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Experimental Study of Pre-Cast Reinforced Concrete Deep Beams (Hallow Core section) Retrofitting with Carbon Fiber Reinforced Polymer (CFRP)
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Experimental programs based test results has been used as a means to find out the response of individual elements of structure. In the present study involves investigated behavior of five reinforced concrete deep beams of dimension (length 1200 x height 300 x width150mm) under two points concentrated load with shear span to depth ratio of (1.52), four of these beams with hallow core and
retrofit with carbon fiber reinforced polymer CFRP (with single or double or sides Strips). Two shapes of hallow are investigated (circle and square section) to evaluated the response of beams in case experimental behavior. Test on simply supported beam was performed in the laboratory & loaddeflection, strain of concrete data and crack pattern of those five reinforced concrete beams was recorded. Parametric studies are also conducted in this study includes the effect of hallow opening (shapes and materials), and CFRP ratio (single, double strips and side horizontal stirrups). Comparisons of test results from experimental data are based on load capacity, deflection, crack pattern and strain of concrete for all beams. From this comparison it was found that hallow effect on strength capacity i.e. decrease by about (13%) and increased in deflection and strain by about (18%, 24%) respectively compared with solid section. Also find that CFRP give more enhancements in loading capacity by about(33 to 66%) and decreased deflection for same applied load by about (26%). Test results that show when sides of beams retrofit with CFRP strip against horizontal shear increased strength by about by (20%). Finally the using double CFRP strips for hallow section gives equivalent or more than strength capacity of solid section. 

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Publication Date
Sat Dec 02 2023
Journal Name
Journal Of Engineering
Deep Learning of Diabetic Retinopathy Classification in Fundus Images
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Diabetic retinopathy is an eye disease in diabetic patients due to damage to the small blood vessels in the retina due to high and low blood sugar levels. Accurate detection and classification of Diabetic Retinopathy is an important task in computer-aided diagnosis, especially when planning for diabetic retinopathy surgery. Therefore, this study aims to design an automated model based on deep learning, which helps ophthalmologists detect and classify diabetic retinopathy severity through fundus images. In this work, a deep convolutional neural network (CNN) with transfer learning and fine tunes has been proposed by using pre-trained networks known as Residual Network-50 (ResNet-50). The overall framework of the proposed

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Publication Date
Wed Jun 01 2022
Journal Name
Results In Engineering
Behavioral nonlinear modeling of prestressed concrete flexural members with internally unbonded steel strands
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Publication Date
Wed Nov 28 2018
Journal Name
International Journal Of Engineering & Technology
Using Polyurethane Coating of Concrete Pipes with Acid Attack Resistance in Sewer Lines
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One of the most important challenges facing the designers of the sewerage system is the corrosion of sewers due to the influence of sewerage contaminates which lead to failure of the main lines of sewers. In this study, a reference mix of 1: 1.5: 3 was used and the 4% Flocrete PC200 by weight of cement was added to the same mixing ratio in the second mixture. Twenty-four samples were tested for each mixture, 12 of which were used to compression strength test in ages (7, 14 and 28) day and six samples were submerged after 28 days of wet treatment at (5 and 10) % concentrations of sulfuric acid. The other six samples were painted after 28 days of wet treatment with coating Polyurethane and after 24 hours were flooded with a concentrat

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Publication Date
Thu Nov 01 2018
Journal Name
Optical Fiber Technology
Enhancing refractive index sensitivity using micro-tapered long-period fiber grating inscribed in biconical tapered fiber
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Publication Date
Tue Feb 12 2019
Journal Name
Iraqi Journal Of Physics
Linear attenuation coefficient measurement in polymer composite
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Linear attenuation coefficient of polymer composite for beta particles and bremsstrahlung ray were investigated as a function of the absorber thickness and energy. The attenuation coefficient were obtained using NaI(Tl) energy selective scintillation counter with 90Sr/90Y beta source having an energy range from 0.1-1.1 MeV. The present results show the capability of this composite to absorber beta particles and bremsstrahlung ray that yield from it. That’s mean it is useful to choice this composite for radiation shielding of beta ray with low thickness.

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Publication Date
Wed Oct 20 2021
Journal Name
Ibn Al- Haitham Journal For Pure And Applied Sciences
Polymer Chain Reaction (PCR): Principle and Applications
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The new, standard molecular biologic system for duplicating DNA enzymatically devoid of employing a living organism, like E. coli or yeast, represents polymerases chain reaction (PCR). This technology allows an exponential intensification of a minor quantity of DNA molecule several times. Analysis can be straightforward with more DNA available. A thermal heat cycler performs a polymerization chain reaction that involves repeated cycles of heating and cooling the reactant tubes at the desired temperature for each reaction step. A heated deck is positioned on the upper reaction tube to avoid evaporating the reaction mixture (normally volumes range from 15 to 100 l per tube), or an oil layer can be placed on a reaction mixture su

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Publication Date
Thu Dec 01 2022
Journal Name
Iaes International Journal Of Artificial Intelligence
Reduced hardware requirements of deep neural network for breast cancer diagnosis
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Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration

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Publication Date
Fri Apr 12 2019
Journal Name
Journal Of Economics And Administrative Sciences
Core competencies and Their Role in Enhancing Organizational flexibility: An Analytical Study of the Views of a Sample of Employees in Presidency University of Mosul
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Abstract

The study aims to identify the levels of core competencies dimensions and types of organizational flexibility in the investigated organization, as well as to determine the nature of the relationship and the impact of core competencies dimensions with the process of organizational flexibility. Thus, a number of research questions were presented to express the research problem as follows:

  • What is the level of the investigated individuals' awareness to core competencies and organizational flexibility across their dimensions and types in the investigated organization?
  • To what extent are core competencies and organizational flexibility available in the Organiz

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Publication Date
Tue Jun 23 2020
Journal Name
Baghdad Science Journal
Anomaly Detection Approach Based on Deep Neural Network and Dropout
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   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

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Publication Date
Mon Mar 01 2021
Journal Name
Al-khwarizmi Engineering Journal
Experimental Study of the Influence of Nanoparticles Additive to Diesel Fuel on the Emission Characteristics
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The present experimental work is conducted to examine the influence of adding Alumina (Al2O3) nanoparticles and Titanium oxide (TiO2) nanoparticles each alone to diesel fuel on the characteristic of the emissions. The size of both Alumina and Titanium oxide nanoparticles which have been added to diesel fuel to obtain nano-fuel is about 20 nm and 25 nm respectively. Three doses of (Al2O3) and (TiO2) were prepared (25, 50, and 100) ppm. The nanoparticles mixed with gas oil fuel by mechanical homogenous (manual electrical mixer) and ultrasonic processor. The study reveals that the adding of Aluminum oxide (Al2O3) and Titanium oxide (TiO2) to g

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