RESUMO
The whole world has witnessed the global pandemic situation caused and hampered very badly due to COVID-19. We had seen the adverse effect globally, in terms of health, economy, social lifestyle. So, it's an urgent need to find a rapid detection technique/test to avoid the spread of the virus. The most effective and world-wide accepted detection method of COVID-19 is the RT-PCR. But due to its slow detection time and False-negative rates, researchers and scientists are trying different detection methods such as use of GC-MS, E-nose, Electrochemical method, use of nanomaterial-based sensor arrays. But all these have limitations in terms of real time sensing, detection time, sample preparation, etc. In order to overcome said drawbacks and to get real-time analysis, we are proposing a concept for COVID-19 detection based on the reported literature. As per recent advancement researchers have evident the presence of VOCs in COVID-19 infected person's breath by GC-MS method. A real time system is very much necessary to detect the VOCs in the Exhaled breath of the COVID-19 infected person to minimize the burden of healthcare system. In this article we will discuss and propose the probable detection techniques for real time sensing of the VOCs presence in the Exhaled breath of the COVID-19 infected person. © Published under licence by IOP Publishing Ltd.
RESUMO
Over the years, e-learning has seen a boost with the advancement in technology. The very pertinent problem of Covid-19 led to the adoption of online education in India. This study aims to understand the online education in India in terms of benefits, challenges, and strategies using sentiment analysis and the positive and negative instances faced by Indian students and teachers during the pandemic time. Responses from students and teachers have been garnered during the pandemic Covid-19 as the primary source of data. The nature of the research conducted is exploratory and qualitative. Further, a comparative analysis has been undertaken using data visualization. Primary data has been collected using questionnaire and interview methods while secondary data through Twitter. The data pertains to the sentiments of undergraduate and management graduate college students and teachers from February 2020 to January 2022. The secondary data corpus collected from Twitter (5000 tweets) was scraped using Application Program Interfaces (APIs) for further analysis. The Findings suggest that most of the opinions in the primary data collected have been negative while the secondary data analysis shows that polarity is more on neutral sentiments and subjectivity is more on positive sentiments. Relevant recommendations have been made on the conclusion drawn. © 2022 Bharati Vidyapeeth, New Delhi.