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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
Mon May 11 2020
Journal Name
Baghdad Science Journal
A Cryptosystem for Database Security Based on TSFS Algorithm
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Implementation of TSFS (Transposition, Substitution, Folding, and Shifting) algorithm as an encryption algorithm in database security had limitations in character set and the number of keys used. The proposed cryptosystem is based on making some enhancements on the phases of TSFS encryption algorithm by computing the determinant of the keys matrices which affects the implementation of the algorithm phases. These changes showed high security to the database against different types of security attacks by achieving both goals of confusion and diffusion.

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Publication Date
Thu Mar 31 2016
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Permeability Prediction in One of Iraqi Carbonate Reservoir Using Hydraulic Flow Units and Neural Networks
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Permeability determination in Carbonate reservoir is a complex problem, due to their capability to be tight and heterogeneous, also core samples are usually only available for few wells therefore predicting permeability with low cost and reliable accuracy is an important issue, for this reason permeability predictive models become very desirable.

   This paper will try to develop the permeability predictive model for one of  Iraqi carbonate reservoir from core and well log data using the principle of Hydraulic Flow Units (HFUs). HFU is a function of Flow Zone Indicator (FZI) which is a good parameter to determine (HFUs).

   Histogram analysis, probability analysis and Log-Log plot of Reservoir Qua

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Publication Date
Sun Sep 01 2019
Journal Name
Journal Of Physics: Conference Series
The combined effectiveness of magnetic force and heat\mass transfer on peristaltic transportation “Hyperbolic Tangent” Nanofluid in a Slopping Non-Regular Non-symmetric Channel.
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Abstract<p>in the present article, we present the peristaltic motion of “Hyperbolic Tangent nanofluid” by a porous area in a two dimensional non-regular a symmetric channel with an inclination under the impact of inclination angle under the impact of inclined magnetic force, the convection conditions of “heat and mass transfer” will be showed. The matter of the paper will be further simplified with the assumptions of long wave length and less “Reynolds number”. we are solved the coupled non-linear equations by using technical analysis of “Regular perturbation method” of series solutions. We are worked out the basic equations of continuity, motion, temperature, and volume fraction</p> ... Show More
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Publication Date
Tue Dec 26 2017
Journal Name
Al-khwarizmi Engineering Journal
Fuzzy Wavenet (FWN) classifier for medical images
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    The combination of wavelet theory and neural networks has lead to the development of wavelet networks. Wavelet networks are feed-forward neural networks using wavelets as activation function. Wavelets networks have been used in classification and identification problems with some success.

  In this work we proposed a fuzzy wavenet network (FWN), which learns by common back-propagation algorithm to classify medical images. The library of medical image has been analyzed, first. Second, Two experimental tables’ rules provide an excellent opportunity to test the ability of fuzzy wavenet network due to the high level of information variability often experienced with this type of images.

&n

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Publication Date
Tue Jun 01 2021
Journal Name
2021 Ieee/cvf Conference On Computer Vision And Pattern Recognition Workshops (cvprw)
Alps: Adaptive Quantization of Deep Neural Networks with GeneraLized PositS
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Publication Date
Sun Sep 06 2009
Journal Name
Baghdad Science Journal
Influence of Immersion Period on the Corrosion Behavior of Heat Treated Biomedical Alloy Ti -5Al - 2.5Fe
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Heat treatment by solid solution method in the ?+? phase region was used at 970°C for Ti-5Al-2.5Fe alloy. The specimens cooled under different cooling media [water quenched (WQ), air cooled (AC) and furnace cooled (FC)], and subsequently aged at 550°C for 4 hours. Five specimens from each treatment were immersed in simulated body fluid SBF for a period of time (3 months). The dependence of corrosion rate on compositional variation in the phases resulted from various type of cooling rates are discussed based on immersion tests. The EDXA results show the precipitation of phosphate and calcium compounds on the alloy after 3 months of immersion in blood plasma solution forming a bone-like apatite, which enhanced the alloy biocompatibility ma

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Publication Date
Fri Mar 15 2019
Journal Name
Al-khwarizmi Engineering Journal
Studying the effect of Different wt % AL2O3 Nanoparticles of 2024Al Alloy / AL2O3 Composites on Mechanical Properties
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The nanocompsite of alumina (Al2O3) produced a number of beneficial effects in alloys. There is increasing in resistance of materials to surface related failures , such as the mechanical properties , fatigue and stress corrosion cracking .The experimental results observed that the adding of reinforced  nanomaterials  type Al2O3  enhanced the   HB hardness, UTS, 0.2 YS and ductility of 2014 Al/Al2O3 nano composites . the analysis of experiments, indicated that The maximum enhancement was observed at 0.4 wt.% Al2O3. The ultimate improvement percentage were 15.78% HB hardness, 18.1% (UTS), 12.86% (

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Publication Date
Sat Dec 01 2018
Journal Name
Al-khwarizmi Engineering Journal
Simulation of Temperature Distribution in TIG Spot Welds of (Al-Mg) Alloy Using Finite Element Method
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      This research concern to analyse and simulate the temperature distribution in the spot welding joints using tungsten arc welding shielded with inert gas (TIG Spot) for the aluminum-magnesium alloy type  (5052-O).

      The effect of and the quantity of the heat input that enter the weld zone has been investigated welding current, welding time and arc length on temperature distribution. The finite element method (by utilizing programme ANSYS 5.4) is presented  the temperature distribution in a circular weld pool and the weld pool penetration (depth of welding) through the top sheet ,across the interface into the lower sheet forming a weld spot.   &nbs

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Publication Date
Thu Dec 28 2017
Journal Name
Al-khwarizmi Engineering Journal
Mathematical Modeling of Glucose Regulation System in Term of Perturbed Coefficients
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In this research a recent developed practical modeling technique is applied for the glucose regulation system identification. By using this technique a set of mathematical models is obtained instead of single one to compensate for the  loss of information caused by the optimization technique in curve fitting algorithms, the diversity of members inside the single set is interpreted in term of restricted range of its parameters, also a diagnosis criteria is developed for detecting any disorder in the glucose regulation system by investigating the influence of variation of the parameters on the response of the system, this technique is applied in this research practically  for 20 cases with association of  National Center for

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Publication Date
Sat Jul 28 2018
Journal Name
Journal Of Engineering
Effectiveness of Meso-Scale Approach in Modeling of Plain Concrete Beam
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The main aim of this research paper is investigating the effectiveness and validity of Meso-Scale Approach (MSA) as a modern technique for the modeling of plain concrete beams. Simply supported plain concrete beam was subjected to two-point loading to detect the response in flexural. Experimentally, a concrete mix was designed and prepared to produce three similar standard concrete prisms for flexural testing. The coarse aggregate used in this mix was crushed aggregate. Numerical Finite Element Analysis (FEA) was conducted on the same concrete beam using the meso-scale modeling. The numerical model was constructed to be a bi-phasic material consisting of cement mortar and coarse aggregate. The interface between the two c

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