One of the most Interesting natural phenomena is clouds that have a very strong effect on the climate, weather and the earth's energy balance. Also clouds consider the key regulator for the average temperature of the plant. In this research monitoring and studying the cloud cover to know the clouds types and whether they are rainy or not rainy using visible and infrared satellite images. In order to interpret and know the types of the clouds visually without using any techniques, by comparing between the brightness and the shape of clouds in the same area for both the visible and infrared satellite images, where the differences in the contrasts of visible image are the albedo differences, while in the infrared images is the temperature d

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

Echocardiography is a widely used imaging technique to examine various cardiac functions, especially to detect the left ventricular wall motion abnormality. Unfortunately the quality of echocardiograph images and complexities of underlying motion captured, makes it difficult for an in-experienced physicians/ radiologist to describe the motion abnormalities in a crisp way, leading to possible errors in diagnosis. In this study, we present a method to analyze left ventricular wall motion, by using optical flow to estimate velocities of the left ventricular wall segments and find relation between these segments motion. The proposed method will be able to present real clinical help to verify the left ventricular wall motion diagnosis.

Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with

The inhibition effect of crude juice of green and black olive on cancer cell line (RD) in vitro has been studied by depending on micro titration system . Eleven different concentration starting from (916-960) mg/ml of crude juice respectively ,for three periods of exposure(24-48-72)hours. The resulted showed that the inhibition effect dependent on type of olive fruit juice ,concentration of dose ,time of exposure and the high concentration of both type of olive juice increased the growth of cell line while other concentration caused decrease in different rates ,moreover the black juice was more effective than green and 48 hours' time exposure was the best for inhibition.

   Addressed this research the impact of intelligence emotional dimensions of the main(self awareness, and self-management, and social awareness, and relationship management) in the performance excellence the university(performance optimization, and strategic development) this is by middling the styles decision making which are (rational and intuitive, and dependent, and spontaneous, and avoidant), and Go search of an intellectual dilemma raise fundamental questions revolve around the search was to answer those questions through a theoretical framework for search variables first and test models of the relationship and second through the impact six hypotheses President.The objective of the research to make sure the contr

The research aims to measure the sustainability of the Iraqi economy for the period 1990-2018 as well as to show the impact of fluctuations in the level of GDP on financial sustainability, where financial sustainability is the necessary and sufficient condition for achieving economic and financial balance in the country, as financial sustainability reflects the movement of the state budget and its relationship to GDP through the indicators of deficit, fiscal surplus and public debt internal and external, as well as reflecting the art of managing public debt, and the more managed public debt is achieved, the more the management of public debt is achieved financial sustainability. for the state in the sense that there is a reciprocal

Tight oil reservoirs have been a concerned of the oil industry due to their substantial influence on oil production. Due to their poor permeability, numerous problems are encountered while producing from tight reservoirs. Petrophysical and geomechanical rock properties are essential for understanding and assessing the fracability of reservoirs, especially tight reservoirs, to enhance permeability. In this study, Saadi B reservoir in Halfaya Iraqi oil field is considered as the main tight reservoir. Petrophysical and geomechanical properties have been estimated using full-set well logs for a vertical well that penetrates Saadi reservoir and validated with support of diagnostic fracture injection test data employing standard equations