A Novel CNN-Based Approach for Distinguishing Between COVID and Common Pneumonia

It is well known that the symptoms of Coronavirus disease (COVID) and common pneumonia (CP) disease are very similar though the first one often leads to severe complications and may even be fatal. Hence, it is of vital importance to be able to correctly distinguish between the two. This paper attempts to achieve this task using whole 3-D CT scans of lungs. A number of models have been experimented with, using convolutional and radiomic features as well as their concatenations, and different classifiers (MLP and Random Forest) with two different sizes of input CT images (50 × 128 × 128 and 25 × 256 × 256 ) and their performances have been compared. The most significant contribution of this work is the postulation of a 3-D dual-scale framework using CT scans, employing both intra-scale and inter-scale information, thereby achieving performance scores which are much higher than the state of the art methods to distinguish between COVID-19 and CP using lung CT scans. Specifically, Accuracy of 98.67% and Receiver Operating Characteristics-Area Under The Curve (AUC) of 99% are worth mentioning. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Forecast of Foreign Direct Investment of India Through ARIMA Under COVID-19 Pandemic

COVID-19 has already affected millions of lives across the globe, and most of the industries and businesses are closed. This pandemic has badly hit the process of globalization. As a result, the flows of FDI are upset and global FDI flows are anticipated to decline between 30 and 40% during 2020–2021. Countries like the USA have negotiated or held up FDI proposals for national security concerns. Regardless of the adverse transitory shocks from COVID-19, aggregate FDI inflows into India have continued resilient. FDI by technology-based enterprises has reached USD 17 billion in the first seven months of 2020, supported by new investments by Google valued at USD 10 billion in since July, 2020, and other global technology-based enterprises like Amazon, Facebook, and Foxconn have also agreed for new large investments in India by this year. The digital revolution of India is anticipated to boost the progress of the retail consumer market and e-business over the next ten years. It helps to captivate prominent international MNCs in merchandise and e-business in the Indian market. India’s apt step to armour against opportunistic economic shadowing of its companies by competing nations during the pandemic is a right move. Also, it has to tap all the existing and emerging areas which possess the potential to attract and absorb huge foreign investment for development. This paper makes a forecast of FDI using ARIMA modelling and explores the compositional and directional impact on it under this COVID scenario in India. Though the long-run forecast over the next 10 years throws a silver lining of a continuation of the upward trend of the inward FDI inflows in India, the fact that it is more skewed towards its lower limits signals the need for streamlined and substantial policy strategies to tap and promote its buoyancies to realize its trend towards the upper limit if not beyond. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Analysis of Online Education System of Bangladesh during COVID-19 Pandemic Based on NLP and Machine Learning: Problem and Prospect

The Coronavirus Disease (COVID-19) pandemic has interrupted the education system throughout the world. Bangladesh is no unlike;all educational institutions are shut down across the country. The online teaching method is quite new especially for the developing countries like Bangladesh. Therefore, the main aim of this work is to mine student's opinions about online class during this COVID-19 pandemic. To achieve this aim, this paper uses a questionnaire survey through the google form to collect Bangladeshi student's opinion on online class, build a corpus of 5005 data containing both Bangla and Romanized Bangla text. After data pre-processing and extracting the features, machine learning classifiers were deployed. Then performance measurement was done in terms of accuracy, precision, recall and F1 score. In the final evaluation, we achieved highest of 80% accuracy with SVM classifier, where the accuracy achieved by Logistic Regression, Random Forest and Multinomial Naïve Bayes classifier was 78%, 77% and 77% respectively. We tried to predictthe problems faced by students and suggested possible solutions about online class. The result showed that 27.9% student faced financial problem and 25.8% student faced unstable internet problem. 54.8% user suggested stable internet facility in low cost or free and 23.1% suggested financial assistance for online class as the possible solution of aforementioned problems. © 2021 IEEE.

Non-Woven Textiles Formed from Contact Drawn Poly(ethylene oxide) Fibers Provide Tunable Filtration and Virucidal Properties via Entrapment of Silver Nanoparticles

Filtering facepiece respirators (FFRs) protect wearers from inhalation of fine particulates and help prevent transmission of airborne viruses. Here, an FFR material is produced by successive deposition of contact drawn poly(ethylene oxide) (PEO) fibers. Fibers are formed by immersing an array of pins in a highly viscous precursor solution of PEO and then rapidly removing the pins such that polymer entanglement occurs, forming multiple liquid bridges that rapidly dry as they extend. Tunable filtration is achieved by varying the number of PEO fiber elongation cycles. Placing the PEO textiles between two woven cotton cloths provides structural support and additional filtration capacity, achieving a maximum filtration efficiency of 95% with a corresponding initial pressure drop of 281 Pa. The entrapment of silver nanoparticles in the PEO fibers imparts virucidal properties to PEO-based textiles, as demonstrated by inactivation of a human coronavirus HCoV-OC43 and influenza A virus inoculum. The ability to tune filtration efficiency to application needs and provide advanced function through entrapment of active materials represents a versatile tool for limiting exposure to airborne particulates and pathogens.