N-type Tin dioxide thin films with thickness (350 nm) prepared by thermal evaporation method. The thin film SnO2 was doped with Ag by the rate (0.01, 0.02 and 0.03). Atomic Force Microscopic (AFM) was adopted to determine the grain size and roughness of the film surface. The electrical properties were determined by mean of Hall Measurement system and mobility was calculated. SnO2: Ag/P–Si photodetectors demonstration the highest described visible responsivity of (0.287 A/W) with the Ag ratio of (0.03). I–V characteristics with different power density were measured. The best sensitive value of the spectral response, specific detectivity and quantum efficiency at wavelength (422 nm).

In this study, the effect of grafting with magnesium (Mg) ratios (0.1, 0.3, 0.5) on the structural and optical properties of cadmium oxide films (CdO) was studied, as these films were prepared on glass bases using the method of pulse laser deposition (PLD). The crystallization nature of the prepared membranes was examined by X-ray diffraction technique (XRD), which showed that the synthesis of the prepared membranes is polycrystalline, and (AFM) images also showed that the increased deformation with magnesium led to an increase in the grain size ratio and a decrease in surface roughness, as well as the absorption coefficient was calculated. And the optical energy gap for the prepared membranes, where it was found that the absorption coef

The thermal properties (thermal transfer and thermal expansion coefficient) of the enhanced epoxy resin (MWCNT / x-TiO₂) were studied by weight ratios with the values (0%, 3%, 5%, 7% and 10%) and a constant ratio of 3% of MWCNT. The ultrasonic technology was used to prepare the neat and composites which were then poured into Teflon molds according to standard conditions. Thermo-analyzer sensor technology was used to measure thermal transfer (thermal conductivity, thermal flow, thermal diffusion, thermal energy and heat resistance). The thermal conductivity, flow, and thermal conductivity values were increased sequentially by increasing the weight ratio of the filler while the results of stored energy values an

         Polymer blended electrolytes of various concentrations of undoped PAN/PMMA (80/20, 75/25, 70/30, 65/35 and 60/40 wt%) and doped with lithium salts (LiCl, Li₂SO₄H₂O, LiNO₃, Li₂CO₃) at 20% wt have been prepared by the solution casting method using dimethylformamide as a solvent. The electrical conductivity has been carried out using an LCR meter. The results showed that the highest ionic conductivity was 2.80x10^-7 (Ω.cm)^-1 and 1.05x10^-1 (Ω.cm)^-1 at 100 kHz frequency at room temperature for undoped (60% PAN + 40% PMMA) and (80% PAN + 20% PMMA) doped with 20%wt Li₂CO₃ composite blends, respect

<p>Combating the COVID-19 epidemic has emerged as one of the most promising healthcare the world's challenges have ever seen. COVID-19 cases must be accurately and quickly diagnosed to receive proper medical treatment and limit the pandemic. Imaging approaches for chest radiography have been proven in order to be more successful in detecting coronavirus than the (RT-PCR) approach. Transfer knowledge is more suited to categorize patterns in medical pictures since the number of available medical images is limited. This paper illustrates a convolutional neural network (CNN) and recurrent neural network (RNN) hybrid architecture for the diagnosis of COVID-19 from chest X-rays. The deep transfer methods used were VGG19, DenseNet121

With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  T