The study aims to predict Total Dissolved Solids (TDS) as a water quality indicator parameter at spatial and temporal distribution of the Tigris River, Iraq by using Artificial Neural Network (ANN) model. This study was conducted on this river between Mosul and Amarah in Iraq on five positions stretching along the river for the period from 2001to 2011. In the ANNs model calibration, a computer program of multiple linear regressions is used to obtain a set of coefficient for a linear model. The input parameters of the ANNs model were the discharge of the Tigris River, the year, the month and the distance of the sampling stations from upstream of the river. The sensitivity analysis indicated that the distance and discharge have the most significant affect on the predicted TDS concentrations. The results showed that a network with (8) hidden neurons was highly accurate in predicting TDS concentration. The correlation coefficient (r), root mean square error (RMSE) and mean absolute percentage error (MAPE) between measured data and model outputs were calculated as 0.975, 113.9 and 11.51%, respectively for testing data sets. Comparisons between final results of ANNs and multiple linear regressions (MLR) showed that the ANNs model could be successfully applied and provides high accuracy to predict TDS concentrations as a water quality parameter.
The Middle Cenomanian-Early Turonian Mishrif Formation includes important carbonate reservoirs in Iraq and some other surrounding countries due to their high reservoir quality and wide geological extension. The 2D models of this study for facies, effective porosity and water saturation indicate the vertical and lateral heterogeneity of the Mishrif Formation reservoir properties in the Majnoon oil field. Construction of 2D reservoir model of the Mishrif Formation to explain the distribution of facies and petrophysical properties (effective porosity and water saturation) by using RockWorks software. The increase of effective porosity is attributed to the presence of shoal facies.The high water saturation is attributed to the existence of rest
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Building Information Modeling (BIM) is becoming a great known established collaboration process in Architecture, Engineering, and Construction (AEC) industry. In various cases in many countries, potential benefits and competitive advantages have been reported. However, despite the potentials and benefits of BIM technologies, it is not applied in the construction sector in Iraq just like many other countries of the world. The purpose of this research is to understand the uses and benefits of BIM for construction projects in Iraq. This purpose has been done by establishing a fr |
Experiments were conducted to study axial liquid dispersion coefficient in slurry bubble column of 0.15 m inside diameter and 1.6 m height using perforated plate gas distributor of 54 holes of a size equal to 1 mm diameter and with a 0.24 free area of holes to the cross sectional area of the column. The three phase system consists of air, water and PVC used as the solid phase. The effect of solid loading (0, 30 and 60 kg/m3) and solid diameter (0.7, 1.5 and 3 mm) on the axial liquid dispersion coefficient at different axial location (25, 50 and 75 cm) and superficial gas velocity covered homogeneous-heterogeneous flow regime (1-10 cm/s) were studied in the present work. The results show that the axial liquid dispersion coeffic
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To identify the fungi associated with water hyacinth (Eichhornia crassipes [Mart.] Solms), an aquatic weed, which presents in Tigris river from Baghdad south ward. Five regions from middle and south of Iraq (Al-Noumanya, Saeid Bin-Jubier, Al-Azizia, Al-Reyfay and Al-Hay) were selected for this study. Twelve fungal species were isolated. Alternaria alternata, Acremonium sp and Cladsporium herbarum, were the most frequently species (91.66 % ,50 % and 25 %) respectively. The fungi Alternaria alternata, Acremonium sp. and Phoma eupyrena were more aggressive to water hyacinth as (91.66%,83,33%, and 75%) in pathogenicity test.
The dynamic development of computer and software technology in recent years was accompanied by the expansion and widespread implementation of artificial intelligence (AI) based methods in many aspects of human life. A prominent field where rapid progress was observed are high‐throughput methods in biology that generate big amounts of data that need to be processed and analyzed. Therefore, AI methods are more and more applied in the biomedical field, among others for RNA‐protein binding sites prediction, DNA sequence function prediction, protein‐protein interaction prediction, or biomedical image classification. Stem cells are widely used in biomedical research, e.g., leukemia or other disease studies. Our proposed approach of
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The Quantitative high-resolution planktonic foraminiferal analysis of the subsurface section in three selected wells in the Ajeel Oil Field (Aj-8, Aj-12, and Aj-15) in Tikrit Governorate, Central Iraq has revealed that Shiranish Formation deposited in Late Campanian- Latest Maastrichtian age. This formation consists mainly of marly and marly limestone yielding diverse planktonic foraminiferal assemblages and calcareous benthic foraminifera, with a total of 46 species that belong to 23 genera, Three zones and four subzones, which cover the Late Campanian to the Latest Maastrichtian, were identified based on the recorded planktonic foraminifera and their ranges. They are as follows:1. Globotruncana aegyptiaca Zone that dated to be Lat
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The aim of the present work to study the effect of changing velocity (Reynold's number) on oxygen cathodic polarization using brass rotating cylinder electrode in 0.1, 0.3 and 0.5N NaCl solutions (PH = 7) at temperatures 40, 50 and 600 C. Cathodic polarization experiments were conducted as a function of electrode rotational speed and concentration.