• International Journal of Computer Science & Network Security
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• 제21권4호
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• pp.93-102
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• 2021

The world is facing an unprecedented economic, social and political crisis with the spread of COVID-19. The Corona Virus (COVID-19) and its global spread have resulted in declaring a pandemic by the World Health Organization. The deadly pandemic of 21st century has spread its wings across the globe with an exponential increase in the number of cases in many countries. The developing and underdeveloped countries are struggling hard to counter the rapidly growing and widespread challenge of COVID-19 because it has greatly influenced the global economies whereby the underdeveloped countries are more affected by its devastating impacts, especially the life of the low-income population. Information and Communication Technology (ICT) were particularly useful in spreading key emergency information and helping to maintain extensive social distancing. Updated information and testing results were published on national and local government websites. Mobile devices were used to support early testing and contact tracing. The government provided free smartphone apps that flagged infection hotspots with text alerts on testing and local cases. The purpose of this research work is to provide an in depth overview of emerging technologies and recent ICT developments to combat COVID-19 Pandemic. Finally, the author highlights open challenges in order to give future research directions.

• 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.

• 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.

• 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%.

• International Journal of Computer Science & Network Security
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• 제24권7호
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• pp.195-201
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• 2024

With the Covid-19(Corona Virus) spread all around the world, people are using this propaganda and the desperate need of the citizens to know the news about this mysterious virus by spreading fake news. Some Countries arrested people who spread fake news about this, and others made them pay a fine. And since Social Media has become a significant source of news, .there is a profound need to detect these fake news. The main aim of this research is to develop a web-based model using a combination of machine learning algorithms to detect fake news. The proposed model includes an advanced framework to identify tweets with fake news using Context Analysis; We assumed that Natural Language Processing(NLP) wouldn't be enough alone to make context analysis as Tweets are usually short and do not follow even the most straightforward syntactic rules, so we used Tweets Features as several retweets, several likes and tweet-length we also added statistical credibility analysis for Twitter users. The proposed algorithms are tested on four different benchmark datasets. And Finally, to get the best accuracy, we combined two of the best algorithms used SVM ( which is widely accepted as baseline classifier, especially with binary classification problems ) and Naive Base.

• 한국융합학회논문지
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• 제11권10호
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• pp.53-61
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• 2020

최근 코로나19 바이러스로 인하여 언컨텍트 서비스가 본격적으로 활성화됨에 따라 비대면 접촉 원격 의료 서비스를 제공하기 위한 시스템 개발의 필요성이 증가하게 되었다. 본 연구에서는 원격진료를 지원하기 위한 스마트 헬스케어 시스템인 Rm_She(Remote Medical Smart Healthcare System)을 제안한다. Rm_She는 IoT를 기반으로 생체신호를 감지하는 다양한 헬스케어 제품을 하나의 애플리케이션으로 연결하여 여러 가지의 생체신호 정보를 수집 및 관리할 수 있다. 스마트 폰에 실행되는 헬스체크 앱(HC_app)을 이용하여 여러 종류의 생체신호 측정 장치와 무선랜으로 연결하고, 생체신호 값을 HC_app에서 전송 받아, 사용자에게 측정된 생체신호를 출력하고, 해당 정보를 헬스케어관리서버로 전송한다. 헬스케어 서버에서는 측정값을 전송 받아 데이터베이스에 저장하고, 저장된 측정값은 의료진들이 원격에서 실시간으로 모니터링 할 수 있도록 웹서비스로 제공한다.

• 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%.

• 대한방사선기술학회지:방사선기술과학
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• 제44권6호
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• pp.679-688
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• 2021

This study is a questionnaire about the lesson environment that radiation major students prefer in a non-face-to-face live online lesson environment for a total of 133 students, 65 second graders and 68 third graders who are enrolled in the department of radiology at a university located in the Seoul metropolitan area. And checked the satisfactory level by grade. The questionnaire consists of three categories: 1st real-time non-face-to-face lectures, 2nd professor lectures, and 3rd corona lectures. A total of 14 questions, with multiple choice and descriptive response methods. As an evaluation method, in the case of a multiple-choice question, the average was calculated using a 5-point Likert scale. As a result of conducting the independent sample T-test of the SPSS program, the response by grade was P > 0.05, and no significant result was shown by the contents of the questionnaire survey of the second grade. As for the lecture method of the department of radiology after the end of Covid-19 virus, it is better to promote face-to-face lessons in radiation training subjects and non-face-to-face real-time education in subjects centered on radiation theory.

• 대한치과의료관리학회지
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• 제9권1호
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• pp.44-50
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• 2021

Owing to the Corona virus (COVID-19) crisis, virtual education has been expanded. Accordingly, this study was conducted to determine the direction of oral health education by examining participants' satisfaction with virtual education and educational media preferences. This study collected data from a Naver Form online survey targeting 290 university students across the country, from May 10 to 31, 2021. The collected data were analyzed using IBM SPSS 20.0. According to the data, satisfaction with virtual classes was 3.36 points in 5-point Likert scale, satisfaction factors were reduced commuting time and money expenditure, and the highest dissatisfaction factor was a decrease in lecture concentration. The media platform that most interested students pursing oral health education was YouTube. The oral health education that participants wished to receive through virtual education included how to prevent tooth decay, how to prevent gum disease, and how to brush teeth. In conclusion, it is necessary to develop various media like Zoom, YouTube, and virtual reality programs so that students feel motivated to utilize oral health education and improve oral health.

• 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.