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alkej-322
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 the surface roughness of incremental forming parts along and across tool path direction. The data required has been generate, compare and evaluate to the proposed models that obtained from SPIF experiments.

Simulated Annealing Algorithm (SAA) is utilized to develop an effective mathematical model to predict optimum level. In simulated algorithm (SA), an exponential cooling schedule depending on Newtonian cooling process is used and by choosing the number of iterations at each step on the experimental work is done. The SA algorithm is used to predict the forming parameters (speed, feed and step size) on surface quality in forming process of Al 1050 based on Taguchi‘s orthogonal array of L9 and (ANOVA) analysis of variance were used to find the best factors that effect on  the surface quality.

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Publication Date
Mon Feb 17 2025
Journal Name
Bmc Nursing
Explaining the barriers and facilitators of the accreditation process in maternity departments
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Publication Date
Fri Mar 01 2024
Journal Name
Iaes International Journal Of Artificial Intelligence (ij-ai)
Analyzing the behavior of different classification algorithms in diabetes prediction
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<span lang="EN-US">Diabetes is one of the deadliest diseases in the world that can lead to stroke, blindness, organ failure, and amputation of lower limbs. Researches state that diabetes can be controlled if it is detected at an early stage. Scientists are becoming more interested in classification algorithms in diagnosing diseases. In this study, we have analyzed the performance of five classification algorithms namely naïve Bayes, support vector machine, multi layer perceptron artificial neural network, decision tree, and random forest using diabetes dataset that contains the information of 2000 female patients. Various metrics were applied in evaluating the performance of the classifiers such as precision, area under the c

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Publication Date
Wed Mar 01 2017
Journal Name
Neural Computing And Applications
The potential of nonparametric model in foundation bearing capacity prediction
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Publication Date
Thu Feb 26 2026
Journal Name
Risalat Al-huquq Journal
The role of the Basel committee in reducing systemic risks that threaten systemically important.
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Publication Date
Mon Mar 30 2020
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Optimization of Hole Cleaning and Cuttings Removal in High Inclined Till Horizontal Well
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The goal of this experimental study is to determine the effects of different parameters (Flow rate, cuttings density, cuttings size, and hole inclination degree) on hole cleaning efficiency. Freshwater was used as a drilling fluid in this experiment. The experiments were conducted by using flow loop consist of approximately 14 m (46 ft) long with transparent glass test section of 3m (9.84 ft.) long with 4 inches (101.6 mm) ID, the inner metal drill pipe with 2 inches (50.8 mm) OD settled with eccentric position positive 0.5. The results obtained from this study show that the hole cleanings efficiency become better with high flow rate (21 m3/hr) and it increase as the hole inclination angles increased from 60 to 90 degree due to dominated

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Publication Date
Sun Sep 02 2012
Journal Name
Baghdad Science Journal
Study Of Factors Affecting The Thermal Conductivity Of Iraqi Bentonite
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Thermal conductivity of compacted bentonite is one of the most important properties where this type of clay is proposed for use as a buffer material. In this study, Lee's disc method was used to measure the thermal conductivity of compacted bentonite specimens. The experimental results have been analyzed to observe the three major factors affecting the thermal conductivity of bentonite buffer material. While the clay density reaches to a target value, the measurement is taken to evaluate the thermal conductivity. By repeating this procedure, a relationship between clay dry density and thermal conductivity has been established in specimens after adjusting the water contents of the bentonite by placing its specimens in a drying oven for diffe

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Publication Date
Mon Dec 30 2002
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Study of the Factors Affecting Cells of Sodium Perchlorate Production
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Publication Date
Mon Jun 30 2003
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Study of the Factors Affecting Cells of Sodium Chlorate Production
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Publication Date
Wed Jul 01 2015
Journal Name
Political Sciences Journal
Factors affecting the future of Iraq's production of crude oil
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As the major role of oil sector in financing and development of Iraqi economy this study tried to research on the factors which influencing the future of oil production in Iraq and for that study addressed the hypothesis (the production and export of crude oil in Iraq , influenced by many factors divided into internal and external factors this factors shared the effect varies in the size of their participation and runs from different sectors economic , political and social , in order to test the study hypothesis study addressed the subject of three axes(an overview of the history and facts of crude oil production in Iraq and factors internal Affecting the future of oil production in Iraq and external factors affecting the future

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Publication Date
Fri Sep 01 2023
Journal Name
Journal Of Engineering
Dual Stages of Speech Enhancement Algorithm Based on Super Gaussian Speech Models
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Various speech enhancement Algorithms (SEA) have been developed in the last few decades. Each algorithm has its advantages and disadvantages because the speech signal is affected by environmental situations. Distortion of speech results in the loss of important features that make this signal challenging to understand. SEA aims to improve the intelligibility and quality of speech that different types of noise have degraded. In most applications, quality improvement is highly desirable as it can reduce listener fatigue, especially when the listener is exposed to high noise levels for extended periods (e.g., manufacturing). SEA reduces or suppresses the background noise to some degree, sometimes called noise suppression alg

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