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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 improved prediction of dispersed phase hold up. The developed correlation also
shows better prediction over a wide range of operation parameters in RDC columns.

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Publication Date
Sun Nov 10 2019
Journal Name
Journal Of Engineering And Applied Sciences
Discrete Fracture Network and Fractured Reservoir Characterization in Khabaz Field-Tertiary Formation
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Publication Date
Thu Feb 01 2018
Journal Name
Journal Of Engineering
A Realistic Aggregate Load Representation for A Distribution Substation in Baghdad Network
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Electrical distribution system loads are permanently not fixed and alter in value and nature with time. Therefore, accurate consumer load data and models are required for performing system planning, system operation, and analysis studies. Moreover, realistic consumer load data are vital for load management, services, and billing purposes. In this work, a realistic aggregate electric load model is developed and proposed for a sample operative substation in Baghdad distribution network. The model involves aggregation of hundreds of thousands of individual components devices such as motors, appliances, and lighting fixtures. Sana’a substation in Al-kadhimiya area supplies mainly residential grade loads. Measurement-based

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Publication Date
Tue Aug 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Energy generation by crystalline silicon photovoltaic network per meter square in Iraq
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<span lang="EN-US">Iraqi people have been without energy for nearly two decades, even though their geographic position provides a high intensity of radiation appropriate for the construction of solar plants capable of producing significant quantities of electricity. Also, the annual sunny hours in Iraq are between 3,600 to 4,300 hours which makes it perfect to use the photovoltaics arrays to generate electricity with very high efficiency compared to many countries, especially in Europe. This paper shows the amount of electric energy generated by the meter square of crystalline silicon in the photovoltaic (PV) array that already installed in 18 states in Iraq for each month of the year. The results of the meter-square of PV arr

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Publication Date
Sat Dec 31 2022
Journal Name
International Journal Of Intelligent Engineering And Systems
Dynamic Virtual Network Embedding with Latency Constraint in Flex-Grid Optical Networks
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Publication Date
Thu Jun 29 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of Hydraulic Flow Units for Jeribe Reservoir in Jambour Oil Field Applying Flow Zone Indicator Method
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The Jeribe reservoir in the Jambour Oil Field is a complex and heterogeneous carbonate reservoir characterized by a wide range of permeability variations. Due to limited availability of core plugs in most wells, it becomes crucial to establish correlations between cored wells and apply them to uncored wells for predicting permeability. In recent years, the Flow Zone Indicator (FZI) approach has gained significant applicability for predicting hydraulic flow units (HFUs) and identifying rock types within the reservoir units.    This paper aims to develop a permeability model based on the principles of the Flow Zone Indicator. Analysis of core permeability versus core porosity plot and Reservoir Quality Index (RQI) - Normalized poros

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Publication Date
Wed May 01 2024
Journal Name
Baghdad Science Journal
Early Prediction of Nephropathy in Iraqi Patient with Diabetes Type II by Evaluating Some Relevant Biochemical Factors
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داء السكري من النوع 2 (T2DM) هو مرض معقد يصيب العديد من الأعضاء إلى جانب البنكرياس مثل الكلى والكبد والدماغ والعين. بسبب ارتفاع السكر في الدم لفترات طويلة وعدم السيطرة على مرض السكري مع وجود عوامل خطر أخرى ، يمكن أن تحدث مضاعفات مرض السكري. تشمل مضاعفات مرض السكري مضاعفات الأوعية الدموية الدقيقة والأوعية الدموية الكبيرة التي تستهدف الكلى. تهدف الدراسة الحالية إلى التحقق من مستوى الانجوتينسن المحول للانزيم  A

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Scopus (7)
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Publication Date
Thu Jun 29 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of Hydraulic Flow Units for Jeribe Reservoir in Jambour Oil Field Applying Flow Zone Indicator Method
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The Jeribe reservoir in the Jambour Oil Field is a complex and heterogeneous carbonate reservoir characterized by a wide range of permeability variations. Due to limited availability of core plugs in most wells, it becomes crucial to establish correlations between cored wells and apply them to uncored wells for predicting permeability. In recent years, the Flow Zone Indicator (FZI) approach has gained significant applicability for predicting hydraulic flow units (HFUs) and identifying rock types within the reservoir units.

   This paper aims to develop a permeability model based on the principles of the Flow Zone Indicator. Analysis of core permeability versus core porosity plot and Reservoir Quality Index (RQI) - Normalized por

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Publication Date
Sun Oct 05 2025
Journal Name
Mesopotamian Journal Of Computer Science
DGEN: A Dynamic Generative Encryption Network for Adaptive and Secure Image Processing
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Cyber-attacks keep growing. Because of that, we need stronger ways to protect pictures. This paper talks about DGEN, a Dynamic Generative Encryption Network. It mixes Generative Adversarial Networks with a key system that can change with context. The method may potentially mean it can adjust itself when new threats appear, instead of a fixed lock like AES. It tries to block brute‑force, statistical tricks, or quantum attacks. The design adds randomness, uses learning, and makes keys that depend on each image. That should give very good security, some flexibility, and keep compute cost low. Tests still ran on several public image sets. Results show DGEN beats AES, chaos tricks, and other GAN ideas. Entropy reached 7.99 bits per pix

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Publication Date
Wed Mar 20 2024
Journal Name
Journal Of Petroleum Research And Studies
Advanced Machine Learning application for Permeability Prediction for (M) Formation in an Iraqi Oil Field
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Permeability estimation is a vital step in reservoir engineering due to its effect on reservoir's characterization, planning for perforations, and economic efficiency of the reservoirs. The core and well-logging data are the main sources of permeability measuring and calculating respectively. There are multiple methods to predict permeability such as classic, empirical, and geostatistical methods. In this research, two statistical approaches have been applied and compared for permeability prediction: Multiple Linear Regression and Random Forest, given the (M) reservoir interval in the (BH) Oil Field in the northern part of Iraq. The dataset was separated into two subsets: Training and Testing in order to cross-validate the accuracy

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Publication Date
Tue Jun 01 2021
Journal Name
Journal Of Advanced Joining Processes
Coupled Eulerian–Lagrangian prediction of thermal and residual stress environments in dissimilar friction stir welding of aluminum alloys
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The evaluation of residual stresses (RS) induced by the friction stir welding (FSW) process is crucial in anticipating the performance of the welded structure. The existence of such residual stresses within a friction stir welded structure may lead to excessive distortion and weakness to afford the applied external loads. To assess quantitatively the effect of these residual stresses generated by FSW process, the current paper implements a Coupled Eulerian–Lagrangian (CEL) finite element simulation to analyze both thermal and subsequent resulted remaining stress environments in dissimilar friction stir welding of AA6061-T6 and AA2024-T3 alloys. The thermal analysis step was conducted first and followed by a mechanical analysis step in whi

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