Preparation of superposed thin film (CdTe)1-xSex / ZnS) with concentration of (x= 0.1, 0.3, 0.5) at a temperature of substrate (Ts= 80 0C) by using Thermal Vacuum Evaporation System. The measurement of X-ray diffraction shows that the compounds CdTe, ZnS, (CdTe)1-xSex and (CdTe)1-xSex / ZnS have a polycrystalline structure, the C-V characteristic shows that the capacitance degrease by increasing the concentration (x) in reverse bias, while the I-V characteristic shows the current dark (Id) increase in forward and reverse bias by increasing (x) and the photocurrent (Iph) increase in reverse bias by increasing the concentration (x), the values of photocurrent are greater than from the values of the dark current for all concentrations

In Iraq, the risk of soil pollution by petroleum products increases with the growth of oil exploration, production and shipping large quantities of oil through pipelines over thousands of kilometers. Numerous oil spills have been documented recently in many sites due to damage in the oil industry infrastructures, which have led to soil contamination causing serious environmental hazards and deterioration to the soil and its engineering properties. So, it is essential to investigate the impact of oil leakage through the soil stratum consequently, assessing the eligibility of the contaminated soil for construction projects or identifying the appropriate treatment method. The paper investigates the general behaviour and the associated variatio

In this study the thermal conductivity of the epoxy composites were characterized as function of volume fraction, particle size of fillers and the time of immersion(30,60,90)days in water .Composites plates were prepared by incorporating (bi-directional) (0º-90º) glass fiber and silicon carbide (SiC) particles of (0.1,0.5,1)mm as particle size at (10%,20%,30%,40%) percent volume in epoxy matrix.
The composites shows slightly increase of the thermal conductivity with increasing volume fraction, particle size and increase with increasing the days of immersion in water. The maximum thermal conductivity (0.51W/m.K) was obtained before the immersion in water at 90 days for epoxy reinforcement by bi-directional glass fiber and SiC particl

The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow

Abstract

Semiconductor-based gas sensors were prepared, that use n-type tin oxide (SnO₂) and  tin oxide: zinc oxide composite (SnO₂)_1-x(ZnO)_x at different x ratios using pulse laser deposition at room temperature. The prepared thin films were examined to reach the optimum conditions for gas sensing applications, namely X-ray diffraction, Hall effect measurements, and direct current conductivity. It was found that the optimum crystallinity and maximum electron density, corresponding to the minimum charge carrier mobility, appeared at 10% ZnO ratio. This ratio appeared has the optimum NO₂ gas sensitivity for 5% gas concentration at 300 °C working temperat