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Microgrid Integration Based on Deep Learning NARMA-L2 Controller for Maximum Power Point Tracking
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This paper presents a hybrid energy resources (HER) system consisting of solar PV, storage, and utility grid. It is a challenge in real time to extract maximum power point (MPP) from the PV solar under variations of the irradiance strength.  This work addresses challenges in identifying global MPP, dynamic algorithm behavior, tracking speed, adaptability to changing conditions, and accuracy. Shallow Neural Networks using the deep learning NARMA-L2 controller have been proposed. It is modeled to predict the reference voltage under different irradiance. The dynamic PV solar and nonlinearity have been trained to track the maximum power drawn from the PV solar systems in real time.

Moreover, the proposed controller is tested under static and dynamic load conditions. The simulation and models are done by using MATLAB/Simulink. The simulation results from the proposed NARMA-L2 controller have been compared with existing Perturb and observe PO-MPPT and Incremental Conductance INC -MPPT methods.

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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
Sun Dec 20 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Negotiating policies for the granting of investment loans: A CASE STUDY ON IRAQI MIDDLE EAST BANK FOR INVESTMENT& COMMERCIAL GULF BANK
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The negotiation phase is gaining great importance in investment loans due to the magnitude of the amounts awarded and the need to obtain adequate lending guarantees and the development of better conditions, and this requires that negotiating policy with fixed principles that balance between meeting the demands of customers and maintain market share and achieve profits and avoid defaults and losses the bank, and so I have touched Find the concept of investment loans and procedures for granting and the concept of the negotiation process for the granting of loans. The practical side to ensure the preparation of examination form consists of questions commensurate with the methodology developed by the researchers, were directed to the officia

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Publication Date
Fri Mar 17 2017
Journal Name
Elixir Mech. Engg. 109 (2017) 47879-47881, Www. Elixirpublishers. Com …‏
Effect of Cutting Angle for a Locally Assembling Motorized Vibration Cutter on Some Operational Characteristics Used for Date Palm Fronds Cutting
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Publication Date
Tue Feb 01 2022
Journal Name
Materials Chemistry And Physics
The role of amino acid functionalization for improvement of adsorption Thioguanine anticancer drugs on the boron nitride nanotubes for drug delivery
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Publication Date
Sat Sep 30 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Effect of Heterogeneity on Recovery Factor for Carbonate Reservoirs. A Case Study for Mishrif Formation in West Qurna Oilfield, Southern Iraq
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Oil recovery could be impacted by the relation between vertical permeability (Kv) and horizontal permeability (Kh) (Kv/Kh). 4816 plugs that have been getting hold of 18 wells of Mishrif formation in the West Qurna oilfield were used. Kv/Kh data provided some scatter, but the mean is ~1. Kv/Kh =1 was used for the Petrel model before upscaling according to the heterogeneity of each layer.

Kv/Kh values for Mishrif Formation in West Qurna Oilfield are 0.8 for relatively homogeneous, 0.4 for heterogeneous rock, and 0.1 for cap rocks (CRII).

   Eclipse TM was used for reservoir simulation. PVT and SCAL data e

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Publication Date
Sun Oct 01 2017
Journal Name
Journal Of Educational And Psychological Researches
The effect of using active learning model in the achievement of fourth -grade material in the de partment of physics teaching aids students and the development then critical thinking
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Goal  of  research  is  to  investigate  the  impact  of the  use  of  effective  learning  model in the  collection  of  the  fourth  grade  students/Department of  physics in the material  educational methods  and the  development  of  critical thinking  .to teach  this goal  has  been  formulated  hypothesis cefereeten zero  subsidiary  of the second hypothesis  .To  investigate  the  research  hypothesis  were  selected  sample  of  fourth-grade  students of the  department  of physics at the univers

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Publication Date
Thu Nov 14 2024
Journal Name
Journal Of Emergency Medicine, Trauma And Acute Care
Novel isolation and optimization of anti-MRSA bacteriophages using plaque-based biokinetic methods
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Background: MRSA (methicillin-resistant Staphylococcus aureus) is a global health problem. Many people are looking for new ways to combat MRSA, for example by using bacteriophages (phages). It has been extremely challenging to isolate a sufficient quantity of lytic anti-MRSA phages. Therefore, new techniques for separating, refining, and reworking anti-MRSA phages were sought in this study.

Methods: Of 437 S. aureus isolates, nine clinical MRSA isolates were obtained from three hospitals in Baghdad, Iraq and two ATCC MRSA strains were used to separate wild anti-MRS

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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
A Digital-Based Optimal AVR Design of Synchronous Generator Exciter Using LQR Technique
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In this paper a new structure for the AVR of the power system exciter is proposed and designed using digital-based LQR. With two weighting matrices R and Q,  this method produces an optimal regulator that is used to generate the feedback control law. These matrices are called state and control weighting matrices and are used to balance between the relative importance of the input and the states in the cost function that is being optimized. A sample power system composed of single machine connected to an infinite- bus bar (SMIB) with both a conventional and a proposed Digital AVR (DAVR) is simulated. Evaluation results show that the DAVR damps well the oscillations of the terminal voltage and presents a faster respo

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Publication Date
Thu Mar 16 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Science
Synthesis and Characterization of Schiff Base Folic Acid Based Ligand and Its Complexes
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D-mannose sugar was used to prepare [benzoic acid 6-formyl-2, 2-dimethyl-tetrahydrofuro [3, 4-d][1, 3] dioxol-4-yl ester](compound A). The condensation reaction of folic acid with (compound A) resulted in the formation of new ligand [L]. These compounds were characterized by elemental analysis CHN, atomic absorption AA,(FT-IR),(UV-Vis), TLC, ES mass (for electrospray), molar conductance, and melting point. The new tetradentate ligand [L], reacted with two moles of some selected metal ions and two moles of (2-aminophenol),(metal: ligand: 2-aminophenol) at reflux in water medium to give a series of new complexes of the general formula K2 [M2 (L)(HA) 2] where M= Co (II), Ni (II), Cu (II) and Cd (II). These complexes were characterized by eleme

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Publication Date
Wed Mar 24 2021
Journal Name
Ieee Access
Smart IoT Network Based Convolutional Recurrent Neural Network With Element-Wise Prediction System
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An Intelligent Internet of Things network based on an Artificial Intelligent System, can substantially control and reduce the congestion effects in the network. In this paper, an artificial intelligent system is proposed for eliminating the congestion effects in traffic load in an Intelligent Internet of Things network based on a deep learning Convolutional Recurrent Neural Network with a modified Element-wise Attention Gate. The invisible layer of the modified Element-wise Attention Gate structure has self-feedback to increase its long short-term memory. The artificial intelligent system is implemented for next step ahead traffic estimation and clustering the network. In the proposed architecture, each sensing node is adaptive and able to

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