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

Several correlations have been proposed for bubble point pressure, however, the correlations could not predict bubble point pressure accurately over the wide range of operating conditions. This study presents Artificial Neural Network (ANN) model for predicting the bubble point pressure especially for oil fields in Iraq. The most affecting parameters were used as the input layer to the network. Those were reservoir temperature, oil gravity, solution gas-oil ratio and gas relative density. The model was developed using 104 real data points collected from Iraqi reservoirs. The data was divided into two groups: the first was used to train the ANN model, and the second was used to test the model to evaluate their accuracy and trend stability

The present work describes the adsorption of Ba2+ and Mg2+ions from aqueous solutions by activated alumina in single and binary system using batch adsorption. The effect of different parameters such as amount of alumina, concentration of metal ions, pH of solution, contact time and agitation speed on the adsorption process was studied. The optimum adsorbent dosage was found to be 0.5 g and 1.5 g for removal of Ba2+ and Mg2+, respectively. The optimum pH, contact time and agitation speed, were found to be pH 6, 2h and 300 rpm, respectively, for removal of both metal ions. The equilibrium data were analyzed by Langmuir and Freundlich isotherm models and the data fitted well to both isotherm modes as indicated by higher correlation of deter

When soft tissue planning is important, usually, the Magnetic Resonance Imaging (MRI) is a medical imaging technique of selection. In this work, we show a modern method for automated diagnosis depending on a magnetic resonance images classification of the MRI. The presented technique has two main stages; features extraction and classification. We obtained the features corresponding to MRI images implementing Discrete Wavelet Transformation (DWT), inverse and forward, and textural properties, like rotation invariant texture features based on Gabor filtering, and evaluate the meaning of every

This research aimed to examine the effect of concentration of dyes stuff, contact time, temperature and ratio of adsorbent weight in (gm) to volume of solution in (ml) on the percentage removal. Two dyes were used; direct blue 6 and direct yellow and the adsorbent was the maize cob. Batch experiments were performed by contacting different weights of adsorbent with 50 ml of solution of desired concentration with continuous stirring at various temperatures. The percentage of removal was calculated and the maximum percentage of removal was 80%. And as the concentration of solution, contact time, temperature and the ratio of adsorbent to volume of solution increase the percentage of removal increase.

The present article delves into the examination of groundwater quality, based on WQI, for drinking purposes in Baghdad City. Further, for carrying out the investigation, the data was collected from the Ministry of Water Resources of Baghdad, which represents water samples drawn from 114 wells in Al-Karkh and Al-Rusafa sides of Baghdad city. With the aim of further determining WQI, four water parameters such as (i) pH, (ii) Chloride (Cl), (iii) Sulfate (SO4), and (iv) Total dissolved solids (TDS), were taken into consideration. According to the computed WQI, the distribution of the groundwater samples, with respect to their quality classes such as excellent, good, poor, very poor and unfit for human drinking purpose, was found to be

Phosphorus is usually the limiting nutrient for eutrophication in inland receiving waters; therefore, phosphorus concentrations must be controlled. In the present study, a series of jar test was conducted to evaluate the optimum pH, dosage and performance parameters for coagulants alum and calcium chloride. Phosphorus removal by alum was found to be highly pH dependent with an optimum pH of 5.7-6. At this pH an alum dosage of 80 mg/l removed 83 % of the total phosphorus. Better removal was achieved when the solution was buffered at pH = 6. Phosphorus removal was not affected by varying the slow mixing period; this is due to the fact that the reaction is relatively fast.
The dosage of calcium chloride and pH of solution play an importa

Information from 54 Magnetic Resonance Imaging (MRI) brain tumor images (27 benign and 27 malignant) were collected and subjected to multilayer perceptron artificial neural network available on the well know software of IBM SPSS 17 (Statistical Package for the Social Sciences). After many attempts, automatic architecture was decided to be adopted in this research work. Thirteen shape and statistical characteristics of images were considered. The neural network revealed an 89.1 % of correct classification for the training sample and 100 % of correct classification for the test sample. The normalized importance of the considered characteristics showed that kurtosis accounted for 100 % which means that this variable has a substantial effect

The proper operation, and control of wastewater treatment plants, is receiving an increasing attention, because of the rising concern about environmental issues. In this research a mathematical model was developed to predict biochemical oxygen demand in the waste water discharged from Abu-Ghraib diary factory in Baghdad using Artificial Neural Network (ANN).In this study the best selection of the input data were selected from the recorded parameters of the wastewater from the factory. The ANN model developed was built up with the following parameters: Chemical oxygen demand, Dissolved oxygen, pH, Total dissolved solids, Total suspended solids, Sulphate, Phosphate, Chloride and Influent flow rate. The results indicated that the constructed A