http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
- 中文 을 입력하시려면 zhongwen을 입력하시고 space를누르시면됩니다.
- 北京 을 입력하시려면 beijing을 입력하시고 space를 누르시면 됩니다.
RISS 인기검색어
- 검색키워드
- 저자 : Chamara Sandeepa (검색결과 1 건)
- 무료
- 기관 내 무료
- 유료
-
Charuka Moremada,Chamara Sandeepa,Nadeeka Dissanayaka,Tharindu Gamage,Madhusanka Liyanage 한국통신학회 2021 Journal of communications and networks Vol.23 No.5
Due to the spread of Coronavirus disease 2019(COVID-19), the world has encountered an ongoing pandemicto date. It is a highly contagious disease. In addition to thevaccination, social distancing and isolation of patients are provento be one of the commonly used strategies to reduce the spread ofdisease. For efficient social distancing, contact tracing is a criticalrequirement in the incubation period of 14-days of the disease tocontain any further spread. However, we identify that there is alack of reliable and practical social interaction tracking methodsand prediction methods for the probability of getting the disease. This paper focuses on user tracking and predicting the infectionprobability based on these social interactions. We first developedan energy-efficient BLE (Bluetooth Low Energy) based socialinteraction tracking system to achieve this. Then, based on thecollected data, we propose an algorithm to predict the possibilityof getting the COVID-19. Finally, to show the practicality of oursolution, we implemented a prototype with a mobile app anda web monitoring tool for healthcare authorities. In additionto that, to analyze the proposed algorithm’s behaviour, weperformed a simulation of the system using a graph-based model.
연관 검색어 추천
이 검색어로 많이 본 자료
활용도 높은 자료
