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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
Sat Aug 12 2017
Journal Name
Journal Of Engineering
Simulation of Groundwater Movement for Nuclear Research Center at AlTuwaitha Area in Baghdad City, Iraq
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ABSTRACT  
     The simulation of groundwater movement has been carried out by using MODFLOW model
in order to show the impact of change of water surface elevation of the Tigris river on layers of
the aquifer system for Nuclear Research Center at Al-Tuwaitha area, in addition to evaluate the
ability of the proposed pumping well to collect groundwater and change the direction of flow at
steady-state. The results of the study indicated that there is a good match between the values of
groundwater levels that calculated in the model and measured in the field, where mean error  is
0.09 m.
     The study also showed that the increasing of water surface elevation of the

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Publication Date
Tue Jan 01 2019
Journal Name
Technologies And Materials For Renewable Energy, Environment And Sustainability: Tmrees19gr
Theoretical calculations involving a standard neutron yield distribution for the T-T nuclear fusion reaction
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A standard theoretical neutron energy flux distribution is achieved for the triton-triton nuclear fusion reaction in the range of triton energy about ≤10 MeV. This distribution give raises an evidence to provide the global calculations including the characteristics fusion parameters governing the T-T fusion reaction.

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Publication Date
Sun Mar 07 2010
Journal Name
Baghdad Science Journal
Determination the concentration for uranium in phosphrous fertilizers by using nuclear track detector CR-39
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The aim of this research was to study the concentrations of Uranium in the phosphorus fertilizers using Nuclear track detector (CR-39). Our present investigation is based on the study of 10 types samples for different kinds of phosphorus fertilizers which were available in the local market Some of them were Iraqi made and the others from different countries like, (Iran, Italy, Holland, Lebanon and Jordan) .. The result obtained shows that the Uranium concentration in phosphorus fertilizers samples varies from (3.59ppm) to(2.59ppm). Based on the radioactive concentration of Uranium in the samples all the results obtained between(3.59ppm) in the Iraqi super phosphate to (2.59ppm) in the mixture Iraqi phosphate fertilizer are withi

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Publication Date
Sun Sep 06 2009
Journal Name
Baghdad Science Journal
Band Gap Energy for SiC Thin Films Prepared By TEACO2 Laser Irradiated With Nuclear Radiation
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The effect of high energy radiation on the energy gap of compound semiconductor Silicon Carbide (SiC) are viewed. Emphasis is placed on those effects which can be interpreted in terms of energy levels. The goal is to develop semiconductors operating at high temperature with low energy gaps by induced permanent damage in SiC irradiated by gamma source. TEACO2 laser used for producing SiC thin films. Spectrophotometer lambda - UV, Visible instrument is used to determine energy gap (Eg). Co-60, Cs-137, and Sr-90 are used to irradiate SiC samples for different time of irradiation. Possible interpretation of the changing in Eg values as the time of irradiation change is discussed

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Publication Date
Sat Apr 01 2023
Journal Name
Iraqi Journal Of Applied Physics
Calculations of Nuclear Two-Component State Density in Non-Equidistant Spacing Model with Modified Williams
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Publication Date
Sat Jan 05 2019
Journal Name
Iraqi Journal Of Physics
Study of nuclear structure for carbon isotopes using local scale transformation technique in shell model
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This work is devoted to study the properties of the ground states such as the root-mean square ( ) proton, charge, neutron and matter radii, nuclear density distributions and elastic electron scattering charge form factors for Carbon Isotopes (9C, 12C, 13C, 15C, 16C, 17C, 19C and 22C). The calculations are based on two approaches; the first is by applying the transformed harmonic-oscillator (THO) wavefunctions in local scale transformation (LST) to all nuclear subshells for only 9C, 12C, 13C and 22C. In the second approach, the 9C, 15C, 16C, 17C and 19C isotopes are studied by dividing the whole nuclear system into two parts; the first is the compact core part and the second is the halo part. The core and halo parts are studied using the

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Publication Date
Sat Dec 17 2022
Journal Name
Applied Sciences
A Hybrid Artificial Intelligence Model for Detecting Keratoconus
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Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a

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Publication Date
Tue Sep 09 2025
Journal Name
Nursing Science Quarterly
Artificial Intelligence in Nursing: Toward a Global Perspective
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The use of artificial intelligence (AI) technology is rapidly expanding in nursing and society. However, its use in healthcare comes with a number of challenges and concerns. The authors of this article use the sociotechnical model to consider the expanding use of AI in nursing and healthcare from a global perspective. Select references from the literature are used to support this important discussion for nurses and other healthcare professionals. Artificial intelligence is a major innovation that, if used properly, can reduce errors and improve efficiency and healthcare quality. It has also been shown to increase patient support, healthcare access and patient care. Here the authors address some of the limitations and challenges of

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Publication Date
Mon Jan 01 2024
Journal Name
Pathology - Research And Practice
Artificial intelligence in cancer diagnosis: Opportunities and challenges
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Publication Date
Tue Sep 30 2025
Journal Name
المجلة العراقية للعلوم السياسية
Spy vs.AI How Artificial Intelligence Will Remake Espionage
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