ABSTRACT
The Covid-19 (coronavirus) pandemic creates a worldwide health crisis. According to the WHO, the effective protection system is wearing a face mask in public places. Many studies proved that carrying a face mask is also one of the precautions to decrease the possibility of viral transmission. Strict monitoring of face mask being worn by people is now enforced in many countries. Manual observation and monitoring is quite tedious. Hence, automated systems have been researched using well-kwown face mask detection methods. However, this research paper, deals with some deep learning models which can be effectively used to detect multiple face masks in a crowded environment when the amount of incoming data from sensors is huge or in otherwise stated to a Big data problem. Hence, standalone face detection models are not quite suited. Deep learning models are required in such Big data scenario which forms the essence of this study.
ABSTRACT
A review was undertaken of locally available energy and nutrient-dense foods used in the management of undernourished children in India. Suitability of the 42 food products identified was examined in terms of nutrient profile, palatability, safety, cost-effectiveness, shelf life and feasibility for scale-up of production. Results showed that there is potential to supplement several existing products with additional foods, multivitamins and mineral mixes to enable their use as therapeutic foods in the management of uncomplicated severe acute malnutrition (SAM) in the community. Based on these findings, an existing locally produced product (Balamrutham) was adapted (Balamrutham+) to provide improved energy, protein and nutrient density to enable its use in SAM treatment. To test Balamrutham+, the product was given to uncomplicated moderate and severe malnutrition cases in children under five years old admitted to a government supplementary feeding programme in a district in Telangana state. Follow-up was only possible for two weeks due to the COVID-19 pandemic. After two weeks of supplementation, 22.3% of children with moderate acute malnutrition (MAM) reached discharge criteria and 17.7% of severe acute malnutrition (SAM) children reached MAM criteria. Production of Balamrutham+ has since been scaled up and is being used in treatment across Telangana state according to pre-existing plans as the food was found acceptable by the children in the community. COVID-19-related adaptations include use of mid-upper arm circumference (MUAC)-only protocols for treatment and a separate strategy for follow-up visits in designated containment zones for COVID.
ABSTRACT
In the current scenario, the words Artificial Intelligence and Virtual Intelligence are the familiar ones among students of all ages. This study analyzes the usage of virtual intelligence during the pandemic period. The students of higher education mostly adopted the present way of teaching by using technology. A Positive approach to virtual Intelligence is exhibited in this study. 142 samples were collected by using a convenient sampling method through the well-framed questionnaire for the data analysis.