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Smoothing Image using Adaptive Median Filter
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Median filter is adopted to match the noise statistics of the degradation seeking good quality smoothing images. Two methods are suggested in this paper(Pentagonal-Hexagonal mask and Scan Window Mask), the study involved modified median filter for improving noise suppression, the modification is considered toward more reliable results. Modification median filter (Pentagonal-Hexagonal mask) was found gave better results (qualitatively and quantitatively ) than classical median filters and another suggested method (Scan Window Mask), but this will be on the account of the time required. But sometimes when the noise is line type the cross 3x3 filter preferred to another one Pentagonal-Hexagonal with few variation. Scan Window Mask gave better results qualitatively when removing line noise than another filters, also will be on the account of the time required.

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Publication Date
Fri Dec 15 2023
Journal Name
Journal Of Baghdad College Of Dentistry
Comparing the effectiveness of using three different re-mineralizing pastes on remineralisation of artificially induced white spot lesion
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Background: This study aimed to compare the surface microhardness (MH) and mineral content of white spot lesions(WSLs) after using bioactive glass (BAG)casein phosphopep-tides-amorphous calcium phosphate(CPP-ACP),and nanohydroxyapatite(Nano-HAP) under pHcycling. Material and method:18 sound maxillary first premolar were used for the study.10 were selected for the vickers microhardness test, For Energy-dispersive X-ray spectroscopy analysis (EDX), the remaining 8 premolar teeth were used, 40 sections of enamel blocks (Four from each tooth) were produced from the middle part of the buccal and palatal surfaces of teeth for MH test while 48 sections of enamel blocks (Six from each tooth) were produced for EDX analysis. Enamel slabs were

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Publication Date
Wed Oct 01 2025
Journal Name
Chinese Journal Of Analytical Chemistry
Synthesis, characterization, antioxidant and bioactivity assessment, and thermodynamic analysis of metal ion complexes using a novel azo dye
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Publication Date
Wed Aug 06 2014
Journal Name
Arabian Journal Of Geosciences
Mineralogy texture and chemistry of the Ellicott meteorite using scanning electron microscope and energy disperse spectroscopy (SEM/EDS)
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Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Cybersecurity And Information Management
A New Automated System Approach to Detect Digital Forensics using Natural Language Processing to Recommend Jobs and Courses
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A resume is the first impression between you and a potential employer. Therefore, the importance of a resume can never be underestimated. Selecting the right candidates for a job within a company can be a daunting task for recruiters when they have to review hundreds of resumes. To reduce time and effort, we can use NLTK and Natural Language Processing (NLP) techniques to extract essential data from a resume. NLTK is a free, open source, community-driven project and the leading platform for building Python programs to work with human language data. To select the best resume according to the company’s requirements, an algorithm such as KNN is used. To be selected from hundreds of resumes, your resume must be one of the best. Theref

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Publication Date
Sun Jun 07 2009
Journal Name
Baghdad Science Journal
The adsorption-desorption process as a method for separation of nitrogen-carbon dioxide gas mixture using activated carbon
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Gas adsorption phenomenon on solid surface has been used as a mean in separation and purification of gas mixture depending on the difference in tendencies of each component in the gas mixture to be adsorbed on the solid surface according to its behaviour. This work concerns to study the possibilities to separate the gas mixture using adsorption-desorption phenomenon on activated carbon. The experimental results exhibit good separation factor at temperature of -40 .

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Publication Date
Thu Mar 31 2022
Journal Name
Iraqi Geological Journal
Development of New Models to Determine the Rheological Parameters of Water-Based Drilling Fluid using Artificial Neural Networks
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It is well known that drilling fluid is a key parameter for optimizing drilling operations, cleaning the hole, and managing the rig hydraulics and margins of surge and swab pressures. Although the experimental works represent valid and reliable results, they are expensive and time consuming. In contrast, continuous and regular determination of the rheological fluid properties can perform its essential functions during good construction. The aim of this study is to develop empirical models to estimate the drilling mud rheological properties of water-based fluids with less need for lab measurements. This study provides two predictive techniques, multiple regression analysis and artificial neural networks, to determine the rheological

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Publication Date
Tue Nov 07 2023
Journal Name
Innovative Infrastructure Solutions
Enhancing load-bearing performance of hybrid recycled aggregate concrete-filled columns using SBR, steel fibers and polypropylene fibers
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Publication Date
Thu Jul 01 2021
Journal Name
Energy
Experimental investigations of the performance of a flat-plate solar collector using carbon and metal oxides based nanofluids
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Publication Date
Thu Aug 29 2024
Journal Name
Materials
Experimental Study to Investigate the Performance-Related Properties of Modified Asphalt Concrete Using Nanomaterials Al2O3, SiO2, and TiO2
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The dual nature of asphalt binder necessitates improvements to mitigate rutting and fatigue since it performs as an elastic material under the regime of rapid loading or cold temperatures and as a viscous fluid at elevated temperatures. The present investigation assesses the effectiveness of Nano Alumina (NA), Nano Silica (NS), and Nano Titanium Dioxide (NT) at weight percentages of 0, 2, 4, 6, and 8% in asphalt cement to enhance both asphalt binder and mixture performance. Binder evaluations include tests for consistency, thermal susceptibility, aging, and workability, while mixture assessments focus on Marshall properties, moisture susceptibility, resilient modulus, permanent deformation, and fatigue characteristics. NS notably im

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Publication Date
Fri Sep 30 2022
Journal Name
Journal Of The Iraqi University
Exclusion optimal portfolio from outlier by using fuzzy c-means clustering - analytical research at the Iraqi Stock Exchange
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This research aims to solve the problem of selection using clustering algorithm, in this research optimal portfolio is formation using the single index model, and the real data are consisting from the stocks Iraqi Stock Exchange in the period 1/1/2007 to 31/12/2019. because the data series have missing values ,we used the two-stage missing value compensation method, the knowledge gap was inability the portfolio models to reduce The estimation error , inaccuracy of the cut-off rate and the Treynor ratio combine stocks into the portfolio that caused to decline in their performance, all these problems required employing clustering technic to data mining and regrouping it within clusters with similar characteristics to outperform the portfolio

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