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Experimental investigation and modelling of residual stresses in face milling of Al-6061-T3 using neural network
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Milling process is a common machining operation that is used in the manufacturing of complex surfaces. Machining-induced residual stresses (RS) have a great impact on the performance of machined components and the surface quality in face milling operations with parameter cutting. The properties of engineering material as well as structural components, specifically fatigue life, deformation, impact resistance, corrosion resistance, and brittle fracture, can all be significantly influenced by residual stresses. Accordingly, controlling the distribution of residual stresses is indeed important to protect the piece and avoid failure. Most of the previous works inspected the material properties, tool parameters, or cutting parameters, but few of them provided the distribution of RS in a direct and singular way. This work focuses on studying and optimizing the effect of cutting speed, feed rate, and depth of cut for 6061-T3 aluminum alloy on the RS of the surface. The optimum values of geometry parameters have been found by using the L27 orthogonal array. Analysis and simulation of RS by using an artificial neural network (ANN) were carried out to predict the RS behavior due to changing machining process parameters. Using ANN to predict the behavior of RS due to changing machining process parameters is presented as a promising method. The milling process produces more RS at high cutting speed, roughly intermediate feed rate, and deeper cut, according to the results. The best residual stress obtained from ANN is ‒135.204 N/mm2 at a cutting depth of 5 mm, feed rate of 0.25 mm/rev and cutting speed of 1,000 rpm. ANN can be considered a powerful tool for estimating residual stress

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of The Mechanical Behavior Of Materials
Influence of water-absorbent polymer balls on the structural performance of reinforced concrete beam: An experimental investigation
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Abstract<p>This research investigated the influence of water-absorbent polymer balls (WAPB) on reinforced concrete beams’ structural behavior experimentally. Four self-compacted reinforced concrete beams of identical geometric layouts 150 mm × 200 mm × 1,500 mm, reinforcement details, and compressive strength <inline-formula> <alternatives> <inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_jmbm-2022-0024_eq_001.png"></inline-graphic> <math xmlns:m="http://www.w3.org/1998/Math/MathML"> <msubsup> <mrow> </mrow></msubsup></math></alternatives></inline-formula></p> ... Show More
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Publication Date
Tue Jun 01 2021
Journal Name
Journal Of Engineering
Experimental Investigation of a Single Basin -Single Slope Solar Still Coupled with Evacuated Tube Solar Collector
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This work is an experimental investigation for single basin-single slope solar still coupled with an evacuated tube solar collector. The work is carried out under the climatic conditions of Baghdad city (33.2456º North and East latitude, 44.3337º longitude) through certain days of the months of the year 2019 to study the impact of using evacuated tube solar collector on the daily productivity and efficiency under the outdoors climatic conditions. It was found that using the evacuated tube solar collector increase daily productivity from 2.175 kg/  to 2.95 kg/ for 9 hours (35.63 %) for clear days, also an enhancement about 10.97 % in daily efficiency.

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Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
Effect of Salt and Osmotic Stresses on the Activity of Some Antioxidant Enzymes and Biochemical Traits in Catharanthus roseus
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Abstract

The experiment has been carried out in the Syrian National Commission of Biotechnology, during the growing season 2018/2019, to study the effect of abiotic stresses (salinity and osmotic stresses) on the activity of some antioxidant enzymes and biochemical traits in Catharanthus roseus. The experiment has been laid according to (CRD) with three replications. The seeds have been sterilized by NaOCl solution (0.5% v/v), then planted on MS medium. Plantlets have been moved to MS medium enriched with NAA (1 mg.L-1) and BA (2 mg.L-1). The callus has been initiated from leaves using MS medium containing NAA (1 mg L-1) and KIN (2 mg.L-1). After 60 days, callus

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Publication Date
Sun Mar 31 2013
Journal Name
Inventi Impact: Artificial Intelligence
SIMULATION OF IDENTIFICATION AND CONTROL OF SCARA ROBOT USING MODIFIED RECURRENT NEURAL NETWORKS
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This paper presents a modified training method for Recurrent Neural Networks. This method depends on the Non linear Auto Regressive (NARX) model with Modified Wavelet Function as activation function (MSLOG) in the hidden layer. The modified model is known as Modified Recurrent Neural (MRN). It is used for identification Forward dynamics of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot. This model is also used in the design of Direct Inverse Control (DIC). This method is compared with Recurrent Neural Networks that used Sigmoid activation function (RS) in the hidden layer and Recurrent Neural Networks with Wavelet activation function (RW). Simulation results shows that the MRN model is bett

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Publication Date
Wed Jun 01 2022
Journal Name
Baghdad Science Journal
Investigating the Effect of Drugs of Chloramphenicol and Gentamicin on Acanthamoeba genotype T3 Causing keratitis Isolated from Environmental samples in vitro
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This study is an investigation of the drugs effect on some pathogenic Acanthamoeba isolated from Iraqi waters, where the problem of environmental adaptation that characterizes this organism in addition to being a reservoir for many pathogenic microorganisms that take shelter in it to escape disinfectants and medicines is sometimes difficult to treat it with traditional treatments.  Twenty water samples were collected from different water regions in Iraq, namely the Dokan Lake, Tigris River, Euphrates River and Najaf Sea, 5 samples from each source.  Acanthamoeba was isolated from water samples on NNA and PYG media, using an inverted microscope with an electron microscope to determine their phenotypic features. PCR and

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Publication Date
Thu Feb 07 2019
Journal Name
Journal Of The College Of Education For Women
SPEECH RECOGNITION OF ARABIC WORDS USING ARTIFICIAL NEURAL NETWORKS
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The speech recognition system has been widely used by many researchers using different
methods to fulfill a fast and accurate system. Speech signal recognition is a typical
classification problem, which generally includes two main parts: feature extraction and
classification. In this paper, a new approach to achieve speech recognition task is proposed by
using transformation techniques for feature extraction methods; namely, slantlet transform
(SLT), discrete wavelet transforms (DWT) type Daubechies Db1 and Db4. Furthermore, a
modified artificial neural network (ANN) with dynamic time warping (DTW) algorithm is
developed to train a speech recognition system to be used for classification and recognition
purposes. T

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Publication Date
Tue Mar 30 2021
Journal Name
Baghdad Science Journal
Future of Mathematical Modelling: A Review of COVID-19 Infected Cases Using S-I-R Model
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The spread of novel coronavirus disease (COVID-19) has resulted in chaos around the globe. The infected cases are still increasing, with many countries still showing a trend of growing daily cases. To forecast the trend of active cases, a mathematical model, namely the SIR model was used, to visualize the spread of COVID-19. For this article, the forecast of the spread of the virus in Malaysia has been made, assuming that all Malaysian will eventually be susceptible. With no vaccine and antiviral drug currently developed, the visualization of how the peak of infection (namely flattening the curve) can be reduced to minimize the effect of COVID-19 disease. For Malaysians, let’s ensure to follow the rules and obey the SOP to lower the

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Publication Date
Thu Nov 01 2018
Journal Name
International Journal Of Science And Research (ij
Mathematical Models for Predicting of Organic and Inorganic Pollutants in Diyala River Using AnalysisNeural Network
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Diyala river is the most important tributaries in Iraq, this river suffering from pollution, therefore, this research aimed to predict organic pollutants that represented by biological oxygen demand BOD, and inorganic pollutants that represented by total dissolved solids TDS for Diyala river in Iraq, the data used in this research were collected for the period from 2011-2016 for the last station in the river known as D17, before the river meeting Tigris river in Baghdad city. Analysis Neural Network ANN was used in order to find the mathematical models, the parameters used to predict BOD were seven parameters EC, Alk, Cl, K, TH, NO3, DO, after removing the less importance parameters. While the parameters that used to predict TDS were fourte

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Publication Date
Fri Feb 01 2019
Journal Name
Environmental Technology &amp; Innovation
The use of Artificial Neural Network (ANN) for modeling of Cu (II) ion removal from aqueous solution by flotation and sorptive flotation process
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Publication Date
Sat Jul 28 2018
Journal Name
Journal Of Engineering
Experimental and Numerical Analysis of Expanded Pipe using Rigid Conical Shape
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The experimental and numerical analysis was performed on pipes suffering large plastic deformation through expanding them using rigid conical shaped mandrels, with three different cone angles (15◦, 25◦, 35◦) and diameters (15, 17, 20) mm. The experimental test for the strain results investigated the expanded areas. A numerical solution of the pipes expansion process was also investigated using the commercial finite element software ANSYS. The strains were measured for each case experimentally by stamping the mesh on the pipe after expanding, then compared with Ansys results. No cracks were generated during the process with the selected angles. It can be concluded that the strain decreased with greater angles of con

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