Early detection of abnormalities in chest X-rays is essential for COVID-19 diagnosis and analysis. It can be effective for controlling pandemic spread by contact tracing, as well as for effective treatment of COVID-19 infection. In the proposed work, we presented a deep hybrid learning-based framework for the detection of COVID-19 using chest X-ray images.
View Article and Find Full Text PDFWorldwide, COVID-19 is a highly contagious epidemic that has affected various fields. Using Artificial Intelligence (AI) and particular feature selection approaches, this study evaluates the aspects affecting the health of students throughout the COVID-19 lockdown time. The research presented in this paper plays a vital role in indicating the factor affecting the health of students during the lockdown in the COVID-19 pandemic.
View Article and Find Full Text PDFThe introduction of new technology, such as the Internet of Things (IoT), entails a growth in digital devices, which could ultimately result in a high amount of electronic trash (e-waste) production if they are not appropriately managed. Apart from that, the regulation on possible "IoT E-waste" generation is yet to be regulated, probably due to the new development and implementation of IoT globally. Hence, this paper proposed a Sustainable IoT E-waste Management guideline for households.
View Article and Find Full Text PDFThe restoration of mechanical properties is desired for creating the self-healing coatings with no corrosion capabilities. The encapsulation of epoxy resins is limited by various factors in urea and melamine formaldehyde microcapsules. An improved method was developed, where epoxy resin was encapsulated by individual wrapping of poly(melamine-formaldehyde) and poly(urea-formaldehyde) shell around emulsified epoxy droplets via oil-in-water emulsion polymerization method.
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