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The effect of Laser Shock Peening on Fatigue Life Using Pure Water and Hydrofluoric Acid As a Confining Layer of Al – Alloy 7075-T6
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Laser shock peening (LSP) is deemed as a deep-rooted technology for stimulating compressive residual stresses below the surface of metallic elements. As a result, fatigue lifespan is improved, and the substance properties become further resistant to wear and corrosion. The LSP provides more unfailing surface treatment and a potential decrease in microstructural damage. Laser shock peening is a well-organized method measured up to the mechanical shoot peening. This kind of surface handling can be fulfilled via an intense laser pulse focused on a substantial surface in extremely shorter intervals. In this work, Hydrofluoric Acid (HF) and pure water as a coating layer were utilized as a new technique to improve the properties and to harden the treated surface of the Al -alloy 7075-T6. Fatigue life by means of laser peened workpieces was improved to 154.3%, 9.78%, respectively, for Hydrofluoric (HF) and pure water compared to un-peened specimens. And the outcomes of Vickers hardness test for laser shock peening with acid and pure water as well as un-peened specimens were 165.2HV30, 143.95HV30 and 134.7HV30, respectively showed a significant improvement in the hardness property.

 

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Publication Date
Mon May 08 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Using Restricted Least Squares Method to Estimate and Analyze the Cobb-Douglas Production Function with Application
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  In this paper, the restricted least squares method is employed to estimate the parameters of the Cobb-Douglas production function and then analyze and interprete the results obtained.         A practical application is performed on the state company for leather industries in Iraq for the period (1990-2010).         The statistical program SPSS is used to perform the required calculations.

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Publication Date
Sat Jun 27 2020
Journal Name
Iraqi Journal Of Science
The Performance Differences between Using Recurrent Neural Networks and Feedforward Neural Network in Sentiment Analysis Problem
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 With the spread use of internet, especially the web of social media, an unusual quantity of information is found that includes a number of study fields such as psychology, entertainment, sociology, business, news, politics, and other cultural fields of nations. Data mining methodologies that deal with social media allows producing enjoyable scene on the human behaviour and interaction. This paper demonstrates the application and precision of sentiment analysis using traditional feedforward and two of recurrent neural networks (gated recurrent unit (GRU) and long short term memory (LSTM)) to find the differences between them. In order to test the system’s performance, a set of tests is applied on two public datasets. The firs

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Publication Date
Wed May 01 2024
Journal Name
Heliyon
Determining the bacterial and viral meningitis trend in Iraq from 2007 till 2023 using joinpoint regression
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Publication Date
Tue Jun 01 2021
Journal Name
Iraqi Journal Of Physics
A Study of Crystallographic and DC Electrical Characteristics of PPy/Ag Nanocomposites
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ABSTRACT: Polypyrrole and polypyrrole / silver nanocomposites were fabricated by in-situ polymerization employing Ammonium Persulphate as an oxidizing agent. Nanocomposites were synthesized by combining polypyrrole and silver nanoparticles in various weight percentages (0.1%, 0.5%, 3%, 5% and 7% wt.). Crystallographic data were collected using X-ray diffraction.  PPy particles were found to have an orthorhombic symmetry. In contrast, PPy/Ag nanocomposites were reported to have monoclinic structure. The crystallite size was determined by XRD using Scherrer equation and considered to be within 49 nm range. DC conductivity of pelletized samples was evaluated in the temperature range of 323.15k to 453.15k. The conductiv

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Publication Date
Tue Jun 01 2021
Journal Name
Iraqi Journal Of Physics
A Study of Crystallographic and DC Electrical Characteristics of PPy/Ag Nanocomposites
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ABSTRACT: Polypyrrole and polypyrrole / silver nanocomposites were fabricated by in-situ polymerization employing Ammonium Persulphate as an oxidizing agent. Nanocomposites were synthesized by combining polypyrrole and silver nanoparticles in various weight percentages (0.1%, 0.5%, 3%, 5% and 7% wt.). Crystallographic data were collected using X-ray diffraction.  PPy particles were found to have an orthorhombic symmetry. In contrast, PPy/Ag nanocomposites were reported to have monoclinic structure. The crystallite size was determined by XRD using Scherrer equation and considered to be within 49 nm range. DC conductivity of pelletized samples was evaluated in the temperature range of 323.15k to 453.15k. The conductivity displayed an

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Publication Date
Mon Aug 01 2022
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
A survey of deepfakes in terms of deep learning and multimedia forensics
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Artificial intelligence techniques are reaching us in several forms, some of which are useful but can be exploited in a way that harms us. One of these forms is called deepfakes. Deepfakes is used to completely modify video (or image) content to display something that was not in it originally. The danger of deepfake technology impact on society through the loss of confidence in everything is published. Therefore, in this paper, we focus on deepfakedetection technology from the view of two concepts which are deep learning and forensic tools. The purpose of this survey is to give the reader a deeper overview of i) the environment of deepfake creation and detection, ii) how deep learning and forensic tools contributed to the detection

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Publication Date
Sun Nov 01 2020
Journal Name
Journal Of Oral And Maxillofacial Surgery
A Clinicopathologic Review of 21 Cases of Head and Neck Primary Tuberculosis
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Purpose A diagnosis of tuberculosis (TB) of the head and neck has been a dilemma for clinicians, because the clinical and pathologic features tend to mimic different pathologies. Our study aimed to identify the demographic, clinical, and pathologic features of head and neck TB to help healthcare providers in the early detection of the disease. Materials and Methods We performed a retrospective analysis using the medical archives at the pathology laboratory. Twenty-one patients with a clinical and pathologic diagnosis of head and neck TB were identified from 2010 to 2019. Results The age distribution was broad, with 28.5% of the patients younger than 15 years old. Seven patients had oral TB, with the most common sites affected the labial ves

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Publication Date
Wed Feb 01 2023
Journal Name
Chemical Engineering Research And Design
Nickel removal from simulated wastewater using a novel bio-electrochemical cell with packed bed rotating cylinder cathode
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Publication Date
Tue Jun 01 2010
Journal Name
Al-khwarizmi Engineering Journal
Land Use/Cover Change Analysis Using Remote Sensing Data: A Case Study, Zhengzhou Area, Henan Province, China
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In the last two decades, arid and semi-arid regions of China suffered rapid changes in the Land Use/Cover Change (LUCC) due to increasing demand on food, resulting from growing population. In the process of this study, we established the land use/cover classification in addition to remote sensing characteristics. This was done by analysis of the dynamics of (LUCC) in Zhengzhou area for the period 1988-2006. Interpretation of a laminar extraction technique was implied in the identification of typical attributes of land use/cover types. A prominent result of the study indicates a gradual development in urbanization giving a gradual reduction in crop field area, due to the progressive economy in Zhengzhou. The results also reflect degradati

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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
A Modified Support Vector Machine Classifiers Using Stochastic Gradient Descent with Application to Leukemia Cancer Type Dataset
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Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca

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