• 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 Information Technology Services
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• v.20 no.5
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• pp.1-9
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• 2021

Since the first confirmed case in January 2020, Coronavirus disease 2019(COVID-19) has brought many changes to our society, and Korea is no exception. Some changes are direct and immediate such as restrictions on overseas travel and social distancing, but the others are indirect and slowly adapted such as lifestyle changes impacting industries and businesses. IT service sector is tremendously influenced by COVID-19. IT service is used extensively in response to COVID-19 taking advantage of its non-face-to-face characteristics. In that sense, the industry is positively affected and in some sense invigorated, giving birth to new kind of services. This special issue focuses on introducing how the IT services are affected, what kind of transformations are undergoing, and how these are expedited after COVID-19. This special issue expands and extends the case research section by collecting new IT service case studies concerning these topics. After competitive review process, 11 studies are selected for this special issue which deals with four different but closely related aspects: (1) evolutions of private IT services, (2) transformations in public IT services, (3) impacts in the hospitality and tourism industry, and (4) changes of people's behavior along with COVID-19. The first set reports on the evolution of private IT services that have created terms such as foodtech and edutech as we enter a rapid non-face-to-face situation. The second set consists of studies dealing with the evolution of public IT services. Evolution and rapid response to non-face-to-face appear to be no exception in the public sector. The third includes studies of hospitality and tourism which is most strongly affected by COVID-19. The last set deals with the behavioral changes of users such as technostress in telecommuting. Lessons learned through best practices and key problems identified in these studies may help us to actively respond to the coming waves of changes incurred by COVID-19 in our society as well as in the IT service industry.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.154-168
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• 2021

COVID-19 has been spreading all around the world, and threatening global health. In this situation, identifying and isolating infected individuals rapidly has been one of the most important measures to contain the epidemic. However, the standard diagnosis procedure with RT-PCR (Reverse Transcriptase Polymerase Chain Reaction) is costly and time-consuming. For this reason, pooled testing for COVID-19 has been proposed from the early stage of the COVID-19 pandemic to reduce the cost and time of identifying the COVID-19 infection. For pooled testing, how many samples are tested in group is the most significant factor to the performance of the test system. When the arrivals of test requirements and the test time are stochastic, batch-service queueing models have been utilized for the analysis of pooled-testing systems. However, most of them do not consider the false-negative test results of pooled testing in their performance analysis. For the COVID-19 RT-PCR test, there is a small but certain possibility of false-negative test results, and the group-test size affects not only the time and cost of pooled testing, but also the false-negative rate of pooled testing, which is a significant concern to public health authorities. In this study, we analyze the performance of COVID-19 pooled-testing systems with false-negative test results. To do this, we first formulate the COVID-19 pooled-testing systems with false negatives as a batch-service queuing model, and then obtain the performance measures such as the expected number of test requirements in the system, the expected number of RP-PCR tests for a test sample, the false-negative group-test rate, and the total cost per unit time, using the queueing analysis. We also present a numerical example to demonstrate the applicability of our analysis, and draw a couple of implications for COVID-19 pooled testing.

• Journal of Yeungnam Medical Science
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• v.39 no.1
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• pp.46-52
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• 2022

Background: The coronavirus disease 2019 (COVID-19) outbreak in the Daegu-Gyeongbuk area in 2020 has caused difficulties in the daily life and hospital care of children with type 1 diabetes mellitus (T1DM). We detected an increase in blood sugar levels in these children and the number of patients hospitalized with more severe diabetic ketoacidosis (DKA) compared to those before COVID-19. Methods: This single-center study was conducted at Kyungpook National University Children's Hospital. The following patient groups were included; 45 returning patients diagnosed with T1DM and undergoing insulin treatment for more than 2 years and 20 patients newly diagnosed with T1DM before and after COVID-19 were selected by age matching. Returning patients before and after the outbreak were selected, and changes in hemoglobin A1c (HbA1c) levels were retrospectively reviewed. The HbA1c levels and severity of symptoms in newly diagnosed patients during hospitalization were examined. Results: HbA1c levels in returning patients with T1DM were significantly increased after COVID-19 (before, 7.70%±1.38% vs. after, 8.30%±2.05%; p=0.012). There were 10 and 10 newly diagnosed patients before and after COVID-19, respectively. The proportion of patients with drowsiness and dyspnea at the time of admission was higher after COVID-19 than before (before, 2 of 10 vs. after, 4 of 10). The HbA1c levels were higher in newly diagnosed patients hospitalized after COVID-19 than before (before, 11.15% vs. after, 13.60%; p=0.036). Conclusion: Due to COVID-19 in the Daegu-Gyeongbuk area, there was an increase in blood glucose levels in children with T1DM and in the incidence of severe DKA in newly diagnosed diabetes mellitus patients.

• Economic Analysis
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• v.27 no.1
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• pp.37-66
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• 2021

This paper examines the potential impacts of COVID-19 on poverty in ASEAN countries. The first estimate, adopted from Summer et al. (2020) and Nonvide (2020), configures three scenarios of contractions in per capita household income or consumption; the impact of each scenario on poverty is calculated using poverty lines at different thresholds. In the second estimate, poverty impacts in 2020 and 2021 were projected using regression models controlling for unobserved country effects, unbalanced data, and endogeneity. COVID-19 has been shown to have negative impacts on poverty reduction in the ASEAN Member States. To reduce poverty, concerted efforts are needed to implement policies for reducing income inequality and promoting economic growth. Such efforts will not only speed up the countries' return to pre-pandemic poverty levels but also contribute to further accelerating poverty reduction.

• Anxiety and mood
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• v.19 no.2
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• pp.61-68
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• 2023

Objective : The purpose of this study was to investigate the associations between psychosocial factors and the mask-wearing behavior after deregulation of COVID-19 quarantine guidelines among adults in Korea. Methods : We collected data (345 subjects) from online questionnaire survey. The questionnaire included the Korean version of the Patient Health Questionnaire-9, the Korean version of fear of COVID-19 Scale, the Korean version of the Patient Health Questionnaire-15, Korean versions of the Perceived Stress Scale, and measurement tools adapted from previous studies for COVID-19 risk perception, social stigma, and appearance interest of subjects. We analysed data using SPSS version 23.0 for descriptive statistics, chi-square test, and logistic regression analysis. Results : People with cohabitant or mask-wearing tendency before COVID-19 pandemic had a higher rate of mask-wearing than those who were not. Subjects reporting higher level of social stigma (OR=1.154, 95% CI 1.049-1.270) and COVID-19 anxiety (OR=1.072, 95% CI 1.007-1.141) were more likely to report maskwearing behavior. Conclusion : From the results, appropriate intervention to those who fear social stigma and are anxious to the infectious diseases will be needed. Additionally, providing policies and guidelines that consider cohabitants and offering continuous education with information of disease to the public are also expected to helpful for recovery of daily life from infectious diseases.

• International Journal of Computer Science & Network Security
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• v.24 no.3
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• pp.125-134
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• 2024

The novel coronavirus 2019 is called COVID-19 has outspread swiftly worldwide. An early diagnosis is more important to control its quick spread. Medical imaging mechanics, chest calculated tomography or chest X-ray, are playing a vital character in the identification and testing of COVID-19 in this present epidemic. Chest X-ray is cost effective method for Covid-19 detection however the manual process of x-ray analysis is time consuming given that the number of infected individuals keep growing rapidly. For this reason, it is very important to develop an automated COVID-19 detection process to control this pandemic. In this study, we address the task of automatic detection of Covid-19 by using a popular deep learning model namely the VGG19 model. We used 1300 healthy and 1300 confirmed COVID-19 chest X-ray images in this experiment. We performed three experiments by freezing different blocks and layers of VGG19 and finally, we used a machine learning classifier SVM for detecting COVID-19. In every experiment, we used a five-fold cross-validation method to train and validated the model and finally achieved 98.1% overall classification accuracy. Experimental results show that our proposed method using the deep learning-based VGG19 model can be used as a tool to aid radiologists and play a crucial role in the timely diagnosis of Covid-19.

• Asian Journal of Innovation and Policy
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• v.9 no.2
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• pp.106-132
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• 2020

This study intends to add a factor to the discussion on the sectoral systems of innovation through Korea's response to the COVID-19 pandemic. The Korean approach is summarized as follows: the first response centers on technology and innovation. These include the development of diagnostic test methods and accurate test kits, first in the world, the use of ICT technology in epidemiological investigations, the technical response in the field, and the competitive edge in the development of medicine and vaccines that were behind the developed countries. The second response is an aggressive effort implemented just after the Chinese announcement, before the domestic outbreak; the third response is the open policy that induces voluntary participation of all subjects and people by opening all information. More important is the leadership at the national level shown in the past Korean experience and most advanced countries. National leadership must be the missing factor.

• Agribusiness and Information Management
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• v.12 no.1
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• pp.6-16
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• 2020

This is a summary of a comparative study of the national policies to foster the agri-food industry implemented by the leading countries of the industry before and after the COVID-19-induced global economic crisis. By comparing the policies of each country, we discovered that key leading countries of the agri-food industry had given up or suspended one-on-one, face-to-face support programs that they had maintained for years, and have started providing financial assistance to companies or self-employed people in relative industries. Korea should implement such decisive policies for the Korean agri-food industry to tackle this unprecedented economic shrink and maintain the competitiveness of the industry. Considering the scale and speed of the spreading of the pandemic, the new policies should be implemented swiftly and boldly. This study can be used as a base material for developing new policies to minimize damage to the agri-food industry and national economy caused by COVID-19.

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.192-200
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• 2021

In the mid of the December 2019, the virus has been started to spread from China namely Corona virus. It causes fatalities globally and WHO has been declared as pandemic in the whole world. There are different methods which can fit such types of values which obtain peak and get flattened by the time. The main aim of the paper is to find the best or nearly appropriate modeling of such data. The three different models has been deployed for the fitting of the data of Coronavirus confirmed patients in Pakistan till the date of 20^th November 2020. In this paper, we have conducted analysis based on data obtained from National Institute of Health (NIH) Islamabad and produced a forecast of COVID-19 confirmed cases as well as the number of deaths and recoveries in Pakistan using the Logistic model, Gompertz model and Auto-Regressive Integrated Moving Average Model (ARIMA) model. The fitted models revealed high exponential growth in the number of confirmed cases, deaths and recoveries in Pakistan.