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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
Wed Dec 13 2017
Journal Name
Al-khwarizmi Engineering Journal
Using Activated Carbon developed from Iraqi Date Palm Seeds as Permeable Reactive Barrier for Remediation of Groundwater Contaminated with Copper
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The possibility of using activated carbon developed from date palm seeds wastes as a permeable reactive barrier (PRB) to remove copper from polluted shallow groundwater was investigated. The activated carbon has been developed from date palm seeds by dehydrating methods using concentrated sulfuric acid. Batch tests were performed to characterize the equilibrium sorption properties of new activated carbon in copper-containing aqueous solutions, while the sandy soil (aquifer) was assumed to be inert. Under the studied conditions, the Langmuir isotherm model gives a better fit for the sorption data of copper by activated carbon than other models. At a pilot scale, One-dimensional column experiments were performed, and an integrated model ba

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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
Sun Jan 01 2023
Journal Name
Journal Of Molecular Liquids
Theoretical modeling study on preparation of nanosized drugs using supercritical-based processing: Determination of solubility of Chlorothiazide in supercritical carbon dioxide
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Publication Date
Tue Oct 02 2018
Journal Name
Iraqi Journal Of Physics
Nonlinear optical properties of polymer [PMMA] thin films doped with dye lasing compounds, Rhodamine 6G and Acriflavine in chloroform solvent by using dip coating method
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The fluorescence emission of Rhodamine 6G (R6G) and Acriflavine dyes in PMMA polymer have been studied by changing the irradiation and exposure time of laser light to know the effect of this parameter. It was found that the fluorescence intensity decreases in the polymer samples doped dyes as the exposure time increases and then reaches stabilization at long times, this behavior called photobleaching, which have been shown in liquid phase less than solid phase. Using 2nd harmonic with wavelength 530 nm laser, the photobleaching effect in the two dye-doped polymers different solvent but same was studied. It was observed that photobleaching of by different solution and by using dip spin coating the photobleaching seem in liquid phase more

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Publication Date
Tue Oct 02 2018
Journal Name
Iraqi Journal Of Physics
Nonlinear optical properties of polymer [PMMA] thin films doped with dye lasing compounds, Rhodamine 6G and Acriflavine in chloroform solvent by using dip coating method
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The fluorescence emission of Rhodamine 6G (R6G) and Acriflavine dyes in PMMA polymer have been studied by changing the irradiation and exposure time of laser light to know the effect of this parameter. It was found that the fluorescence intensity decreases in the polymer samples doped dyes as the exposure time increases and then reaches stabilization at long times, this behavior called photobleaching, which have been shown in liquid phase less than solid phase. Using 2nd harmonic with wavelength 530 nm laser, the photobleaching effect in the two dye-doped polymers different solvent but same was studied. It was observed that photobleaching of by different solution and by using dip spin coating the photobleaching seem in liquid phase

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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
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
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
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Computer, Communication, Control And System Engineering
Unmasking Deepfakes Based on Deep Learning and Noise Residuals
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The main reason for the emergence of a deepfake (deep learning and fake) term is the evolution in artificial intelligence techniques, especially deep learning. Deep learning algorithms, which auto-solve problems when giving large sets of data, are used to swap faces in digital media to create fake media with a realistic appearance. To increase the accuracy of distinguishing a real video from fake one, a new model has been developed based on deep learning and noise residuals. By using Steganalysis Rich Model (SRM) filters, we can gather a low-level noise map that is used as input to a light Convolution neural network (CNN) to classify a real face from fake one. The results of our work show that the training accuracy of the CNN model

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