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Artificial Neural Network Application to Permeability Prediction from Nuclear Magnetic Resonance Log
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Reservoir permeability plays a crucial role in characterizing reservoirs and predicting the present and future production of hydrocarbon reservoirs. Data logging is a good tool for assessing the entire oil well section's continuous permeability curve. Nuclear magnetic resonance logging measurements are minimally influenced by lithology and offer significant benefits in interpreting permeability. The Schlumberger-Doll-Research model utilizes nuclear magnetic resonance logging, which accurately estimates permeability values. The approach of this investigation is to apply artificial neural networks and core data to predict permeability in wells without a nuclear magnetic resonance log. The Schlumberger-Doll-Research permeability is used to train the model, where the model prediction result is validated with core permeability. Seven oil well logs were used as input parameters, and the model was constructed with Techlog software. The predicted permeability with the model compared with Schlumberger-Doll-Research permeability as a cross plot, which results in the correlation coefficient of 94%, while the predicted permeability validated with the core permeability of the well, which obtains good agreement where R2 equals 80%. The model was utilized to forecast permeability in a well that did not have a nuclear magnetic resonance log, and the predicted permeability was cross-plotted against core permeability as a validation step, with a correlation coefficient of 77%. As a result, the low percentage of matching was due to data limitations, which demonstrated that as the amount of data used to train the model increased, so did the precision.

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Publication Date
Fri Mar 01 2024
Journal Name
International Journal Of Medical Informatics
An artificial intelligence approach to predict infants’ health status at birth
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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
Mon Sep 06 2021
Journal Name
Journal Of Mechanical Engineering Research And Developments
Using Micro-Ceramic as an Abrasive Material to Remove Surface Roughness by Magnetic Abrasive Finishing
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Due to the rapid advancement of technology and the technology of things, modern industries start to need a highprecision equipment and surface finishing, so many finishing processes began to develop. One of the modern processes is Magnetic Abrasive Finishing (MAF), which is a high-precision process for internal and external finishing under the influence of a magnetic field of abrasive particles. Boron Carbide (B4C) ceramics was tested by mixing it with iron (Fe) and produced abrasive particles to reduce the intensity of scraping on the surface, reduce the economic cost and achieve a high finishing addition to remove the edges at the same time. The material selected for the samples was mild steel (ASTM E415) under (Quantity of Abrasives, Mac

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Publication Date
Mon Dec 11 2017
Journal Name
Al-khwarizmi Engineering Journal
ptimization the Parameters of Magnetic Abrasive Process Using Taguchi Method to Improve the Surface Roughness
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Abstract  

Magnetic abrasive finishing (MAF) process is one of non-traditional or advanced finishing methods which is suitable for different materials and produces high quality level of surface finish where it uses magnetic force as a machining pressure. A set of experimental tests was planned according to Taguchi orthogonal array (OA) L27 (36) with three levels and six input parameters. Experimental estimation and optimization of input parameters for MAF process for stainless steel type 316 plate work piece, six input parameters including amplitude of tooth pole, and number of cycle between teeth, current, cutting speed, working gap, and finishing time, were performed by design of experiment

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Publication Date
Tue Jan 13 2026
Journal Name
Ibn- Al - Haitham Journal For Pure And Applied Science
Magnetic Properties of Nano-Iron Oxide α-Fe2O3 Prepared in Green Chemistry from Capsicum Plant Extract
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In this study, iron oxide nanoparticles (α-Fe₂O₃ NPs) were prepared using a readily available chili pepper plant extract from local markets. This study aims to evaluate the magnetic properties of α-Fe₂O₃ prepared in green chemistry from Capsicum plant extract. After several simple preparatory steps, such as washing and cutting, they were treated with an inorganic complex (potassium hexacyanoferrate) (K3[Fe(CN)₆]). In the first analytical step, the in vitro detection of the plant extract solution after reaction with the potassium hexacyanoferrate (III) complex revealed characteristic adsorption bands of the cyanide group, which disappeared upon complexation. The iron oxide NPs were characterized using various methods, including X

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Publication Date
Tue Mar 01 2022
Journal Name
Journal Of Hydrology
Boosted artificial intelligence model using improved alpha-guided grey wolf optimizer for groundwater level prediction: Comparative study and insight for federated learning technology
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Publication Date
Tue Feb 01 2022
Journal Name
Baghdad Science Journal
Application of Groebner Bases to Study a Communication System
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This paper introduces a relationship between the independence of polynomials associated with the links of the network, and the Jacobian determinant of these polynomials. Also, it presents a way to simplify a given communication network through an algorithm that splits the network into subnets and reintegrates them into a network that is a general representation or model of the studied network. This model is also represented through a combination of polynomial equations and uses Groebner bases to reach a new simplified network equivalent to the given network, which may make studying the ability to solve the problem of network coding less expensive and much easier.

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Publication Date
Sun Dec 12 2010
Journal Name
Alustath Journal For Human And Social Sciences
Suggested Approach to deal with Multicollinearity Problem – with Application –
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This research introduce a study with application on Principal Component Regression obtained from some of the explainatory variables to limitate Multicollinearity problem among these variables and gain staibilty in their estimations more than those which yield from Ordinary Least Squares. But the cost that we pay in the other hand losing a little power of the estimation of the predictive regression function in explaining the essential variations. A suggested numerical formula has been proposed and applied by the researchers as optimal solution, and vererifing the its efficiency by a program written by the researchers themselves for this porpuse through some creterions: Cumulative Percentage Variance, Coefficient of Determination, Variance

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Publication Date
Sun Sep 07 2008
Journal Name
Baghdad Science Journal
Production of Zinc oxide for medical application from Zinc scraps
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In this work ,medical zinc oxide was produced from zinc scraps instead of traditional method which used for medical applications such as skin diseases, Iraq is importing around 50 ton/year for samarra plant the producted powder has apartical size less than 5 micron and the purity was more than 99.98%,also apilot plant of yield capacitiy 15 kg/8hours wsa designed and manufactured .

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Publication Date
Sat Sep 30 2023
Journal Name
Al–bahith Al–a'alami
Trends in Media Discourse during International Crises: An Analytical Study of the US Withdrawal from the Nuclear Deal
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The research focuses on the withdrawal of the United States from the nuclear agreement signed between the permanent members of the United Nations Security Council and the Islamic Republic of Iran concerning its nuclear program. This withdrawal has caused disruption in the official media discourse of the concerned countries. Therefore, the main question can be posed: Are there differences in the positions of countries related to the nuclear agreement, as well as those countries affected by it, before and after the official withdrawal of the United States on May 8, 2018?
The research aims to shed light on the trends in media discourse of the countries that signed the nuclear agreement and those affected by it b

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