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Experimental Evaluation and Finite Element Simulation to Produce Square Cup by Deep Drawing Process
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Deep drawing process to produce square cup is very complex process due to a lot of process parameters which control on this process, therefore associated with it many of defects such as earing, wrinkling and fracture. Study of the effect of some process parameters to determine the values of these parameters which give the best result, the distributions for the thickness and depths of the cup were used to estimate the effect of the parameters on the cup numerically, in addition to experimental verification just to the conditions which give the best numerical predictions in order to reduce the time, efforts and costs for producing square cup with less defects experimentally is the aim of this study. The numerical analysis is used to study the effect of some parameters such as die profile radius, radial clearance between die and punch, blank diameter on the length and thickness  distributions on the cup, dynamic-explicit (ANSYS11) code based on finite element method is utilized to simulate the square deep drawing operation. Experiments were done for comparison and verification the numerical predictions. effective square cup with less defects and acceptable thickness distributions were produced in this study. It is concluded  the most thinning appear in the corner cup due to excessive stretching occur in this region and also it is found the cup thickness and height prediction by numerical analysis and in general in harmony with experimental analysis.

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Publication Date
Sun Jun 02 2024
Journal Name
Journal Of Communicable Diseases
Evaluation of Susceptibility of Candida species to Six Antifungal Drugs in Iraqi Specimens
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Introduction: Candida spp. has become increasingly resistant to antifungal drugs, with elevated MIC levels causing a negative medical impact and increasing the number of patients at risk of candidiasis. According to the CDC, about 7% of Candida blood samples show reduced susceptibility to fluconazole. Monitoring the antifungal resistance profile of Candida spp. is vital, as non-Albicans species may limit treatment options. Objective: Evaluate the antifungal effectiveness against clinical Candida spp. isolates of six antifungals: amphotericin B, fluconazole, voriconazole, itraconazole, caspofungin, and 5-fluorocytosine. Methods: 100 samples were collected from various clinical samples at the National Centre of Teaching Laboratories

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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
Thu Nov 29 2018
Journal Name
Civil Engineering Journal
Strength and Serviceability of Reinforced Concrete Deep Beams with Large Web Openings Created in Shear Spans
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Deep beams are used in wide construction fields such as water tanks, foundations, and girders in multi-story buildings to provide certain areas free of columns. In practice it is quite often occurring to create web opening in deep beams to supply convenient passage of ventilation ducts, cable channels, gas and water pipes. Experimental studies of ten 10 deep beams were carried out, where two of them are control specimens without openings and eight with large web openings in the shear spans. The variables that have been adopted are the ratio of the shear span to the overall depth of the member cross-section, location and dimensions of the opening. Test results showed that there was a decrease in the load carrying capacity of deep bea

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Publication Date
Thu Nov 29 2018
Journal Name
Civil Engineering Journal
Strength and Serviceability of Reinforced Concrete Deep Beams with Large Web Openings Created in Shear Spans
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Deep beams are used in wide construction fields such as water tanks, foundations, and girders in multi-story buildings to provide certain areas free of columns. In practice it is quite often occurring to create web opening in deep beams to supply convenient passage of ventilation ducts, cable channels, gas and water pipes. Experimental studies of ten 10 deep beams were carried out, where two of them are control specimens without openings and eight with large web openings in the shear spans. The variables that have been adopted are the ratio of the shear span to the overall depth of the member cross-section, location and dimensions of the opening. Test results showed that there was a decrease in the load carrying capacity of deep bea

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Publication Date
Tue Jun 22 2021
Journal Name
Expert Systems
Hybrid intelligent technology for plant health using the fusion of evolutionary optimization and deep neural networks
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Publication Date
Fri Apr 14 2023
Journal Name
Journal Of Big Data
A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications
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Abstract<p>Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for</p> ... Show More
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Publication Date
Thu Dec 01 2022
Journal Name
Iaes International Journal Of Artificial Intelligence
Reduced hardware requirements of deep neural network for breast cancer diagnosis
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Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration

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Publication Date
Sat Apr 01 2023
Journal Name
The Ocular Surface
Detecting dry eye from ocular surface videos based on deep learning
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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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