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alkej-115
Neural Network Modeling of Cutting Force and Chip Thickness Ratio for Turning Aluminum Alloy 7075-T6
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The turning process has various factors, which affecting machinability and should be investigated. These are surface roughness, tool life, power consumption, cutting temperature, machining force components, tool wear, and chip thickness ratio. These factors made the process nonlinear and complicated. This work aims to build neural network models to correlate the cutting parameters, namely cutting speed, depth of cut and feed rate, to the machining force and chip thickness ratio. The turning process was performed on high strength aluminum alloy 7075-T6. Three radial basis neural networks are constructed for cutting force, passive force, and feed force. In addition, a radial basis network is constructed to model the chip thickness ratio. The inputs to all networks are cutting speed, depth of cut, and feed rate. All networks performances (outputs) for all machining force components (cutting force, passive force and feed force) showed perfect match with the experimental data and the calculated correlation coefficients were equal to one. The built network for the chip thickness ratio is giving correlation coefficient equal one too, when its output compared with the experimental results. These networks (models) are used to optimize the cutting parameters that produce the lowest machining force and chip thickness ratio. The models showed that the optimum machining force was (240.46 N) which can be produced when the cutting speed (683 m/min), depth of cut (3.18 mm) and feed rate (0.27 mm/rev). The proposed network for the chip thickness ratio showed that the minimum chip thickness is (1.21), which is at cutting speed (683 m/min), depth of cut (3.18 mm) and feed rate (0.17 mm/rev).

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
Reducing the Mutual Coupling of Cylindrical Circular Microstrip Antennas (CCMAs) Array Using EBG Structure
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A theoretical study to design a conformal microstrip antennas was introduced in this work. Conformal microstrip antennas define antennas which can be conformed to a certain shape or to any curved surface. It is used in high-speed trains, aircraft, defense and navigation systems, landing gear and various communications systems, as well as in body wearable. Conformal antennas have some advantages such as a wider-angle coverage compared to flat antennas and low radar cross-sectional (RCS) and they are suitable for using in Radome. The main disadvantage of these antennas is the narrow bandwidth. The FDTD method is extremely useful in simulating complicated structures because it allows for direct integration of Maxwell's equations depending o

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Publication Date
Thu Mar 12 2020
Journal Name
Al-khwarizmi Engineering Journal
Optimization the Effect of Electrode Material Change on EDM Process Performance Using Taguchi Method
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Electrical Discharge Machining (EDM) is a widespread Nontraditional Machining (NTM) processes for manufacturing of a complicated geometry or very hard metals parts that are difficult to machine by traditional machining operations. Electrical discharge machining is a material removal (MR) process characterized by using electrical discharge erosion. This paper discusses the optimal parameters of EDM on high-speed steel (HSS) AISI M2 as a workpiece using copper and brass as an electrode. The input parameters used for experimental work are current (10, 24 and 42 A), pulse on time (100, 150 and 200 µs), and pulse off time (4, 12 and 25 µs) that have effect on the material removal rate (MRR), electrode wear rate (EWR) and wear ratio (WR). A

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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Effective Solution of University Course Timetabling using Particle Swarm Optimizer based Hyper Heuristic approach
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The university course timetable problem (UCTP) is typically a combinatorial optimization problem. Manually achieving a useful timetable requires many days of effort, and the results are still unsatisfactory. unsatisfactory. Various states of art methods (heuristic, meta-heuristic) are used to satisfactorily solve UCTP. However, these approaches typically represent the instance-specific solutions. The hyper-heuristic framework adequately addresses this complex problem. This research proposed Particle Swarm Optimizer-based Hyper Heuristic (HH PSO) to solve UCTP efficiently. PSO is used as a higher-level method that selects low-level heuristics (LLH) sequence which further generates an optimal solution. The proposed a

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Publication Date
Mon Feb 02 2026
Journal Name
Al–bahith Al–a'alami
Cultural and educational values for children
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Programs directed to children through the media in general and in television in particular are among the main factors that help in forming the cultural and educational values of this important segment of society, and in light of this the study problem was identified in answering a major question: What are the cultural and educational values that Ajyal channel seeks Space planted in children through my program, Iftah Ya Simsim (in its new season) and Friends of Ajyal? , While the objectives of the study were evident in identifying the most prominent cultural and educational values that the Ajyal satellite channel worked to instill in children, and identifying the nature of the techniques used by Ajyal channel in providing the value conten

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Publication Date
Wed Sep 30 2015
Journal Name
College Of Islamic Sciences
Isthmus life and prepare for it
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Isthmus life and prepare for it

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Publication Date
Thu Jan 02 2020
Journal Name
Journal Of The College Of Languages (jcl)
Principles of modeling a dictionary article in the «Dictionary of the Russian Folklore: lexicon epics» (M.A. Bobunova, A.T. Khro: Принципы моделирования словарной статьи В «словаре языка русского фольклора: Лексика былины» (М. А. Бобунова, А. Т. Хроленко)
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The article describes the basic principles of modeling a dictionary article in the “Dictionary of the Language of Russian Folklore Lexicon epics” (M. A. Bobunova, A. T. Khrolenko). Among such principles are the principle of linguocentrism (representation of universal cognitions in strict observance of the traditions of lexicographic science), the principle of anthropocentrism (language learning as a means of human consciousness / subconsciousness), the principle of expansionism (attracting material from various knowledge bases), the principle of explanatory ("explanatory moment"), and fractal principle (synergistic potential of the presented material: nonlinearity and self-similarity; hierarchical organizati

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Publication Date
Tue Jan 23 2018
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
ESTIMATION OF SOME CHEMICAL AND PHYSICAL PROPERTIES USING A WATER TREATMENT UNIT VORTISAND COMPARED TO THEIR CONCENTRATION IN WATER PRODUCED BY TRIDINTINAL DRINKING WATER PROJECTS IN BAGHDAD.: ESTIMATION OF SOME CHEMICAL AND PHYSICAL PROPERTIES USING A WATER TREATMENT UNIT VORTISAND COMPARED TO THEIR CONCENTRATION IN WATER PRODUCED BY TRIDINTINAL DRINKING WATER PROJECTS IN BAGHDAD.
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This study was conducted to determine the ability of water treatment system (Vortisand) to reduce some chemical and physical properties for tigris river raw water, It consisted of turbidity, electrical conductivity, pH, total hardness, calcium Hardness as well as temperature in order to determine the unit`s efficiency for reducing their concentration as compared to those in the water produced by some classical potable water projects (Dora and Wathba) in Baghdad. Samples were collected during the cold months (December 2016 and January 2017) and during the hot months (May and June 2017). The results showed that this system has the ability to reduce some properties such as turbidity, the values were 215NTU in raw water and decreased to NTU

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Publication Date
Sat Dec 01 2018
Journal Name
Al-khwarizmi Engineering Journal
Design and Implementation of an Automatic Control for Two Axis Tracking System for Applications of Concentrated Solar Thermal Power
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The present work presents design and implementation of an automated two-axis solar tracking system using local materials with minimum cost, light weight and reliable structure. The tracking system consists of two parts, mechanical units (fixed and moving parts) and control units (four LDR sensors and Arduino UNO microcontroller to control two DC servomotors). The tracking system was fitted and assembled together with a parabolic trough solar concentrator (PTSC) system to move it according to information come from the sensors so as to keep the PTSC always perpendicular to sun rays. The experimental tests have been done on the PTSC system to investigate its thermal performance in two cases, with tracking system (case 1) and without trackin

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Publication Date
Fri Oct 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Forecasting the financial failure of Islamic banks using the Altman model, ---- springate model and ---- Sherrod model / an analytical study in Islamic banks listed on the Iraq Stock Exchange
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Profit is a goal sought by all banks because it brings them income and guarantees them survival and continuity, and on the other hand, facing commitments without financial crisis. Hence the idea of research in his quest to build scientific tools and means that can help bank management in particular, investors, lenders and others to predict financial failure and to detect early financial failures. The research has produced a number of conclusions, the most important of which is that all Islamic banks sample a safe case of financial failure under the Altman model, while according to the Springate model all Islamic banks sample a search for a financial failure except the Islamic Bank of Noor Iraq for Investment and Finance )BINI(. A

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Publication Date
Fri Mar 29 2024
Journal Name
Iraqi Journal Of Science
Evaluating the Performance and Behavior of CNN, LSTM, and GRU for Classification and Prediction Tasks
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     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

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