In this paper, a self-tuning adaptive neural controller strategy for unknown nonlinear system is presented. The system considered is described by an unknown NARMA-L2 model and a feedforward neural network is used to learn the model with two stages. The first stage is learned off-line with two configuration serial-parallel model & parallel model to ensure that model output is equal to actual output of the system & to find the jacobain of the system. Which appears to be of critical importance parameter as it is used for the feedback controller and the second stage is learned on-line to modify the weights of the model in order to control the variable parameters that will occur to the system. A back propagation neural network is appl

Consistent "with the thought of tax talk is unified tax natural evolution for him, as the application leads to the inclusion of tax all branches of income and its sources and through truncated part of this entry through the application of price ascending it, it means the procedures of tax reform. Taxes on total income characterized by giving a clear picture of the total income of the taxpayer and its financial situation and its burden family which allows granting exemptions, downloads, and application of prices that fit this case. This requires reconsideration of the structure of the tax system in force and the transition from a system specific taxes to the tax system on the total income of the integration of income from the rental of re

Despite efforts to contain and manage the SARS-CoV-2 outbreak which was declared a public health emergency of international concern in January 2020 by the World Health Organization (WHO), the COVID-19 pandemic still remains a major global challenge. Patients who display the classical symptoms of the infection are easily identified, tested, isolated and monitored. However, many cases of infected asymptomatic patients have been documented. These patients are not easily identified even though many evidences suggest that they can spread the virus to others. How and why these COVID-19 asymptomatic presentations occur remain unclear. The many theories and views are conjectural, and supporting evidences are still needed. In this review, we

Biomedical alloy 316L stainless steel enhancing to replace biological tissue or to help stabilize a biological structure, such as bone tissue, enhancing were coated with deposition a thin layer of silver nanoparticles as anti-bacterial materials by using DC- magnetron sputtering device. The morphology surface of The growth nanostructure under the influence of different working pressure were studied by atomic force microscope. The average grain size decrease but roughness of the silver thin layer was increased with‖ ―increasing the working pressure. The thickness of silver thin layer was increased from 107 nm at 0.08 mbar to 126 nm at 1.1 mbar. Antimicrobial activity of silver thin layers at different working pressure were studied. Th

Nowadays, the mobile communication networks have become a consistent part of our everyday life by transforming huge amount of data through communicating devices, that leads to new challenges. According to the Cisco Networking Index, more than 29.3 billion networked devices will be connected to the network during the year 2023. It is obvious that the existing infrastructures in current networks will not be able to support all the generated data due to the bandwidth limits, processing and transmission overhead. To cope with these issues, future mobile communication networks must achieve high requirements to reduce the amount of transferred data, decrease latency and computation costs. One of the essential challenging tasks in this subject

The preparation and characterization of innovative nanocomposites based on zinc oxide nanorods (ZNR) encapsulated by graphene (Gr) nanosheets and decorated with silver (Ag), and cupper (Cu) nanoparticles (NP) were studied. The prepared nanocomposites (ZNR@Gr/Cu-Ag) were examined by different techniques including Field Emission Scanning Electron Microscope (FESEM), Transmission electron microscopy (TEM), Atomic force microscopy (AFM), UV-Vis spectrophotometer and fluorescence spectroscopy. The results showed that the ZNR has been good cover by five layers of graphene and decorated with Ag and Cu NPs with particles size of about 10-15 nm. The ZNR@Gr/Cu-Ag nanocomposites exhibit high absorption behavior in ultraviolet (UV) region of sp

(( The Basic word and Terms of sports, games and motions in the Holy Quran : semantic
study )).
The research consists of apreface followed by an Introduction , and three sections and
aconclusion, finally the research concluded with a list of the sources . and also alist of terms
and word in English language for a wider use .
As for reach sections, they are section one it covers a group of words sports games that
are forty two words .
Section two : it covers five fields :-
a- A group of words ( sports ruless) that an seventeen words.
b- A group of ( sports montions ) that are ten .
c- A group of ( sports tools ) that are seven words.
d- A group of ( sports sciences ) that are seven words only .
e- A gro

Nonlinear time series analysis is one of the most complex problems ; especially the nonlinear autoregressive with exogenous variable (NARX) .Then ; the problem of model identification and the correct orders determination considered the most important problem in the analysis of time series . In this paper , we proposed splines  estimation method for model identification , then we used three criterions for the correct orders determination. Where ; proposed method used to estimate the additive splines for model identification , And the rank determination depends on the additive property  to avoid the problem of curse dimensionally . The proposed method is one of the nonparametric methods , and the simulation results give a

Magnetic  Resonance  Imaging  (MRI)  is  one  of  the  most important diagnostic tool. There are many methods to segment the

tumor of human brain. One of these, the conventional method that uses pure image processing techniques that are not preferred because they need human interaction for accurate segmentation. But unsupervised methods do not require any human interference and can segment   the   brain   with   high   precision.   In   this   project,   the unsupervised  classification methods have been used in order to detect the tumor  disease from MRI images.    These metho

Pavement crack and pothole identification are important tasks in transportation maintenance and road safety. This study offers a novel technique for automatic asphalt pavement crack and pothole detection which is based on image processing. Different types of cracks (transverse, longitudinal, alligator-type, and potholes) can be identified with such techniques. The goal of this research is to evaluate road surface damage by extracting cracks and potholes, categorizing them from images and videos, and comparing the manual and the automated methods. The proposed method was tested on 50 images. The results obtained from image processing showed that the proposed method can detect cracks and potholes and identify their severity levels wit