alaa abdullah

In the present work nanocomposite thin films have been prepared from poly(vinyl alcohol) (PVA) mixed with carbon nanotube (CNT) and carbon nano particles (CN) by casted method. The aim of this work produce texture of PVA with CNT and CN, the effect of CNT and CN content in thin films nanocomposite were measured by utilizing reflectance and absorbance data. The contents of CNT and CN reinforcement in the PVA matrix increase the optical properties such as reflectance, absorption coefficient, refractive index, extinction factor. But the transmittance and reflectance of thin films nanocomposite (PVA-0.05CNT, PVA-0.05CN, and PVA-0.025CNT-0.025CN) decreased, on anther hand the conductivity and dielectric constant were increased. The direct allowed transition of energy gap decreased from 4.0 eV to 2.9 eV, the indirect allowed transition of energy gap decreased from 4.4 eV to 2.8 eV, respectively. Urbach energy was increased from 1.238 eV to 2.711 eV after added the CNT and CN to PVA texture. The scanning electron microscope was used to evaluate the particle sizes of CNT and CN after preparation from the experimental method, which used in the PVA lattice to constitute the thin films nanocomposite (PVA-0.05CNT, PVA-0.05CN, and PVA-0.025CNT-0.025CN). The AFM test used to exhibit the roughness.

In late 2019,  a virus appeared suddenly he claims Covid-19, which started in China and began to spread very widely around the world. And because of its effects, which are not limited to human life only, but rather in economic and social aspects, and because of the increase in daily injuries and significantly with the limited hospitals that cannot accommodate these large numbers, it is necessary to find an automatic and rapid detection method that limits the spread of the disease and its detection at an early stage in order to be treated more quickly. In this paper, deep learning was relied upon to create a CNN model to detect COVID-19 infected lungs using chest X-ray images. The base consists of a set of images taken of lungs infected with Covid-19 disease and normal lungs, as the CNN structure gave accuracy, Precision, Recall and F-Measure 100%