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Fault Location of Doukan-Erbil 132kv Double Transmission Lines Using Artificial Neural Network ANN
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Transmission lines are generally subjected to faults, so it is advantageous to determine these faults as quickly as possible. This study uses an Artificial Neural Network technique to locate a fault as soon as it happens on the Doukan-Erbil of 132kv double Transmission lines network. CYME 7.1-Programming/Simulink utilized simulation to model the suggested network. A multilayer perceptron feed-forward artificial neural network with a back propagation learning algorithm is used for the intelligence locator's training, testing, assessment, and validation. Voltages and currents were applied as inputs during the neural network's training. The pre-fault and post-fault values determined the scaled values. The neural network's performance was evaluated, and tests were run. Line-to-ground faults were examined. The study demonstrates how effective, rapid, and precise this method is at locating faults. The neural network's performance was examined, and tests were run on it. The overall performance of the mean square error in the trained network execution was 0.11792 at 35 epochs. The correlation coefficient at the entire target was 0.99987 percent of an error on the Doukan-Erbil double transmission lines.

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Publication Date
Sat Oct 28 2023
Journal Name
Baghdad Science Journal
New Records of Non-Diatom Algae in Aquatic Habitat along Greater Zab River Path from Bekhma to Gwer District in Erbil Province, Iraq
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A study of non-diatom algal species composition in twelve sites from Greater Zab River path within
Erbil Province, was carried out from April 2021 to January 2022 with monthly sample collection in twelve studied sites. Among them site 4,5,6,7 and 9 are the first for algal study in this area. The 112 different species of algae belong to 33 genera, 25 families, 13 orders and 4 divisions have been identified. The predominant genera included Spirogyra and Cosmarium 17, 8 taxa respectively. 13 taxa were new recorded to Iraqi
Kurdistan algal flora and 9 of them were new recorded to Iraqi algal flora: Botryosphaerella sudetica, Muriella magna, Gloeotaenium loitlesbergianum, Apiocystis brauniana, Anabaena oscillarioides, C. distentum

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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
Fri May 31 2019
Journal Name
Journal Of Engineering
WSN-WCCS: A Wireless Sensor Network Wavelet Curve Ciphering System
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With wireless sensor network (WSN) wide applications in popularity, securing its data becomes a requirement. This can be accomplished by encrypting sensor node data. In this paper a new an efficient symmetric cryptographic algorithm is presented. This algorithm is called wireless sensor network wavelet curve ciphering system (WSN-WCCS).  The algorithm idea based on discrete wavelet transformation to generate keys for each node in WSN.  It implements on hierarchical clustering WSN using LEACH protocol. Python programming language version 2.7 was used to create the simulator of WSN framework and implement a WSN-WCCS algorithm. The simulation result of the proposed WSN-WCCS with other symmetric algorithms has show

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Publication Date
Wed Mar 24 2021
Journal Name
Journal Of Research In Medical And Dental Science
Efficacy of Oregano Essential Oil Mouthwash in Reducing Oral Halitosis: A Randomized, Double-Blind Clinical Trial
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Efficacy of Oregano Essential Oil Mouthwash in Reducing Oral Halitosis: A Randomized, Double-Blind Clinical Trial, Mohamed Saeed M Ali, Ayser Najah Mohammed*

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Publication Date
Tue Dec 31 2013
Journal Name
Al-khwarizmi Engineering Journal
Design of an Adaptive PID Neural Controller for Continuous Stirred Tank Reactor based on Particle Swarm Optimization
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 A particle swarm optimization algorithm and neural network like self-tuning PID controller for CSTR system is presented. The scheme of the discrete-time PID control structure is based on neural network and tuned the parameters of the PID controller by using a particle swarm optimization PSO technique as a simple and fast training algorithm. The proposed method has advantage that it is not necessary to use a combined structure of identification and decision because it used PSO. Simulation results show the effectiveness of the proposed adaptive PID neural control algorithm in terms of minimum tracking error and smoothness control signal obtained for non-linear dynamical CSTR system.

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Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
On Comparison Study between Double Sumudu and Elzaki Linear Transforms Method for Solving Fractional Partial Differential Equations
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        In this paper, double Sumudu and double Elzaki transforms methods are used to compute the numerical solutions for some types of fractional order partial differential equations with constant coefficients and explaining the efficiently of the method by illustrating some numerical examples that are computed by using  Mathcad 15.and graphic in Matlab R2015a.

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Publication Date
Sun Jul 01 2018
Journal Name
International Journal Of Engineering Research And Management
The first and Second Order Polynomial Models with Double Scalar Quantization for Image Compression
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Publication Date
Sat Nov 01 2014
Journal Name
International Journal Of Statistics
Single and Double Stage Shrinkage Estimators for the Normal Mean with the Variance Cases
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Publication Date
Sun Dec 30 2012
Journal Name
Journal Of Kufa For Mathematics And Computer
On Jeffery Prior Distribution in Modified Double Stage Shrinkage-Bayesian Estimator for Exponential Mean
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Publication Date
Sun Jun 01 2025
Journal Name
International Communications In Heat And Mass Transfer
Augmenting solidification dynamics in double-pipe latent heat storage: Exploring optimized curved fin configurations
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This work is to examine the employment of curved fins to boost heat recovery in a double-pipe containment system filled with phase change material (PCM). The study utilizes CFD modeling, validated against experimental benchmarks, to evaluate how various geometric parameters of curved fins affect system performance. Findings demonstrate that adjusting the fin angular curvature from 60◦ to 180◦ yielded a 22.1 % decrease in the time required for solidification while simultaneously improving heat recovery efficiency by 32.0 %. When the fin base spacing was increased from 5 mm to 15 mm, the system showed a 14.5 % solidification time saving and a 20.9 % heat recovery improvement. Furthermore, modifying the joining angle between upper fins fro

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