No abstract

There was a fury of the pandemic because of novel coronavirus (2019-nCoV/SARS-CoV-2) that happened in Wuhan, Hubei province, in China in December 2019. Since then, many model predictions on the COVID-19 pandemic in Wuhan and other parts of China have been reported. The first incident of coronavirus disease 2019 (COVID-19) in India was reported on 30 January 2020, which was a student from Wuhan. The number of reported cases has started to increase day by day after 30 February 2020. The purpose of this investigation is to provide a prediction of the epidemic peak for COVID-19 in India by utilizing real-time data from 30 February to 14 April 2020. We apply the well-known epidemic compartmental model "SEIR" to predict the epidemic peak of COVID-19, India. Since we do not have the complete detail of the infective population, using the available infected population data, we identify the R0 by using polynomial regression. By using the third-order polynomial equation, we estimate that the basic reproduction number for the epidemic in India is R0 = 3.3 (95%CI, 3.1 to 3.5), and the epidemic peak could be reached by September 2020.

In this paper, a high throughput modified Advanced Encryption Standard (AES)-128 bit algorithm is implemented. A new increased parallelism technique is introduced in modified AES architecture in Mix Column round which increases the overall throughput of AES algorithm. This technique is implemented in XC5VLX50T FPGA device Virtex-5.Using this technique throughput is increased 5 % and area is decreased by 30 % when compared to parallel mixcolumn.

No abstract

There was a fury of the pandemic because of novel coronavirus (2019-nCoV/SARS-CoV-2) that happened in Wuhan, Hubei province, in China in December 2019. Since then, many model predictions on the COVID-19 pandemic in Wuhan and other parts of China have been reported.The first incident of coronavirus disease 2019 (COVID-19) in India was reported on 30 January 2020, which was a student from Wuhan. The number of reported cases has started to increase day by day after 30 February 2020. The purpose of this investigation is to provide a prediction of the epidemic peak for COVID-19 in India by utilizing real-time data from 30 February to 14 April 2020. We apply the well-known epidemic compartmental model "SEIR" to predict the epidemic peak of COVID-19, India. Since we do not have the complete detail of the infective population, using the available infected population data, we identify the R 0 by using polynomial regression. By using the third-order polynomial equation, we estimate that the basic reproduction number for the epidemic in India is R 0 = 3.3 (95%CI, 3.1-3.5), and the epidemic peak could be reached by September 2020.