Abstract 

For sparse system identification,recent suggested algorithms are  -norm Least Mean Square (  -LMS), Zero-Attracting LMS (ZA-LMS), Reweighted Zero-Attracting LMS (RZA-LMS), and p-norm LMS (p-LMS) algorithms, that have modified the cost function of the conventional LMS algorithm by adding a constraint of coefficients sparsity. And so, the proposed algorithms are named  -ZA-LMS, 

In this article, the high accuracy and effectiveness of forecasting global gold prices are verified using a hybrid machine learning algorithm incorporating an Adaptive Neuro-Fuzzy Inference System (ANFIS) model with Particle Swarm Optimization (PSO) and Gray Wolf Optimizer (GWO). The hybrid approach had successes that enabled it to be a good strategy for practical use. The ARIMA-ANFIS hybrid methodology was used to forecast global gold prices. The ARIMA model is implemented on real data, and then its nonlinear residuals are predicted by ANFIS, ANFIS-PSO, and ANFIS-GWO. The results indicate that hybrid models improve the accuracy of single ARIMA and ANFIS models in forecasting. Finally, a comparison was made between the hybrid foreca

In 2020 one of the researchers in this paper, in his first research, tried to find out the Modified Weighted Pareto Distribution of Type I by using the Azzalini method for weighted distributions, which contain three parameters, two of them for scale while the third for shape.This research compared the distribution with two other distributions from the same family; the Standard Pareto Distribution of Type I and the Generalized Pareto Distribution by using the Maximum likelihood estimator which was derived by the researchers for Modified Weighted Pareto Distribution of Type I, then the Mont Carlo method was used–that is one of the simulation manners for generating random samples data in different sizes ( n= 10,30,50), and in di

Preparation of epoxy/MgO and epoxy/SiO2 nanocomposites is
studding. The nano composites were processed by different nano
fillers concentrations (0, 0.01, 0.02, 0.03, 0.04, 0.05, 0.07 and
0.1 wt%). Epoxy resin and nanocomposites containing different
shape nano fillers of (MgO:SiO2 composites), are shear mixing with
ratio 1:1,with different nano hybrid fillers concentrations (0.025,
0.05, 0.1, 0.15, 0.2 and 0.25 wt%) to preparation of epoxy/(MgOSiO2)
hybrid nanocomposites. Experimental tests results indicate that
the composite materials have significantly higher modulus of
elasticity than the matrix material but the hybrid nanocomposites
have lower modulus of elasticity. The wear rate was decreased in
nanoc

The current research aims to determine the impact of the cognitive reconstruction program on the development of psychological hardness among middle school students through the experimental verification of three hypotheses. The research sample consisted of (16) out of (450) students selected from Ibn Rushud preparatory school- Al-Rusafa 2. These participants have been randomly distributed into two equal groups. The researcher has used the method of cognitive reconstruction with the experimental group, whereas with the controlling group, he used nothing. The researcher has further used the scale of psychological hardness of Kobassa with the participants; the scale has been built in a way that suits the sample of the study, which consisted