Early detection of eye diseases can forestall visual deficiency and vision loss. There are several types of human eye diseases, for example, diabetic retinopathy, glaucoma, arteriosclerosis, and hypertension. Diabetic retinopathy (DR) which is brought about by diabetes causes the retinal vessels harmed and blood leakage in the retina. Retinal blood vessels have a huge job in the detection and treatment of different retinal diseases. Thus, retinal vasculature extraction is significant to help experts for the finding and treatment of systematic diseases. Accordingly, early detection and consequent treatment are fundamental for influenced patients to protect their vision. The aim of this paper is to detect blood vessels from

This study aims at evaluating the performance of MA students in the College of Education for Women in using the digital transformation and identifying the significant difference in performance evaluation according to the variable of academic qualification (Master or PHD). In order to achieve the aim of the research the researcher prepared a questionnaire of 20 items, and this happens after the researcher's getting acquaintance of the literature of previous studies related to the variable of the research. The apparent validity of the items was examined by exposing them to 10 juries specialized in education, psychology and evaluation and measurement. The stability of the items was examined via two methods, the test-repetition and half-divisio

Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

Highly Modified Asphalt (HiMA) binders have garnered significant attention due to their superior resistance to rutting, fatigue cracking, and thermal distress under heavy traffic loads and extreme environmental conditions. While elastomeric polymers such as Styrene- Butadiene-Styrene (SBS) have been extensively used in HiMA applications, the potential of plastomeric polymers, including Polyethylene (PE) and Ethylene Vinyl Acetate (EVA), remains largely unexplored. This study aims to evaluate the performance of reference binder (RB) modified with plastomeric HiMA asphalt in comparison to SBS-modified binders and determine the optimal polymer dosage for achieving an optimal balance between rutting resistance and fatigue durability. The experi

This work describes the effect of temperature on the phase transformation of titanium dioxide (TiO2) prepared using metal organic precursors as starting materials. X-ray diffraction (XRD) was used to investigate the structural properties of TiO2 gels calcined at different temperatures (300, 500, 700) ?C. the results showed that the samples have typical peaks of TiO2 polycrystalline brookite nanopowders after calcined at (300 ?C), which confirmed by (111), (121), (200), (012), (131), (220), (040), (231), (132) and (232) diffraction peaks. Also, XRD diffraction spectra showed the presence of crystallites of anatase with low proportion of rutile phase where calcined at (500 ?C), while rutile phase domains at (700 ?C). The crystallite size of

The purpose  of the research is interpretation of what quality transformations In the Arab commercial banks' management, and determine which fields that have been achieved in the third millennium, and elicitation the governance trends for future vision to manage them and estimate the expected value for these transformations, the importance of the idea of ​​research in investment the implicit and the apparent of practical knowledge stocks in the minds of managers by specialized language with the application of electronic business philosophy in response to the challenges of the information age and who should occupies those banks the center of Arab leadership and excellence, and try to upgrade to command centers in their co

This paper presents a proposed method for (CBIR) from using Discrete Cosine Transform with Kekre Wavelet Transform (DCT/KWT), and Daubechies Wavelet Transform with Kekre Wavelet Transform (D4/KWT) to extract features for Distributed Database system where clients/server as a Star topology, client send the query image and server (which has the database) make all the work and then send the retrieval images to the client. A comparison between these two approaches: first DCT compare with DCT/KWT and second D4 compare with D4/KWT are made. The work experimented over the image database of 200 images of 4 categories and the performance of image retrieval with respect to two similarity measures namely Euclidian distance (ED) and sum of absolute diff

Text based-image clustering (TBIC) is an insufficient approach for clustering related web images. It is a challenging task to abstract the visual features of images with the support of textual information in a database. In content-based image clustering (CBIC), image data are clustered on the foundation of specific features like texture, colors, boundaries, shapes. In this paper, an effective CBIC) technique is presented, which uses texture and statistical features of the images. The statistical features or moments of colors (mean, skewness, standard deviation, kurtosis, and variance) are extracted from the images. These features are collected in a one dimension array, and then genetic algorithm (GA) is applied for image clustering.