Sodium adsorption ratio (SAR) is considered as a measure of the water suitability for irrigation usage. This study examines the effect of the physicochemical parameters on water quality and SAR, which included Calcium(Ca+2), Magnesium(Mg+2), Sodium (Na+), Potassium (K), Chloride (Cl-), Sulfate(SO4-2), Carbonate (CO3-2), Bicarbonate (HCO3-), Nitrate (NO3-), Total Hardness (TH), Total Dissolved Salts (TDS), Electrical Conductivity (EC), degree of reaction (DR), Boron (B) and the monthly and annually flow discharge (Q). The water samples were collected from three stations across the Tigris River in Iraq, which flows through Samarra city (upstream), Baghdad city (central) and the end of Kut city (downstream) for the periods of 2016-2018. Results showed that the water quality of the Tigris River water is within the world health organization (WHO) specifications for drinking water except for Sulfate concentration. An artificial neural network (ANN) was used to develop the model for the three locations to predict SAR. The sum of the squared error function and the coefficient of determination (R2) were used to evaluate the amount of error in predicting values of SAR and performance evaluation of the model. The results showed that the highest value of the coefficient of determination was 0.992, 0.986, and 0.955 for Samarra, Baghdad, and Kut, respectively and the ANN analysis indicated that the prediction of SAR was effected by Sodium for three stations. Thus, the ANN model has been found to provide SAR prediction tool that can be used effectively to describe the suitability of river water quality for irrigation purposes.
The useful of remote sensing techniques in Environmental Engineering and another science is to save time, Coast and efforts, also to collect more accurate information under monitoring mechanism. In this research a number of statistical models were used for determining the best relationships between each water quality parameter and the mean reflectance values generated for different channels of radiometer operate simulated to the thematic Mappar satellite image. Among these models are the regression models which enable us to as certain and utilize a relation between a variable of interest. Called a dependent variable; and one or more independent variables
The economy is exceptionally reliant on agricultural productivity. Therefore, in domain of agriculture, plant infection discovery is a vital job because it gives promising advance towards the development of agricultural production. In this work, a framework for potato diseases classification based on feed foreword neural network is proposed. The objective of this work is presenting a system that can detect and classify four kinds of potato tubers diseases; black dot, common scab, potato virus Y and early blight based on their images. The presented PDCNN framework comprises three levels: the pre-processing is first level, which is based on K-means clustering algorithm to detect the infected area from potato image. The s
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The main aim of this study is to evaluate the remaining oil in previously produced zones, locate the water productive zone and look for any bypassed oil behind casing in not previously perforated intervals. Initial water saturation was calculated from digitized open hole logs using a cut-off value of 10% for irreducible water saturation. The integrated analysis of the thermal capture cross section, Sigma and Carbon/oxygen ratio was conducted and summarized under well shut-in and flowing conditions. The logging pass zone run through sandstone Zubair formation at north Rumaila oil field. The zones where both the Sigma and the C/O analysis show high remaining oil saturation simila
... Show MoreThe main aim of this study is to evaluate the remaining oil in previously produced zones, locate the water productive zone and look for any bypassed oil behind casing in not previously perforated intervals. Initial water saturation was calculated from digitized open hole logs using a cut-off value of 10% for irreducible water saturation. The integrated analysis of the thermal capture cross section, Sigma and Carbon/oxygen ratio was conducted and summarized under well shut-in and flowing conditions. The logging pass zone run through sandstone Zubair formation at north Rumaila oil field. The zones where both the Sigma and the C/O analysis show high remaining oil saturation similar to the open hole oil saturation, could be good oil zones that
... Show MoreWater produced from power plants is one of the most important sources of water pollution, especially for areas like Baghdad, Contaminated industrial wastewater is a major environmental challenge due to the rapid growth of industries, leading to increased accumulation of harmful pollutants in water resources, the work is intended to study the impact of water generated from a power plant in the south on the level of heavy metals before and after the treatment process and after its discharge to the Tigris River. Objective is to determine the extent of heavy metals such as iron, copper, chromium, and zinc concentration in water extracted from various points and subsequently study the monthly variations of these elements with a view to assessmen
... Show MoreAlzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of
... Show MoreThis research was conducted to determine content levels of heavy metal pollution. Samples taken from Ishaqi River bank and adjacent agricultural soils area, in ten sites, distributed along 48 km of the Ishaqi River, north Baghdad. The evaluated metals were Zinc, Copper, Manganese, Iron, Cobalt, Nickel, Chromium, Cadmium, Vanadium and Lead. PH and Electric Conductivity (EC) were measured to evaluate the acidity and (EC). Results showed that most site were contaminated with metals evaluated. Among these metals, Zn, Mn, Fe and Ni were consistently higher in all the samples (both river bank and adjacent soil) followed by PB, CU, V, Cd, Co and Cr. The level concentrations of river bank were almost higher than that of adjacent soil. As will be re
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