were generally positive opinions on the effectiveness of COVID-19 vaccination in children aged 5-11 years, and experts gathered a slightly positive opinion that the adverse events of pediatric COVID-19 were not numerous. The benefits of COVID-19 vaccination were evaluated at a level similar to the potential risks in children. Currently, the only approved mRNA platform vaccine in children seemed to be sustainable; however, the recombinant protein platform COVID-19 vaccines were evaluated as better options. Conclusions: Due to the surge of the Omicron variant and an increase in pediatric cases, the COVID-19 vaccination in young children may have to be considered. Panels had neutral opinions regarding the COVID-19 vaccination in children aged 5-11 years. Thus monitoring of the epidemiology and the data about the safety of COVID-19 vaccination should be continued.

• Journal of Korean Biological Nursing Science
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• v.23 no.1
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• pp.55-63
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• 2021

Purpose: To identify the differences in perception of and adherence to the COVID-19 social distancing behavior guidelines among health care workers, patients, and the general public and to use them to prevent the spread of COVID-19. Methods: From October 16 2020 to November 30, 2020, a survey was conducted among 85 health care workers, 85 patients, and 82 general public regarding the perception of and adherence to the COVID-19 social distancing behavior guidelines. Results: Patients scored significantly higher than the general public in the adherence to the COVID-19 social distancing behavior guideline, and there was no difference between health care workers and general public, and patients and health care workers. In the multivariate analysis, the factors that influence the adherence of the COVID-19 social distancing behavior guide were found in women and the perception of the COVID-19 social distancing behavior guideline. Conclusion: In order to promote the implementation of the COVID-19 social distancing behavior guideline, it is necessary to increase the perception of the COVID-19 social distancing behavior guideline and provide additional education in men. It is necessary to investigate the reason behind why men have low adherence to the COVID-19 social distancing behavior guideline.