In this research ,Undoped Nio and 1%Li doped Nio thin films were deposited utilizing chemical spray pyrolysis on the glass substrates heated (450C). The effects of non-thermal plasma on the structural and optical properties were studied. XRD measurement shows that Nio and Nio:1%Li films were found to be polycrystalline and have cubic structure with a preferred orientation (111). Decreased crystal size after exposure especially at (7) sec. AFM data indicate that the surface roughness average and (RMS) values of the prepared doped films are increasing after exposure to plasma, the transmittance increases after doped samples exposure to plasma, it was found that the energy gap value decreased when doped samples exposure to plasma, also, thickn

The main objective of this study is to experimentally investigate the effect of the CMC polymeric drag reducer on the pressure drop occurred along the annulus of the wellbore in drilling operation and investigate the optimum polymer concentration that give the minimum pressure drop. A flow loop was designed for this purpose consist from 14 m long with transparent test section and differential pressure transmitter that allows to sense and measure the pressure losses along the test section. The results from the experimental work show that increasing in polymer concentration help to reduce the pressure drop in annulus and the optimum polymer concentration with the maximum drag reducing is 0.8 kg/m³. Also increasing in flow rate a

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

CO2 Laser (10600nm) is the recent method in the management of challenging skin scar resulting from trauma, burn and surgical wound. The aim of this study was to evaluate the efficacy & safety of fractional CO2 laser (10600nm) in treatment of skin scar. Materials and Methods:Twenty patients with different types of scars treated with fractional CO2 (10600nm) laser, (10 patients) were given additional intralesional Triamcinolone. Results: All of the twenty patients included in this study showed some sort of improvements in scar texture, height and pliability and all of the ten patients who received intralesional Triamcinolone after laser show complete satisfaction. Conclusion:Fractional CO2 (10600nm) laser can be used as alternative, ef