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The Experimental and Theoretical Effect of Fire on the Structural Behavior of Laced Reinforced Concrete Deep Beams
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A Laced Reinforced Concrete (LRC) structural element comprises continuously inclined shear reinforcement in the form of lacing that connects the longitudinal reinforcements on both faces of the structural element. This study conducted a theoretical investigation of LRC deep beams to predict their behavior after exposure to fire and high temperatures. Four simply supported reinforced concrete beams of 1500 mm, 200 mm, and 240 mm length, width, and depth, respectively, were considered. The specimens were identical in terms of compressive strength (  40 MPa) and steel reinforcement details. The same laced steel reinforcement ratio of 0.0035 was used. Three specimens were burned at variable durations and steady-state temperatures (one hour at 500 °C and 600 °C, and two hours at 500 °C). The flexural behavior of the simply supported deep beams, subjected to the two concentric loads in the middle third of the beam, was investigated with ABAQUS software. The results showed that the laced reinforcement with an inclination of 45˚ improved the structural behavior of the deep beams, and the lacing resisted failure and extended the life of the model. The optimal structural response was observed for the specimens. The laced reinforcement improved the failure mode and converted it from shear to flexure-shear failure. The parametric study showed that the lacing bars remarkably improved the strength of the deep beams and they were not affected more by the steady-state temperature and duration. Furthermore, a greater increase in load-carrying capacity was associated with an increase in the flexural diameter of approximately 12 and 16 mm by approximately 24.77% and 87.61%, respectively, compared to the reference LRC deep beams.

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Publication Date
Fri Sep 26 2025
Journal Name
Applied Data Science And Analysis
Deep Learning in Genomic Sequencing: Advanced Algorithms for HIV/AIDS Strain Prediction and Drug Resistance Analysis
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Genome sequencing has significantly improved the understanding of HIV and AIDS through accurate data on viral transmission, evolution and anti-therapeutic processes. Deep learning algorithms, like the Fined-Tuned Gradient Descent Fused Multi-Kernal Convolutional Neural Network (FGD-MCNN), can predict strain behaviour and evaluate complex patterns. Using genotypic-phenotypic data obtained from the Stanford University HIV Drug Resistance Database, the FGD-MCNN created three files covering various antiretroviral medications for HIV predictions and drug resistance. These files include PIs, NRTIs and NNRTIs. FGD-MCNNs classify genetic sequences as vulnerable or resistant to antiretroviral drugs by analyzing chromosomal information and id

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Publication Date
Tue Apr 16 2024
Journal Name
International Development Planning Review
THE EFFECT OF THE IMPERATIVE METHOD IN TEACHING PHYSICAL EDUCATION CURRICULA FOR THE PRIMARY STAGE
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Y Adnan, H Atiyah, IH Neamah…, International Development Planning Review, 2024

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Publication Date
Wed Mar 15 2023
Journal Name
International Journal Of Advances In Intelligent Informatics
An automatic lip reading for short sentences using deep learning nets
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One study whose importance has significantly grown in recent years is lip-reading, particularly with the widespread of using deep learning techniques. Lip reading is essential for speech recognition in noisy environments or for those with hearing impairments. It refers to recognizing spoken sentences using visual information acquired from lip movements. Also, the lip area, especially for males, suffers from several problems, such as the mouth area containing the mustache and beard, which may cover the lip area. This paper proposes an automatic lip-reading system to recognize and classify short English sentences spoken by speakers using deep learning networks. The input video extracts frames and each frame is passed to the Viola-Jone

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Publication Date
Wed Sep 30 2015
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Kick tolerance control during well drilling in southern Iraqi deep wells
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The importance of kick tolerance in well operations has recently increased due to its implications in well design, in drilling and well control. To study a simple method for the application of kick tolerance concept in an effective way on the basis of field data, this research purpose is to improve knowledge about Kick Tolerance and represents a technical basis for the discussion on revision of standard procedure.

   The objective of this work is to review and to present a methodology of determination the kick tolerance parameters using the circulation kicks tolerance concepts.

   The proposed method allows to know, to evaluate and to analyze the kick tolerance problem in order to make the drilling exe

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Indoor/Outdoor Deep Learning Based Image Classification for Object Recognition Applications
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With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se

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Publication Date
Tue Sep 01 2015
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Kick tolerance control during well drilling in southern Iraqi deep wells
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The importance of kick tolerance in well operations has recently increased due to its implications in well design, in drilling and well control. To study a simple method for the application of kick tolerance concept in an effective way on the basis of field data, this research purpose is to improve knowledge about Kick Tolerance and represents a technical basis for the discussion on revision of standard procedure. The objective of this work is to review and to present a methodology of determination the kick tolerance parameters using the circulation kicks tolerance concepts. The proposed method allows to know, to evaluate and to analyze the kick tolerance problem in order to make the drilling execution safer and more economical by reducin

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
An Effective Hybrid Deep Neural Network for Arabic Fake News Detection
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Recently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural

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Publication Date
Thu Dec 16 2021
Journal Name
Translational Vision Science & Technology
A Hybrid Deep Learning Construct for Detecting Keratoconus From Corneal Maps
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Publication Date
Thu Apr 11 2019
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
STUDY THE MICROBIAL CONTAMINATION OF BROKEN AND CRACKED COMMERCIAL TABLE EGG IN BAGHDAD MARKETS AND ITS ECONOMIC EFFECT: STUDY THE MICROBIAL CONTAMINATION OF BROKEN AND CRACKED COMMERCIAL TABLE EGG IN BAGHDAD MARKETS AND ITS ECONOMIC EFFECT
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The aim of this novel native study was to determine the microbial contamination of broken and cracked imported commercial table egg in Baghdad markets and its economic effect. A total of 21510 commercial chicken table eggs were checked and surveyed from retail markets in different popular regions of Baghdad city during a year period from January 3rd to December 28th of 2018 and its microbial contamination were studied. Results revealed that significant differences (P<0.01) were appeared in the studied microbial counts during months of the study and significant differences (P<0.01) in the average counts between broken and cracked eggs and sound (not bro

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Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Engineering
Simulation and Experimental Walking Pattern Generation for Two Types of Degrees of Freedom Bipedal Locomotion Robot
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Humanoids or bipedal robots are other kinds of robots that have legs. The balance of humanoids is the general problem in these types when the other in the support phase and the leg in the swing phase. In this work, the walking pattern generation is studied by MATLAB for two types of degrees of freedom, 10 and 17 degrees of freedom. Besides, the KHR-2HV simulation model is used to simulate the experimental results by Webots. Similarly, Arduino and LOBOT LSC microcontrollers are used to program the bipedal robot. After the several methods for programming the bipedal robot by Arduino microcontroller, LOBOT LSC-32 driver model is the better than PCA 96685 Driver-16 channel servo driver for programming the bipedal walking rob

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