The main purpose of the work is to analyse studies of themagnetohydrodynamic “MHD” flow for a fluid of generalized Burgers’ “GB” within an annular pipe submitted under impulsive pressure “IP” gradient. Closed form expressions for the velocity profile, impulsive pressure gradient have been taken by performing the finite Hankel transform “FHT” and Laplace transform “LT” of the successive fraction derivatives. As a result, many figures are planned to exhibit the effects of (different fractional parameters “DFP”, relaxation and retardation times, material parameter for the Burger’s fluid) on the profile of velocity of flows. Furthermore, these figures are compared the flow without MHD.
Prediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bay
... Show MoreTransforming the common normal distribution through the generated Kummer Beta model to the Kummer Beta Generalized Normal Distribution (KBGND) had been achieved. Then, estimating the distribution parameters and hazard function using the MLE method, and improving these estimations by employing the genetic algorithm. Simulation is used by assuming a number of models and different sample sizes. The main finding was that the common maximum likelihood (MLE) method is the best in estimating the parameters of the Kummer Beta Generalized Normal Distribution (KBGND) compared to the common maximum likelihood according to Mean Squares Error (MSE) and Mean squares Error Integral (IMSE) criteria in estimating the hazard function. While the pr
... Show MoreIn this paper has been one study of autoregressive generalized conditional heteroscedasticity models existence of the seasonal component, for the purpose applied to the daily financial data at high frequency is characterized by Heteroscedasticity seasonal conditional, it has been depending on Multiplicative seasonal Generalized Autoregressive Conditional Heteroscedastic Models Which is symbolized by the Acronym (SGARCH) , which has proven effective expression of seasonal phenomenon as opposed to the usual GARCH models. The summarizing of the research work studying the daily data for the price of the dinar exchange rate against the dollar, has been used autocorrelation function to detect seasonal first, then was diagnosed wi
... Show MoreIn this paper,the homtopy perturbation method (HPM) was applied to obtain the approximate solutions of the fractional order integro-differential equations . The fractional order derivatives and fractional order integral are described in the Caputo and Riemann-Liouville sense respectively. We can easily obtain the solution from convergent the infinite series of HPM . A theorem for convergence and error estimates of the HPM for solving fractional order integro-differential equations was given. Moreover, numerical results show that our theoretical analysis are accurate and the HPM can be considered as a powerful method for solving fractional order integro-diffrential equations.
... Show MoreThe survival analysis is one of the modern methods of analysis that is based on the fact that the dependent variable represents time until the event concerned in the study. There are many survival models that deal with the impact of explanatory factors on the likelihood of survival, including the models proposed by the world, David Cox, one of the most important and common models of survival, where it consists of two functions, one of which is a parametric function that does not depend on the survival time and the other a nonparametric function that depends on times of survival, which the Cox model is defined as a semi parametric model, The set of parametric models that depend on the time-to-event distribution parameters such as
... Show MoreThe study was conducted to e'aluate the effect of Myrrh essential oil on growth of three isolates of Candida albicans. Results
.showed inhlbitory effect of Myrrh essential o.il on growth of the teste<:!
isolates. MTC tor vaginal and nail .isolates· was 5% where is for the standard isolate it w I 0%. AdditionaUy, Es ential oil affect morphology types of Candida albiccms cells, .resuJting double increase in pseu.dohyphae percentage and double decrease in budding cell percentage .compared to the control types which may indicate JYossible
e£fect on division and reproduction.
Activity of essential oil of Myrrh using gaseous contact
method showed .inhibitory effect of the ojl for the hree isolates. with
MIC more than