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Predictive model for stress at ultimate in internally unbonded steel tendons based on genetic expression programming
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Publication Date
Fri Jan 01 2016
Journal Name
Ibn Al-haitham Journal For Pure And Applied Science
Genetic--Based Face Retrieval Using Statistical Features
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Publication Date
Sun Dec 17 2017
Journal Name
Al-khwarizmi Engineering Journal
Formation of Compressive Residual Stress by Face Milling Steel AISI 1045
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Abstract

     Machining residual stresses correlate very closely with the cutting parameters and the tool geometries. This research work aims to investigate the effect of cutting speed, feed rate and depth of cut on the surface residual stress of steel AISI 1045 after face milling operation. After each milling test, the residual stress on the surface of the workpiece was measured by using X-ray diffraction technique. Design of Experiment (DOE) software was employed using the response surface methodology (RSM) technique with a central composite rotatable design to build a mathematical model to determine the relationship between the input variables and the response. The results showed that both

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Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Engineering
Strengthening and Closing Cracks for Existing Reinforced Concrete Girders Using Externally Post-Tensioned Tendons
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This research is devoted to study the strengthening technique for the existing reinforced concrete beams using external post-tensioning. An analytical methodology is proposed to predict the value of the effective prestress force for the external tendons required to close cracks in existing beams. The external prestressing force required to close cracks in existing members is only a part from the total strengthening force.
A computer program created by Oukaili (1997) and developed by Alhawwassi (2008) to evaluate curvature and deflection for reinforced concrete beams or internally prestressed concrete beams is modified to evaluate the deflection and the stress of the external tendons for the externally strengthened beams using Matlab

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
An Efficient Shrinkage Estimators For Generalized Inverse Rayleigh Distribution Based On Bounded And Series Stress-Strength Models
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Abstract<p>In this paper, we investigate two stress-strength models (Bounded and Series) in systems reliability based on Generalized Inverse Rayleigh distribution. To obtain some estimates of shrinkage estimators, Bayesian methods under informative and non-informative assumptions are used. For comparison of the presented methods, Monte Carlo simulations based on the Mean squared Error criteria are applied.</p>
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Publication Date
Thu Nov 17 2022
Journal Name
Journal Of Information And Optimization Sciences
Hybrid deep learning model for Arabic text classification based on mutual information
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Publication Date
Fri Dec 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Influence of Water Stress on Expression of the X95950 Gene and Several Cellular Callus Components in Violet-Treated Sunflower Varieties
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Abstract<p>The research was conducted between 2017 and 2019 at the College of Agricultural Engineering Sciences and Laboratory of Plant Tissue Culture for Postgraduate Studies at the University of Baghdad. One experiment used a totally random design. The experiment examined the effects of PEG (Polyethylene glycol) at concentrations of 0, 2, 4, 6, and 8% on the development of three sunflower types (Ishaqi<sup>-1</sup>, Aqmar, and AL-Haja) exposed to UV-C rays for 40 minutes as a result of the growing of the juvenile peduncle outside the live body. The aim of the study was to better comprehend the physiological and biochemical changes caused by water stress on the callus of several sunfl</p> ... Show More
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Publication Date
Mon Feb 21 2022
Journal Name
Iraqi Journal For Computer Science And Mathematics
Fuzzy C means Based Evaluation Algorithms For Cancer Gene Expression Data Clustering
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The influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster. Clustering is a type of unsupervised learning that can be used to divide unknown cluster data into clusters. The k-means and fuzzy c-means (FCM) algorithms are examples of algorithms that can be used for clustering. Consequently, clustering is a common approach that divides an input space into several homogeneous zones; it can be achieved using a variety of algorithms. This study used three models to cluster a brain tumor dataset. The first model uses FCM, whic

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
A Linear Programming Method Based Optimal Power Flow Problem for Iraqi Extra High Voltage Grid (EHV)
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The objective of an Optimal Power Flow (OPF) algorithm is to find steady state operation point which minimizes generation cost, loss etc. while maintaining an acceptable system performance in terms of limits on generators real and reactive powers, line flow limits etc. The OPF solution includes an objective function. A common objective function concerns the active power generation cost. A Linear programming method is proposed to solve the OPF problem. The Linear Programming (LP) approach transforms the nonlinear optimization problem into an iterative algorithm that in each iteration solves a linear optimization problem resulting from linearization both the objective function and constrains. A computer program, written in MATLAB environme

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Publication Date
Sun Dec 31 2023
Journal Name
Sumer Journal For Pure Science
COVID-19Disease Diagnosis using Artificial Intelligence based on Gene Expression: A Review
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Publication Date
Sat Aug 04 2012
Journal Name
University Of Thi-qar Journal
Prediction of Ultimate Soil Bearing Capacity for Shallow Strip Foundation on Sandy Soils by Using (ANN) Techniqu
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Bearing capacity of soil is an important factor in designing shallow foundations. It is directly related to foundation dimensions and consequently its performance. The calculations for obtaining the bearing capacity of a soil needs many varying parameters, for example soil type, depth of foundation, unit weight of soil, etc. which makes these calculation very variable–parameter dependent. This paper presents the results of comparison between the theoretical equation stated by Terzaghi and the Artificial Neural Networks (ANN) technique to estimate the ultimate bearing capacity of the strip shallow footing on sandy soils. The results show a very good agreement between the theoretical solution and the ANN technique. Results revealed that us

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