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joe-1524
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
Sun Mar 31 2024
Journal Name
Iraqi Geological Journal
Permeability Prediction and Facies Distribution for Yamama Reservoir in Faihaa Oil Field: Role of Machine Learning and Cluster Analysis Approach
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Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F

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Publication Date
Wed May 31 2023
Journal Name
International Journal Of Sustainable Development And Planning
Prediction of Formal Transformations in City Structure (Kufa as a Model) Based on the Cellular Automation Model and Markov Chains
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The research utilizes data produced by the Local Urban Management Directorate in Najaf and the imagery data from the Landsat 9 satellite, after being processed by the GIS tool. The research follows a descriptive and analytical approach; we integrated the Markov chain analysis and the cellular automation approach to predict transformations in city structure as a result of changes in land utilization. The research also aims to identify approaches to detect post-classification transformations in order to determine changes in land utilization. To predict the future land utilization in the city of Kufa, and to evaluate data accuracy, we used the Kappa Indicator to determine the potential applicability of the probability matrix that resulted from

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Publication Date
Sun Dec 01 2019
Journal Name
2019 First International Conference Of Computer And Applied Sciences (cas)
A Comparison for Some of the estimation methods of the Parallel Stress-Strength model In the case of Inverse Rayleigh Distribution
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Publication Date
Wed Apr 01 2020
Journal Name
Iop Conference Series: Earth And Environmental Science
Strategic Analysis of New Cities (Case Study Basmaya City - Republic of Iraq) An Analytical Study of Strength, Weakness, Opportunity, and Threat
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The rapid growth of cities and their inflation is a big problem, especially in the last years. this growth is accompanied by such problems like population growth, housing need, low level of services, random expansion, traffic congestion as well as pollution of the environment, which leads to a decline in the quality of life in Baghdad, the population are concentration in Baghdad therefore that leads to imbalance of development among cities and productive concentration for service projects in a mega cities, causing migration from other provinces In search of a better life. The main objective of the new cities is to relieve pressure on major cities and guide the growth of cities. Basmaya city it’s a new city project adopted f

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Publication Date
Tue May 23 2023
Journal Name
Journal Of Engineering
Combined effect of fineness modulus and grading zones of fine aggregate on fresh properties and compressive strength of self compacted concrete
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Self-compacted concrete (SCC) considered as a revolution progress in concrete technology due to its ability for flowing through forms, fusion with reinforcement, compact itself by its weight without using vibrators and economic advantages. This research aims to assess the fresh properties of SCC and study their effect on its compressive strength using different grading zones and different fineness modulus (F.M) of fine aggregate. The fineness modulus used in this study was (2.73, 2.82,2.9& 3.12) for different zones of grading (zone I, zone II& marginal zone(between zone I&II)) according to Iraqi standards (I.Q.S No.45/1984).Twelve mixes were prepared, each mix were tested in fresh state with slump, V-Funnel and L-Box tests, t

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Publication Date
Sat Mar 14 2026
Journal Name
Sciences Journal Of Physical Education
Comparison of maximum strength and peak electrical activity (EMG) of the muscles of the two legs among bodybuilding players and Weightlifting
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Publication Date
Fri Jun 21 2013
Journal Name
Journal Of Engineering
Combined effect of fineness modulus and grading zones of fine aggregate on fresh properties and compressive strength of self compacted concrete
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Self-compacted concrete (SCC) considered as a revolution progress in concrete technology due to its ability for flowing through forms, fusion with reinforcement, compact itself by its weight without using vibrators and economic advantages. This research aims to assess the fresh properties of SCC and study their effect on its compressive strength using different grading zones and different fineness modulus (F.M) of fine aggregate. The fineness modulus used in this study was (2.73, 2.82,2.9& 3.12) for different zones of grading (zone I, zone II& marginal zone(between zone I&II)) according to Iraqi standards (I.Q.S No.45/1984).Twelve mixes were prepared, each mix were tested in fresh state with slump, V-Funnel and L-Box tests, then 72

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Publication Date
Thu May 30 2024
Journal Name
Iraqi Journal Of Science
Lipid Profile Parameters and Adipokines among Adolescents Infected with Toxoplasmosis
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The lipid profile and adipokines of an adolescent may be affected by some parasite infections. Recently, it has been discovered that these parasites are connected to body mass index (BMI), lipids and adipokines. The current study, therefore, aimed to specify how Toxoplasma gondii (T. gondii) affect BMI, lipid profile and adipokines. This study was conducted in Al Madain hospital, Baghdad from October to December 2022. An ELISA test was performed to examine the anti-T. gondii IgG and IgM for a group of adolescents attending the hospital. Based on this examination ninety adolescents were chosen to be involved in the study. They were separated in to two groups: individuals who tested positive for the parasite (n=45) and those who teste

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Publication Date
Fri Jan 01 2021
Journal Name
Biochemical & Cellular Archives
A COMPARATIVE STUDY ON SOME BIOCHEMICAL PARAMETERS IN INFERTILE PATIENTS.
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Publication Date
Sat Apr 01 2023
Journal Name
Kuwait Journal Of Science
Evaluate the argon plasma jet parameters by optical emission spectroscopy
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