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On the Impact of Lacing Reinforcement Arrangement on Reinforced Concrete Deep Beams Performance
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The optimum design is characterized by structural concrete components that can sustain loads well beyond the yielding stage. This is often accomplished by a fulfilled ductility index, which is greatly influenced by the arrangement of the shear reinforcement. The current study investigates the impact of the shear reinforcement arrangement on the structural response of the deep beams using a variety of parameters, including the type of shear reinforcement, the number of lacing bars, and the lacing arrangement pattern. It was found that lacing reinforcement, as opposed to vertical stirrups, enhanced the overall structural response of deep beams, as evidenced by test results showing increases in ultimate loads, yielding, and cracking of 30.6, 20.8, and 100%, respectively. There was also a 53.6% increase in absorbed energy at the ultimate load. The shear reinforcement arrangement had a greater impact and a significant effect on the structural response than the number of lacing bars. For lacing reinforcement with a phase difference equivalent to the half-lacing cycle (i.e., phase lag lacing), the percentage of improvement under different loading stages was 6.7-27.1% and 20.8-113.3%, respectively. The structural responses are significantly impacted by the lacing arrangement; members with two and three lacing bars, respectively, exhibited improvements in ultimate load of 30.6% and 47%. Beyond the yielding stage, the phase lag lacing specimens deviated from those without phase lag lacing and normal shear stirrups because of the lacing contribution. Phase lag specimens showed more strain than specimens without phase lag lacing, meaning that the lacing reinforcement contributed more to the beam strength. It was found that the first shear cracking load of all the laced reinforced specimens was higher than that of the conventional shear stirrup specimens. Phase lag lacing produced the greatest improvement, with two bars achieving 92.44% and three bars achieving 217.07%. For the aforementioned number of bars, lacing shear reinforcement without phase lag was less successful, with 36.91% and 46.53%, respectively. Doi: 10.28991/CEJ-2025-011-02-019 Full Text: PDF

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Publication Date
Sun Jan 01 2023
Journal Name
The Egyptian Journal Of Hospital Medicine
Training of Skilled Force with The Different Medical Ball and Their Effect on Developing Some Special Physical Abilities and the Accuracy of Long Shooting Performance in Handball
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Publication Date
Tue Jun 01 2021
Journal Name
Iop Conference Series: Earth And Environmental Science
Simulation of Syngas Addition Effect on Emissions Characteristics, Combustion, and Performance of the Diesel Engine Working under Dual Fuel Mode and Lambda Value of 1.6.
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Abstract<p>The present work aims to study the combustion characteristics related to syngas-diesel dual-fuel engine operates at lambda value of 1.6 operated by five different replacement ratios (RR) of syngas with diesel, which are (10%, 20%, 30 %, 40 % and 50%). ANSYS Workbench (CFD) was used for simulating the combustion of the syngas-diesel dual-fuel engine. The numerical simulations were carried out on the Ricardo-Hydra diesel engine. The simulation results revealed that the diesel engine’s combustion efficiency was enhanced by increasing the diesel replacement with Syngas fuel. The diesel engine’s combustion efficiency The peak in-cylinder temperature was enhanced from 915.9K to 2790.5K </p> ... Show More
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Publication Date
Fri Dec 30 2011
Journal Name
Al-kindy College Medical Journal
The Role of the Use of Low Molecular Weight Heparin in the Prevention of Deep Venous Thrombosis after Total Knee Arthroplasty
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Background A prospective clinical study was
performed to compare the efficacy of the use of lowmolecular-
weight heparin group (enoxparin group)
with control group in the prevention of deep-vein
thrombosis after total knee arthroplasty.
Aim of the study: to assess the prevalence of DVT
after total knee arthroplasty and evaluate the
importance of the use of low molecular weight
heparin in the prevention of this DVT.
Methods Thirty-three patients undergoing total
knee arthroplasty were randomly divided into two
groups. One group consisted of 12 patients who
received no prophylaxis with an anticoagulant (the
control group), other group consisted of 21 patients
who received the low-molecular-weight h

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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
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
Mon Jan 09 2023
Journal Name
2023 15th International Conference On Developments In Esystems Engineering (dese)
Deep Learning-Based Speech Enhancement Algorithm Using Charlier Transform
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Publication Date
Mon Jul 01 2019
Journal Name
Iop Conference Series: Materials Science And Engineering
On Estimation of the Stress – Strength Reliability Based on Lomax Distribution
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Abstract<p>The present paper concerns with the problem of estimating the reliability system in the stress – strength model under the consideration non identical and independent of stress and strength and follows Lomax Distribution. Various shrinkage estimation methods were employed in this context depend on Maximum likelihood, Moment Method and shrinkage weight factors based on Monte Carlo Simulation. Comparisons among the suggested estimation methods have been made using the mean absolute percentage error criteria depend on MATLAB program.</p>
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