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Water Quality Assessment and Sodium Adsorption Ratio Prediction of Tigris River Using Artificial Neural Network
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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.

Publication Date
Wed Dec 15 2021
Journal Name
Al-academy
Websites Quality Assessment of Iraqi Universities Using the WDQI Index
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The Web Design Quality Index, known as WDQI, was applied to assess the quality of websites for six Iraqi universities, namely Basra University, Mosul, Muthanna, Samarra, Dijla University College, and Al-Isra University College. The results of the index showed that the universities of Basra and Dijla University College had the highest value, at 71.07 and 70.39, respectively. Its final evaluation metric was that the website of these two universities needed a slight improvement. As for the rest of the other universities, the final values of the index ranged from 64.72-69.71. When the final values of the index are displayed on the final evaluation scale, it appears that the websites of the four universities need many improvements. The study

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
Detection and Removal of Polycyclic Aromatic Hydrocarbon from Selected Areas in Tigris River in Baghdad City
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Aromatic hydrocarbons present in Iraqi national surface water were believed to be raised principally from combustion of various petroleum products, industrial processes and transport output and their precipitation on surface water.
Polycyclic aromatic hydrocarbons (PAHs) were included in the priority pollutant list due to their toxic and carcinogenic nature. The concern about water contamination and the consequent human exposure have encouraged the development of new methods for
PAHs detection and removal.
PAHs, the real contaminants of petroleum matter, were detected in selected sites along Tigris River within Baghdad City in summer and winter time, using Shimadzu high performance liquid chromatography (HPLC) system.
Analysi

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Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
Removal of Amoxicillin from Water by Adsorption on Water Treatment Residues
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The presence of residual antibiotics in water results in the development of antibiotics resistant genes. The available wastewater treatment systems are not capable of removing such antibiotics from sewage. Thus, antibiotics need to be removed before the discharge of wastewater. Adsorption is among the promising techniques for the wastewater treatment to aid the removal of a wide range of organic and inorganic pollutants. The present work is a contribution to the search for an economical method for the removal of low concentrations of amoxicillin (AMX) from water by adsorption on water treatment residue, WTR, taken from a local drinking water facility. The chemical composition and the adsorptive characteristics of the material were first

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Publication Date
Fri Oct 11 2019
Journal Name
Journal Of The College Of Education For Women
The South Baghdad Electrical Station and its Environmental Impact on the Tigris River
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The South Baghdad electrical station located on the eastern bank of the Tigris River south of Baghdad city was selected within the municipality of Karrada between  two  latitude ( 3315 , 33 0  18 )North  and  longitude ( 44 0  27 , 44 030 ) East . The purpose of the study is to determine the contribution of the station to the effect of pollution of the Tigris water by taking water samples at the station site and two sites, one before and the other after the station, distributed over time periods of three months between each sample of water and the beginning of August and November Shabat and Mayar and analyzed water samples physically, chemically and biologic

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Publication Date
Sun Sep 07 2014
Journal Name
Baghdad Science Journal
Qualitative and Quantitative study of Epipelic algae in Tigris River within Baghdad City, Iraq
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The present study conducted to study epipelic algae in the Tigris River within Baghdad city for one year from September 2011 to August 2012 due to the importance role of benthic algae in lotic ecosystems. Five sites have been chosen along the river. A total of 154 species of epipelic algae was recorded belongs to 45 genera, where Bacillariophyceae (Diatoms) was the dominant groups followed by Cyanophyceae and Chlorophyceae. The numbers of common types in three sites were 47 species. Bacillariophyceae accounted 88.31% of the total number of epipelic algae, followed by Cyanophyceae 7.14 % and Chlorophyceae 4.55%. A 85 species (29 genera) recorded in site 1, 103 species (34 genera) in site2, 112 species (35 genera) in site3, 96 species

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Publication Date
Sun Dec 04 2016
Journal Name
Baghdad Science Journal
A Study of Epiphytic and Epipelic Algae in Al-Dora Site/Tigris River in Bagdad Province- Iraq
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There is a scarcity of data regarding algal flora of Tigris River in the territory of Baghdad. The present study deals with Tigris River in Al-Dora site in Baghdad province from November 2014 to June 2015 in order to shed light on its epiphytic Algae on (Phragmites australis) and epipelic algae. An amount of 183 and 154 species of epiphytic and epipelic algae are identified respectfully. The Bacillariophyceae (diatoms) are the dominant algal group followed by Cyanophyceae and Chlorophyceae. Moreover, 90 species are shared between two groups of algae (epiphytic and epipelic) and identified at the study site. Additionally, the seasonal variations and diversity of algal species are noticed. The highest number of epiphytic algae is 772.05 x 104

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Publication Date
Fri Dec 30 2022
Journal Name
Eastern-european Journal Of Enterprise Technologies
Experimental investigation and modelling of residual stresses in face milling of Al-6061-T3 using neural network
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Milling process is a common machining operation that is used in the manufacturing of complex surfaces. Machining-induced residual stresses (RS) have a great impact on the performance of machined components and the surface quality in face milling operations with parameter cutting. The properties of engineering material as well as structural components, specifically fatigue life, deformation, impact resistance, corrosion resistance, and brittle fracture, can all be significantly influenced by residual stresses. Accordingly, controlling the distribution of residual stresses is indeed important to protect the piece and avoid failure. Most of the previous works inspected the material properties, tool parameters, or cutting parameters, bu

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Publication Date
Sun Feb 10 2019
Journal Name
Journal Of The College Of Education For Women
The hydrological regime of the Tigris River in the city of Baghdad
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Water drainage pattern in the rivers and changed the nature of the renewed feeding areas
in the basin in terms of topographic and geological conditions and climate in addition to the
human role in organizing the process flow within these basins. This study addressed the
development of the Tigris River Hydrological in the city of Baghdad and found that the
annual rate of water drainage in the Tigris River was driven down very significantly,
especially in the past twenty years, and since 1996 up to 2014 record flow rates of less than
the overall rate of discharge of water, a (950 m3 / s ), in addition to the quarterly decrease the
discharge rates, especially since the beginning of the year 2000 and took converge all fo

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
DYNAMIC MODELING FOR DISCRETE SURVIVAL DATA BY USING ARTIFICIAL NEURAL NETWORKS AND ITERATIVELY WEIGHTED KALMAN FILTER SMOOTHING WITH COMPARISON
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Survival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms re

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Publication Date
Mon Sep 30 2024
Journal Name
Iraqi Journal Of Science
Attention-Deficit Hyperactivity Disorder Prediction by Artificial Intelligence Techniques
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Attention-Deficit Hyperactivity Disorder (ADHD), a neurodevelopmental disorder affecting millions of people globally, is defined by symptoms of hyperactivity, impulsivity, and inattention that can significantly affect an individual's daily life. The diagnostic process for ADHD is complex, requiring a combination of clinical assessments and subjective evaluations. However, recent advances in artificial intelligence (AI) techniques have shown promise in predicting ADHD and providing an early diagnosis. In this study, we will explore the application of two AI techniques, K-Nearest Neighbors (KNN) and Adaptive Boosting (AdaBoost), in predicting ADHD using the Python programming language. The classification accuracies obtained w

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