• Journal of Industrial Convergence
• /
• v.19 no.6
• /
• pp.59-66
• /
• 2021

Globally, the prolonged pandemic of COVID-19 (COVID-19) has had a great impact on all industries. In particular, in the field of education, online classes (non-face-to-face) had some negative perceptions of online classes, such as lack of preparation for learning and student dissatisfaction with the class. According to the current situation survey in 2020, non-face-to-face classes accounted for about 56% of the class, and streaming real-time classes and video content-based classes accounted for most of the class. This study empirically analyzes the problems to be solved by online classes through the 2020-2021 survey (software application practical class university students), and explains the detailed program and development plan (implementation result). This study intends to contribute to the development of online learning development of each educational institution after the end of the corona crisis.

• Journal of the Korea Society of Computer and Information
• /
• v.26 no.8
• /
• pp.91-101
• /
• 2021

This paper intends to draw implications for preparing for Post-Corona in the health field and policy fields as the global pandemic is experienced due to COVID-19. The purpose of this study is to analyze the news and trends of media companies through temporal analysis of the three infectious diseases, SARS-CoV, MERS-CoV, and SARS-CoV-2 (COVID-19), in which the domestic infectious disease preventive system was active throughout the first year of the outbreak. To this end, by using the news analysis program of the Korea Press Foundation 'Big Kinds', the number of news articles per year was digitized based on the period when each infectious disease had an impact on Korea, and major trends were implemented and analyzed in a word cloud. As a result of the analysis, the number of articles related to infectious diseases peaked when the World Health Organization (WHO) declared a warning and (suspicious) confirmed cases occurred. According to keyword and word cloud analysis, 'infectious disease outbreak and major epidemic areas', 'prevention authorities', and 'disease information and confirmed patient information' were found to be the main common features, and differences were derived from the three infectious diseases. In addition, the current status of the infodemic was identified by performing word cloud analysis on information in uncertainty. The results of this study are significant in that they were able to derive the roles of the health authorities and the media that should be preceded in the event of a new disease epidemic through previously experienced infectious diseases, and areas to be rearranged.

• The Journal of Bigdata
• /
• v.5 no.1
• /
• pp.125-138
• /
• 2020

After the spread of COVID-19 in 2020, the country's Crisis Alert Level went up to the highest level, Level 4. Respond of COVID-19 pandemic, Governments, and cities secured each province's duty for the citizens. The government provided health assistance first and stepped forward to support the necessary resources for the citizens. Busan City proposed policy response to prepare and implement the Corona support for each county as well. The high occupant rate of self-business owners lost basic incomes, and the effect varies on industries. In our paper, to avoid any crisis in such an epidemic, we propose a clustering analysis for the guidance of policy support for Busan City. By analyzing patterns and clustering on districts and Sectors, we would like to provide reference materials for determining the direction of support and guiding preemptive response in the event of a similar epidemic.

• Journal of the Korean Applied Science and Technology
• /
• v.38 no.3
• /
• pp.860-869
• /
• 2021

This study tried to provide basic data for predicting consumers by applying the structural analysis method (SEM) to the causal relationship model that applied the technology acceptance theory for mobile home training, exercise commitment, and continuous intention. Therefore, in order to identify the strategic tools due to the current COVID-19 pandemic, the survey was conducted using the mobile program "Survey Monkey" according to the sampling plan from February 1, 2021 to May 21, 2021, and a total of 287 valid samples. people were used in the final analysis of consumers. As a result of the study, it was found that the acceptance model had a significant effect(+) on exercise commitment, and the acceptance model had a significant effect(+) on the exercise continuation intention. Finally, it was found that exercise commitment had a significant(+) effect on exercise continuity intention.

• Human Ecology Research
• /
• v.60 no.2
• /
• pp.163-176
• /
• 2022

The purpose of this study is to understand the changes in the daily life and quality of life of the elderly due to the spread of COVID-19. This study attempted to supplement the limitations of quantitative analysis by performing both quantitative and qualitative analysis. A large-scale representative data, the Elderly Survey 2017 and 2020, were analyzed, and in-depth interviews were conducted with a total of 16 elderly people in Gwangju and Seoul. As a result, it was found that the overall quality of life was positively changed compared to before Corona. The frequency of contact and visits with family members decreased whereas the time spent watching TV increased. The elderly's adaptation to daily life has a series of processes since the first outbreak of COVID-19. At the beginning of the outbreak, there were fear, anxiety, and depression due to isolation, but gradually made efforts to adapt to the new situation. They reported that they realized the importance of human relationships, especially spouses, in a crisis situation and that there were some positive aspects as well. Finally, in all these results a difference was found between single-person households and multi-person households. Through the above research results, academic and policy measures were discussed.

• Journal of Convergence for Information Technology
• /
• v.10 no.8
• /
• pp.77-86
• /
• 2020

The study aims to analyze the compliance and non-compliance of the Korean health authorities regarding WHO's mask use recommendations following the spread of Covid-19, and to suggest the limitations and implications of the recommendations in the prevention of epidemics by deriving the causes of non-compliance with the results of alternative options. To this end, documents related to masks at home and abroad are reviewed, and WHO's mask recommendations and the Korean health authorities' mask guidelines are targeted for analysis. The analysis results are as follows. First, Korea's health authorities have basically accepted and applied WHO's "limited mask user perspective" in two recommendations. Second, Korea's health authorities have implemented differently from WHO mask recommendations due to the lack of supply and demand of masks. Third, Korea's health authorities were able to succeed in the initial prevention of Corona 19 based on the stabilization of the mask supply. Fourth, in the WHO mask recommendations, mask user restriction resulted in partial errors as a recommendation. The implication derived from the analysis is that even international recommendations based on medical evidence need to be allowed to follow autonomous guidelines according to the country's quarantine situation and competence, rather than strict adherence to international rules, in the infectious disease pandemic situation.

• ETRI Journal
• /
• v.46 no.2
• /
• pp.290-306
• /
• 2024

To treat the novel COronaVIrus Disease (COVID), comparatively fewer medicines have been approved. Due to the global pandemic status of COVID, several medicines are being developed to treat patients. The modern COVID medicines development process has various challenges, including predicting and detecting hazardous COVID medicine responses. Moreover, correctly predicting harmful COVID medicine reactions is essential for health safety. Significant developments in computational models in medicine development can make it possible to identify adverse COVID medicine reactions. Since the beginning of the COVID pandemic, there has been significant demand for developing COVID medicines. Therefore, this paper presents the transferlearning methodology and a multilabel convolutional neural network for COVID (MLCNN-COV) medicines development model to identify negative responses of COVID medicines. For analysis, a framework is proposed with five multilabel transfer-learning models, namely, MobileNetv2, ResNet50, VGG19, DenseNet201, and Inceptionv3, and an MLCNN-COV model is designed with an image augmentation (IA) technique and validated through experiments on the image of three-dimensional chemical conformer of 17 number of COVID medicines. The RGB color channel is utilized to represent the feature of the image, and image features are extracted by employing the Convolution2D and MaxPooling2D layer. The findings of the current MLCNN-COV are promising, and it can identify individual adverse reactions of medicines, with the accuracy ranging from 88.24% to 100%, which outperformed the transfer-learning model's performance. It shows that three-dimensional conformers adequately identify negative COVID medicine responses.

• Atmosphere
• /
• v.32 no.1
• /
• pp.51-60
• /
• 2022

Corona Virus Disease 19 pandemic (COVID-19) causes many deaths worldwide, and has enormous impacts on society and economy. The COVID-19 was caused by a new type of coronavirus (Severe Acute Respiratory Syndrome Cornonavirus 2; SARS-CoV-2), which has been found that these viruses can be effectively inactivated by ultraviolet (UV) radiation of 290~315 nm. In this study, 90% inactivation time of the SARS-CoV-2 virus was analyzed using ground observation data from Brewer spectrophotometer at Yonsei University, Seoul and simulation data from UVSPEC for the period of 2015~2017 and 2020. Based on 12:00-13:00 noon time, the shortest virus inactivation time were estimated as 13.5 minutes in June and 4.8 minutes in July/August, respectively, under all sky and clear sky conditions. In the diurnal and seasonal variations, SARS-CoV-2 could be inactivated by 90% when exposed to UV radiation within 60 minutes from 10:00 to 14:00, for the period of spring to autumn. However, in winter season, the natural prevention effect was meaningless because the intensity of UV radiation weakened, and the time required for virus inactivation increased. The spread of infectious diseases such as COVID-19 is related to various and complex interactions of several variables, but the natural inactivation of viruses by UV radiation presented in this study, especially seasonal differences, need to be considered as major variables.

• The Journal of the Convergence on Culture Technology
• /
• v.9 no.2
• /
• pp.285-294
• /
• 2023

The trade dispute between China and the U.S. began before Corona and is easing at this time by bringing new changes to the pendemic, and the development of the Chinese manufacturing industry has increased interdependence between the U.S. and China. However, the overall global trade should be less than before pendemic, and Korea's response strategy should be made serious at this time.However, new changes are taking place again these days. With the recent outbreak of COVID-19 in Shanghai, China, new changes are expected to occur in China's industrial chain. As the Chinese government strictly creates quarantine figures for COVID-19, many factories and companies among industries are forced to close for a while. As economic globalization and division of labor continue to deepen, multinationals choose suppliers and industrial chains within the world to form a global supply chain structure to pursue cost minimization and profit maximization. China is an indispensable part. Whether it is China, the U.S. or Korea, it can be a risk and an opportunity now.

• Journal of the Korea Convergence Society
• /
• v.11 no.7
• /
• pp.19-24
• /
• 2020

WHO declared a global pandemic on March 11th for Corona 19. However, there is a situation where you have to go to building for face-to-face education or seminars for economic and social activities. The first check method of COVID-19 infection is to measure body temperature, so the primary entrance and exit is blocked for near-field body temperature measurement. However, since it is troublesome to check directly, thermal camera is installed at the entrance of the building, and body temperature is measured indirectly using the infrared camera to control access. In case of middle and high schools, universities, and lifelong education center, we need a system that is possible to interoperate with attendance checks and automatically recognizes whether to wear masks and can authenticate students. We proposed the system that is to confirm whether to wear a mask with a camera that is embedded in a smart mirror, and that authenticates the user through voice recognition of the user who wants to enter the building by using voice recognition technology and determines whether to enter them or not. The proposed system can check attendance if it is linked with near-field temperature measurement and attendance check APP of student's smart phone.