• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.101-107
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• 2020

This paper aims to compare and analyze the major keywords according to the political orientation of progressive and conservative newspapers by utilizing the big data of the four major domestic daily newspapers related to COVID-19, which has entered a long-term war. To this end, 93,917 news reports from Jan. 20 to Sept. 15, 2020 were divided into four stages and the major keywords of the four newspapers were implemented and analyzed in WordCloud. According to the analysis, the conservative newspaper focused on the government's response, criticism, and China's responsibility by mentioning the keywords "government," "president," "state of affairs" and "mask" more than the progressive newspaper, while the progressive newspaper uses keywords that emphasize the seriousness of the disease and the occurrence of a dangerous situation. The Chosun Ilbo found that the use of various keywords during the massive outbreak of collective infections (2.18-5.15), and that the JoongAng Ilbo used keywords criticizing government policies in relation to reports of infectious diseases such as COVID-19, but also used keywords that emphasize the seriousness of diseases used by progressive newspapers and the occurrence of dangerous situations.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.287-294
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• 2022

The purpose of this study is to find out consumers' perceptions of "metaverse," a newly spotlighted technology, through big data analysis as a non-face-to-face society continues after the outbreak of COVID-19. This study conducted a big data analysis using text mining to analyze consumers' perceptions of metaverse before and after COVID-19. The top 30 keywords were extracted through word purification, and visualization was performed through network analysis and concor analysis between each keyword based on this. As a result of the analysis, it was confirmed that the non-face-to-face society continued and metaverse emerged as a trend. Previously, metaverse was focused on textual data such as SNS as a part of life logging, but after that, it began to pay attention to virtual reality space, creating many platforms and expanding industries. The limitation of this study is that since data was collected through the search frequency of portal sites, anonymity was guaranteed, so demographic characteristics were not reflected when data was collected.

• Journal of the Korean Society of Radiology
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• v.16 no.5
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• pp.661-672
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• 2022

After the outbreak of the SARS-CoV2 virus that causes COVID-19, it spreads around the world with the number of infections and deaths rising rapidly caused a shortage of medical resources. As a way to solve this problem, chest X-ray diagnosis using Artificial Intelligence(AI) received attention as a primary diagnostic method. The purpose of this study is to comprehensively analyze the detection of COVID-19 via AI. To achieve this purpose, 292 studies were collected through a series of Classification methods. Based on these data, performance measurement information including Accuracy, Precision, Area Under Cover(AUC), Sensitivity, Specificity, F1-score, Recall, K-fold, Architecture and Class were analyzed. As a result, the average Accuracy, Precision, AUC, Sensitivity and Specificity were achieved as 95.2%, 94.81%, 94.01%, 93.5%, and 93.92%, respectively. Although the performance measurement information on a year-on-year basis gradually increased, furthermore, we conducted a study on the rate of change according to the number of Class and image data, the ratio of use of Architecture and about the K-fold. Currently, diagnosis of COVID-19 using AI has several problems to be used independently, however, it is expected that it will be sufficient to be used as a doctor's assistant.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.1-7
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• 2023

Since the first outbreak of COVID-19 in 2019, it has caused a huge blow to the restaurant industry. However, as social distancing was lifted as of April 2022, the restaurant industry gradually recovered, and as a result, interest in restaurant start-ups increased. Therefore, in this paper, big data analysis was conducted by selecting "restaurant start-up" as a key keyword through social media big data analysis using Textom and then conducting word frequency and CONCOR analysis. The collection period of keywords was selected from May 1, 2022 to May 23, 2023, after the lifting of social distancing due to COVID-19, and based on the analysis, the development of a restaurant start-up consulting chatbot service is proposed.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.647-650
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• 2021

The most powerful and modern face recognition techniques are using deep learning methods that have provided impressive performance. The outbreak of COVID-19 pneumonia has spread worldwide, and people have begun to wear a face mask to prevent the spread of the virus, which has led existing face recognition methods to fail to identify people. Mainly, it pushes masked face recognition has become one of the most challenging problems in the face recognition domain. However, deep learning methods require numerous data samples, and it is challenging to find benchmarks of masked face datasets available to the public. In this work, we develop a new simulated masked face dataset that we can use for masked face recognition tasks. To evaluate the usability of the proposed dataset, we also retrained the dataset with ArcFace based system, which is one the most popular state-of-the-art face recognition methods.

• International Journal of Advanced Culture Technology
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• v.12 no.1
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• pp.94-99
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• 2024

In this paper, we aim to examine the recent state of the streaming industry in the U.S., and its future prospects as the most important force shaping the media landscape across the globe. First, we examine the launch of Disney's streaming services in late 2019 that heralded the start of the so-called streaming war to win subscribers and how the outbreak of COVID-19 in early 2020 helped its rapid growth. Then, we look at the crisis of the streaming industry in 2022, as subscriber growth slowed down for the first time and losses increased, and how this led to the growing emphasis on profitability. We also explore the subsequent attempts by streaming companies to cut costs and create more revenue, with the result that they were retreating from the previous strategy to grow their platforms at all costs. From this, we highlight that, while the future course of the streaming industry is not yet determined, the recent upheavals certainly made it more cost-conscious and conservative and less consumer-friendly.

• Journal of Korean Society for Quality Management
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• v.48 no.3
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• pp.493-510
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• 2020

Purpose: As of July 31, there were 14,336 confirmed cases of COVID-19 in South Korea, including 301 deaths. Since the daily confirmed number of cases hit 909 on February 29, the spread of the disease had gradually decreased due to the active implementation of preventive control interventions, and the daily confirmed number had finally recorded a single digit on April 19. Since May, however, the disease has re-emerged and retaining after June. In order to eradicate the disease, it is necessary to suggest suitable forward preventive strategies by predicting future infectivity of the disease based on the cases so far. Therefore, in this study, we aim to evaluate the transmission potential of the disease in early phases by estimating basic reproduction number and assess the preventive control measures through effective reproduction number. Methods: We used publicly available cases and deaths data regarding COVID-19 in South Korea as of July 31. Using ensemble model integrated stochastic linear birth model and deterministic linear growth model, the basic reproduction number and the effective reproduction number were estimated. Results: Estimated basic reproduction number is 3.1 (95% CI: 3.0-3.2). Effective reproduction number was the highest with 7 on February 15, decreased as of April 20. Since then, the value is gradually increased to more than unity. Conclusion: Preventive policy such as wearing a mask and physical distancing campaigns in the early phase of the outbreak was fairly implemented. However, the infection potential increased due to weakening government policy on May 6. Our results suggest that it seems necessary to implement a stronger policy than the current level.

• Journal of East-West Nursing Research
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• v.28 no.2
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• pp.170-178
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• 2022

Purpose: This study aimed to identify the factors influencing post-traumatic stress disorder in intensive care unit nurses in dedicated hospitals for coronavirus disease of 2019 (COVID-19) during the peak of the outbreak. Methods: This study used a cross-sectional correlational design. A total of 100 participants completed questionnaires comprising the Impact of Event Scale-Revised (IES-R), coping strategy indicator, social support, and post-traumatic growth. Post-traumatic stress disorder was classified as normal, mild risk, and high risk. Data were analyzed using 𝛘² test, Fisher's exact test, Kruskal-Wallis test with multiple comparison analysis, Pearson correlation coefficient, and multinominal logistic regression analysis. Results: Fifty seven nurses (57.0%) had a high risk of post-traumatic stress. Higher levels of post traumatic stress were associated with higher levels of social support seeking, and higher levels of avoidance, and lower levels of social support from supervisors. Higher post traumatic growth was correlated with higher social support for seeking coping, and problem solving coping strategies, and social support from supervisors and colleagues. Post-traumatic stress risk was associated with social support seeking and supervisors' social support. In addition, a higher risk of post-traumatic stress was related to COVID-19 work duration and supervisors' social support. Conclusion: Supportive programs, including increasing social support and building coping skills, may be suggested to safeguard the mental health of critical care nurses during the pandemic.

• Journal of the Korea Institute of Building Construction
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• v.22 no.1
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• pp.91-102
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• 2022

Many industries are being severely damaged by COVID-19, a respiratory infection that has recently been prevalent around the world. In particular, for workers in the construction industry, it is impossible to work from home, and if an outbreak on a construction site is confirmed, it can lead to great damage. Accordingly, the government has drafted 「Guidelines for Response to Construction Sites for Prevention and Spread of COVID-19」. In addition, domestic and foreign research about COVID-19 in the field of construction sites is being actively conducted. However, Korea has lacked studies on the effectiveness of the countermeasures in place at construction sites, or that reflect the opinions of construction site workers. Therefore, this study conducted a survey of construction site workers by dividing the construction of the COVID-19 quarantine management system and response plan into on-site management and social management. Through the AHP/IPA analysis, it was found that among social management, 'infectious disease management system and cooperation system with related institutions' and 'reduction of working hours' are areas with high importance but low satisfaction. After that, the causes of the two items were analyzed and related countermeasures were suggested. The results of this study will be able to contribute to the improvement of the quarantine management system and response plan at construction sites, and to minimize the damage to the construction industry related to COVID-19.

• Journal of Family Resource Management and Policy Review
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• v.26 no.3
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• pp.87-106
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• 2022

This study compared working arrangements, interest in rural migration, and life satisfaction in Japan in two periods: immediately after the COVID-19 (2019 coronavirus disease) pandemic and two years after the global outbreak. The comparison was based on data from the "Survey on Changes in Attitudes and Behaviors in Daily Life under the Influence of Novel Coronavirus Infection, 2020, 2021", which was conducted four times by the Japanese Cabinet Office directly after the COVID crisis (May 2020 and September 2021). The respondents who participated in both the first and fourth surveys were employed individuals aged 20 years or older. The results are as follows. First, the proportion of Tokyo residents engaging in telework immediately after the COVID-19 pandemic was 36.1%, which is higher than the levels observed nationwide. Second, individuals involved in telework and those working under flexible arrangements were more highly interested in moving to rural areas than those who commute to work. Third, among people engaged in telework, life satisfaction diminished immediately after the COVID-19 pandemic compared with the period before this crisis. After two years of the pandemic, however, life satisfaction among this group improved. Changes in working arrangements due to the pandemic can be expected to promote migration, as well as help revitalize regions and encourage the discovery of new lifestyles.