The aim of this paper is adopted to give an approximate solution for advection dispersion equation of time fractional order derivative by using the Chebyshev wavelets-Galerkin Method . The Chebyshev wavelet and Galerkin method properties are presented. This technique is used to convert the problem into the solution of linear algebraic equations. The fractional derivatives are described based on the Caputo sense. Illustrative examples are included to demonstrate the validity and applicability of the proposed technique.

Segmented regression consists of several sections separated by different points of membership, showing the heterogeneity arising from the process of separating the segments within the research sample. This research is concerned with estimating the location of the change point between segments and estimating model parameters, and proposing a robust estimation method and compare it with some other methods that used in the segmented regression. One of the traditional methods (Muggeo method) has been used to find the maximum likelihood estimator in an iterative approach for the model and the change point as well. Moreover, a robust estimation method (IRW method) has used which depends on the use of the robust M-estimator technique in

The telescope works to magnify images of distant objects in general, but it needs special optical elements to complete the task to the fullest. The telescope needs optimal balance values of the optical parameters used to produce the best image, such as the effective focal length and the diameter of the pupil aperture, which are combined in a single concept called the focal number. The ground-based binary telescope relies on special lenses and an exceptional prism to achieve a hybrid design that produces clear images of relatively distant terrestrial objects. The pupil diameter of the telescope is relatively large to ensure that the largest possible amount of light is received, and as a result, a good image is obtained.

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Computations of the relative permeability curves were made through their representation by two functions for wetting and nonwetting phases. Each function contains one parameter that controls the shape of the relative permeability curves. The values of these parameters are chosen to minimize an objective function, that is represented as a weighted sum of the squared differences between experimentally measured data and the corresponding data calculated by a mathematical model simulating the experiment. These data comprise the pressure drop across core samples and the recovery response of the displacing phase. Two mathematical models are constructed in this study to simulate incompressible, one-dimensional, two-phase flow. The first model d

Two-dimensional unsteady mixed convection in a porous cavity with heated bottom wall is numerically studied in the present paper. The forced flow conditions are imposed by providing a hydrostatic pressure head at the inlet port that is located at the bottom of one of the vertical side walls and an open vent at the top of the other vertical side wall. The Darcy model is adopted to model the fluid flow in the porous medium and the combination effects of hydrostatic pressure head and the heat flux quantity parameters are carefully investigated. These governing parameters are varied over wide ranges and their effect on the heat transfer characteristics is studied in detail. It is found that the time required to reach a desired temperature at th

Producing pseudo-random numbers (PRN) with high performance is one of the important issues that attract many researchers today. This paper suggests pseudo-random number generator models that integrate Hopfield Neural Network (HNN) with fuzzy logic system to improve the randomness of the Hopfield Pseudo-random generator. The fuzzy logic system has been introduced to control the update of HNN parameters. The proposed model is compared with three state-ofthe-art baselines the results analysis using National Institute of Standards and Technology (NIST) statistical test and ENT test shows that the projected model is statistically significant in comparison to the baselines and this demonstrates the competency of neuro-fuzzy based model to produce

Diabetes mellitus (DM) is a metabolic and hormonal disorder in which the body does not produce sufficient or respond ordinarily to insulin, leading to an increase in blood sugar (glucose) levels. This disordered has many side effects on body health, one of them being oral health. This study aimed to find these effects on several oral immune parameters included (IL6, CRP, and alpha-amylase) and the possible use of these parameters in the prediction of oral health and further risk sequel. A total of 91 specimens including 51 DM patients and 40 apparently healthy individuals were enrolled in this study which was carried out from November/2021 to February/2022. The results revealed that, abnormal increase of both IL6 and CRP in the saliva of