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

     Many authors investigated the problem of the early visibility of the new crescent moon after the conjunction and proposed many criteria addressing this issue in the literature. This article presented a proposed criterion for early crescent moon sighting based on a deep-learned pattern recognizer artificial neural network (ANN) performance. Moon sight datasets were collected from various sources and used to learn the ANN. The new criterion relied on the crescent width and the arc of vision from the edge of the crescent bright limb. The result of that criterion was a control value indicating the moon's visibility condition, which separated the datasets into four regions: invisible, telescope only, probably visible, and certai

<p>Combating the COVID-19 epidemic has emerged as one of the most promising healthcare the world's challenges have ever seen. COVID-19 cases must be accurately and quickly diagnosed to receive proper medical treatment and limit the pandemic. Imaging approaches for chest radiography have been proven in order to be more successful in detecting coronavirus than the (RT-PCR) approach. Transfer knowledge is more suited to categorize patterns in medical pictures since the number of available medical images is limited. This paper illustrates a convolutional neural network (CNN) and recurrent neural network (RNN) hybrid architecture for the diagnosis of COVID-19 from chest X-rays. The deep transfer methods used were VGG19, DenseNet121

Isobaric Vapor-Liquid-Liquid equilibrium data for the binary systems ethyl acetate + water, toluene + water and the ternary system toluene + ethyl acetate + water were determined by a modified equilibrium still, the still consisted of a boiling and a condensation sections supplied with mixers that helped to correct the composition of the recycled condensed liquid and the boiling temperature readings in the condensation and boiling sections respectively. The VLLE data where predicted and correlated using the Peng-Robinson Equation of State in the vapor phase and one of the activity coefficient models Wilson, NRTL, UNIQUAC and the UNIFAC in the liquid phase and also were correlated using the Peng-Robinson Equation of State in both the vapo

Background: Arterial stiffness is related with atherosclerosis and cardiovascular disease events. Patients with atherosclerotic disease show to have larger diameters, reduced arterial compliance and lower flow velocities. Aim of study : To compare between patients of two age groups with concomitant diseases diabetes and hypertension in regard to intima media thickness and blood flow characteristics in order to estimate the blood perfusion to the brain via the common and internal carotid arteries. Subject and Methods : 40 patients with (diabetic and hypertension) diseases were enrolled , they were classified according to age. Color Doppler and B mode ultrasound was used to determine lumen Diameter (D), Intima – media thickness (IMT)

The natural ventilation in buildings is one of effective strategies for achieving energy efficiency in buildings by employing methods and ways of passive design, as well as its efficiency in providing high ranges of thermal comfort for occupants in buildings and raises their productivity. Because the concept of natural ventilation for many people confined to achieve through the windows and openings only, become necessary to provide this research to demonstrate the various passive design strategies for natural ventilation. Then, research problem: Insufficient knowledge about the importance and mechanism of the application of passive design strategies for natural ventilation in buildings. The research objective is: Analysis of passive desi

Insulin like growth factor-1 has metabolic and growth-related roles all over the body and is strongly associated and regulated by growth hormone. It is produced by almost any type of tissue, especially the liver. The study aimed to measure insulin like growth factor in growth hormone deficient patients and find its relation with other studied parameters. The Subjects in the study were 180 studied in the National Diabetic Center for Treatment and Research/Al-Mustansiriya University in Baghdad/Iraq for the period from November 2021 to April 2022. Blood was drawn and investigated for the levels of IGF-1, IGFBP-3, LH, and FSH. Also testosterone and statistical analysis was carried out to find the potential correlations. The results relived t

E-learning is a necessity imposed by the Corona pandemic, which has disrupted various educational institutions in the world, but some of these institutions have not been affected and education has continued with them, due to their flexible educational system that was able to employ technology in the continuity of the educational process in the so-called e-learning, because It has characteristics that make it the most suitable alternative to avoid the consequences of the Corona pandemic and its damage to the educational process, as e-learning is one of the modern methods that contribute to enhancing the effectiveness of the learner, and enabling him to assume greater responsibility compared to traditional education, so the learner becomes