• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.145-146
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• 2021

본 논문은 최근 이슈가 되고 있는 코로나19 시대에서 확진자 동선을 파악하기 위해 매장 등 시설에 방문했다는 기록을 남기는 과정 중 방문자가 QR 코드를 생성하고 관리자가 방문자의 QR 코드를 인식하는 방식과 반대로 방문자가 매장의 QR 코드를 직접 인식하게 하여 방문자와 매장 관리자가 겪을 수 있는 불편함을 덜어주기 위한 논문이다. App은 방문자와 매장 관리자 App이 따로 나눠져 있으며 사용자 App은 관리자의 QR을 스캔하여 방문기록을 남기고 관리자 App은 QR 코드를 생성만 하고 출입문에 비치하기만 하면 된다. Web도 관리자와 사용자로 나눠지는데 사용자는 자신의 방문기록과 감염 위험 경로 목록을 확인할 수 있으며 관리자는 매장에 다녀간 방문자의 목록과 확진자가 다녀갈 경우 감염 위험 경로 목록에 해당 사용자 정보가 나타나게 설계하였다.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2020.12a
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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.

• International Journal of Computer Science & Network Security
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• v.22 no.1
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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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• v.9 no.4
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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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• v.16 no.6
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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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• v.19 no.2
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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.

• Journal of Wellbeing Management and Applied Psychology
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• v.5 no.4
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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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• v.10 no.1
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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.

• The Journal of Information Systems
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• v.29 no.4
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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.

• Journal of Integrative Natural Science
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• v.14 no.1
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• pp.11-20
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• 2021

On November 17, 2019, an infectious disease with symptoms of pneumonia, called the Wuhan virus at the time, occurred in Wuhan, China. Since then, the name has been changed to COVID-19, and the virus has spread all over the world, and the WHO has declared the highest warning level for infectious diseases, "Pandemic". The coronavirus has also caused great confusion in South Korea. This resulted in large infected people.The first confirmed cases occurred on January 20, 2020, and the number of infected patients is steadily increasing after experiencing several waves, and many corona confirmed cases are also occurring in 2021 after the year. As the whole world enters a pandemic, walls are created between people and people, companies and businesses, and countries and countries, and all growth stops or declines, including human relationships, domestic companies and industries, and foreign industries. As a result, society in general is experiencing a lot of stagnation. Among them, small and medium-sized enterprises (SMEs), which are the basis of all growth in Korea, and youth who are trying to contribute to the national development by entering society, are struggling to find jobs. Even before the coronavirus outbreak, the difficulty of job hunting and the prospect of small and medium-sized businesses were not very good. In this situation, as the country's overall economic situation is poor, the vitality of SMEs has decreased a lot, the prospects are not good, so jobs are reduced, and there are many difficulties due to reluctance to hire new employees. In this study, with 2019 before the corona era and 2020 after the corona era, we compare SMEs before and after the corona era and overall job search and job search activities through average difference analysis, and whether they are affecting through correlation analysis. Through this, it suggests a direction to increase job search through corporate and government policies after raising the prospects of SMEs first.