A mathematical model of coronavirus transmission by using the heuristic computing neural networks.

In this study, the nonlinear mathematical model of COVID-19 is investigated by stochastic solver using the scaled conjugate gradient neural networks (SCGNNs). The nonlinear mathematical model of COVID-19 is represented by coupled system of ordinary differential equations and is studied for three different cases of initial conditions with suitable parametric values. This model is studied subject to seven class of human population N(t) and individuals are categorized as: susceptible S(t), exposed E(t), quarantined Q(t), asymptotically diseased IA (t), symptomatic diseased IS (t) and finally the persons removed from COVID-19 and are denoted by R(t). The stochastic numerical computing SCGNNs approach will be used to examine the numerical performance of nonlinear mathematical model of COVID-19. The stochastic SCGNNs approach is based on three factors by using procedure of verification, sample statistics, testing and training. For this purpose, large portion of data is considered, i.e., 70%, 16%, 14% for training, testing and validation, respectively. The efficiency, reliability and authenticity of stochastic numerical SCGNNs approach are analysed graphically in terms of error histograms, mean square error, correlation, regression and finally further endorsed by graphical illustrations for absolute errors in the range of 10-05 to 10-07 for each scenario of the system model.

Implementation of e-learning in learning management education innovation during the COVID-19 pandemic

This study aims to see the effectiveness of e-learning implementation and student responses to e-learning during the COVID-19 pandemic on learning innovation management in education. The sample data in this study were 21 students. The instrument used in this study was a student response questionnaire sheet consisting of 15 items. The results of this study indicate that the instruments used were valid and reliable. This was evidenced by the results of the validity calculation which states that 15 questions were valid, and no questions were issued. And also, for the results of data reliability calculations using the Cronbach alpha method with a score of 0.88 this value was greater when compared with the rtable value for α = 0.05 namely 0.4329. So, it could be said that the data used was reliable. For the results of the analysis with the Rasch model assisted by the Winstep application it was found that the quality of the questionnaire responses to E-Learning g on innovation and educational management materials at MAP Bengkulu University was very good. From the pairing T-test also obtained SIG <0.05 which means that there was a significant difference.