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Behavior of Reinforced Concrete Deep Beams Strengthened with Carbon Fiber Reinforced Polymer Strips
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This research is concerned to investigate the behavior of reinforced concrete (RC) deep beams strengthened with carbon fiber reinforced polymer (CFRP) strips. The experimental part of this research is carried out by testing seven RC deep beams having the same dimensions and steel reinforcement which have been divided into two groups according to the strengthening schemes. Group one was consisted of three deep beams strengthened with vertical U-wrapped CFRP strips. While, Group two was consisted of three deep beams strengthened with inclined CFRP strips oriented by 45o with the longitudinal axis of the beam. The remaining beam is kept unstrengthening as a reference beam. For each group, the variable considered was the center to center spacing between strips (orthogonal spacing) which are (100 mm, 125 mm and 150 mm). Based on the experimental results it is found that the strengthening deep beams with CFRP strips by the two strengthening schemes, the mid-span deflection was decreased and both first cracking and ultimate loads capacities were increased compared to reference deep beam. For beams having the same spacing between strips, the enhancement occurred by using vertical U- wrapped scheme was somewhat better than using inclined scheme but it needs to use additional numbers of CFRP strips. The percentages increase in first cracking and ultimate loads were (50.0%, 46.0% and 20.5%) and (14.6%, 13.3% and 12.2%) respectively for beams strengthened with vertical U-wrapped scheme. While these percentages were changed to (36.5%, 18.0% and 12.5%) and (12.5%, 10.4% and 8.6%) for beams strengthened with inclined scheme. These results were obtained for center to center spacing between strips of (100 mm, 125 mm and 150 mm) respectively. The analytical part of this research was also adopted using the ACI 440 Code provisions to calculate the additional shear resistance carried by the CFRP strips. Good agreement was obtained between the experimental and analytical results.  

 

 

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Publication Date
Sat Mar 01 2025
Journal Name
Al-khwarizmi Engineering Journal
Deep-Learning-Based Mobile Application for Detecting COVID-19
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Patients infected with the COVID-19 virus develop severe pneumonia, which typically results in death. Radiological data show that the disease involves interstitial lung involvement, lung opacities, bilateral ground-glass opacities, and patchy opacities. This study aimed to improve COVID-19 diagnosis via radiological chest X-ray (CXR) image analysis, making a substantial contribution to the development of a mobile application that efficiently identifies COVID-19, saving medical professionals time and resources. It also allows for timely preventative interventions by using more than 18000 CXR lung images and the MobileNetV2 convolutional neural network (CNN) architecture. The MobileNetV2 deep-learning model performances were evaluated

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Publication Date
Tue Nov 19 2024
Journal Name
Aip Conference Proceedings
CT scan and deep learning for COVID-19 detection
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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
3D scenes semantic segmentation using deep learning based Survey
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Abstract<p>Semantic segmentation realization and understanding is a stringent task not just for computer vision but also in the researches of the sciences of earth, semantic segmentation decompose compound architectures in one elements, the most mutual object in a civil outside or inside senses must classified then reinforced with information meaning of all object, it’s a method for labeling and clustering point cloud automatically. Three dimensions natural scenes classification need a point cloud dataset to representation data format as input, many challenge appeared with working of 3d data like: little number, resolution and accurate of three Dimensional dataset . Deep learning now is the po</p> ... Show More
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Publication Date
Sat Dec 03 2022
Journal Name
Al-kut University College Of Humanities
Deep understanding skills in chemistry among middle school students
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Publication Date
Mon Jan 01 2024
Journal Name
Computers, Materials &amp; Continua
Credit Card Fraud Detection Using Improved Deep Learning Models
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Publication Date
Mon Apr 19 2021
Journal Name
Bridge Maintenance, Safety, Management, Life-cycle Sustainability And Innovations
Flexure strengthening of concrete bridge girders with concavely curved soffit using near-surface-mounted CFRP bars
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Publication Date
Mon Jun 15 2020
Journal Name
Journal Of Baghdad College Of Dentistry
Effect of plasma treatment on some surface properties of acrylic resin polymer
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Background: Polymer surfaces usually present problems in bonding and finishing due to their low hydrophilicity. The aim of this study is to investigate the effect of plasma treatment with the use of two types of gases (oxygen and argon) on surface roughness, and chemical surface properties of acrylic resin denture base polymer material. Materials and Methods: Three heat cured acrylic resin specimens of (2*8*30 mm) dimensions were prepared for each test carried out in this study. Two tests were conducted, surface roughness test and chemical surface analysis test. Results: Application of plasma treatment increased surface roughness for both oxygen and argon plasma treated acrylic resin specimen groups compared with control untreated group,

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Publication Date
Fri Jul 01 2022
Journal Name
International Journal Of Nonlinear Analysis And Applications
Survey on distributed denial of service attack detection using deep learning: A review
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Distributed Denial of Service (DDoS) attacks on Web-based services have grown in both number and sophistication with the rise of advanced wireless technology and modern computing paradigms. Detecting these attacks in the sea of communication packets is very important. There were a lot of DDoS attacks that were directed at the network and transport layers at first. During the past few years, attackers have changed their strategies to try to get into the application layer. The application layer attacks could be more harmful and stealthier because the attack traffic and the normal traffic flows cannot be told apart. Distributed attacks are hard to fight because they can affect real computing resources as well as network bandwidth. DDoS attacks

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Publication Date
Wed Mar 30 2022
Journal Name
Journal Of Educational And Psychological Researches
Ingratiating Behavior of the University Students
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The current study aims to find out:

  1. The ingratiating behavior of university students.
  2. The differences of statistical significance in The ingratiating behavior among university students according to the variables of sex and specialization

The current study is determined by University of Baghdad students of both genders (males and females) and for both majors (scientific and humanities) for the academic year (2019-2020).

In order to achieve the researcher's objectives:Ingratiating behavior scale has been constructed. It consists in its final form of (32) items divided into four behaviors. The researcher has extracted scale validity and reliability.

The researcher based the two scales

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Publication Date
Fri Sep 15 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Determine, Predict and Map Soil pH Level by Fiber Optic Sensor
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Abstract<p>Soil pH is one of the main factors to consider before undertaking any agricultural operation. Methods for measuring soil pH vary, but all traditional methods require time, effort, and expertise. This study aimed to determine, predict, and map the spatial distribution of soil pH based on data taken from 50 sites using the Kriging geostatistical tool in ArcGIS as a first step. In the second step, the Support Vector Machines (SVM) machine learning algorithm was used to predict the soil pH based on the CIE-L*a*b values taken from the optical fiber sensor. The standard deviation of the soil pH values was 0.42, which indicates a more reliable measurement and the data distribution is normal.</p> ... Show More
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