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Direction Finding Using GHA Neural Networks
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 This paper adapted the neural network for the estimating of the direction of arrival (DOA). It uses an unsupervised adaptive neural network with GHA algorithm to extract the principal components that in turn, are used by Capon method to estimate the DOA, where by the PCA neural network we take signal subspace only and use it in Capon (i.e. we will ignore the noise subspace, and take the signal subspace only).

 

 

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Publication Date
Wed Nov 16 2016
Journal Name
Eurasip Journal On Wireless Communications And Networking
Evaluation of efficient vehicular ad hoc networks based on a maximum distance routing algorithm
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Traffic management at road intersections is a complex requirement that has been an important topic of research and discussion. Solutions have been primarily focused on using vehicular ad hoc networks (VANETs). Key issues in VANETs are high mobility, restriction of road setup, frequent topology variations, failed network links, and timely communication of data, which make the routing of packets to a particular destination problematic. To address these issues, a new dependable routing algorithm is proposed, which utilizes a wireless communication system between vehicles in urban vehicular networks. This routing is position-based, known as the maximum distance on-demand routing algorithm (MDORA). It aims to find an optimal route on a hop-by-ho

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Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Engineering And Sustainable Development
Improving Performance Classification in Wireless Body Area Sensor Networks Based on Machine Learning Techniques
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Wireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two s

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Publication Date
Mon Dec 14 2020
Journal Name
Baghdad Science Journal
Smart Flow Steering Agent for End-to-End Delay Improvement in Software-Defined Networks
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Publication Date
Thu Oct 30 2025
Journal Name
Journal Of University Of Babylon For Engineering Sciences
Adaptive Beamforming and Ai-Driven Low-Power Signal Processing on ‎Fpga For 6G Networks
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As the demands of sixth-generation (6G) networks escalate towards achieving high speeds and improved energy efficiency, there is an increasing need for intelligent and real-time adaptive solutions within the physical processing layer. This study proposes an innovative engineering framework based on an encapsulated architecture utilising FBGA (micro-distributed spherical array) technology, integrated with an internal artificial intelligence module, to achieve adaptive beamforming with high efficiency in dense wireless environments. The primary objective of this research is to develop an intelligent communication architecture that determines the optimal transmission angles and regulates power consumption in real-time by integrating ar

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Publication Date
Fri Aug 01 2025
Journal Name
Journal Of Communications
Deep Reinforcement Learning for Dynamic Routing, Modulation, and Spectrum Assignment in Elastic Optical Networks
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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
" Measuring the competitive performance of the National Insurance Company and some of its branches using the Revealed comparative advantage index RCAI "
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The research dealt with the subject of measuring the competitive performance of the National Insurance Company and some of its branches (Basra, Ninwa, Kirkuk and Babil), Depending on the Revenue Growth Index at the activity level, and the Revealed Comparative Advantage Index RCAIAt the branch level,To measure the competitiveness of the company And some branches, As the problem of research in the lack of adoption by some companies in the insurance service sector on scientific indicators to measure their competitive performance, The aims of the research is to measure the competitiveness of the National Insurance Company, as well as the competitiveness of its branches according to the scientific method, One of the main Conclusions of the re

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Using the Elzaki decomposition method to solve nonlinear fractional differential equations with the Caputo-Fabrizio fractional operator
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The techniques of fractional calculus are applied successfully in many branches of science and engineering, one of the techniques is the Elzaki Adomian decomposition method (EADM), which researchers did not study with the fractional derivative of Caputo Fabrizio. This work aims to study the Elzaki Adomian decomposition method (EADM) to solve fractional differential equations with the Caputo-Fabrizio derivative. We presented the algorithm of this method with the CF operator and discussed its convergence by using the method of the Cauchy series then, the method has applied to solve Burger, heat-like, and, couped Burger equations with the Caputo -Fabrizio operator. To conclude the method was convergent and effective for solving this type of

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Publication Date
Wed Nov 28 2018
Journal Name
Al-khwarizmi Engineering Journal
Effect of Using Combined Square Nozzle & winglet with Helical Tape on Thermal Characteristics in Tube Heat Exchanger
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Influence of combined square nozzle with helical tape inserted in a constant heat flux tube on heat transfer enhancement for turbulent airflow for Reynolds number ranging from 7000 to 14500 were investigated experimentally. Three different pitch ratios for square nozzle (PR = 5.8, 7.7 and 11.6) according to three different numbers of square nozzle (N = 3, 4 and 5) and constant pitch ratios for helical tape were used. The results observed that the Nusselt number and friction factor for combination with winglets were found to be up to 33.8 % and 21.4 %, respectively higher than nozzle alone for pitch ratio PR=5.8. The maximum value of thermal performance for using combination with winglets was about 1.351 for pitch ratio= 5.8. Nusselt numb

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Publication Date
Sun Dec 30 2018
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of penetration Rate and cost with Artificial Neural Network for Alhafaya Oil Field
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Prediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
A Comparison between Ericson's Formulae Results and Experimental Data Using New Formulae of Single Particle Level Density
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The partial level density PLD of pre-equilibrium reactions that are described by Ericson’s formula has been studied using different formulae of single particle level density . The parameter  was used from the equidistant spacing model (ESM) model and the non- equidistant spacing model (non-ESM) and another formula of  are derived from the relation between  and level density parameter . The formulae used to derive  are the Roher formula, Egidy formula, Yukawa formula, and Thomas –Fermi formula. The partial level density results that depend on  from the Thomas-Fermi formula show a good agreement with the experimental data.

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