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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
Mon May 01 2023
Journal Name
Journal Of Molecular Liquids
On the influence of hydrocarbons solvents on the inhibition efficiency of some organic corrosion inhibitors: Theoretical and validation studies
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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Petroleum Research And Studies
Stress Ratio Method to Predict Fracture Pressure Gradient in Southern Iraqi Deep Wells
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This research presents a method for calculating stress ratio to predict fracture pressure gradient. It also, describes a correlation and list ideas about this correlation. Using the data collected from four wells, which are the deepest in southern Iraqi oil fields (3000 to 6000) m and belonged to four oil fields. These wells are passing through the following formations: Y, Su, G, N, Sa, Al, M, Ad, and B. A correlation method was applied to calculate fracture pressure gradient immediately in terms of both overburden and pore pressure gradient with an accurate results. Based on the results of our previous research , the data were used to calculate and plot the effective stresses. Many equations relating horizontal effective stress and vertica

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Publication Date
Fri Aug 12 2022
Journal Name
Future Internet
Improved DDoS Detection Utilizing Deep Neural Networks and Feedforward Neural Networks as Autoencoder
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Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Face Recognition and Emotion Recognition from Facial Expression Using Deep Learning Neural Network
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Abstract<p>Face recognition, emotion recognition represent the important bases for the human machine interaction. To recognize the person’s emotion and face, different algorithms are developed and tested. In this paper, an enhancement face and emotion recognition algorithm is implemented based on deep learning neural networks. Universal database and personal image had been used to test the proposed algorithm. Python language programming had been used to implement the proposed algorithm.</p>
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Publication Date
Thu Dec 01 2022
Journal Name
Journal Of Engineering
Deep Learning-Based Segmentation and Classification Techniques for Brain Tumor MRI: A Review
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Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

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Publication Date
Tue Jun 01 2021
Journal Name
Al-khwarizmi Engineering Journal
Effect of Environmental Factors on the Accuracy of a Quality Inspection System Based on Transfer Learning
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In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images. So, this study aimed at testing the system performance at poo

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Publication Date
Wed Dec 01 2021
Journal Name
Journal Of Engineering
Laboratory Study on the Effect of Water-Cement Ratio on Strength Characteristics of Jet Grouting Columns
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Jet grouting is one of the most widely applied soil improvement techniques. It is suitable for most geotechnical problems, including improving bearing capacity, decreasing settlement, forming seals, and stabilizing slopes. One of the difficulties faced by designers is determining the strength and geometry of elements created using this method. Jet grouted soil-cement columns in soil are a complicated issue because they are dependent on a number of parameters such as soil type, grout and water flow rate, rotation and lifting speed of monitor, nozzle jetting force, and water to cement ratio of slurry. This paper discusses the effect of the water-cement ratio on the physical and mechanical characteristics of soilcrete. In t

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Publication Date
Wed May 31 2017
Journal Name
Journal Of Engineering
Construction Policies on Campus An Analytical Study of the Policy of Construction Planning on Kufa Campus
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     University Campuses, as any lively physical entity, is subject to continuous variation due to . growth, development and change. This reality covers the existing or futuristic additives or  additions, consecutively these changes may have a strong sensation of disorientation as a result of formatic changes in buildings, or in movement paths. And it epitomized the research problem to "the need for knowledge to clarify the impact of intellectual and executive policy in achieving coherence, functional and space organization of the elements of the university urban environment and in the stages of future growth and change,"  the search targeted "to highlight the study of constraction politics on campus Bmqomad

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Publication Date
Mon Aug 01 2022
Journal Name
Biochemical And Cellular Archives
EVALUATION OF THE TOXICITY OF DELTAMETHRIN INSECTICIDE ON SOME HEMATOLOGICAL PARAMETERS AND OXIDATIVE STRESS ON MICE
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Publication Date
Tue Jun 01 2021
Journal Name
Al-khwarizmi Engineering Journal
Effect of Environmental Factors on the Accuracy of a Quality Inspection System Based on Transfer Learning
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In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images.

So, this study aimed at testing the system performance at poor s

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