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Mineral Inversion Approach to Improve Ahdeb Oil Field's Mineral Classification
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Knowledge of the mineralogical composition of a petroleum reservoir's formation is crucial for the petrophysical evaluation of the reservoir. The Mishrif formation, which is prevalent in the Middle East, is renowned for its mineralogical complexity. Multi-mineral inversion, which combines multiple logs and inversions for multiple minerals at once, can make it easier to figure out what minerals are in the Mishrif Formation. This method could help identify minerals better and give more information about the minerals that make up the formation. In this study, an error model is used to find a link between the measurements of the tools and the petrophysical parameters. An error minimization procedure is subsequently applied to determine the optimal solution. The quality curve is useful for assessing the model's reliability and data depth. Gamma rays and traditional logs both show that calcite and dolomite are the most common matrix minerals in the Mishrif Formation. The clay minerals present in the formation are smectite, illite, and glauconite. Accurate detection of mineral composition resulted in improved identification of fluid content, particularly free and bound water saturation, and, by extension, hydrocarbon saturation.

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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
Development of an ANN Model for RGB Color Classification using the Dataset Extracted from a Fabricated Colorimeter
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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Classification of Arabic Alphabets Using a Combination of a Convolutional Neural Network and the Morphological Gradient Method
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The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet

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Publication Date
Wed Jul 01 2015
Journal Name
Arabian Journal Of Geosciences
Mishrif carbonates facies and diagenesis glossary, South Iraq microfacies investigation technique: types, classification, and related diagenetic impacts
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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
Development of an ANN Model for RGB Color Classification using the Dataset Extracted from a Fabricated Colorimeter
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Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

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Publication Date
Mon Jan 01 2024
Journal Name
Ieee Access
Transfer Learning and Hybrid Deep Convolutional Neural Networks Models for Autism Spectrum Disorder Classification From EEG Signals
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Publication Date
Wed Jun 22 2022
Journal Name
Journal Of Oral &dental Research
The Antibacterial Effect of Tea Tree Oil, Clove Oil and 3% Sodium Hypochlorite against Enterococcus faecalis in Endodontics: An in vitro Study
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Irrigation has significant role in endodontic treatment, many types of antimicrobial irrigation solutions have been used, but due to the ineffectiveness, safety concerns and side effects of this irrigation, the herbal alternatives for endodontic irrigants might be beneficial. Objectives This study compared the in vitro effectiveness of tea tree oil and clove oil as possible irrigants in endodontics against Enterococcus faecalis in comparison with 3% Sodium hypochlorite. Materials and Methods E. faecalis was isolated from patients in need for endodontic treatment; VITEK was employed for E. faecalis isolate conformation. Muller Hinton agar was prepared with 100μl of freshly prepared suspension of E.faecalis. Wells of 6mm diameter and 4mm dep

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Publication Date
Wed Jun 22 2022
Journal Name
Journal Of Oral &dental Research
The Antibacterial Effect of Tea Tree Oil, Clove Oil and 3% Sodium Hypochlorite against Enterococcus faecalis in Endodontics: An in vitro Study
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Irrigation has significant role in endodontic treatment, many types of antimicrobial irrigation solutions have been used, but due to the ineffectiveness, safety concerns and side effects of this irrigation, the herbal alternatives for endodontic irrigants might be beneficial. Objectives This study compared the in vitro effectiveness of tea tree oil and clove oil as possible irrigants in endodontics against Enterococcus faecalis in comparison with 3% Sodium hypochlorite. Materials and Methods E. faecalis was isolated from patients in need for endodontic treatment; VITEK was employed for E. faecalis isolate conformation. Muller Hinton agar was prepared with 100μl of freshly prepared suspension of E.faecalis. Wells of 6mm diameter and 4mm dep

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Publication Date
Sun Nov 01 2009
Journal Name
Tencon 2009 - 2009 Ieee Region 10 Conference
Optimizing the MPLS support for real time IPv6-Flows using MPLS-PHS approach
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Publication Date
Sun May 01 2016
Journal Name
Iosr Journal Of Computer Engineering
Combining Arabic Nested Noun Compound and Collocation Extraction Using Linguistic and Statistical Approach
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Publication Date
Sun Mar 31 2019
Journal Name
Association Of Arab Universities Journal Of Engineering Sciences
Behavior of Clay Masonry Prism under Vertical Load Using Detailed Micro Modeling Approach
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The aim of this research is to assess the validity of Detailed Micro-Modeling (DMM) as a numerical model for masonry analysis. To achieve this aim, a set of load-displacement curves obtained based on both numerical simulation and experimental results of clay masonry prisms loaded by a vertical load. The finite element method was implemented in DMM for analysis of the experimental clay masonry prism. The finite element software ABAQUS with implicit solver was used to model and analyze the clay masonry prism subjected to a vertical load. The load-displacement relationship of numerical model was found in good agreement with those drawn from experimental results. Evidence shows that load-displacement curvefound from the finite element m

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