The influence of silver doped n-type polycrystalline CdTe film with thickness of 200 nm and rate deposition of 0.3 nm.s -1 prepared under high vacuum using thermal co-evaporation technique on its some structural and electrical properties was reported. The X- ray analysis showed that all samples are polycrystalline and have the cubic zinc blend structure with preferential orientation in the [111] direction. Films doping with impurity percentages (2, 3, and 4) %Ag lead to a significant increase in the carrier concentration, so it is found to change from 23.493 108 cm -3 to 59.297 108 cm -3 for pure and doped CdTe thin films with 4%Ag respectively. But films doping with impurity percentages above lead to a significant decrease in the electrica

 Indium doped CdTe polycrystalline films of thickness equals to 300nm were grown on corning glass substrates at temperature equals to 423K by thermal co-evaporation technique. The structural and electrical properties for these films were studied as a function of heat treatment (323,373,423)K. The x-ray analysis showed that all samples are polycrystalline and have the cubic zincblende structure with preferential orientation in the [111] direction, no diffraction peaks corresponding to metallic Cd, Te or other compounds were observed. It was found that the electrical resistivity drops and the carrier concentration increases when the CdTe film doped with 1.5% indium and treated at different annealing temperatures.

Design of experiments (DOE) was made by Minitab software for the study of three factors used in the precipitation process of the Sodium Aluminate solution prepared from digestion of α-Al₂O₃  to determine the optimum conditions to a produce Boehmite which is used in production of ɤ-Al₂O₃ during drying and calcination processes, the factors are; the temperature of the sodium aluminate solution, concentration of HCl acid added for the precipitation and the pH of the solution at which the precipitation was ended. The design of the experiments leads to 18 experiments.

   The results show that the optimum conditions for the precipitation of the sodium aluminate solution which

In this study, the ZnTe thin films were deposited on a glass substrate at a thickness of 400nm using vacuum evaporation technique (2×10^-5mbar) at RT. Electrical conductivity and Hall effect measurements have been investigated as a function of variation of the doping ratios (3,5,7%) of the Cu element on the thin ZnTe films. The temperature range of (25-200°C) is to record the electrical conductivity values. The results of the films have two types of transport mechanisms of free carriers with two values of activation energy (E_a1, E_a2), expect 3% Cu. The activation energy (E_a1) increased from 29meV to 157meV before and after doping (Cu at 5%) respectively. The results of Hal

   Chaotic features of nuclear energy spectrum in ⁶⁸Ge nucleus are investigated by nuclear shell model. The energies are calculated through doing shell model calculations employing the OXBASH computer code with effective interaction of F5PVH. The ⁶⁸Ge nucleus is supposed to have an inert core of ⁵⁶Ni with 12 nucleons (4 protons and 8 neutrons) move in the f5p-model space ( and ). The nuclear level density of considered classes of states is seen to have a Gaussian form, which is in accord with the prediction of other theoretical studies. The statistical fluctuations of the energy spectrum (the level spacing P(s) and the Dyson-Mehta (or statistics) are well described by the Gaussian orthogonal ens

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

The growth of developments in machine learning, the image processing methods along with availability of the medical imaging data are taking a big increase in the utilization of machine learning strategies in the medical area. The utilization of neural networks, mainly, in recent days, the convolutional neural networks (CNN), have powerful descriptors for computer added diagnosis systems. Even so, there are several issues when work with medical images in which many of medical images possess a low-quality noise-to-signal (NSR) ratio compared to scenes obtained with a digital camera, that generally qualified a confusingly low spatial resolution and tends to make the contrast between different tissues of body are very low and it difficult to co