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Detecting dry eye from ocular surface videos based on deep learning
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Publication Date
Mon Dec 18 2017
Journal Name
Al-khwarizmi Engineering Journal
Optimization and Prediction of Process Parameters in SPIF that Affecting on Surface Quality Using Simulated Annealing Algorithm
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Incremental sheet metal forming is a modern technique of sheet metal forming in which a uniform sheet is locally deformed during the progressive action of a forming tool. The tool movement is governed by a CNC milling machine. The tool locally deforms by this way the sheet with pure deformation stretching. In SPIF process, the research is concentrate on the development of predict models for estimate the product quality. Using simulated annealing algorithm (SAA), Surface quality in SPIF has been modeled. In the development of this predictive model, spindle speed, feed rate and step depth have been considered as model parameters. Maximum peak height (Rz) and Arithmetic mean surface roughness (Ra) are used as response parameter to assess th

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Publication Date
Tue Jun 30 2015
Journal Name
Al-khwarizmi Engineering Journal
The Influence of the Magnetic Abrasive Finishing System for Cylindrical Surfaces on the Surface Roughness and MRR
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Abstract

Magnetic abrasive finishing (MAF) is one of the advanced finishing processes, which produces a high level of surface quality and is primarily controlled by a magnetic field. This paper study the effect of the magnetic abrasive finishing system on the material removal rate (MRR) and surface roughness (Ra) in terms of magnetic abrasive finishing system for eight of input parameters, and three levels according to Taguchi array (L27) and using the regression model to analysis the output (results). These parameters are the (Poles geometry angle, Gap between the two magnetic poles, Grain size powder, Doze of the ferromagnetic abrasive powder, DC current, Workpiece velocity, Magnetic poles velocity, and Finishi

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Publication Date
Mon May 27 2019
Journal Name
Al-khwarizmi Engineering Journal
Prediction of Process Parameters That Affecting on Surface Roughness in Multi-Point Forming Process Using ANOVA Algorithm
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Multipoint forming process is an engineering concept which means that the working surface of the punch and die is produced as hemispherical ends of individual active elements (called pins), where each pin can be independently, vertically displaced using a geometrically reconfigurable die. Several different products can be made without changing tools saved precious production time. Also, the manufacturing of very expensive rigid dies is reduced, and a lot of expenses are saved. But the most important aspects of using such types of equipment are the flexibility of the tooling. This paper presents an experimental investigation of the effect of three main parameters which are blank holder, rubber thickness and forming speed th

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Publication Date
Sat Nov 15 2025
Journal Name
Baghdad Science Journal
Studying the Corrosion Inhibition Ability of Metoclopramide Drug on the Copper Surface in Seawater and Theoretical Studies
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Protection study of the corrosion behavior of Copper surface was conducted with several concentrations of drug. Experimentally, voltammetric measurements were used to check the inhibition efficiency (% IE) in saline solution of 3.5% NaCl. The results showed an increase in the inhibition efficiency with increasing the concentration of the drug was 95.90%. Theoretical treatment of the drug in the gas phase was performed using the (hyperchem-8.07) program for molecular mechanics and semi-empirical computations. The (PM3) approach was used to determine the heat of formation (1H˚f), binding energy (1Eb), and total energy (ET

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Publication Date
Fri Apr 01 2022
Journal Name
Chemical Engineering Science
Numerical modelling of flow through nodes in foams within the “dry” limit in the presence of solid particles
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Publication Date
Mon Feb 04 2019
Journal Name
Journal Of The College Of Education For Women
Effect of Active Learning Strategy on Mathematical Concepts Acquisition in Mathematics for Fourth Grade Primary
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Learn new methods of teaching mathematics contribute to raising the level of pupils to acquire mathematical concepts primary stage
Attempt advancement in the level of mathematics teaching for the better through the use of modern teaching strategies. The research aims at the progress in the acquisition of mathematical concepts schoolgirls after subjecting the fourth grade to teach in active learning strategies, the number of research sample (60) schoolgirl, by (30) schoolgirl experimental group and 30 pupils of the control group. Clear from the results shown the presence of a statistically significant difference between the acquisition of concepts of schoolgirls two groups (experimental and control) for the benefit of pupils of the exp

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Publication Date
Tue May 06 2025
Journal Name
Retos
The effect of the photomagnetic poles strategy on learning the skill of spiking in volleyball
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Objective: preparing educational units for the magnet poles strategy in learning the spiking skill in volleyball, and identifying the effect of the magnet poles strategy in learning the spiking skill in volleyball for female students.Research methodology: The experimental design with two equal experimental and control groups with tight control was also adopted in the pre- and post-tests. The boundaries of this research community are represented by fourth-grade middle school students at Basra Girls' Middle School (2024-2025), whose total number is (90) students, distributed by nature into 4 sections. Sections (A-B) were determined by lottery, so that Section (A) represents the experimental group and Section (B) represents the control

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Publication Date
Thu Apr 30 2026
Journal Name
International Journal Of Engineering Pedagogy (ijep)
The Impact of Intelligent Adaptive Learning on Flexible Thinking and Academic Achievement for Undergraduate Students
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In the knowledge society, artificial intelligence (AI) forms a cornerstone of global education. This quasi-experimental study examines the impact of an Intelligent Adaptive Learning Strategy (IALS) on flexible thinking (FT) and academic achievement among 60 3rd-year undergraduate students at the College of Education/University of Baghdad (experimental n = 30; control n = 30). The IALS was implemented via an AI-supported educational platform, while the control group received conventional instruction. Post-test intervention assessments included an FT test (10 items, content validity = 0.89, Cronbach’s α = 0.87) and an achievement test (10 objective items, α = 0.85). Results revealed statistically significant superiority of the exp

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Publication Date
Sat Jun 01 2019
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Lung cancer classification using data mining and supervised learning algorithms on multi-dimensional data set
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These With recent developments in machine learning, data mining and computer vision, there is great potential for improvements in early detection of lung cancer using scans and data available. This paper details the methods and techniques used in our project, where the objective is to develop algorithms to determine whether a patient has or is likely to develop lung cancer using dataset images using data mining and machine learning for the classification and examination. We explore approaches to address the problem. Cancer is the most important cause of death globally. The disease diagnosis is a major process to treat the patients who are affected by cancer disease. The diagnosis process is more difficult comparatively known about t

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Scopus
Publication Date
Tue Dec 27 2022
Journal Name
2022 3rd Information Technology To Enhance E-learning And Other Application (it-ela)
Diabetes Prediction Using Machine Learning
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Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att

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