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Harnessing Technological Innovation and Artificial Intelligence in Iraqi Commercial Banks to Achieve Sustainability
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Publication Date
Thu Oct 01 2020
Journal Name
Journal Of Engineering Science And Technology (jestec)
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 2016-201

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Publication Date
Thu Oct 01 2020
Journal Name
Journal Of Engineering Science And Technology
Water quality assessment and sodium adsorption ratio prediction of Tigris River using artificial neural network
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Publication Date
Sun May 01 2022
Journal Name
Journal Of Engineering
Estimating Pitting Corrosion Depth and Density on Carbon Steel (C-4130) using Artificial Neural Networks
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The purpose of this research is to investigate the impact of corrosive environment (corrosive ferric chloride of 1, 2, 5, 6% wt. at room temperature), immersion period of (48, 72, 96, 120, 144 hours), and surface roughness on pitting corrosion characteristics and use the data to build an artificial neural network and test its ability to predict the depth and intensity of pitting corrosion in a variety of conditions. Pit density and depth were calculated using a pitting corrosion test on carbon steel (C-4130). Pitting corrosion experimental tests were used to develop artificial neural network (ANN) models for predicting pitting corrosion characteristics. It was found that artificial neural network models were shown to be

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Publication Date
Tue Jul 17 2018
Journal Name
International Journal Of Adaptive Control And Signal Processing
Single channel informed signal separation using artificial-stereophonic mixtures and exemplar-guided matrix factor deconvolution
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Publication Date
Thu Aug 31 2017
Journal Name
Journal Of Engineering
Optimum Dimensions of Hydraulic Structures and Foundation Using Genetic Algorithm coupled with Artificial Neural Network
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      A model using the artificial neural networks and genetic algorithm technique is developed for obtaining optimum dimensions of the foundation length and protections of small hydraulic structures. The procedure involves optimizing an objective function comprising a weighted summation of the state variables. The decision variables considered in the optimization are the upstream and downstream cutoffs lengths and their angles of inclination, the foundation length, and the length of the downstream soil protection. These were obtained for a given maximum difference in head, depth of impervious layer and degree of anisotropy. The optimization carried out is subjected to constraints that ensure a safe structure aga

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Publication Date
Thu Aug 01 2024
Journal Name
Iop Conference Series: Earth And Environmental Science
Combining Bourgoyne and Young Equations by Bagging Tree Regression to Predict Rate of Penetration in a Southern Iraqi Field, Case Study
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Abstract<p>Achieving an accurate and optimal rate of penetration (ROP) is critical for a cost-effective and safe drilling operation. While different techniques have been used to achieve this goal, each approach has limitations, prompting researchers to seek solutions. This study’s objective is to conduct the strategy of combining the Bourgoyne and Young (BYM) ROP equations with Bagging Tree regression in a southern Iraqi field. Although BYM equations are commonly used and widespread to estimate drilling rates, they need more specific drilling parameters to capture different ROP complexities. The Bagging Tree algorithm, a random forest variant, addresses these limitations by blending domain kno</p> ... Show More
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Publication Date
Thu May 22 2025
Journal Name
Revista Iberoamericana De Psicología Del Ejercicio Y El Deporte, Issn 1886-8576, Vol. 18, Nº. 3, 2023, Págs. 288-290
The History of Clubs?: Participation in the Iraqi Volleyball Premier League and Its Results for the Period from (1991 to 2022)
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Autorías: Omar Saeed Sabbar, Ali Mousa Jawad, Maher Amer Jabbar. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 3, 2023. Artículo de Revista en Dialnet.

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Publication Date
Sun Jan 01 2023
Journal Name
Revista Iberoamericana De Psicología Del Ejercicio Y El Deporte
The History of Clubs?: Participation in the Iraqi Volleyball Premier League and Its Results for the Period from (1991 to 2022)
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The purpose of this paper is to identifying the results of the clubs participating in the men's Volleyball Premier League for the period from (1991) to (2022), archive the results of the Iraqi clubs participating in the Iraqi Premier League for men for the period from (1991) to (2022), and diagnosing and analyzing the causes of fluctuation in the participation of some Iraqi clubs in the Premier League for men for the period from (1991) to (2022). The nature of the research necessitated that the researcher use the historical approach or the so-called documentary approach, taking advantage of the historical development that took place for the participation of Iraqi clubs for men in the Premier League from (1991) until 2022), the last league h

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Publication Date
Sat Oct 20 2018
Journal Name
Journal Of Economics And Administrative Sciences
Using Multivariate GARCH Models CCC (Constant Conditional Correlation) and DCC(Dynamic Conditional Correlation) To Forecast Iraqi Dinar Exchange Rate in Dollar
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Abstract

Multivariate GARCH Models take several forms , the most important DCC dynamic conditional correlation, and CCC constant conditional correlation , The Purpose of this research is the Comparison for both Models.Using three  financial time series which is a series of daily Iraqi dinar exchange rate indollar, Global daily Oil price in dollar and Global daily gold price in dollarfor the period from 01/01/2014 till 01/01/2016, Where it has been transferred to the three time series returns to get the Stationarity, some tests were conducted including Ljung-Box , JarqueBera  , Multivariate ARCH to Returns Series and Residuals Series for both models In Comparison

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Publication Date
Wed Apr 01 2020
Journal Name
Journal Of Economics And Administrative Sciences
The effect of credit risk indicators on the profitability of banks in the Arab gulf countries
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The purpose of this study is to investigate the effect of credit risk indicators on the Arab Gulf countries' banks Profitability over the period of 2015 to 2017.  The banking credit risk was calculated using non-performing loans ratio affecting banks profitability indicators like net income and by using fixed effect and random effect model analyses, the study found that increasing in non-performing loans ratio will decrease the net income in gulf banks, the study also found that personal loans represent the largest share of loans granted in gulf banks. Also, the study recommends the importance of developing the capabilities of credit departments in commercial banks in dealing with bad loans, and studying the financial statem

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