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Prediction of Surface Roughness after Turning of Duplex Stainless Steel (DSS)
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Feed Forward Back Propagation artificial neural network (ANN) model utilizing the MATLAB Neural Network Toolbox is designed for the prediction of surface roughness of Duplex Stainless Steel during orthogonal turning with uncoated carbide insert tool. Turning experiments were performed at various process conditions (feed rate, cutting speed, and cutting depth). Utilizing the Taguchi experimental design method, an optimum ANN architecture with the Levenberg-Marquardt training algorithm was obtained. Parametric research was performed with the optimized ANN architecture to report the impact of every turning parameter on the roughness of the surface. The results suggested that machining at a cutting speed of 355 rpm with a feed rate of 0.07 mm/rev and a depth of cut 0.4 mm was found to achieve lower surface roughness with,  an increase in the cutting speed and feed rate with the increases of the surface roughness. In addition, an increase in the depth of cut was found to reduces the surface roughness. The outcome of this study showed that ANN is a versatile tool for prediction of surface roughness and may be easily extended with greater confidence to various metal cutting processes.

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Publication Date
Wed May 31 2023
Journal Name
International Journal Of Sustainable Development And Planning
Prediction of Formal Transformations in City Structure (Kufa as a Model) Based on the Cellular Automation Model and Markov Chains
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The research utilizes data produced by the Local Urban Management Directorate in Najaf and the imagery data from the Landsat 9 satellite, after being processed by the GIS tool. The research follows a descriptive and analytical approach; we integrated the Markov chain analysis and the cellular automation approach to predict transformations in city structure as a result of changes in land utilization. The research also aims to identify approaches to detect post-classification transformations in order to determine changes in land utilization. To predict the future land utilization in the city of Kufa, and to evaluate data accuracy, we used the Kappa Indicator to determine the potential applicability of the probability matrix that resulted from

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Publication Date
Sun Mar 31 2024
Journal Name
Iraqi Geological Journal
Permeability Prediction and Facies Distribution for Yamama Reservoir in Faihaa Oil Field: Role of Machine Learning and Cluster Analysis Approach
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Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F

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Publication Date
Sat Feb 01 2025
Journal Name
Advanced Journal Of Chemistry, Section A
Synthesis and Characterization of Heterocyclic Derivatives to Evaluate their Efficiency as Corrosion Inhibitors for Carbon Steel in Saline Medium
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This work includes preparation of Az, Qz, and Tz derivatives from the reaction of Schiff base (Sb) derivative with anthranilic acid, chloroacetyl chloride, and sodium azide, as well as, the characterization via FT-IR, 1H-NMR, and 13CNMR. The anticorrosion inhibition of these compounds was studied and the measurements of carbon steel (CS) corrosion in sodium chloride solution 3.5% (blank) and inhibitor in solutions were calculated at a temperature range of 293-323 K by the technique of electrochemical polarization. In addition, some thermodynamic and kinetic activation parameters for inhibitor and blank solutions (Ea⋇, ΔH⋇, ΔS⋇, and ΔG⋇) were determined. The results showed high inhibition efficacy for all the prepared compounds,

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Publication Date
Tue Dec 11 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Prevalence of Posttraumatic Stress Disorder (PTSD) among the Iraqi Repatriated Prisoners of the Iran-Iraq War, 1980-1988
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Objective: To determine the prevalence of Posttraumatic Stress Disorder (PTSD) among Iraqi repatriated
prisoners of Iran-Iraq war, and the relationship with demographic factors.
Methodology: A descriptive study was carried out from Oct. 18th, 2009 through Jan. 10th, 2010. A nonprobability
based snowball sampling technique was used to recruit 92 Iraqi repatriated prisoners of war
(IRPOWs) who had visited Ministry of Human Rights. A data collection instrument was constructed that
consisted of six demographic characteristics, and eight items to measure the level of PTSD in POWs. Data were
collected with the constructed instrument during a brief interview. Data were analyzed through the application of
descriptive statist

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Publication Date
Tue Jun 14 2016
Journal Name
Al-academy
Technical openness in the formation of postmodernism Pop Art Example (An analytical study)
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Addressed the problem of the research is marked (technical openness in the formation of post-modernism - Pop Art an Example) the nature of the technical expansion of the output artifacts postmodern, and the nature of the raw materials taken as components of its sensual. The search came in four sections: general framework for research and identified the research problem and the need for him. With an indication of the importance of his presence. From then select the search goal (revealed openness to hire technical material in the art of Pop Art), followed by the establishment of the three search limits (objectivity, the temporal and spatial) were then determine the terms related to the title. Then provide the theoretical framework and indi

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Publication Date
Wed Dec 13 2017
Journal Name
Al-khwarizmi Engineering Journal
Optimization of Friction Stir Welding Process Parameters of Dissimilar AA2024-T3 and AA7075-T73 Aluminum Alloys by Using Taguchi Method
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The aim of present study is to determine the optimum parameters of friction stir welding process and known the most important parameter along with percentage contribution of each parameter which effect on tensile strength and joint efficiency of FS welded joint of  dissimilar aluminum alloys AA2024-T3 and AA7075-T73 of 3 mm thick plates by applied specific number of experiments using Taguchi method .AA2024 was placed on the advancing side and AA7075 on the retreating side. FSW was achieved under three different rotation speeds (898, 1200 and 1710) rpm, three different welding speeds (20, 45 and 69) mm\min , three different pin profiles (cylindrical, threaded cylindrical and cone) and tool tilt angle 2. Taguchi method w

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Publication Date
Wed Dec 01 2010
Journal Name
Journal Of Economics And Administrative Sciences
التنبؤ بالأحتياجات من أدوية الأمراض المزمنة والمحافظة على المال العام* دراسة تطبيقية في دائرة العيادات الطبية الشعبية
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Abstract                                                                                

The health section is considered to be one of the most important section in the  field of service economical and social unit because of its concern in the life of human begin and society and the  process of determining t

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Publication Date
Mon Dec 25 2017
Journal Name
Biomedical And Pharmacology Journal
Effect of the Addition of Polyamide (Nylon 6) Micro-Particles on Some Mechanical Properties of RTV Maxillofacial Silicone Elastomer Before and After Artificial Aging
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Publication Date
Sun May 01 2016
Journal Name
Journal Of Engineering
Prediction of Ryznar Stability Index for Treated Water of WTPs Located on Al-Karakh Side of Baghdad City using Artificial Neural Network (ANN) Technique
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In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respe

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Publication Date
Sat Sep 04 2021
Journal Name
القانون والعلوم السياسية
المصالح الامريكية في القارة الافريقية بعد عام 2000
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تنشر الولايات المتحدة قوات في جميع دول القارة الافريقية بهدف السيطرة الكاملة عليها وتحقيق اهدافها ومصالحها

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