G-DCNN: GAN based Deep 2D-CNN for COVID-19 Classification

Recent progress in COVID-19 detection techniques involve deep learning models. The patient's image data like Chest X-Ray Images, CT-scan data help the physician for analyzing whether the patient is COVID-19 positive or negative. However, huge data size is essential for improving the classification accuracy of deep learning model. Data Augmentation (DA) is a promising solution to generate synthetic samples of data. Sampling is a traditional data augmentation technique to generate synthetic samples. Recently, Generative Adversarial Networks (GAN) have declared in generating high quality synthetic data from acutal small data to treat imbalance issue. This work proposed a method called GAN based Deep 2D-CNN (G-DCNN) for COVID-19 recognition. In this study, GAN has been used for synthesizing Chest X-Ray and CT-scan images followed by Deep 2D-CNN with the goal of detecting COVID-19. © 2022 IEEE.

Conceptual Framework of Factors Affecting Online Teaching

This study will add to the body of knowledge by creating a conceptual framework around fundamental concepts related to examining the factors that influence the efficiency of online teaching. The framework is based on an assessment of the online teaching literature found using Emerald, Institute of Electrical and Electronics Engineers (IEEE) Explore, ProQuest, and Google Scholar searches. A conceptual matrix is used to combine the findings into a framework of online instruction and effectiveness. A questionnaire was utilized and 81 respondents participated in the survey. We found that Google Meet is the most used platform for online teaching. In terms of stress level, teachers between the ages of 36 and 50 are the most stressed. As per time spent on online teaching, most teachers spent 3-5 hours a day and we also found that the more hours spent on online teaching, the more benefit the teachers and students will get. The study's findings can help the school and Malaysia's Ministry of Education understand the factors that affect how well teachers can conduct online teaching. © 2022 by the authors.

Agent-mediation in RADT Framework for Self-Quarantine Monitoring

The technology advancement is beckoned by the recent pandemic crisis at all levels. With the situation of self-quarantined individuals found to be in public places against the rules, causing threat to the spread of the COVID-19 virus, the health industry and the whole nation started to revisit the monitoring capabilities in hand that runs parallel with the massive fight against the pandemic. Shortage of resources to curb the spread that is caused by stubborn self-quarantined individuals added to the pain. This paper presents a conceptual framework for agent-mediated self-quarantine monitoring to lessen the burden of the health officers. This framework consists of four main software agents performing tasks from data capture in sensor device to the analysis and transmission of alerts to health officers and appointed recipients. The name RADT framework is given for the main tasks the agents are assigned with, namely Retrieve, Analyse, Decide and Transmit. In general, the software agents perform their tasks in their environment, with the capabilities deemed possible at their level. As their services are required for only 14 days according to the self-quarantine procedure, the agents are programmed to self-terminate after that. © 2021 IEEE.

Clinical characteristics of patients with COVID-19 in Asian countries

Severe Acute Respiratory Syndrome Coronavirus 2 [SARS-CoV-2] has been identified as the cause of an outbreak of respiratory illness in Wuhan, China beginning December 2019. As of 14th July 2020, the pandemic recorded 12,964,809 confirmed cases with 570,288 deaths globally. A thorough review of the clinical characteristics of this infection will help in understanding this widespread but seemingly localizing disease. This research aimed to review the clinical characteristic of Covid-19 including the risk factors, clinical manifestations, laboratory and radiological findings and complications exhibited in Asia. A narrative review was conducted along with 48 research articles published in Scopus journals in 2020 in Asian countries on clinical characteristics of the disease. It was concluded that despite being in the same region, clinical characteristics of COVID-19 varies among the Asian countries. The mortality rate among Asian countries was varied with the competency of public health measures as one of the vital contributing factors. The variable findings on the clinical characteristics may be due to inconsistent quality of methodology in recent researches which was a rapid response to the pandemic. Although these studies are necessary to manage the current global emergency, more high-quality researches are needed to provide a valid and reliable scientific understanding of the disease. © 2020, All India Institute of Medical Sciences. All rights reserved.