ABSTRACT
MOOCs have gained a lot of popularity for past few years. Especially after the outbreak of Coronavirus, everyone is trying to gain some knowledge and skill while being at the comfort of home and making themselves safe. Due to sudden increase in the number of participants on MOOCs there is a need for an automated system to be able to assess the reviews and feedbacks given by the learners and find the sentiments behind their statements. This analysis will help trainers identify their shortcoming and make their courses even better. For sentiments analysis, several approaches may be used. This research aims to provide a system which will perform sentiments analysis on the novel dataset and show the comparison of lexicon-based vs transformer-based sentiment analysis models. For lexicon based, VADER was chosen and for transformer-based, state-of-The-Art BERT was chosen. BERT was found to be exceptionally good with an accuracy of 84% and F1-score of 0.64. © 2022 IEEE.
ABSTRACT
The dark cloud of the vigorously spreading pandemic is still seen hovering over our heads. Though the situation presently seems under control, a continuation of the same is not guaranteed. The massive disturbance to the environmental assets leading to the melting of polar ice caps, ozone depletion, global warming, etc., poses a towering threat to every surviving species. The most recently faced devastation by the people is the 'Corona' virus;a ginormous pandemic, which has affected people living in almost every nook and corner of the world. For which the primary steps were to wear a mask, maintain social distancing and sanitize almost every single thing that comes in physical contact with more than one human. This brings in a crucial technical catastrophe, the physical barrier to be maintained, and the face masks covering the face, making fingerprint and face recognition systems totally impractical. This demands a grave need for a situation-friendly technical solution. © 2022 IEEE.
ABSTRACT
The infection triggered by the SARS-CoV-2 virus resulted in the novel coronavirus infection (COVID-19), which was firstly identified in city of China, namely Wuhan. The main symptoms such as muscle fatigability, aches, and pain are associated with this condition. Thus, a high proportion of patients who recovered manifest a plethora of long-lasting symptoms. Although, many patients fully recover, health complications can delay a person's complete return to a regular lifestyle. Fatigue is experienced by a considerable percentage of individuals who have recovered from COVID-19 disease. Thus, the neurological symptoms of COVID-19 are frequent and debilitating enough to have piqued the interest of the scientific and general press for their brief and long effect on population health. The authors have searched articles from various search engines. The articles on coronavirus have been collected from PubMed and Scopus databases from Jan., 2019 to July, 2021. On the basis of their importance and uniqueness, articles were included in this review. The study aims on COVID-19 infection on survivors and complications to return to normal life and role of consulting sessions, physiotherapy and other medications after recovery. Some long-term researches are created to investigate the COVID-19's medical, psychological, and socio-economic complications. To resume normal life, COVID-19 survivors are required to take aid to consultations, physiotherapy, and dermatological care.