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Impact of Asphalt Stabilization on Deformation Behavior of Reinforced Soil Embankment Model under Cyclic Loading
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Gypseous soil, which covers vast area in west, middle, east and south west regions of Iraq exhibit acceptable strength properties when dry, but it is weak and collapsible when it comes in touch with moisture from rain or other sources. When such weak soil is adopted for earth reinforced embankment construction, it may exhibit hazardous situation. Gypseous soil was investigated for the optimum liquid asphalt requirements of both cutback and emulsion using the one-dimensional unconfined compression strength test. The optimum fluid content was 13% (7% of cutback with 6% water content), and 17% (9% of emulsion with 8% water content). A laboratory model box of 50x50x25 cm was used as a representative of embankment; soil or asphalt stabilized soil have been compacted in five layers at maximum dry density (modified compaction) and an aluminum reinforcement strips were introduced between layers and connected to the facing strips. The model was subjected to cyclic loading and the lateral deformation of facing strips and the vertical deformation were detected at different stages of loading cycles and different height of the facing strips using LVDT. The reference embankment model was that of reinforced pure soil under absorbed condition. For asphalt-stabilized soil, the cutback asphalt stabilized- soil model exhibit improvement in load carrying capacity by nine folds. It shows a reduction of 23% in vertical displacement under sustained load of 436 repetitions. For emulsion-stabilized soil, the reduction in vertical displacement was 38.5% under a sustained load of 950 cycles. The load carrying capacity was improved by twenty folds. The lateral displacement at the upper first and third layers were lower by 0.55% and 1.9% respectively when compared to cutback asphalt stabilized model

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
A New Model Design for Combating COVID -19 Pandemic Based on SVM and CNN Approaches
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       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

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Publication Date
Tue Jul 11 2023
Journal Name
Journal Of Educational And Psychological Researches
Aunimania Behavior (Compulsive Buying) and Its Relationship to the Histrionic Personality of Primary School Teachers
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The current research aims to identify the level of compulsive buying behavior and Histrionic Personality among a sample of primary school teachers for the academic year (2021-2022) and in the light of some variables

(sex, marital status). To measure the Histrionic Personality, the researcher applied two scales to a random stratified sample of (200) male and female teachers. The results showed statistically significant differences in the level of compulsive buying behavior according to the gender variable and in favor of female teachers. There are no statistically significant differences in terms of marital status. There are statistically significant differences in the Histrionic Personality based on gender variables in favor of f

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Publication Date
Fri Mar 29 2024
Journal Name
Iraqi Journal Of Science
Evaluating the Performance and Behavior of CNN, LSTM, and GRU for Classification and Prediction Tasks
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     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

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Publication Date
Sat Jan 01 2022
Journal Name
Materials Today: Proceedings
Investigating the elastic and plastic behavior of I-steel beams by using carbon fiber laminates
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Publication Date
Mon Mar 31 2014
Journal Name
Al-khwarizmi Engineering Journal
Corrosion Behavior of V2AlC and Cr2AlC Compared with SS 316L in NaOH at Four Temperatures
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Abstract

      This work involves the manufacturing of MAX phase materials include V2AlC and Cr2AlC using powder metallurgy as a new class of materials which characterized by regular crystals in lattice. Corrosion behavior of these materials was investigated by Potentiostat to estimate corrosion resistance and compared with the most resistant material represented by SS 316L. The experiments were carried out in 0.01N of NaOH solution at four temperatures in the range of 30–60oC. Polarization resistance values which calculated by Stern-Geary equation indicated that the MAX phase materials more resistant than SS 316L. Also cyclic polarization tests confirme

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Publication Date
Wed Sep 22 2021
Journal Name
The Structural Design Of Tall And Special Buildings
Utilizing I‐shaped shear links as dampers to improve the behavior of concentrically braced frames
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Publication Date
Sun Dec 14 2014
Journal Name
Molecular Crystals And Liquid Crysta
Synthesis and Mesomorphic Behavior of Two New Homologous Series Containing Azobenzene and 1,3,4-Oxadiazole Units
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Two new nonsymmetrical mesogenic homologous series of terminal substituent ether (series [Vn]) and carboxy (series [VIn]) incorporating azobenzene and 1,3,4-oxadiazole group were synthesized. Both series have been All compounds thus isolated were purified and characterized by elemental analysis, Fourier Transform Infrared Spectroscopy, 1H NMR, along with thermal analysis and texture observation using Differential Scanning Calorimetry (DSC) and Polarizing Optical Microscopy (POM), respectively. All compounds of the first series exhibited liquid crystalline properties. The homologues [V1]-[V3] display a nematic mesophase, the compounds [V4]-[V7] exhibit a dimorphism behavior, nematic (N) and smectic A (SmA) mesophases, the compounds [V8] and

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Publication Date
Wed Mar 18 2009
Journal Name
Molecular Crystals And Liquid Crystals
Synthesis and Mesomorphic Behavior of Some Novel Compounds Containing 1,3,4-Thiadiazole and 1,2,4-Triazole Rings
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Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
Modeling of Corrosion Rate Under Two Phase Flow in Horizontal Pipe Using Neural Network
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The present study develops an artificial neural network (ANN) to model an analysis and a simulation of the correlation between the average corrosion rate carbon steel and the effective parameter Reynolds number (Re), water concentration (Wc) % temperature (T o) with constant of PH 7 . The water, produced fom oil in Kirkuk oil field in Iraq from well no. k184-Depth2200ft., has been used as a corrosive media and specimen area (400 mm2) for the materials that were used as low carbon steel pipe. The pipes are supplied by Doura Refinery . The used flow system is all made of Q.V.F glass, and the circulation of the two –phase (liquid – liquid ) is affected using a Q.V.F pump .The input parameters of the model consists of Reynolds number , w

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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Engineering
Galvanic Corrosion of Carbon Steel -Stainless Steel Couple in Sulfuric Acid under Flow Conditions
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Galvanic corrosion of stainless steel 316 (SS316) and carbon steel (CS) coupled in 5% wt/v sulfuric acid solution at agitation velocity was investigated. The galvanic behavior of coupled metals was also studied using zero resistance ammeter (ZRA) method. The effects of agitation velocity, temperature, and time on galvanic corrosion current and loss in weight of both metals in both free corrosion and galvanic corrosion were investigated. The trends of open circuit potential (OCP) of each metal and galvanic potential (Eg) of the couple were, also, determined. Results showed that SS316 was cathodic relative to CS in galvanic couple and its OCP was much more positive than that of CS for all investigated ranges of

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