In this work, the spectra for plasma glow produced by pulse
Nd:YAG laser (λ=532 and 1064nm) on Ag:Al alloy with same molar
ratio samples in distilled water were analyzed by studying the atomic
lines compared with aluminum and silver strong standard lines. The
effect of laser energies of the range 300 to 800 mJ on spectral lines,
produced by laser ablation, were investigated using optical
spectroscopy. The electron temperature was found to be increased
from 1.698 to 1.899 eV, while the electron density decreased from
2.247×1015 to 5.08×1014 cm-3 with increasing laser energy from 300
to 800 mJ with wavelength of 1064 nm. The values of electron
temperature using second harmonic frequency are greater than of<

This paper aims to deal with the understanding of the properties of the molecular gas hydrogen in the extragalactic spirals sample. It is critical to make observations of CO (J = 1-0) line emission for spiral galaxies, particularly those with an energetic nucleus.  In the sample of spiral galaxies compiled, a carbon monoxide CO (1-0) emission line can be observed. This sample of galaxies' gas kinematics and star-forming should be analyzed statistically utilizing appropriate atomic gas HI, molecular gas H2, infrared (1μm-1000μm), visual (at λblue-optical=4400A0), and radio spectrum (at νradio=1.4 GHz and 5GHz) databases. STATISTICA is software that allows us to perform this statistical analysis. The presence of a high scale of s

In this work, silver nanoparticles (AgNPs) were biosynthesized from leaves of Ziziphus mauritiana Lam. jujube plant in Iraq and tested against fungal pathogens. Extract of leaves of Z. mauritiana mixed with 10-3 M AgNO3exposed to slight sunlight for 3 days. Characterization of AgNPs was done using UV-visible spectroscopy, SPM (scanning probe microscopy) and atomic force microscopy (AFM). The change of solution color from pale brown to dark brown and the exhibited maximum peak at 445 nm accepted as an indicator to biosynthesized AgNPs. Aqueous extract of Ziziphus mauritiana is considered as biological reduced and stabilized agent for Ag+ to Ag0. AFM showed the formation of irregular shapes of AgNPs. The biosynthesized silver nanoparticles ha

In this research, we studied the multiple linear regression models for two variables in the presence of the autocorrelation problem for the error term observations and when the error is distributed with general logistic distribution. The auto regression model is involved in the studying and analyzing of the relationship between the variables, and through this relationship, the forecasting is completed with the variables as values. A simulation technique is used for comparison methods depending

In this research, we studied the multiple linear regression models for two variables in the presence of the autocorrelation problem for the error term observations and when the error is distributed with general logistic distribution. The auto regression model is involved in the studying and analyzing of the relationship between the variables, and through this relationship, the forecasting is completed with the variables as values. A simulation technique is used for comparison methods depending on the mean square error criteria in where the estimation methods that were used are (Generalized Least Squares, M Robust, and Laplace), and for different sizes of samples (20, 40, 60, 80, 100, 120). The M robust method is demonstrated the best metho

In this paper we estimate the coefficients and scale parameter in linear regression model depending on the residuals are of type 1 of extreme  value distribution for the largest values . This can be regard as an improvement for the studies with the smallest values . We study two estimation methods ( OLS  & MLE ) where we resort to Newton – Raphson (NR) and Fisher Scoring methods to get MLE estimate because the difficulty of using the usual approach with MLE . The relative efficiency criterion is considered beside to the statistical inference procedures for the extreme value regression model of type 1 for largest values . Confidence interval , hypothesis testing for both scale parameter and regression coefficients

The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet

Actinomycetes are free, spore-forming, high (G+C) ratio (>55%) saprophytic microorganisms that are widely distributed in most soils, colonize plants, and are prevalent in water. This is frequently accompanied by the production of filament airborne mycelium. Actinomycetes are well-known microcolonies for creating antibiotics and other critical bioactive components that are beneficial to humans. Approximately 70% to 80% of commercially available medications and antiviral active compounds have been synthesized so far. Secondary metabolites produced by microbes have the potential to be used in a variety of sectors, including antimicrobial agents, enzyme technology, pigment manufacture, antitumor agents against cancer cells, and toxin pr