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Investigation of the performance of integrated intelligent models to predict the roughness of Ti6Al4V end-milled surface with uncoated cutting tool
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Abstract<p>Titanium alloys are broadly used in the medical and aerospace sectors. However, they are categorized within the hard-to-machine alloys ascribed to their higher chemical reactivity and lower thermal conductivity. This aim of this research was to study the impact of the dry-end-milling process with an uncoated tool on the produced surface roughness of Ti6Al4V alloy. This research aims to study the impact of the dry-end milling process with an uncoated tool on the produced surface roughness of Ti6Al4V alloy. Also, it seeks to develop a new hybrid neural model based on the training back propagation neural network (BPNN) with swarm optimization-gravitation search hybrid algorithms (PSO-GSA). Full-factorial design of the experiment with L27 orthogonal array was applied, and three end-milling parameters (cutting speed, feed rate, and axial depth of cut) with three levels were selected (50, 77.5, and 105 m/min; 0.1, 0.15, and 0.2 mm/tooth; and 1, 1.5, and 2 mm) and investigated to show their influence on the obtained surface roughness. The results revealed that the surface roughness is significantly affected by the feed rate followed by the axial depth. A 0.49 µm was produced as a minimum surface roughness at the optimized parameters of 105 m/min, 0.1 mm/tooth, and 1 mm. On the other hand, a neural network having a single hidden layer with 1–20 hidden neurons, 3 input neurons, and 1 output neuron was trained with both PSO and PSO–GSA algorithms. The hybrid BPNN–PSO–GSA model showed its superiority over the BPNN–PSO model in terms of the minimum mean square error (MSE) that was calculated during the testing stage. The best BPNN–PSO–GSA hybrid model was the 3–18–1 structure, which reached the best testing MSE of 3.8 × 10<sup>−11</sup> against 2.42 × 10<sup>−5</sup> of the 3–8–1 BPNN–PSO hybrid model.</p>
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Publication Date
Sun Jan 02 2011
Journal Name
Journal Of Educational And Psychological Researches
Social Tolerance of Baghdad College students and its Relation With Parental Treatment Styles
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The social tolerance is one of the important variables in personality; it helps growth and development of individual's personality. Theories and the students affirmed that social Tolerance affects the society growth and development as well.
The presents study aims:
1. Estimating the social Tolerance for Baghdad College students.
2. Realizing how College students vary in social Tolerance according to:
Sex, (Male, Female) ٍSpecialization (Scientific, Humanity).
3. Realizing the nature of relationship between social Tolerance of College students and father and mother styles. To achieve this research goals the researcher established parameter (scale) for social Tolerance applied to sample of (500) students male and female. Th

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Publication Date
Fri Mar 31 2017
Journal Name
Al-khwarizmi Engineering Journal
Corrosion Behavior of Nanocomposite Al-9 wt% Si Alloy Reinforced with Carbon Nanotubes
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An effort is made to study the effect of composite nanocoating using aluminum-9%wt silicon alloys reinforced with different percentage (0.5,1,2,4)wt.% of carbon nanotubes (CNTs) using  plasma spraying. The effect of this composite on corrosion behavior for AA6061-T6 by extrapolation Tafel test in sea water 3.5wt% NaCl was invested. Many specimens where prepared from AA6061-T6 by the dimension (15x15x3)mm as this first set up and other steps include coating process, X-ray diffraction and SEM examination .The results show the CNTs increase the corrosion rate of the nanocomposite coatings with increasing the weight percentage of CNTs within the Al-Si matrix. Al-9wt%Si coating layer itself has less corrosion rate if compared with both n

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Publication Date
Sat Apr 15 2023
Journal Name
Journal Of Robotics
A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

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Publication Date
Sun Jun 06 2021
Journal Name
Materials
Strengthening of Continuous Reinforced Concrete Deep Beams with Large Openings Using CFRP Strips
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To accommodate utilities in buildings, different sizes of openings are provided in the web of reinforced concrete deep beams, which cause reductions in the beam strength and stiffness. This paper aims to investigate experimentally and numerically the effectiveness of using carbon fiber reinforced polymer (CFRP) strips, as a strengthening technique, to externally strengthen reinforced concrete continuous deep beams (RCCDBs) with large openings. The experimental work included testing three RCCDBs under five-point bending. A reference specimen was prepared without openings to explore the reductions in strength and stiffness after providing large openings. Openings were created symmetrically at the center of spans of the other specimens

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Publication Date
Fri Sep 22 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Spectrophotometric Determination of Chlorpromazine -HCI by Ion -Pair Complex Formation with Acid Dyes
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A simple, rapid, accurate and sensitive spectrophotometric method is  proposed  for  the  detennination  of chlorprQm<tZine -HCl  in  pwe form  and  in pharmaceutical  formulation. This method is based on the formation.  of ion  assodation complexes  of  dmg   with either  thymol

blue or  bromophenol  blue  in an acidic buffer at pH  values 4.17  and

3.68, respectively.

The ion-pair  complexes  formed exhibit absorption maxima  at 41 Onm for  both  thymol   blue and  bromophenol  blue.  These  complexes· are quantitatively extracted  &n

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Publication Date
Fri Nov 09 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Assessment of stressful life events for patients with substance abuse in Baghdad city
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Objective: The present study aims to assess the stressful life events for patients with substance abuse in Baghdad city.
Methodology: A descriptive study was carried out at (Baghdad teaching hospital and Ibn-Rushed Psychiatric hospital).
Starting from 1
st of December 2012 to 3
rd of July 2013, A non-probability (purposive) sample of 64 patients that
diagnosed with substance abuse, the data were collected through the use of semi-structured interview by
questionnaire, which consists of three parts sociodemographic data, medical information, and Life events scale
consists of 49-items distributed to six domains including, family and social domain, health domain, security, legal and
criminal domain, work and school do

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Publication Date
Fri Jun 17 2022
Journal Name
International Journal Of Health Sciences
Corrosion inhibitor of carbon steel in 3.5%NaCl solution with Schiff base compounds
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In this work, synthesized N4,N4`-bis(2, 3, 4 nitro benzylidene) biphenyi-4-4`-diamine(B1-B3) , was tested as an inhibitors in controlling the corrosion of carbon steel in NaCl 3.5% solution by using open circuit potential (OCP),at four different temperatures (293, 303, 313 and 323 K). Furthermore, the surface morphology was investigated using the Atomic force microscopy (AFM). The effect of using different Schiff bases and temperature was also investigated. Schiff bases was synthesized and characterized via using. Fourier Transform Infrared Spectroscopy (FT-IR)and Atomic Force Microscope (AFM) characterized . The experimental results shown that Schiff bases can consider as an excellent corrosion inhibitors for carbon steel in NaCl 3

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Publication Date
Mon Feb 01 2010
Journal Name
Food Chemistry
Determination of aflatoxins in animal feeds by HPLC with multifunctional column clean-up
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A reversed-phase HPLC method with fluorescence detection for the determination of the aflatoxins B1, B2, G1 and G2 in 42 animal feeds, comprising corn (16), soya bean meal (8), mixed meal (13), sunflower, wheat, canola, palm kernel, copra meals (1 each) was carried out. The samples were first extracted using acetonitrile:water (9:1), and was further cleaned-up using a multifunctional column. Optimum conditions for the extraction and chromatographic separation were investigated. By adopting an isocratic chromatographic system using a mobile phase comprising acetonitrile:methanol:water (8:27:65, v/v/v), the separation of the four aflatoxins was possible within 30 min. Recoveries for aflatoxins B1, B2, G1 and G2 were 98 ± 0.7%, 95 ± 1.0%, 94

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Publication Date
Tue Feb 26 2019
Journal Name
Journal Of Contemporary Medical Sciences
Demographic and clinical profiles of female patients diagnosed with breast cancer in Iraq
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Objective To highlight the main demographic characteristics and clinical profiles of female patients registered with breast cancer in Iraq; focusing on the impact of age.Methods This retrospective study enrolled 1172 female patients who were diagnosed with breast cancer at the Main Center for Early Detection of Breast Cancer/Medical City Teaching Hospital in Baghdad. Data were extracted from an established information system, developed by the principal author under supervision of WHO, that was based on valid clinical records of Iraqi patients affected by breast cancer. The recorded information regarding clinical examination comprised positive palpable lumps, bloody nipple discharge, skin changes, bilateral breast involvement, tumor

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Publication Date
Sat Apr 15 2023
Journal Name
Journal Of Robotics
A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

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