• 한국자원식물학회:학술대회논문집
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• 한국자원식물학회 2020년도 추계국제학술대회
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• pp.15-15
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• 2020

In an internal document, CORONA-VIRUS DISEASE 2019 (COVID-19) PLAN, release developed stated that "on January 22, 2020, Palau Ministry of Health activated its emergency operations center, and since then has prepared and put in place measures in response to this global pandemic." The actions eventually led to the closure of most flights coming into Palau as a method to protect its population. The population of is at high risk with COVID19 due to the very elevated rate of NCD's, as well as the limited access to proper testing and treatment facilities. Increased use of traditional medicines in the population has reduced the co-morbidities by reducing risk factors. Furthermore, the expansion of tradtional NCD therapies, especially that of DAK reduce pressure due to obesity and diabetes therefore allowing for unimpaired immune systems to combat deadly infectious diseases such as COVID19.

• 동의생리병리학회지
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• 제36권5호
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• pp.147-154
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• 2022

In order to secure practising rapid pattern(證, zheng) differentiation against acute infectious diseases like corona virus disease-19(COVID-19) showing rapid variation and contagion, a simplified classification of stages centering on the exterior-interior pattern identification with 2 step-subdivision by cold, heat, deficiency, excess pattern and pathogens is proposed. Pattern differentiation by compound patterns of 8 principles is made for the non-severe stage of general cold and the early mild stage of epidemic disease. Compound pattern's names of 8 principles about external infectious diseases are composed of three stages, that is disease site-characters-etiology. Based on early stage symptoms of fever or chilling etc., exterior, interior and half exterior and half interior patterns are determined first, and then cold, heat, deficiency, excess patterns of exterior and interior pattern respectively are determined, and then more concrete differentiation on pathogens of wind, dryness, dampness and dearth of qi, blood, yin, yang accompanied with constitutional and personal illness factors. Summarizing above descriptions, 4 patterns of exterior cold, exterior heat, exterior deficiency, exterior excess and their secondary compound patterns of exterior cold deficiency and exterior cold excess and so on are classified together with treatment method and available decoction for a standard measure of eight principle pattern differentiation.

• International Journal of Computer Science & Network Security
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• 제22권1호
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• pp.225-233
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• 2022

The recent outbreak of corona virus (COVID-19) infectious disease had made its forecasting critical cornerstones in most scientific studies. This study adopts a machine learning based time series model - Auto Regressive Integrated Moving Average (ARIMA) model to forecast COVID-19 confirmed cases in Botswana over 60 days period. Findings of the study show that COVID-19 confirmed cases in Botswana are steadily rising in a steep upward trend with random fluctuations. This trend can also be described effectively using an additive model when scrutinized in Seasonal Trend Decomposition method by Loess. In selecting the best fit ARIMA model, a Grid Search Algorithm was developed with python language and was used to optimize an Akaike Information Criterion (AIC) metric. The best fit ARIMA model was determined at ARIMA (5, 1, 1), which depicted the least AIC score of 3885.091. Results of the study proved that ARIMA model can be useful in generating reliable and volatile forecasts that can used to guide on understanding of the future spread of infectious diseases or pandemics. Most significantly, findings of the study are expected to raise social awareness to disease monitoring institutions and government regulatory bodies where it can be used to support strategic health decisions and initiate policy improvement for better management of the COVID-19 pandemic.

• International journal of advanced smart convergence
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• 제9권4호
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• pp.132-138
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• 2020

Worldwide, the number of corona virus disease 2019 (COVID-19) confirmed cases is rapidly increasing. Although vaccines and treatments for COVID-19 are being developed, the disease is unlikely to disappear completely. By attaching a smart sensor to the respirator worn by medical staff, Internet of Things (IoT) technology and artificial intelligence (AI) technology can be used to automatically detect the medical staff's infection symptoms. In the case of medical staff showing symptoms of the disease, appropriate medical treatment can be provided to protect the staff from the greater risk. In this study, we design and develop a system that detects cough, a typical symptom of respiratory infectious diseases, by applying IoT technology and artificial technology to respiratory protection. Because the cough sound is distorted within the respirator, it is difficult to guarantee accuracy in the AI model learned from the general cough sound. Therefore, coughing and non-coughing sounds were recorded using a sensor attached to a respirator, and AI models were trained and performance evaluated with this data. Mel-spectrogram conversion method was used to efficiently classify sound data, and the developed cough recognition system had a sensitivity of 95.12% and a specificity of 100%, and an overall accuracy of 97.94%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권6호
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• pp.2018-2043
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• 2022

Nowadays, COVID-19 infections are influencing our daily lives which have spread globally. The major symptoms' of COVID-19 are dry cough, sore throat, and fever which in turn to critical complications like multi organs failure, acute respiratory distress syndrome, etc. Therefore, to hinder the spread of COVID-19, a Computerized Doughty Predictor Framework (CDPF) is developed to yield benefits in monitoring the progression of disease from Chest CT images which will reduce the mortality rates significantly. The proposed framework CDPF employs Convolutional Neural Network (CNN) as a feature extractor to extract the features from CT images. Subsequently, the extracted features are fed into the Adaptive Dragonfly Algorithm (ADA) to extract the most significant features which will smoothly drive the diagnosing of the COVID and Non-COVID cases with the support of Doughty Learners (DL). This paper uses the publicly available SARS-CoV-2 and Github COVID CT dataset which contains 2482 and 812 CT images with two class labels COVID⁺ and COVI^-. The performance of CDPF is evaluated against existing state of art approaches, which shows the superiority of CDPF with the diagnosis accuracy of about 99.76%.

• Journal of Medicine and Life Science
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• 제19권2호
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• pp.74-77
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• 2022

We present a fatal case of cerebral arterial thrombosis after corona virus disease 19 (COVID-19) vaccination with ChAdOx1 nCOV-19. The deceased was a 63-year-old woman with no relevant medical history. She presented symptoms of nausea, fatigue, and headache immediately after vaccination. Ten days after vaccination, she suddenly started vomiting and developed high blood pressure. The patient eventually died 23 days after vaccination. Autopsy findings showed that the cerebral arteries and internal carotid arteries were fully enlarged and were compacted with thrombi. The brain stem showed ischemic necrosis, and extravasation from this necrotic lesion led to focal subarachnoid hemorrhage around the brain stem where large blood clots still remained. No aneurysms or atherosclerotic changes were found in these arteries. We note the following three facts. Firstly, all symptoms occurred immediately after vaccination; secondly, the main cause of death was consistent with known side effects of the vaccine; and lastly, the mechanism of thrombus formation in this case goes beyond the general category of thrombogenesis known so far. While the authors know that this case does not fall into known categories of vaccine side effects, we presenting this case to demonstrate that a comprehensive review of various possibilities related to vaccine side effects is needed to establish a COVID-19 defense system.

• 웰빙융합연구
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• 제5권4호
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• pp.11-17
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• 2022

Purpose: This study discusses how Indonesia's response to the Corona Virus Disease-19 pandemic based on the perspective of housing policy capacity which consists of resources, organizations, and networks, politics, systems, and finance. Research design, data and methodology: This study used a qualitative method through a literature review. Data collection techniques were carried out by searching various sources and literature related to housing capacity theory and various data on Indonesia's response to the Covid 19 pandemic. Based on a literature review, this study adapted and modified the five components of capacity, namely resource capacity, organizational and network capacity, political capacity, system capacity and financial capacity in Indonesia in responding to the Covid-19 pandemic. Data analysis used analytical themes which consist of understanding the data, generating initial codes, looking for themes, reviewing themes, defining and naming themes, producing of manuscripts. Results: The results show that the weakness of the system capacity greatly affects Indonesia's housing policy capacity in responding to the Covid-19 pandemic and on the other hand the five housing capacities are an integrated process within the housing policy framework in Indonesia, especially to overcome the Covid-19 pandemic. Conclusions: The findings of this study are the importance of building a system capacity that is directly integrated with housing policy and the strengthening of the resources capacity, organizations, and networks, politics, and finance in the context of Indonesia's housing policy, especially in dealing with the Covid-19 pandemic situation.

• International Journal of Advanced Culture Technology
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• 제10권1호
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• pp.204-210
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• 2022

From the 1970s to the present, the number of new infectious diseases such as SARS, Ebola virus, and MERS has steadily increased. The new infectious disease, COVID-19, which began in Wuhan, Hubei Province, China, has pushed the world into a pandemic era. As a result, Countries imposed restrictions on entry to foreign countries due to concerns over the spread of COVID-19, which led to a decrease in the movement of tourists. Due to the restriction of travel, keywords such as "Corona blue" have soared and depression has increased. Therefore, this study aims to analyze the stress meaning network of the COVID-19 era to derive keywords and come up with a plan for a travel-related platform of the Post-COVID 19 era. This study conducted analysis of travel and stress caused by COVID-19 using TEXTOM, a big data analysis tool, and conducted semantic network analysis using UCINET6. We also conducted a CONCOR analysis to classify keywords for clustering of words with similarities. However, since we have collected travel and stress-oriented data from the start to the present, we need to increase the number of analysis data and analyze more data in the future.

• 한국정보시스템학회지:정보시스템연구
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• 제29권4호
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• pp.123-135
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• 2020

Purpose The purpose of this study is to investigate the development process and the effectiveness of the EISS (epidemiological investigation support system), which prevents the spread of infectious diseases like a novel corona virus disease, COVID-19. Design/methodology/approach This study identified the existing epidemiological support system for MERS through prior research and studied the case of the development of a newly developed epidemiological support system based on cloud computing infrastructure for COVID-19 through inter-ministerial collaboration in 2020. Findings The outbreak of COVID-19 drove the Korean Government began the development of the EISS with private companies. This system played a significant role in flattening the spread of infection during several waves in which the number of confirmed cases increased rapidly in Korea, However, we need to be careful in handling confirmed patients' private data affecting their privacy.

• 통합자연과학논문집
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• 제14권1호
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• pp.11-20
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• 2021

2019년 11월 17일, 중국 우한에서 당시 우한 바이러스라는 이름으로 한 폐렴 증상이 나타나는 감염병이 발발했다. 코로나19 (COVID-19)로 공식 명명됐으며 해당 바이러스가 전 세계 곳곳으로 퍼지면서 세계보건기구(WHO)는 감염병 최고 경고 등급인 "팬데믹(Pandemic)"을 선언을 하였다. 코로나19는 대한민국 역시도 큰 혼란에 빠뜨렸다. 이는 큰 감염자들을 낳았는데, 2020년 1월 20일에 첫 확진자가 발생했으며 여러 번의 파동을 겪으면서 감염자가 꾸준히 증가 중이고, 해가 지난 2021년도 역시 많은 코로나 확진자가 발생 중이다. 전 세계가 팬데믹 상황에 접어들면서 사람과 사람 사이에, 기업과 기업 사이에, 나라와 나라 사이에 벽이 생기면서 인간관계, 국내사업 및 산업, 해외산업까지 모든 성장이 멈추거나 하락하는 추세에 들어서면서 전반적인 사회가 많은 침체를 겪는 중이다. 이 중 우리나라의 모든 성장의 기본이 되는 중소기업과 사회에 진입하여 국가 발전에 이바지하려 하는 청년들은 구인 구직활동에 애를 먹고 있다. 코로나가 발생하기 전에도 구인·구직의 어려움이나 중소기업의 전망은 크게 좋지 못했다. 이런 상황에 코로나까지 발생하여 국가의 전반적인 경제상황이 좋지 않으니, 중소기업의 활력도 많이 감소하고, 전망도 좋지 않아 일자리도 줄여가고, 신입사원 채용도 꺼려하여 많은 어려움이 있다. 본 연구에서는 2019년을 코로나 시대 이전, 2020년을 코로나 시대 이후로 두고 코로나 시대 이전과 이후의 중소기업과 전반적 구인·구직 활동에 대해 평균 차이분석을 통해 비교해보고, 상관분석을 통해 영향을 미치고 있는지에 대해 분석한다. 이를 통해 중소기업의 전망을 우선적으로 높인 이후 기업과 정부의 정책을 통해 구인 구직을 늘리는 방향을 제시한다.