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In this paper a mathematical model is developed to identify the meantime to respiratory failure in Covid-19. According to this model the respiratory failure occurs whenever the total number of damaged cells in lowers respiratory and air sacs in lungs of the infected exceeds their corresponding thresholds. Due to uncertainty, these parameters are considered as random variables. The performance measures of respiratory failure are derived by assuming suitable distributions for the random variables. Finally, the performance predictions are numerically illustrated. This study will help to predict the number of affected who needs ICU and also it creates awareness to peoples, which would helps to reduce the spread of Covid-19. [ABSTRACT FROM AUTHOR]

Machine learning algorithms are being used extensively for rainfall prediction in recent times. This article examines the actual rainfall distribution in All India during each monsoon season for the past 25 years, up to 2017-2018, using data-driven methods. A comparison is made between Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) to forecast the rainfall. The experimental model shows that the prediction accuracy is higher when using ANN than MLR, as determined by their respective performance metrics. [ABSTRACT FROM AUTHOR]

Machine learning algorithms are being used extensively for rainfall prediction in recent times. This article examines the actual rainfall distribution in All India during each monsoon season for the past 25 years, up to 2017-2018, using data-driven methods. A comparison is made between Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) to forecast the rainfall. The experimental model shows that the prediction accuracy is higher when using ANN than MLR, as determined by their respective performance metrics. [ABSTRACT FROM AUTHOR]

In this paper a mathematical model is developed to identify the meantime to respiratory failure in Covid-19. According to this model the respiratory failure occurs whenever the total number of damaged cells in lowers respiratory and air sacs in lungs of the infected exceeds their corresponding thresholds. Due to uncertainty, these parameters are considered as random variables. The performance measures of respiratory failure are derived by assuming suitable distributions for the random variables. Finally, the performance predictions are numerically illustrated. This study will help to predict the number of affected who needs ICU and also it creates awareness to peoples, which would helps to reduce the spread of Covid-19. [ABSTRACT FROM AUTHOR]

The N-Policy for M/G/1 preemptive priority retrial queue with multiple working vacations is presented in this study. Priority customers and regular customers are the two categories of customers. When an orbit is empty, the server takes a working vacation (WV) and operates at a reduced service rate. If there are customers in the queue at the service completion, the server is resumed to a regular busy period (or) it remains on working vacation. When the server finishes serving a customer, the server finds the system empty; the server enters the N-policy vacation (the dormant period) until N customers accumulated. If the server finds no customer in the orbit, it enters the idle period. The steady-state generating functions for the system and its orbit have been obtained by applying the Supplementary Variable Technique (SVT). The system performance measurements, the mean system length and the mean waiting time of the system are obtained. [ABSTRACT FROM AUTHOR]

The N-Policy for M/G/1 preemptive priority retrial queue with multiple working vacations is presented in this study. Priority customers and regular customers are the two categories of customers. When an orbit is empty, the server takes a working vacation (WV) and operates at a reduced service rate. If there are customers in the queue at the service completion, the server is resumed to a regular busy period (or) it remains on working vacation. When the server finishes serving a customer, the server finds the system empty; the server enters the N-policy vacation (the dormant period) until N customers accumulated. If the server finds no customer in the orbit, it enters the idle period. The steady-state generating functions for the system and its orbit have been obtained by applying the Supplementary Variable Technique (SVT). The system performance measurements, the mean system length and the mean waiting time of the system are obtained. [ABSTRACT FROM AUTHOR]

In this paper, a SIRI(Susceptible-Infected-Recovered-Infected) model is framed using the concept of retrial queues. The proposed model is analysed through queueing theory techniques. The SIRI epidemic model is formulated on an individual level. The stability of the proposed epidemic model is checked and the stationary distribution, generating function, explicit and recursive formulae of the proposed model is derived. The stability condition of the proposed model and the modified model are derived. The proposed SIRI(Susceptible-Infected-Recovered-Infected) model is modified with quarantine technique and analysed. The proposed SIRI model and a traditional SIRI model are simulated using Simulink and MATLAB respectively. The numerical simulations suggest that the proposed SIRI model is efficient in predicting the disease spread. [ABSTRACT FROM AUTHOR]

In this paper, a SIRI(Susceptible-Infected-Recovered-Infected) model is framed using the concept of retrial queues. The proposed model is analysed through queueing theory techniques. The SIRI epidemic model is formulated on an individual level. The stability of the proposed epidemic model is checked and the stationary distribution, generating function, explicit and recursive formulae of the proposed model is derived. The stability condition of the proposed model and the modified model are derived. The proposed SIRI(Susceptible-Infected-Recovered-Infected) model is modified with quarantine technique and analysed. The proposed SIRI model and a traditional SIRI model are simulated using Simulink and MATLAB respectively. The numerical simulations suggest that the proposed SIRI model is efficient in predicting the disease spread. [ABSTRACT FROM AUTHOR]