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Evaluation of Bond Strength of Acrylic Artificial Teeth with Unreinforced and Nano Silica Reinforced Denture Base Material after Chemical Disinfection
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Soaking dentures with disinfection solutions is an effective way of keeping dentures in a healthy status; however, immersions in these solutions have a negative effect on the bond strength of denture base and denture teeth. The aim of this study was to evaluate the bond strength between denture acrylic teeth and heat-cured Poly (methyl methacrylate) denture base material (with and without nano silica) after disinfection with different chemical disinfectants for a simulated period of six months. One hundred specimens of maxillary central incisors attached to PMMA were divided into two groups; 50 specimens of PMMA without nano silica and 50 specimens of PMMA reinforced with 5 wt% of nano silica. Specimens of each group were immersed in five immersion solutions (n=10): distal water (control), Fittydent® cleansing tablets, 4% chlorohexidine, 1% sodium hypochlorite and Dettol personal care solution. Bond strength were carried out in a universal testing machine with crosshead speed of 0.5 mm/min. Data analysis was done using independent sample t-test, one-way ANOVA and Tukey’s HSD post hoc test. Results showed that bond strength increased significantly in nano silica groups compared to groups without nano silica. Bond strength decreased in all immersion groups, for both groups of PMMA, but the Dettol group showed the least significant decrease (P>0.05). Reinforcing PMMA denture base with nano silica increased the bond strength with acrylic teeth. Denture tablets, chlorohexidine and sodium hypochlorite decreased the bond strength significantly, while Dettol personal care solution did not significantly reduce bond strength.

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Publication Date
Sun Jun 01 2025
Journal Name
International Journal Of Environmental Sciences
Critical Discourse Analysis Of Ideological Interdiscursivity In Selected Artificial Intelligence English Extracts
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The study employs Critical Discourse Analysis (CDA) to analyze how technological discourses are influenced by AI-generate d English texts. The research marries Fairclough’s three-dimensional discourse analysis, Van Dijk’s socio-cognitive approach, and Corpus-Assisted Discourse Studies (CADS) in the use of mixed-methods research, integrating primarily qualitative analysis with quantitative corpus-based data, to perform a thorough analysis of twenty AI-produced English texts. The findings identify the sophisticated linguistic mechanisms through which AI language employs modality, nominalization, passive voice, and interdiscursive blending to normalize and legitimize dominant contemporary ideologies. These mechanisms serve to legitimize te

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Publication Date
Sun Oct 19 2025
Journal Name
Studies In Systems, Decision And Control
The Role of Artificial Intelligence in Achieving Tax Compliance: Evidence from Iraq
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This study focuses on how tax administrations in Iraq use Artificial Intelligence (AI) techniques to monitor tax evasion for individuals and companies to achieve Tax Compliance (TC). AI was measured through four dimensions: Advanced Data Analytics Techniques (ADAT), Explainable AI (EAI), Machine learning (ML), and Robotic Process Automation (RPA). At the same time, TC was measured through registration, accounting, and tax payment stages. We relied on the questionnaire form to measure the variables. A sample of employees in the General Tax Authority in Iraq was selected, and a questionnaire was distributed to 132 people. The results indicated that the dimensions of AI affect achieving TC at all stages. This study provides evidence of using A

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Publication Date
Sun Dec 30 2007
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of Fractional Hold-Up in RDC Column Using Artificial Neural Network
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In the literature, several correlations have been proposed for hold-up prediction in rotating disk contactor. However,
these correlations fail to predict hold-up over wide range of conditions. Based on a databank of around 611
measurements collected from the open literature, a correlation for hold up was derived using Artificial Neiral Network
(ANN) modeling. The dispersed phase hold up was found to be a function of six parameters: N, vc , vd , Dr , c d m / m ,
s . Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 6.52%
and Standard Deviation (SD) 9.21%. A comparison with selected correlations in the literature showed that the
developed ANN correlation noticeably

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Publication Date
Thu Mar 30 2023
Journal Name
Journal Of Economics And Administrative Sciences
An Artificial Intelligence Algorithm to Optimize the Classification of the Hepatitis Type
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Hepatitis is one of the diseases that has become more developed in recent years in terms of the high number of infections. Hepatitis causes inflammation that destroys liver cells, and it occurs as a result of viruses, bacteria, blood transfusions, and others. There are five types of hepatitis viruses, which are (A, B, C, D, E) according to their severity. The disease varies by type. Accurate and early diagnosis is the best way to prevent disease, as it allows infected people to take preventive steps so that they do not transmit the difference to other people, and diagnosis using artificial intelligence gives an accurate and rapid diagnostic result. Where the analytical method of the data relied on the radial basis network to diagnose the

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Publication Date
Thu Mar 21 2019
Journal Name
J. Eng. Appl. Sci
Developing an Arabic handwritten recognition system by means of artificial neural network
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The matter of handwritten text recognition is as yet a major challenge to mainstream researchers. A few ways deal with this challenge have been endeavored in the most recent years, for the most part concentrating on the English pre-printed or handwritten characters space. Consequently, the need to effort a research concerning to Arabic texts handwritten recognition. The Arabic handwriting presents unique technical difficulties because it is cursive, right to left in writing and the letters convert its shapes and structures when it is putted at initial, middle, isolation or at the end of words. In this study, the Arabic text recognition is developed and designed to recognize image of Arabic text/characters. The proposed model gets a single l

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Publication Date
Mon Jun 01 2020
Journal Name
Al-khwarizmi Engineering Journal
Prediction of Cutting Force in Turning Process by Using Artificial Neural Network
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Cutting forces are important factors for determining machine serviceability and product quality. Factors such as speed feed, depth of cut and tool noise radius affect on surface roughness and cutting forces in turning operation. The artificial neural network model was used to predict cutting forces with related to inputs including cutting speed (m/min), feed rate (mm/rev), depth of cut (mm) and work piece hardness (Map). The outputs of the ANN model are the machined cutting force parameters, the neural network showed that all (outputs) of all components of the processing force cutting force FT (N), feed force FA (N) and radial force FR (N) perfect accordance with the experimental data. Twenty-five samp

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Publication Date
Wed Jun 05 2024
Journal Name
International Journal Of Engineering Pedagogy (ijep)
The Impact of Artificial Intelligence on Computational Thinking in Education at University
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This study aims to reveal the role of one of the artificial intelligence (AI) techniques, “ChatGPT,” in improving the educational process by following it as a teaching method for the subject of automatic analysis for students of the Chemistry Department and the subject of computer security for students of the Computer Science Department, from the fourth stage at the College of Education for Pure Science (Ibn Al-Haitham), and its impact on their computational thinking to have a good educational environment. The experimental approach was used, and the research samples were chosen intentionally by the research community. Research tools were prepared, which included a scale for CT that included 12 items and the achievement test in b

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Publication Date
Mon Mar 01 2021
Journal Name
Al-khwarizmi Engineering Journal
Adsorption of Indigo Carmen Dye by Using Corn Leaves as Natural Adsorbent Material
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    In this paper, the ability of using corn leaves as low-cost natural biowaste adsorbent material for the removal of Indigo Carmen (IC) dye was studied. Batch mode system was used to study several parameters such as, contact time (4 days), concentration of dye (10-50) ppm, adsorbent dosage (0.05-0.25) gram, pH (2-12) and temperature (30-60) oC. The corn leaf was characterized by Fourier-transform infrared spectroscopy device before and after the adsorption process of the IC dye and scanning electron microscope device was used to find the morphology of the adsorbent material. The experimental data was imputing with several isotherms where it fits with Freundlich (R2 = 0.9937) and followed pseudo second order kinetic. The hi

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Publication Date
Mon Feb 01 2021
Journal Name
Journal Of Engineering
Decolorizing of Malachite Green Dye by Adsorption Using Corn Leaves as Adsorbent Material
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This paper presents the ability to use cheap adsorbent (corn leaf) for the removal of Malachite Green (MG) dye from its aqueous solution. A batch mode was used to study several factors, dye concentration (50-150) ppm, adsorbent dosage (0.5-2.5) g/L, contact time (1-4) day, pH (2-10), and temperature (30-60)   The results indicated that the removal efficiency increases with the increase of adsorbent dosage and contact time, while inversely proportional to the increase in pH and temperature. An SEM device characterized the adsorbent corn leaves. The adsorption's resulting data were in agreement with Freundlich isotherm according to the regression analysis, and the kinetics data followed pseudo-first-order kinetic with a correlation

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Publication Date
Sun Dec 30 2018
Journal Name
Journal Of Engineering
Abrasive Wear Characteristics of Composite Material (AA 7075 / SiC) Synthesized by Stir Casting
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Aluminum Metal Matrix Composites (ALMMCs) was prepared by using stir casting technique for AA 7075 aluminum alloy as a matrix reinforced with SiC particles at various percentages (3, 6, 9 and 12 wt. % ) and 75µm in grain size. The prepared composite material can be used for many applications such as aerospace, automobiles and many industrial sectors. Abrasive wear test was carried out by two stages: the first stage was done by changing the emery papers at various grit sizes 180, 320, 500, and 1000µm with constant applied load 15N. While the second stage was carried out by changing the applied loads 5, 10, 15, 20 and 25N with constant emery paper at 320 µm grit size. Microstructure examination, hardness test and roughn

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