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Prediction of Shear Strength Parameters of Gypseous Soil using Artificial Neural Networks
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The shear strength of soil is one of the most important soil properties that should be identified before any foundation design. The presence of gypseous soil exacerbates foundation problems. In this research, an approach to forecasting shear strength parameters of gypseous soils based on basic soil properties was created using Artificial Neural Networks. Two models were built to forecast the cohesion and the angle of internal friction. Nine basic soil properties were used as inputs to both models for they were considered to have the most significant impact on soil shear strength, namely: depth, gypsum content, passing sieve no.200, liquid limit, plastic limit, plasticity index, water content, dry unit weight, and initial voids ratio. Multi-layer perceptron training by the backpropagation algorithm was used in creating the network. It was found that both models can predict shear strength parameters for gypseous soils with good reliability. Sensitivity analysis of the first model indicated that dry unit weight and plasticity index have the most significant effect on the predicted cohesion. While in the second model, the results indicated that the gypsum content and plasticity index have the most significant effect on the predicted angle of internal friction.

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Publication Date
Tue Aug 15 2023
Journal Name
Al-academy
Applications of Artificial Intelligence in Graphic Design
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If the Industrial Revolution has enabled the replacement of humans with machines, the digital revolution is moving towards replacing our brains with artificial intelligence, so it is necessary to consider how this radical transformation affects the graphic design ecosystem. Hence, the research problem emerged (what are the effects of artificial intelligence on graphic design) and the research aimed to know the capabilities and effects of artificial intelligence applications in graphic design, and the study dealt in its theoretical framework with two main axes, the first is the concept of artificial intelligence, and the second is artificial intelligence applications in graphic design. The descriptive approach adopted a method of content

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Publication Date
Tue Jul 06 2021
Journal Name
Journal Of Ecological Engineering
Chromium Elimination from Contaminated Soil by Electro kinetic Remediation, Using Garlic Peels Powder
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Publication Date
Wed May 01 2019
Journal Name
Journal Of Engineering
Using Ultrasonic Pulse Velocity Test to Assess the Effect of Water-Cement Ratio on the Compressive Strength of Concrete
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This study aims to find the effect of water-cement ratio on the compressive strength of concrete by using ultrasonic pulse velocity test (UPVT). Over 230 standard cube specimens were used in this study, with dimensions of 150mm, and concrete cubes were cured in water at 20 °C. Also, the specimens used in the study were made of concrete with varied water-cement ratio contents from 0.48 to 0.59. The specimens were taken from Diyarbakir-Turkey concrete centers and tested at the structure and material science lab, civil engineering, faculty of engineering from Dicle University.  The UPV measurement and compressive strength tests were carried out at the concrete age of 28 days. Their UPV and compressive strength ranged

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Publication Date
Fri Nov 01 2019
Journal Name
International Journal Of Engineering
Structural Behavior of Axially Loaded Composite Concrete-steel Plate Shear Walls
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Publication Date
Mon Mar 23 2020
Journal Name
Journal Of Engineering
prediction Capacity of Euphrates River at Assamawa City
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The reduction in the rivers capacity is one the most important issue to give the decision maker an idea during the flood season. The study area included the rivers of the Al Atshan, Al Sabeel and Euphrates, which are surveyed with a length of 21, 5 and 20 km respectively. The Euphrates , the Atshan and Al Sabeel rivers were simulated by using HEC-RAS 5.0.3 software to study the real condition within the city of Assamawa. As well as the simulation was implemented by modifying the cross sections of the Euphrates and Al Sabeel rivers to increase their capacity to 1300 and 1200 m3/s respectively which are a flood discharges100 year return periods. The results showed that the maximum discharge capacity under real conditions o

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Publication Date
Sat Mar 30 2019
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of Fracture Pressure Gradient in Halfaya Oilfield
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   Fracture pressure gradient prediction is complementary in well design and it is must be considered in selecting the safe mud weight, cement design, and determine the optimal casing seat to minimize the common drilling problems. The exact fracture pressure gradient value obtained from tests on the well while drilling such as leak-off test, formation integrity test, cement squeeze ... etc.; however, to minimize the total cost of drilling, there are several methods could be used to calculate fracture pressure gradient classified into two groups: the first one depend on Poisson’s ratio of the rocks and the second is fully empirical methods. In this research, the methods selected are Huubert and willis, Cesaroni I, Cesaroni II,

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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
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Using the artificial TABU algorithm to estimate the semi-parametric regression function with measurement errors
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Artificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing artificial TABU algorithm to find the best estimate of the semi-parametric regression function with measurement errors in the explanatory variables and the dependent variable, where measurement errors appear frequently in fields such as sport, chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement.

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Publication Date
Thu Sep 08 2022
Journal Name
Al-khwarizmi Engineering Journal
Performance Prediction in EDM Process for Al 6061 Alloy Using Response Surface Methodology and Genetic Algorithm
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The Electric Discharge (EDM) method is a novel thermoelectric manufacturing technique in which materials are removed by a controlled spark erosion process between two electrodes immersed in a dielectric medium. Because of the difficulties of EDM, determining the optimum cutting parameters to improve cutting performance is extremely tough. As a result, optimizing operating parameters is a critical processing step, particularly for non-traditional machining process like EDM. Adequate selection of processing parameters for the EDM process does not provide ideal conditions, due to the unpredictable processing time required for a given function. Models of Multiple Regression and Genetic Algorithm are considered as effective methods for determ

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Publication Date
Thu Nov 02 2023
Journal Name
Journal Of Engineering
The Effect of Using Different Aspect Ratios of Sustainable Copper Fiber on Some Mechanical Properties of High-Strength Green Concrete
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To achieve sustainability, use waste materials to make concrete to use alternative components and reduce the production of Portland cement. Lime cement was used instead of Portland cement, and 15% of the cement's weight was replaced with silica fume. Also used were eco-friendly fibers (copper fiber) made from recycled electrical. This work examines the impact of utilizing sustainable copper fiber with different aspect ratios (l/d) on some mechanical properties of high-strength green concrete. A high-strength cement mixture with a compressive strength of 65 MPa in line with ACI 211.4R was required to complete the assignment. Copper fibers of 1% by volume of concrete were employed in mixes with four different aspect ratios

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