A Deep Learning Approach for Sentiment Analysis of COVID-19 Reviews

User-generated multi-media content, such as images, text, videos, and speech, has recently become more popular on social media sites as a means for people to share their ideas and opinions. One of the most popular social media sites for providing public sentiment towards events that occurred during the COVID-19 period is Twitter. This is because Twitter posts are short and constantly being generated. This paper presents a deep learning approach for sentiment analysis of Twitter data related to COVID-19 reviews. The proposed algorithm is based on an LSTM-RNN-based network and enhanced featured weighting by attention layers. This algorithm uses an enhanced feature transformation framework via the attention mechanism. A total of four class labels (sad, joy, fear, and anger) from publicly available Twitter data posted in the Kaggle database were used in this study. Based on the use of attention layers with the existing LSTM-RNN approach, the proposed deep learning approach significantly improved the performance metrics, with an increase of 20% in accuracy and 10% to 12% in precision but only 12–13% in recall as compared with the current approaches. Out of a total of 179,108 COVID-19-related tweets, tweets with positive, neutral, and negative sentiments were found to account for 45%, 30%, and 25%, respectively. This shows that the proposed deep learning approach is efficient and practical and can be easily implemented for sentiment classification of COVID-19 reviews.

Medical Waste from COVID-19 Pandemic-A Systematic Review of Management and Environmental Impacts in Australia.

The coronavirus (COVID-19) pandemic has created a global medical emergency. The unforeseen occurrence of a pandemic of this magnitude has resulted in overwhelming levels of medical waste and raises questions about management and disposal practices, and environmental impacts. The amount of medical waste generated from COVID-19 since the outbreak is estimated to be 2.6 million tons/day worldwide. In Australia, heaps of single-use gowns, facemasks/face shields, aprons, gloves, goggles, sanitizers, sharps, and syringes are disposed everyday as a result of the pandemic. Moreover, the establishment of new home/hotel quarantine facilities and isolation/quarantine centres in various Australian states and territories have increased the risks of transmission among people in these facilities and the likelihoods of general waste becoming contaminated with medical waste. This warrants the need to examine management and disposal practices implemented to reduce the transmission and spread of the virus. This study reviews the various management and disposal practices adopted in Australia for dealing with medical waste from the COVID-19 pandemic and their impacts on public health and the environment. To achieve the aims of this study, prior studies from 2019-2021 from various databases are collected and analysed. The study focuses on generation of medical waste from COVID-19, management and disposal methods, current problems/challenges and environmental and public health impacts. Considering the enormous risks involved and the significance of appropriate handling and disposal of medical waste from COVID-19, this study provides insights on short and long term responses towards managing COVID-19 waste in Australia. The study contributes to Australia's efforts against the transmission and spread of COVID-19 and provides recommendations for the development of workable and sustainable strategies for mitigating similar pandemics in the future.

Application of the Extended Reality Technology for Teaching New Languages: A Systematic Review

Much attention has been given to the use of extended reality (XR) technology in educational institutions due to its flexibility, effectiveness, and attractiveness. However, there is a limited study of the application of XR technology for teaching and learning languages in schools. Thus, this paper presents a systematic review to identify the potential benefits and challenges of using XR technology for teaching new languages. This review provides a basis for adopting XR technology for teaching languages in schools. This research also provides recommendations to successfully implement the XR technology and ways to improve motivation, engagement, and enhanced accessibility of learning and teaching resources on both students and teachers. To fulfil the aims of this research, previous studies from 2011 to 2021 are collected from various academic databases. This study finds that there is still a need to develop appropriate strategies for the development and implementation of XR technology for teaching new languages to school students.