Some researchers are interested in using the flexible and applicable properties of quadratic functions as activation functions for FNNs. We study the essential approximation rate of any Lebesgue-integrable monotone function by a neural network of quadratic activation functions. The simultaneous degree of essential approximation is also studied. Both estimates are proved to be within the second order of modulus of smoothness.

Technological development in recent years leads to increase the access speed in the networks that allow a huge number of users watching videos online. Video streaming is one of the most popular applications in networking systems. Quality of Experience (QoE) measurement for transmitted video streaming may deal with data transmission problems such as packet loss and delay. This may affect video quality and leads to time consuming. We have developed an objective video quality measurement algorithm that uses different features, which affect video quality. The proposed algorithm has been estimated the subjective video quality with suitable accuracy. In this work, a video QoE estimation metric for video strea

The water vapor is one of the constituent elements of the rain and the superiority
of its importance in the study of climate because it is the basis on which depends all
the different aspects of condensation. The purpose of research is to analyze the time
series of the Baghdad station andan analyze these series to see whether there is a
relationship between these two variables. Obtained the data used in this research
from the National Center for Environmental Prediction for the period from 1948 to
2011. The use of statistical criteria included linear regression and Mann Kandal test
to find the link. The results of time series monthly presence decrease in rainfall and
all months except October, either the results o

     The superconductor compound (YBa2Cu2.8Zn0.2O7+δ) is prepared by solid state reaction (SSR), Sol-gel (SG) and laser Pulse deposition (PLD) methods. We used the X-ray diffraction technique, which shows an orthorhombic crystalline system for all the samples, and increase in the high-phase (Y-123) and decrease in low-phase and vary in proportion according to the method of preparation with the emergence of some impurities. The behavior of the samples in terms of electrical resistance and critical temperature was investigated all samples showed superconducting behavior. The properties of the dielectric (real dielectric constant, imaginary dielectric constant, loss tangent, alternating electrical conductivity) were s

In 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.

In this paper, we used maximum likelihood method and the Bayesian method to estimate the shape parameter (θ), and reliability function (R(t)) of the Kumaraswamy distribution with two parameters l , θ (under assuming the exponential distribution, Chi-squared distribution and Erlang-2 type distribution as prior distributions), in addition to that we used method of moments for estimating the parameters of the prior distributions. Bayes

In this study, we used Bayesian method to estimate scale parameter for the normal distribution. By considering three different prior distributions such as the square root inverted gamma (SRIG) distribution and the non-informative prior distribution and the natural conjugate family of priors. The Bayesian estimation based on squared error loss function, and compared it with the classical estimation methods to estimate the scale parameter for the normal distribution, such as the maximum likelihood estimation and th