ABSTRACT
The COVID-19 outbreak has been affecting the health of people all around the world. With the number of confirmed cases and deaths still rising daily, so the main aim is to detect positive cases as soon as and provide them with the necessary treatment. The utilization of imaging data including chest x-rays and computed tomography (CT) was proven that is would be beneficial for quickly diagnosing COVID-19. Since Computerized Tomography provides a huge number of images, recognizing these visual traits would be difficult and take enormous amounts of time for radiologists so automated diagnosis technologies including deep learning (DL) models are recently for COVID-19 screening in CT scans. This review paper presents different researches which used deep learning approaches including various models of convolutional neural networks (CNN) used in image classification tasks well, and large training, like ResNet, VGG, AlexNet, LeNet, GoogleNet, and others for COVID-19 diagnosing and severity assessments using chest CT images. As a result, automated COVID-19 analysis on CT images is essential to save medical personnel and essential time for disease prevention. © 2023 Institute of Advanced Engineering and Science. All rights reserved.
ABSTRACT
In the article titled "Nanotechnology-Based Sensitive Biosensors for COVID-19 Prediction Using Fuzzy Logic Control" [1], there was a spelling error in affiliation nine. The correct affiliation is "Department of Chemical Engineering, Addis Ababa Science and Technology University, Ethiopia, " and it is corrected above. © 2022 Shuangshuang Fan and Xiaoxue Liu.
ABSTRACT
Technology-assisted learning (TAL) is one of the key factors to realize the goals of sustainable development, being exemplified in the form of smart cities in urban areas. Student satisfaction is an important predictor of success and achievement in all modes of education including TAL. In the unique circumstances created by COVID-19 pandemic, online education became the new normal. However, remote online education was already being used in educational institutions in some countries, including Saudi Arabia, for imparting education to female students by male instructors. The current study, based in Saudi Arabia, aims to measure the perception of female students about the interactive televised classes (ITV), a type of TAL. The survey was conducted using the standard scale called the telecourse evaluation questionnaire (TEQ). This instrument measures students’ satisfaction with ITV classes on three main dimensions namely;instructor, technology and course management. A total number of 108 valid responses were received. The results show that the students perceive the quality of such classes to be just above average on each item as well as in total. The findings of this study should offer better insights into the pedagogical research dealing with TAL. Further, each stakeholder engaged in education would find the results of this study useful in improving the quality of TAL that became a new normal, and is set to persist in future especially in the context of smart cities. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
Covid-19 was declared as a pandemic by World Health Organization (WHO) on March 11, 2020, creating chaos among all the countries around the world. Millions of people have lost their lives with this outbreak. It’s been a year and still countries like India are fighting this global pandemic. Under such circumstances, having the right information about the cases and facilities around would be of great use. In this context, we aim to develop a chatbot for the people of Bangalore to gain the necessary information about the situation. The proposed application includes statistics about the covid cases in Karnataka, Bruhat Bengaluru Mahanagara Palike (BBMP) Help-Line Number for specific zones, Home Intensive Care Unit (ICU) Service Providers, Online Doctor consultation, Oxygen Providers Information and availability of vaccine slots. In this way, our bot can help people gain better understanding of current condition and take informed decisions. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
Novel coronavirus or 2019-nCoV) disease (COVID-19) outbreak IS occur in one of the most chief health problems worldwide. WHO stated that COVID- 19 is the sixth Public heath disaster of global concern involved more than 300 countries .COVID-19 was found to cause a severe type acute respiratory syndrome (ARDS), which is similar to that caused by bat-SL-CoVZC45 and bat-CoVZXC21 corona viruses. It has been reported by World health organization that around 3,848,683 confirmed reported cases with 30,980,21 deaths were declared from at least 260 countries well confirmed cases have been diagnosed in number of countries and regions all over the world, most of them was in China. Precautions and preventive measures are best known method. Social distancing and self-quarantine were advised to smoothen the epidemic curve in the hope of restraining the effects the coronavirus may have had on human health. Ministry has advised that all the schools, universities, social palaces, and any nonessential business to be close till further instruction. These measures were put into place to prompt self-quarantine. The influence of self-quarantine on factors that impact weight change and obesity-related behaviors in adults is unknown. The aim of this study is to determine the self-quarantine impacts n has on human behaviors associated with weight gain and anxiety or depression during the pandemic.