• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.58-63
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• 2022

The daily number of confirmed cases of Coronavirus disease 2019(COVID-19) ranges between 1,000 and 2,000. Despite higher vaccination rates, the number of confirmed cases continues to increase. The Mu variant of COVID-19 reported in some countries by WHO has been identified in Korea. In this study, we predicted the number of confirmed COVID-19 cases in Korea using the SARIMA for the Covid-19 prevention strategy. Trends and seasonality were observed in the data, and the ADF Test and KPSS Test was used accordingly. Order determination of the SARIMA(p,d,q)(P, D, Q, S) model helped in extracting the values of p, d, q, P, D, and Q parameters. After deducing the p and q parameters using ACF and PACF, the data were transformed and schematized into stationary forms through difference, log transformation, and seasonality removal. If seasonality appears, first determine S, then SARIMA P, D, Q, and finally determine ARIMA p, d, q using ACF and PACF for the order excluding seasonality.

• Journal of the Korean Society of Radiology
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• v.84 no.4
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• pp.964-969
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• 2023

Guillain-Barré syndrome (GBS) is an immune-mediated demyelinating polyneuropathy characterized by progressive, ascending, and symmetrical paralysis. It is known to be triggered by an antecedent infection or vaccination. Recently, GBS development following coronavirus disease 2019 (COVID-19) vaccination has been reported. Cranial neuropathies in typical GBS patients usually involve the facial and the lower cranial nerves (from IX to XII). We report a rare case of multiple cranial neuropathies involving trigeminal, abducens, and facial nerves in a patient who developed GBS following COVID-19 vaccination on the basis of obvious MRI features.

• Journal of the Korean Applied Science and Technology
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• v.39 no.3
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• pp.407-416
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• 2022

This study was attempted to determine how knowledge and fear of COVID-19 affects job-seeking anxiety of nursing students in the COVID-19 pandemic situation. The subjects of this study were 157 students from the 1st to 4th graders attending nursing universities. Data collection was collected from December 9, 2021, to February 21, 2022. Data were analyzed with the SPSS/WIN 24.0 program. As a result of this study, the job-seeking anxiety of the subjects was significantly correlated with the fear of COVID-19(r=.386, p<.001). And, influencing factors the job-seeking anxiety of nursing students identified in the order of fear of COVID-19, satisfaction with college. Therefore, it is necessary to develop a program that can reduce the fear of COVID-19 in order to lower the job-seeking anxiety of nursing students.

• Journal of the Korean Society of Radiology
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• v.15 no.3
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• pp.381-390
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• 2021

The purpose of this study was to examine the lecture satisfaction of radiological science majors in total remote classes due to coronavirus disease 2019, and influencing factors were analyzed. An online survey was conducted from September 1, 2020 to November 15, 2020, lecture satisfaction, teaching presence, academic motivation, self efficacy, behavior regulation and usage simplicity of remote classes for 458 3 and 4-year radiological science majors located in the Yeongnam area. Lecture satisfaction was significantly different according to grade, self-review time, and preferred teaching method. In addition, lecture satisfaction showed a significant positive corrleation with the teaching presence and usage simplicity of remote classes. In the multiple regression model, lecture satisfaction showed a significant explanatory power of 45.7% through usage simplicity, teaching presence, self efficacy and academic motivation. This study was attempted to provide basic data to increase the effect of remote classes at universities that are expected to expand in the post-corona.

• Journal of the Korea Society of Computer and Information
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• v.26 no.5
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• pp.1-8
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• 2021

Coronavirus disease 2019 (COVID-19) has affected the world seriously. Every person is required for wearing a mask properly in a public area to prevent spreading the virus. However, many people are not wearing a mask properly. In this paper, we propose an efficient mask detection system. In our proposed system, we first detect the faces of input images using YOLOv5 and classify them as the one of three scene complexity classes (Simple, Moderate, and Complex) based on the number of detected faces. After that, the image is fed into the Faster-RCNN with the one of three ResNet (ResNet-18, 50, and 101) as backbone network depending on the scene complexity for detecting the face area and identifying whether the person is wearing the mask properly or not. We evaluated our proposed system using public mask detection datasets. The results show that our proposed system outperforms other models.

• The Journal of the Convergence on Culture Technology
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• v.6 no.4
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• pp.567-573
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• 2020

The COVID-19 outbreak had a substantial impact on our lives. Social distancing policies are especially causing severe concern for the cultural and creative industries across the globe. Most performing arts festivals and other venues are being canceled due to COVID-19 fears and social distancing measures. Instead, many individual artists and organizations attempt to deliver their arts online using ICT and live streaming. The actions of the Government in responding to the COVID-19 crisis also provide financial support toward freelance artists and creators, and company. Finally, future directions and areas that need further support are described.

• Journal of the Korea Convergence Society
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• v.11 no.4
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• pp.95-108
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• 2020

A coronavirus disease 2019 (COVID-19) is a new global health problem. The Korean government is pursuing to gain its future growth engines and promoting short-term economic stimulation by investing in research and development (R&D) to improve national technological capabilities that can respond to the spread of the global epidemic. It is required to need knowledge information to establish the direction of future national planning thru understanding the status quo of R&D investment in terms of research fields. Four corona-related R&D fields were drawn on the basis of analyzing major nations' R&D funding data (USA, EU etc.) and two differentiated R&D fields were added through comparative analysis with domestic R&D projects. Domestic and foreign research organization-the research title-the scale of the research funding-the project period were presented in terms of the suggested 6(7 details) R&D research fields. Meanwhile R&D projects that have featured in the convergence of interdisciplinary were provided. This study proved the excellence of coronavirus detection and on-site diagnostic capabilities that are currently globally highlighted by deriving differentiated research fields from the domestic competitive advantage fields related to corona viruses and also suggested intensive investment research fields.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.151-152
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• 2020

최근 코로나바이러스(COVID-19)의 여파로 경기침체가 이루어 지고 있는 중, 반대로 역성장을 이루고 있는 중고시장의 흥행요인을 분석하고, 또한 기존 지역단위의 중고거래시장이 아닌 새로운 소규모 동네단위 중고시장의 급성장 요인을 분석하여 향후동향을 예측하고자 한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.143-144
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• 2021

본 연구는 위치정보를 기반으로 앱과 웹에 위치정보 및 경로 정보를 관리하는 코로나 대응 및 관리 시스템이다. 현재 코로나19 바이러스 때문에 많은 사람들이 언제 어디서 감염이 되었는지 모르고 어떠한 위치에 있었는지 정확히 동선 파악이 어렵다. 이 문제를 해결하기 위해 본 연구는 앱과 웹을 활용해 사용자 위치정보 저장, 문자 전송, 지도에 경로를 안내하는 시스템을 연구하였다. 매장에는 방문자 정보를 수집하는 단말기를 설치하고 수집된 정보는 웹 데이터베이스에 저장되어 웹과 앱에 코로나 관련 서비스를 제공한다. 주요기능으로는 게시판, 코로나19 정보, 환자현황, 경로 추적 정보, 메시지전송, 통계 정보를 제공한다.

• Annual Conference on Human and Language Technology
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• 2021.10a
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• pp.85-90
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• 2021

코로나바이러스감염증-19로 인한 팬데믹 상황이 지속되면서 감염증 정보의 불확실성으로 인해 코로나 관련 루머가 온라인상에서 빠르게 전파되고 있다. 이러한 코로나 관련 가짜 뉴스를 사전에 탐지하기 위해, 본 연구에서는 한국어 코로나 가짜 뉴스 데이터셋을 구축하고, 개체명과 사용자 재확산 정보를 이용한 한국어 가짜 뉴스 탐지 모델을 제안한다. 가짜 뉴스 팩트체킹 언론인 서울대팩트체크센터에서 코로나 관련 루머 및 가짜 뉴스에 대한 검증 기사를 수집한 후, 기사로부터 개체명 추출 모델을 통해 주제 키워드를 추출하고, 이를 이용해 유튜브 상의 사용자 재확산 정보를 수집하여 데이터셋을 구성하였다. BERT 기반의 제안 모델을 다양한 비교군과 비교하였고, 특성 조합에 따른 실험을 통해 각 특성 정보(기사 텍스트, 개체명 데이터, 유튜브 데이터)가 가짜 뉴스 탐지 성능에 미치는 영향을 알아보았다.