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Prediction of bearing capacity of driven piles for Basrah governatore using SPT and MATLAB
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Based on the results of standard penetration tests (SPTs) conducted in Al-Basrah governorate, this research aims to present thematic maps and equations for estimating the bearing capacity of driven piles having several lengths. The work includes drilling 135 boreholes to a depth of 10 m below the existing ground level and three standard penetration tests (SPT) at depths of 1.5, 6, and 9.5 m were conducted in each borehole. MATLAB software and corrected SPT values were used to determine the bearing capacity of driven piles in Al-Basrah. Several-order interpolation polynomials are suggested to estimate the bearing capacity of driven piles, but the first-order polynomial is considered the most straightforward. Furthermore, the root means squared error (RMSE) for all suggested polynomials are roughly the same. The production of thematic maps demonstrates the variation in bearing capacity of driven piles over the entire territory of Al-Basrah governorate in correlation with different depths. The results of the statistical equations showed that there is good agreement with those obtained from the SPT data. When compared with the observed values from SPT, the allowable bearing capacity results for the driven piles ranged from (−3 to +38)%. The main results of this study showed a variation of 30% between calculated and estimated values of bearing capacity of driven piles for all lengths of piles at a 95% confidence interval.

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Publication Date
Wed Sep 01 2010
Journal Name
Al-khwarizmi Engineering Journal
Prediction of the Scale Removal Rate in Heat Exchanger Piping System Using the Analogies between Mass and Momentum Transfer
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The possibility of predicting the mass transfer controlled CaCO3 scale removal   rate has been investigated.

Experiments were carried out using chelating agents as a cleaning solution at different time and Reynolds’s number. The results of CaCO3 scale removal or (mass transfer rate) (as it is the controlling process) are compared with proposed model of prandtl’s and Taylor particularly based on the concept of analogy among momentum and mass transfer.

Correlation for the variation of Sherwood number ( or mass transfer rate ) with Reynolds’s number have been obtained .

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Publication Date
Sun Apr 01 2018
Journal Name
Journal Of Engineering/
Water quality assessment and total dissolved solids prediction using artificial neural network in Al-Hawizeh marsh south of Iraq
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The Iraqi marshes are considered the most extensive wetland ecosystem in the Middle East and are located in the middle and lower basin of the Tigris and Euphrates Rivers which create a wetlands network and comprise some shallow freshwater lakes that seasonally swamped floodplains. Al-Hawizeh marsh is a major marsh located east of Tigris River south of Iraq. This study aims to assess water quality through water quality index (WQI) and predict Total Dissolved Solids (TDS) concentrations in Al-Hawizeh marsh based on artificial neural network (ANN). Results showed that the WQI was more than 300 for years 2013 and 2014 (Water is unsuitable for drinking) and decreased within the range 200-300 in years 2015 and 2016 (Very poor water). The

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Publication Date
Mon Feb 16 2026
Journal Name
Agribusiness
Economic Analysis of AI‐Driven Resource Efficiency in Sustainable Agriculture in Iraq
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Abstract<p> Water scarcity, rising energy costs, and declining irrigation efficiency are significant barriers to wheat production in Iraq. This study evaluates the economic, environmental, and sustainability impacts of integrating artificial intelligence (AI) into irrigation management under semiarid conditions. Field experiments conducted at the Al‐Ra'id Research Station in Baghdad during the 2025 season compared conventional diesel‐based irrigation with AI‐assisted irrigation that used soil moisture sensors, Internet of Things (IoT) controllers, and predictive weather algorithms. The analysis employed Cobb–Douglas production modeling, cost–benefit analysis, net</p> ... Show More
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Publication Date
Sun Jan 01 2023
Journal Name
Computers, Materials &amp; Continua
Hybrid Deep Learning Enabled Load Prediction for Energy Storage Systems
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Publication Date
Thu May 01 2025
Journal Name
Journal Of Water Process Engineering
Developing a versatile visible-light-driven polyvinylidene fluoride/Ag2O@CRA photocatalytic membrane for efficient treatment of organic pollutants-contained wastewater
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Publication Date
Thu Dec 23 2010
Journal Name
Arabian Journal Of Geosciences
Climatic prediction of the terrestrial and coastal areas of Iraq
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Publication Date
Fri May 01 2020
Journal Name
International Journal Of Psychosocial Rehabilitation
The Psychological Pollution And Its Role In The Effectiveness Of The Administrative Performance Of International Stadiums Staff (Baghdad, Arbil, Basrah)
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MT Abed, ALSG Irhayyim, TH Rija, International Journal of Psychosocial Rehabilitation, 2020 - Cited by 1

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Publication Date
Thu May 01 2025
Journal Name
2025 3rd International Conference On Business Analytics For Technology And Security (icbats)
Comparison of Deep Neural Network Models (LSTM, Bi-LSTM, GRU and Bi-GRU) for Gold Price Prediction
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This research studies the comparison of deep neural network models and performance evaluation to predict the gold prices of time series, where the gold prices contain high fluctuations and non-linear patterns that are difficult to capture using traditional models, which makes predicting them a significant challenge. Therefore, the focus was on using deep learning models represented by (LSTM), (Bi-LSTM), (GRU) and (Bi-GRU). The results showed the superiority of the (Bi-GRU) model according to comparison criteria (MSE), (RMSE), (MAE), and (R∧2) compared to other models because it was able to understand the time patterns better by processing the data in both directions and provided superior performance, which indicates its effectiveness, eff

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Publication Date
Wed Sep 01 2021
Journal Name
Iop Conference Series: Earth And Environmental Science
Response of Piles Group embedded in Sandy Soil with Cavities to Seismic Loading
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Publication Date
Sat Jan 01 2022
Journal Name
Geotechnical Engineering And Sustainable Construction
Numerical Modeling of Under Reamed Piles Behavior Under Dynamic Loading in Sandy Soil
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Under-reamed piles defined by having one or more bulbs have the potential for sizeable major sides over conventional straight-sided piles, most of the studies on under-reamed piles have been conducted on the experimental side, while theoretical studies, such as the finite element method, have been mainly confined to conventional straight-sided piles. On the other hand, although several laboratory and experimental studies have been conducted to study the behavior of under-reamed piles, few numer­ical studies have been carried out to simulate the piles' performance. In addition, there is no research to compare and evaluate the behavior of these piles under dynamic loading. Therefore, this study aimed to numerically investigate bearing capaci

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