Thin films Tin sulfide SnS pure and doped with different ratios of Cu (X=0, 0.01, 0.03 and 0.05) were prepared using thermal evaporation with a vacuum of 4*10^-6mbar on two types of substrates n-type Si and glass with (500) nm thickness for solar cell application. X-ray diffraction and AFM analysis were carried out to explain the influence of Cu ratio dopant on structural and morphological properties respectively. SnS phase appeared forming orthorhombic structure with preferred orientation (111), increase the crystallinity degree and surface roughness with increase Cu ratio. UV/Visible measurement revealed the decrease in energy gap from 1.9eV for pure SnS to 1.5 for SnS: Cu (0.05) making these samples suitable f

the power of the federal supreme court to stop the implementation of the law

 In the current study, the definition of mapping of fuzzy neutrosophic generalized semi-continuous and fuzzy neutrosophic alpha has generalized mapping as continuous. The study confirmed some theorems regarding such a concept. In the following, it has been found relationships among fuzzy neutrosophic alpha generalized mapping as continuous, fuzzy neutrosophic mapping as continuous, fuzzy neutrosophic alpha mapping as continuous, fuzzy neutrosophic generalized semi mapping as continuous, fuzzy neutrosophic pre mapping as continuous and fuzzy neutrosophic γ mapping as continuous.

The present study has conducted to investigate the effect of hot aqueous extract of seeds and leaves of fenugreek (Trigonella foenum-graecum) on embryonic development in Swiss albino mice morphologically , the results is showed throught dosage pregnant female orally after period 4, 8, 12days at the beginning of pregnancy by doses 100 , 200 , 300 mg/kg of body weight , the results showed normal period of pregnancy 21 days and abortion did not occur when the pregnant mice take the hot aqueous extract of leaves of fenugreek, but the pregnant mice that take the hot aqueous extract of seeds of fenugreek occurred abortion of embryos and showed some histopathological changes in ovaries and uterus such as congestion, hemorrhage, necrosis, odema,

The importance of operational risks increases with the increase in technological development, the development of banking operations, the extent of banking compliance, and the attempt of many banks to achieve quality in banking services. And the extent of the position occupied by Iraqi banks for banking compliance and reducing operational risks. The Basel Committee (2) paid its attention to operational risks and the interest of international banks to follow policies that work to ensure banking compliance and cover operational risks, because of its role in reducing losses due to increased costs and achieving an increase in profits. Realizing and working to confront the best possible and traditional methods, that some risks Operational problem

Sorting and grading agricultural crops using manual sorting is a cumbersome and arduous process, in addition to the high costs and increased labor, as well as the low quality of sorting and grading compared to automatic sorting. the importance of deep learning, which includes the artificial neural network in prediction, also shows the importance of automated sorting in terms of efficiency, quality, and accuracy of sorting and grading. artificial neural network in predicting values and choosing what is good and suitable for agricultural crops, especially local lemons.

The Machine learning methods, which are one of the most important branches of promising artificial intelligence, have great importance in all sciences such as engineering, medical, and also recently involved widely in statistical sciences and its various branches, including analysis of survival, as it can be considered a new branch used to estimate the survival and was parallel with parametric, nonparametric and semi-parametric methods that are widely used to estimate survival in statistical research. In this paper, the estimate of survival based on medical images of patients with breast cancer who receive their treatment in Iraqi hospitals was discussed. Three algorithms for feature extraction were explained: The first principal compone

Some of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems.  Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic.  Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance.  In this study, two different sets of select