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Multiple coating assessments of fiber optics utilizing micropolar convection non-Newtonian third-order liquid in the existence of Hall effect are examined and executed throughout this academic article. The wet-on-wet (WOW) coating process is used in the research. The fourth Runge–Kutta–Fehlberg algorithm is used to computationally solve the governing equations which dictate the movement of fluid inside the container. In this research, the RK4-Fehlberg algorithm is applied to get numerical results for a list of nonlinear ordinary differential equations (ODEs) describing liquid motion. Pictorially, the contribution of regulating variables on velocity and temperature profiles is examined. It is observed that the velocity profile enhances as the viscoelastic parameter increases and the velocity profile increases for both the non-Newtonian and Hall current increasing parameters in the presence and absence of magnetic parameter M. It is observed that the velocity of the fluid decreases with the increasing values of the Hartmann number m, Brinkman number Br, and magnetic parameter M. Furthermore, the temperature profile increase for BrBr, K, M, and opposite effect is observed for β\beta increases. The suggested approach is compared to homotopy analysis method (HAM) for verification purpose, and excellent agreement is obtained. In addition, as a restricted scenario, a connection is made with the existing literature.

In this study, we proposed a new model to improve the accuracy of forecasting the stock market volatility pattern. The hypothesized model was validated empirically using a data set collected from the Saudi Arabia stock Exchange (Tadawul). The data is the daily closed price index data from August 2011 to December 2019 with 2027 observations. The proposed forecasting model combines the best maximum overlapping discrete wavelet transform (MODWT) function (Bl14) and exponential generalized autoregressive conditional heteroscedasticity (EGARCH) model. The results show the model's ability to analyze stock market data, highlight important events that contain the most volatile data, and improve forecast accuracy. The results were compared from a number of mathematical models, which are the non-linear spectral model, autoregressive integrated moving average (ARIMA) model and EGARCH model. The performance of the forecasting model will be evaluated based on some of error functions such as Mean absolute percentage error (MAPE), Mean absolute scaled error (MASE) and Root means squared error (RMSE). [ABSTRACT FROM AUTHOR]

In this work, we studied the impacts of transmitting light, nonlinear thermal, and micropolar fluid mechanics on a wire surface coating utilizing non-Newtonian viscoelastic flow. Models with temperature-dependent variable viscosity were used. The boundary layer equations governing the flow and heat transport processes were solved using the Runge–Kutta fourth order method. A distinguished constituent of this study was the use of a porous matrix that acted as an insulator to reduce heat loss. In this paper we discuss the effects of numerous development parameters, including β 0 , Q ,   m ,   Ω ,   K p , and B r (non-Newtonian parameter, heat-producing parameter, viscosity parameter, variable viscosity parameter, porosity parameter, and Brinkman number, respectively). Furthermore, the effects of two other parameters, D and M, are also discussed as they relate to velocity and temperature distributions. We observed that the velocity profiles decreased with increasing values of K p . Fluid velocity increased as the values of M ,   B r ,   N , and D increased, while it decreased when the values of K p , Q and D increased. For increasing values of M , the temperature profile showed increasing behavior, while B r   and   Q showed decreasing behavior. Furthermore, the present work is validated by comparison with HAM and previously published work, with good results. [ABSTRACT FROM AUTHOR]