• 한국자원식물학회:학술대회논문집
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• 한국자원식물학회 2020년도 추계국제학술대회
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• pp.14-14
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• 2020

In December 2019, the COVID-19 epidemic was discovered in Wuhan, China, and since has disseminated around the world impacting human health for millions. Herein, in-silico drug discovery approaches were utilized to identify potential candidates as Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) main protease (M^pro) inhibitors. We investigated several databases including natural and natural-like products (>100,000 molecules), DrugBank database (10,036 drugs), major metabolites isolated from daily used spices (32 molecules), and current clinical drug candidates for the treatment of COVID-19 (18 drugs). All tested compounds were prepared and screened using molecular docking techniques. Based on the calculated docking scores, the top ones from each project under investigation were selected and subjected to molecular dynamics (MD) simulations followed by molecular mechanics-generalized Born surface area (MM-GBSA) binding energy calculations. Combined long MD simulations and MM-GBSA calculations revealed the potent compounds with prospective binding affinities against M^pro. Structural and energetic analyses over the simulated time demonstrated the high stabilities of the selected compounds. Our results showed that 4-bis([1,3]dioxolo)pyran-5-carboxamide derivatives (natural and natural-like products database), DB02388 and Cobicistat (DB09065) (DrugBank database), salvianolic acid A (spices secondary metabolites) and TMC-310911 (clinical-trial drugs database) exhibited high binding affinities with SARS-CoV-2 M^pro. In conclusion, these compounds are up-and-coming anti-COVID-19 drug candidates that warrant further detailed in vitro and in vivo experimental estimations.

• 유통과학연구
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• 제22권1호
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• pp.47-59
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• 2024

Purposes: The study aimed at examining the impact of the COVID-19 pandemic on the shift of online consumer purchasing behavior and whether the new behaviors would be maintained after the epidemic season. The study also aims to investigate how online customers change based on perceived risks. Research design and Methodology: The study investigated purchasing behavior of the same 377 online Vietnamese consumers during two periods: (1) during the period of social distancing and (2) one and half year after that, allowing data to be collected in real time, so that consumers do not have to recall their behavior. Results: Purchasing behavior appeared to be more influenced by gender, age and household size. Aged consumers are more concerned about risks than those in the younger group, who only worry about the risks during the pandemic. Consumers in households with two or more people are more concerned about the risks than those living alone. Female appeared to be more influential in both during and after pandemic than male. Conclusions: The findings contribute to clarify shift of online consumer purchasing behavior, which helps business to develop effective marketing strategies and enhance their presence in the e-commerce sector.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권11호
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• pp.4145-4162
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• 2021

During the period of epidemic prevention and control, contact tracing systems are developed in many countries, to stop or slow down the progression of COVID-19 contamination. However, the privacy issues involved in the use of contact tracing apps have also attracted people's attention. First, we divide contact tracing techniques into two types: Bluetooth Low Energy (BLE) based and Global Positioning System (GPS) based techniques. In order to clear understand the system structure and its elements, we create data flow diagram (DFD) of each types. Second, we analyze the possible privacy threats contained in various types of contact tracing apps by applying LINDDUN, which is a threat modeling technique for personal information protection. Third, we make a comparison and analysis of various contact tracing techniques from privacy point of view. These studies can facilitate improve tracing and security performance to contact tracing apps through comparisons between different types.

• International Journal of Advanced Culture Technology
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• 제9권2호
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• pp.130-135
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• 2021

Because of the COVID-19 epidemic, many countries have made the obligation to wear masks normal. Wearing masks in public places has become a must. At present, wearing a mask to participate in sports makes it very common. People seek to gain health through exercise but ignore the potential respirato-ry health threat. That is, wearing a mask will cause a decrease in oxygen content in the body. This neg-ative impact becomes more prominent as the wear-ing time and oxygen consumption increase. To pro-tect people from viruses and enjoy a healthy life. This paper proposes a breathing pattern that im-proves blood oxygen saturation while wearing a jogging mask and walking. Namely, shouting breathing pattern. Use a pulse oximeter to measure the blood oxygen saturation of running at different speeds and compare the normal breathing pattern and the shouting breathing pattern. The results show that the shouting breathing pattern has a sig-nificant improvement in the blood oxygen satura-tion of low-speed walking and medium-speed jog-ging.

• Journal of applied mathematics & informatics
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• 제41권6호
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• pp.1393-1407
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• 2023

In this study, we propose a dynamic SEIQRV mathematical model and examine it to comprehend the dynamics of COVID-19 pandemic transmission in the Coimbatore district of Tamil Nadu. Positiveness and boundedness, which are the fundamental principles of this model, have been examined and found to be reliable. The reproduction number was calculated in order to predict whether the disease would spread further. Existing arrangements of infection-free, steady states are asymptotically stable both locally and globally when R₀ < 1. The consistent state arrangements that are present in diseases are also locally steady when R₀ < 1 and globally steady when R₀ > 1. Finally, the numerical data confirms our theoretical study.

• 한국콘텐츠학회논문지
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• 제21권12호
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• pp.816-827
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• 2021

이 연구는 국내에서 2000년 이후 주요 발생한 신종감염병(사스, 신종플루, 메르스, 코로나19) 유행 당시 대중매체 메시지가 표출한 공포, 분노 감정과 주요 이슈 사이의 관계를 파악함을 목적으로 한다. 연구자는 중앙 일간지의 사설을 주요 신종감염병 유행 시기별로 수집하여, 계량적텍스트분석 방법을 활용한 확장병렬처리모형(EPPM)을 통해 분석하였다. 모든 신종감염병 유행 시기에 공포는 분노에 비해 강하게 나타나지만, 공포의 비중이 작을수록 위험통제 가능성이 큰 메시지가 생산된다. 공포는 주로 신종감염병 자체, 경제적 혼란을 향하며, 분노는 정부 등 방역 주체나 집단감염 발생 조직, 감염병 관련 정보의 은폐 등 정보불균형 문제를 다루는 특징이 나타난다. 이 과정에서 공동체 안보를 위협하는 사건, 대상을 향한 분노가 강하게 표출된다. 이때 분노는 방역 조치를 정당화할 수 있는 근거로 작용하기도 하나, 소수자 및 사회적 약자 혐오 담론의 토대가 될 수 있는 양면성을 가질 수 있음을 주목할 필요가 있다.

• 디지털융복합연구
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• 제20권3호
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• pp.367-376
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• 2022

본 연구의 목적은 코로나19 방역상황에 투입된 공중보건의사(PHD)의 업무 수행 현황을 조사하고, 향후 효과적인 국가 감염병 방역을 위한 공중보건의사 지원방안을 제시하는 것이다. 연구결과, 공중보건의사는 주로 검체채취, 문진 및 진료, 치료를 수행했던 것으로 나타났다. 방역에 투입된 공중보건의사의 39%는 음압시설이 없는 곳에서 근무했고, 개인 보호 장비와 복리후생 지원도 열악했던 것으로 나타났다. 또한 높은 감염위험성, 정신적 고통, 의사결정과정에서 배제, 공무원과의 갈등, 업무지침 문제, 사전교육 부족 등을 경험한 것으로 조사되었다. 따라서 향후 효과적인 감염병 관리를 위해서는 공중보건의사에게 적절한 직급 부여, 방역 관련 의사결정 과정 참여, 적절한 보상과 규정 명시, 교육과 정신건강 지원이 필요하다.

• 대한물리의학회지
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• 제16권1호
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• pp.123-141
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• 2021

PURPOSE: Focusing on the factors that influence the infectious disease emergency response policy (approached by dividing the factors into health policy management and economic policies), both SARS and MERS cases were based on the legal system, manpower, and budget, but there has not been enough learning from the epidemic. This study focused on infectious disease emergency governance, which various studies have neglected despite its social and academic importance. METHODS: The research is based on an analysis of SARS, MERS, and COVID-19 and compares global policies. In this study, infectious disease emergency governance was divided into health policy management and economic factors. This study focused on planning and leadership before and after the outbreak of infectious diseases and how cooperation was achieved to monitor and respond to infectious diseases successfully. RESULTS and CONCLUSION: The limit of this study was that COVID-19 is a currently ongoing infectious disease with high uncertainty. Because it is an ongoing problem, only some data and statistics are reflected, and many limitations prevent a proper comparison under the same criteria as other infectious diseases. In addition, because continuous changes are expected, there is also room for infectious diseases to develop in a completely different pattern from the current situation, and continuous research must be accompanied in the future.

• 지능정보연구
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• 제27권1호
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• pp.47-64
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• 2021

전 세계적으로 퍼진 코로나 19 상황은 우리의 일상생활의 많은 부분에 영향을 끼쳤을 뿐만 아니라, 경제·사회 등 많은 부분에 걸쳐 막대한 영향력을 미치고 있다. 확진자와 사망자 수가 증가함에 따라 의료진과 대중은 불안, 우울, 스트레스 등 심리적인 문제를 겪고 있다고 한다. 장기적인 부정적인 감정은 사람들의 면역력을 감소시키고 신체적인 균형을 파괴할 수도 있으므로 코로나 19로 인한 심리적인 상태를 이해하는 것이 필수적인 상황이다. 본 연구에서는 코로나 19 감정과 관련된 뉴스 데이터를 수집하여, 텍스트 마이닝을 통해 키워드를 분류하고, 키워드 사이의 의미 네트워크 분석을 통해 단어들의 관계를 시각화하였다. 코로나 감정과 관련된 기사의 키워드에 나타난 단어들의 빈도수를 확인하고 이를 워드 클라우드로 분석하였다. 키워드 빈도 분석 결과 코로나 19 감정과 관련하여 '중국', '불안', '상황', '마음', '사회', '건강'과 같은 단어의 빈도가 높게 나타난 것을 확인할 수 있었다. 각 데이터 간 연결 중심성을 분석한 결과 키워드 중심성 네트워크에서 가장 중심적인 핵심어는 '심리'와 '코로나 19', '블루', '불안'이라는 단어가 높은 연결 중심성을 가지는 것을 확인할 수 있었다. 기사의 헤드라인에 나타난 주요 핵심어 사이의 동시 출현 빈도 네트워크를 그래프로 시각화한 결과, '코로나-블루' 쌍이 가장 굵게 표시되었고, '코로나-감정', '코로나-불안' 쌍이 비교적 굵은 선으로 표시된 것을 알 수 있었다. 코로나와 관련된 '블루'는 우울증을 의미하는 단어로, 코로나와 우울증은 이제 관심을 가져야 할 키워드임을 확인할 수 있었다. 본 연구에서는 장기화한 코로나 19 상황에서 신체적인 방역뿐만 아니라 심리적인 방역에도 힘써야 할 이 시기에 보건 정책담당자가 빠르고 복잡한 의사결정 과정에 도움이 되고자 미디어 뉴스를 모니터링 함으로써, 더욱더 쉬운 소셜 미디어 네트워크 분석 방법을 제시하고자 한다.

• Journal of Multimedia Information System
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• 제8권3호
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• pp.159-166
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• 2021

COVID-19 has dramatically changed people's daily life. Wearing masks is considered as a simple but effective way to defend the spread of the epidemic. Hence, a real-time and accurate mask wearing detection system is important. In this paper, a deep learning-based mask wearing detection system is developed to help people defend against the terrible epidemic. The system consists of three important functions, which are image detection, video detection and real-time detection. To keep a high detection rate, a deep learning-based method is adopted to detect masks. Unfortunately, according to the suddenness of the epidemic, the mask wearing dataset is scarce, so a mask wearing dataset is collected in this paper. Besides, to reduce the computational cost and runtime, a simple online and real-time tracking method is adopted to achieve video detection and monitoring. Furthermore, a function is implemented to call the camera to real-time achieve mask wearing detection. The sufficient results have shown that the developed system can perform well in the mask wearing detection task. The precision, recall, mAP and F1 can achieve 86.6%, 96.7%, 96.2% and 91.4%, respectively.