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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
Mon Jan 27 2020
Journal Name
Iraqi Journal Of Science
Deep Belief Network for Predicting the Predisposition to Lung Cancer in TP53 Gene
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Lung cancer, similar to other cancer types, results from genetic changes. However, it is considered as more threatening due to the spread of the smoking habit, a major risk factor of the disease. Scientists have been collecting and analyzing the biological data for a long time, in attempts to find methods to predict cancer before it occurs. Analysis of these data requires the use of artificial intelligence algorithms and neural network approaches. In this paper, one of the deep neural networks was used, that is the enhancer Deep Belief Network (DBN), which is constructed from two Restricted Boltzmann Machines (RBM). The visible nodes for the first RBM are 13 nodes and 8 nodes in each hidden layer for the two RBMs. The enhancer DBN was tr

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Publication Date
Fri Apr 19 2019
Journal Name
Iraqi Journal Of Science
Effect of Photodeposition Time on the Concentration of Silver Nanoparticles on Core of Optical Fiber End
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In this work an experimental study of deposited silver nanoparticles on the core of optical fiber end at different time based on photodeposition technique is presented. The results demonstrated that the concentration of silver nanoparticles deposited on the core of optical fiber end was effected by the deposition time. The photodeposition system was fabricated using multi-mode optical fiber and laser diode source. The results show that the silver deposition concentration increases linearly with the deposition time. The deposition rate was 3.25 (wt/ s)

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Publication Date
Wed Feb 20 2019
Journal Name
Iraqi Journal Of Physics
The effect of volume fraction on the fatigue strength of unsaturated polyester / glass fiber composite
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 In this work polymeric composites were done from unsaturated polyester as a matrix reinforced with glass fiber type (E-glass) with two different volume fraction 20% & 40%. Fatigue tests showed that the number of fatigue cycles to failure limit for samples reinforced with uniform (woven Roving 0-90°) E-glass fiber and random (continuous fibers) with volume fraction 40% more than that for the same samples with volume fraction 20%. Also the fatigue results showed that the uniform samples failed with fatigue cycles more than that of random.

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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Engineering
Preparation and Characterization of Activated Carbon for Adsorption of Fluoroquinolones Antibiotics
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           In this research, the preparation of a chemically activated carbon from date stones by using electric and microwave assisted K2CO3 activation was studied. The effect of radiation power, radiation time, and impregnation ratio on the yield and Iodine number on the activated carbons was investigated. The activated carbon characterizations were examined by its surface area, pore structure analysis, bulk density, moisture content, ash content, iodine number, FTIR, and scanning electron microscopy (SEM). The adsorption capacity was also studied by adsorption of fluoroquinolones antibiotics, CIP, NOR, and LEVO, by the prepared activated carbon.

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Publication Date
Wed Mar 30 2022
Journal Name
Iraqi Journal Of Science
Word Embedding Methods for Word Representation in Deep Learning for Natural Language Processing
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    Natural Language Processing (NLP) deals with analysing, understanding and generating languages likes human. One of the challenges of NLP is training computers to understand the way of learning and using a language as human.  Every training session consists of several types of sentences with different context and linguistic structures. Meaning of a sentence depends on actual meaning of main words with their correct positions. Same word can be used as a noun or adjective or others based on their position. In NLP, Word Embedding is a powerful method which is trained on large collection of texts and encoded general semantic and syntactic information of words. Choosing a right word embedding generates more efficient result than others

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Publication Date
Mon Sep 30 2024
Journal Name
Medical Journal Of Babylon
Effectiveness of Deep Breathing Technique on Pain Level of School Children during Catheterization
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Scopus
Publication Date
Tue Jan 08 2019
Journal Name
Iraqi Journal Of Physics
Refractive index sensor based on a solid-core photonic crystal fiber interferometer
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Photonic crystal fiber interferometers are widely used for sensing applications. In this work, solid core-Photonic crystal fiber based on Mach-Zehnder modal interferometer for sensing refractive index was presented. The general structure of sensor applied by splicing short lengths of PCF in both sides with conventional single mode fiber (SMF-28). To apply modal interferometer theory; collapsing technique based on fusion splicing used to excite higher order modes (LP01 and LP11). Laser diode (1550 nm) has been used as a pump light source. Where a high sensitive optical spectrum analyzer (OSA) was used to monitor and record the transmitted. The experimental work shows that the interference spectrum of Photonic crystal fiber interferometer

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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Polyacrylamide Polymer Gel Systems for Conformance Control Technology: A Review
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Low oil extraction and early high water production are caused in part by reservoir heterogeneity. Huge quantities of water production are prevalent issues that happen in older reservoirs. Polyacrylamide polymer gel systems have been frequently employed as plugging agents in heterogeneous reservoirs to regulate water output and increase sweep efficiency. Polyacrylamide polymer gel systems are classified into three classes depending on their composition and application conditions, which are in-situ monomer gel, in-situ polymer gel, and preformed particle gel (PPG).

   This paper gives a comprehensive review of PPG’s status, preparation, and mechanisms. Many sorts of PPGs are categorized, for example, millimeter-sized preformed p

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Publication Date
Tue May 30 2023
Journal Name
Iraqi Journal Of Science
Deep Convolutional Neural Network Architecture to Detect COVID-19 from Chest X-Ray Images
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      Today, the world is living in a time of epidemic diseases that spread unnaturally and infect and kill millions of people worldwide. The COVID-19 virus, which is one of the most well-known epidemic diseases currently spreading, has killed more than six million people as of May 2022. The World Health Organization (WHO) declared the 2019 coronavirus disease (COVID-19) after an outbreak of SARS-CoV-2 infection. COVID-19 is a severe and potentially fatal respiratory disease caused by the SARS-CoV-2 virus, which was first noticed at the end of 2019 in Wuhan city. Artificial intelligence plays a meaningful role in analyzing medical images and giving accurate results that serve healthcare workers, especially X-ray images, which are co

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Scopus (7)
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Publication Date
Thu Sep 30 2004
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Adsorption of Hydrogen and Methane as Single Gases on Activated Carbon
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