The buildup factor of cylindrical samples (shields) for Brass, Copper & lead (Brass, Cu, Pb (was studied, where buildup factor were calculated with thickness between (0-12) m.f.p. for Co60 and Cs137sources with activities (30) & (41) MBq respectively , using scintillation detector NaI(T?) with (3"×3")volume .The results shows increases of buildup factor for low atomic number(Z) samples where the energy of radiation source was constant, also shows increases of buildup factor with decreases the energy of radiation source. An empirical equation was obtained using Matlab7 program this equation have agreements with most obtained data for 96%.

􀀑􀀃Pure Cu (CZTSe) and Ag dopant CZTSe (CAZTSe) thin films with Ag content of 0.1 and 0.2 were fabricated on coring glass substrate at R.T with thickness of 800nm by thermal evaporation method. Comparison between the optical characteristics of pure Cu and Ag alloying thin films was done by measuring and analyzing the absorbance and transmittance spectra in the range of (400-1100)nm. Also, the effect of annealing temperature at 373K and 473K on these characteristics was studied. The results indicated that all films had high absorbance and low transmittance in visible region, and the direct bang gap of films decreases with increasing Ag content and annealing temperature. Optical parameters like extinction coefficientrefractive index, and

A novel metal complexes Cu (II), Co (II), Cd (II), Ru (III) from azo ligand 5-((2-(1H-indol-2-yl)
ethyl) diazinyl)-2-aminophenol were synthesized by simple substitution of tryptamine with 2-aminophenol.
Structures of all the newly synthesized compounds were characterized by FT IR, UV-Vis, Mass spectroscopy
and elemental analysis. In addition measurements of magnetic moments, molar conductance and atomic
absorption. Then study their thermal stability by using TGA and DSC curves. The DCS curve was used to
calculate the thermodynamic parameters ΔH, ΔS and Δ G. Analytical information showed that all complexes
achieve a metal:ligand ratio of [1:1]. In all complex examinations, the Ligand performs as a tri

Nanoferrite materials have been synthesized by sol-gel auto combustion method. The effect of doping different percentages of Y₂O₃ (0.34 µm) on the physical and mechanical properties of selected mixed ferrite [(Li_2.5Fe_0.5) 0.9(Co₄Fe₂O₄) _0.1] by adding 10% Cobalt ferrite was studied. Physical properties (i.e. .density, porosity and water absorption) were affected by the doping, where the density increased about 32% at 6 wt% Y₂O₃, while porosity has a drastically decreased about 80% at 6% Y₂O₃ and has a correlation effect on the mechanical properties(Splitting  tensile strength and Vicker

In this paper, an algorithm is suggested to train a single layer feedforward neural network to function as a heteroassociative memory. This algorithm enhances the ability of the memory to recall the stored patterns when partially described noisy inputs patterns are presented. The algorithm relies on adapting the standard delta rule by introducing new terms, first order term and second order term to it. Results show that the heteroassociative neural network trained with this algorithm perfectly recalls the desired stored pattern when 1.6% and 3.2% special partially described noisy inputs patterns are presented.

The rapid development of Internet of Things (IoT) devices and their increasing numbers have caused a tremendous increase in network traffic and a wider range of cyber-attacks. This growing trend has complicated the detection process for traditional intrusion detection systems and heightened the challenges faced by these devices, such as imbalanced and large training data. This study presents a cohesive methodology of a series of intelligent techniques to prepare clean and balanced data for training the first (core) layer of a robust hierarchical intrusion detection system. The methodology was built by cleaning and compressing the data using an Autoencoder and preparing a strong latent space for balancing using a hybrid method that combines

Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d

The objectives of this study revolve around identifying the extent of funding impact on the future of the printed Iraqi press, and whether it threatens their chances of survival, stating the extent of technological development on the income of the printed newspaper, and identifying the causes of the financial crisis on the newspaper.
This research is classified as descriptive research, and the researcher used the survey method, and adopted the questionnaire of the views of the contactors, in five Iraqi newspapers (morning - extent - time - the way of the people - the call).
The research community included (68) respondents, whereby the comprehensive inventory method was used to define the research community, and the researcher used

يحتل موضوع الاستهلاك اهمية كبيرة في الدراسات الاقتصادية في حالتي السلم والحرب وذلك لارتباط هذا الموضوع بالانسان والمجتمع ولكونه احد مؤشرات مستوى الرفاهية الاقتصادية والاجتماعية وتزداد اهمية ضبط حركة هذا المتغير السلوكي والكمي في زمن الحرب اكثر مما هو عليه في حالة السلم، في هذا البحث تم استخدام بيانات احصائية عن الانفاق الاستهلاكي الخاص ونصيب الفرد من الدخل القومي اضافة الى الرقم القياسي لاسعار المس