This article presents and  explores the theoretical aspect in the use of Arab Islamic theme by the western writers to obtain and achieve individual motives. In this study the model for the theory of Arab presence in Andalusia  , through the book entitled “ Alhamra” by the English writer Washington Erving ,was  analyzed.

The most important results in this research: the success of  the author in the employment of the Islamic history in the formation of the first American legend, Columbus legend, through the selection of the right thoughts to establish his American National theory.  The author compared between the Andalusia experience and the Arab occupation to Spain and the American conquest of the new

Dielectric measurements were carried on pure and doping potassium sulfate with copper and iron ions samples at 1wt.% and 3wt.% for both of copper and iron. The dielectric constant (ε') decreases exponentially from 2.8 to 1.5 as frequency increase for both dopant which is attributed to the space charge and structural distortion. The dielectric loss (ε") for Cu dopant decrease gradually with frequency. The same behavior for 1%Fe dopant while its 3%Fe doping started from 0.27 then decrease exponential. Band gaps for all samples almost constant around 6 eV.

This work aims to study the exploding copper wire plasma parameters by optical emission spectroscopy. The emission spectra of the copper plasma have been recorded and analyzed The plasma electron temperature (Te), was calculated by Boltzmann plot, and the electron density (ne) calculated by using Stark broadening method for different copper wire diameter (0.18, 0.24 and 0.3 mm) and current
of 75A in distilled water. The hydrogen (Hα line) 656.279 nm was used to calculate the electron density for different wire diameters by Stark broadening. It was found that the electron density ne decrease from 22.4×1016 cm-3 to 17×1016 cm-3 with increasing wire diameter from 0.18 mm to 0.3 mm while the electron temperatures increase from 0.741 to

Wireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two s

  The Dopping effect by methyl orange ( )on optical constants [Refractive index (n), extinction coefficient(K0),real and imaginary parts of dielectric constant(εr &εi)] of poly methyl methacrylat (PMMA)  that additive to this polymer with both percentages 2% and 4% at thickness(145)µm have been studied. This study has been done by recording the absorption and transmission spectra in the wavelength range (200-900)nm . The results  showed that all  optical parameters are increased by increasing dopping rate except the transmission was decreased.
 
 

The aim of the study is to detect the malignant conditions of the skin tumors through the features of optical images. This research included some of image processing techniques to detect skin cancer as a strong threat to human beings' lives. Using image processing and analysis methods to improves the ability of pathologists to detect this disease leading to more specified diagnosis and better treatment of them. One hundred images were collected from Benign and Malignant tumors and some appropriate image features were calculated, like Maximum Probability, Entropy, Coefficient of Variation, Homogeneity and Contrast, and using Minimum Distance method to separate these images. These features with Minimum Distance as a proposed making decision a

Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo