This paper presents a method to classify colored textural images of skin tissues. Since medical images havehighly heterogeneity, the development of reliable skin-cancer detection process is difficult, and a mono fractaldimension is not sufficient to classify images of this nature. A multifractal-based feature vectors are suggested hereas an alternative and more effective tool. At the same time multiple color channels are used to get more descriptivefeatures.Two multifractal based set of features are suggested here. The first set measures the local roughness property, whilethe second set measure the local contrast property.A combination of all the extracted features from the three colormodels gives a highest classification accuracy with 99.4

The tagged search (The aesthetic images in Mohammed Thanoun graphic) four chapters, Chapter I was concerned the statement of the research problem, the research importance and it’s needed, the goal of research in identifying the aesthetic images in the graphic of the artist's, the research limits, and identifying the most important terms, chapter II came with theoretical framework and included three chapters: chapter I was interested in the aesthetic concept. chapter II is the image aesthetic in the graphic, and chapter III is the artist experience, Chapter III specializes in research procedures: community, sample, curriculum, tool, and sample analysis. Chapter IV ended with results, including: dynamic research sample illustrated of the

In this study, Cr−Mo−N thin films with different Mo contents were synthesised via closed field unbalanced magnetron sputtering ion plating. The effects of Mo content on the microstructure, chemical bonding state, and optical properties of the prepared films were investigated by X-ray diffraction spectroscopy (XRD), X-ray photoelectron spectroscopy (XPS), field emission scanning electron microscopy, and ultraviolet-visible spectrophotometry. XRD results determined the face centered cubic (fcc) structure of pure CrN film. The incorporation of molybdenum (Mo) in the CrN matrix was confirmed by both XRD and XPS analyses. The CrMoN coatings demonstrate various polycrystalline phases including CrN, γ-Mo2N, Cr with oxides layers of MoO3, CrO3

In this study, generation of elliptical gears with different teeth profiles of crowned involute, double circular arc (DCA), and combined (crowned involute with DCA) has been developed. The resulting mathematical equations have been computerized and feed to CNC end mill machine to manufacture elliptical gear models with different profiles. These models are investigated in plane polariscope to show the resulting stresses under certain load. Comparison of photo-elastic stress results shows that combined elliptical gears with DCA side as a loaded side have a minimum resulting contact stress with a reduction percentage of 40% compare with contact stresses in counterpart elliptical gear of involute profile (which is commonly u

n this study, Cr−Mo−N thin films with different Mo contents were synthesised via closed field unbalanced magnetron sputtering ion plating. The effects of Mo content on the microstructure, chemical bonding state, and optical properties of the prepared films were investigated by X-ray diffraction spectroscopy (XRD), X-ray photoelectron spectroscopy (XPS), field emission scanning electron microscopy, and ultraviolet-visible spectrophotometry. XRD results determined the face centered cubic (fcc) structure of pure CrN film. The incorporation of molybdenum (Mo) in the CrN matrix was confirmed by both XRD and XPS analyses. The CrMoN coatings demonstrate various polycrystalline phases including CrN, γ-Mo2N, Cr with oxides layers of MoO3, CrO3,

Diabetic retinopathy is an eye disease in diabetic patients due to damage to the small blood vessels in the retina due to high and low blood sugar levels. Accurate detection and classification of Diabetic Retinopathy is an important task in computer-aided diagnosis, especially when planning for diabetic retinopathy surgery. Therefore, this study aims to design an automated model based on deep learning, which helps ophthalmologists detect and classify diabetic retinopathy severity through fundus images. In this work, a deep convolutional neural network (CNN) with transfer learning and fine tunes has been proposed by using pre-trained networks known as Residual Network-50 (ResNet-50). The overall framework of the proposed

It is well known that sonography is not the first choice in detecting early breast tumors. Improving the resolution of breast sonographic image is the goal of many workers to make sonography a first choice examination as it is safe and easy procedure as well as cost effective. In this study, infrared light exposure of breast prior to ultrasound examination was implemented to see its effect on resolution of sonographic image. Results showed that significant improvement was obtained in 60% of cases.

In this work we present a technique to extract the heart contours from noisy echocardiograph images. Our technique is based on improving the image before applying contours detection to reduce heavy noise and get better image quality. To perform that, we combine many pre-processing techniques (filtering, morphological operations, and contrast adjustment) to avoid unclear edges and enhance low contrast of echocardiograph images, after implementing these techniques we can get legible detection for heart boundaries and valves movement by traditional edge detection methods.

Elzaki Transform Adomian decomposition technique (ETADM), which an elegant combine, has been employed in this work to solve non-linear Riccati matrix differential equations. Solutions are presented to demonstrate the relevance of the current approach. With the use of figures, the results of the proposed strategy are displayed and evaluated. It is demonstrated that the suggested approach is effective, dependable, and simple to apply to a range of related scientific and technical problems.