Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp

Carbon nanoparticles are prepared by sonication using carbon black powder. The surface morphology of carbon black (CB) and carbon nanoparticles (CNPs) is investigated using scanning electron microscopy (SEM). The particles size ranges from 100 nm to 400 nm for CB and from 10 nm to 100 nm for CNPs. CNPs and CB are mixed with silicon glue of different ratios of 0.025, 0.2, 0.05, and 0.1 to synthesis films. The optical properties of the prepared films are investigated through reflectance and absorbance analyses. The ratio of 0.05 for CNPs and CB is the best for solar paint because of its higher solar water heater efficiency and is then added to the silicon glue . Temperature of cold water and temperature of hot water in storage tank were ta

           In this research, radon concentrations in some types of healthy drinking water samples available in Iraq's market were measured using a technique called Durridge RAD-7-H₂O with closed loop. Then the rate of annual effective dose in human taken this water is determined.

          It was found that, radon concentrations in studied samples ranged between 1.2 Bq.m^-3 to 142 Bq.m^-3. The results of the radon concentrations and the rate of annual effective dose for drinking water samples were significantly lower than the USEPA and WHO recommended limits that equal 500 Bq/m³ and 1 mSv/y resp

Abstract

Due to the momentum of winning in the streets of the city of Baghdad as a result of the large number of checkpoints so felt researcher to conduct a field visit to find out the main reasons that led to this congestion and to find practical solutions to mitigate wastage winning the arrival time citizen to where you want the least possible time.

This research aims to overcome the difficulties experienced by citizens to reach their places of work and reduce waste at the time of service and waiting time as well as reduce the cost of waiting.

Has emerged study a set of conclusions, including the use of model queue (G / G / C) and the mome

Stress with all its kinds are the results of a nick development Leading to delinquency burdening the ability of people.. development gas its effect on self and body reflecting on health ( physically, Psychological. And mentally) and finally leading to death (Al emara,2001,2).

Stress refers to he degree of response of the individual to events and environmental changes in his daily life with their physiological effects  such as headaches , backaches, and gastric ulcer that have different effect depending on the personality of the person and his psychological characteristics differences airing individuals ( Al emirs, zool,2  )

The aims:

• knowi

Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c