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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 artificial intelligence algorithms with hardware acceleration. The main contribution is to develop a practical model that combines mathematical precision with physical implementation, utilising an FBGA-based helicopter design and supported by comprehensive simulation within the MATLAB/Simulink environment. The experimental results demonstrated a significant improvement in performance indicators, including a 42% reduction in response time, a 35% decrease in power consumption, and an average signal quality improvement of 3.8 dB. These results highlight the effectiveness of the proposed design as a promising solution for building intelligent, high-performance, and low-consumption 6G communication networks.

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Publication Date
Thu Jun 01 2023
Journal Name
Baghdad Science Journal
Spatiotemporal Modeling in Wireless Communication Networks
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This study aims to analyze the flow migration of individuals between Iraqi governorates using real anonymized data from Korek Telecom company in Iraq. The purpose of this analysis is to understand the connection structure and the attractiveness of these governorates through examining the flow migration and population densities. Hence, they are classified based on the human migration at a particular period. The mobile phone data of type Call Detailed Records (CDRs) have been observed, which fall in a 6-month period during COVID-19 in the year 2020-2021. So, according to the CDRs nature, the well-known spatiotemporal algorithms: the radiation model and the gravity model were applied to analyze these data, and they are turned out to be comp

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Publication Date
Sat Dec 02 2017
Journal Name
Al-khwarizmi Engineering Journal
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
Mon Aug 01 2011
Journal Name
Journal Of Engineering
Preservation of Required Chlorine Concentration in Baghdad Water Supply Networks using On-Site Chlorine Injection
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The chlorine concentration variation in Baghdad water networks was studied. The
chlorine data were collected from Mayoralty of Baghdad and Ministry of Environment
(MOE) for the networks for both sides of the city Karkh and Rasafa for (2008-2009). The
study of these data indicates that there are no systematic testing program .Classified GIS
maps showed that the areas far from the treatment plants have almost always low
chlorine concentration .This indicates that the problem of the low chlorine concentration
in the far areas is due to cracks of pipe along the conveyance path ,as expected. The area's
most frequently have low concentration are Al-sadir,Al-Kadhimya, and Al-Amiria . It
was found also that the chlorine c

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Publication Date
Tue Nov 01 2016
Journal Name
Journal Of Engineering
Ultrafiltration and Reverse Osmosis Membranes for Treating Wastewater Effluent from Gas Turbine Power Plants using the Statistical Method of Taguchi
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A study on the treatment and reuse of oily wastewater generated from the process of fuel oil treatment of gas turbine power plant was performed. The feasibility of using hollow fiber ultrafiltration (UF) membrane and reverse osmosis (RO) membrane type polyamide thin-film composite in a pilot plant was investigated. Three different variables: pressure (0.5, 1, 1.5 and 2 bars), oil content (10, 20, 30 and 40 ppm), and temperature (15, 20, 30 and 40 ᵒC) were employed in the UF process while TDS was kept constant at 150 ppm. Four different variables: pressure (5, 6, 7 and 8 bar), oil content (2.5, 5, 7.5 and 10 ppm), total dissolved solids (TDS) (100, 200,300 and 400 ppm), and temperature (15, 20, 30 and 40 ᵒC) were mani

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Publication Date
Thu Jun 26 2014
Journal Name
Engineering Optimization
A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising
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The main intention of this study was to investigate the development of a new optimization technique based on the differential evolution (DE) algorithm, for the purpose of linear frequency modulation radar signal de-noising. As the standard DE algorithm is a fixed length optimizer, it is not suitable for solving signal de-noising problems that call for variability. A modified crossover scheme called rand-length crossover was designed to fit the proposed variable-length DE, and the new DE algorithm is referred to as the random variable-length crossover differential evolution (rvlx-DE) algorithm. The measurement results demonstrate a highly efficient capability for target detection in terms of frequency response and peak forming that was isola

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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
An Experimental Study of the Server-based Unfairness Solutions for the Cross-Protocol Scenario of Adaptive Streaming over HTTP/3 and HTTP/2
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Since the introduction of the HTTP/3, research has focused on evaluating its influences on the existing adaptive streaming over HTTP (HAS). Among these research, due to irrelevant transport protocols, the cross-protocol unfairness between the HAS over HTTP/3 (HAS/3) and HAS over HTTP/2 (HAS/2) has caught considerable attention. It has been found that the HAS/3 clients tend to request higher bitrates than the HAS/2 clients because the transport QUIC obtains higher bandwidth for its HAS/3 clients than the TCP for its HAS/2 clients. As the problem originates from the transport layer, it is likely that the server-based unfairness solutions can help the clients overcome such a problem. Therefore, in this paper, an experimental study of the se

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Publication Date
Fri Jan 01 2021
Journal Name
Journal Of Mechanical Engineering Research And Developments
Fatigue life of welded joint improvement with various welding principles and shot peening process for AISI 1020 low carbon steel
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Publication Date
Wed Feb 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Using Fuzzy Games Theory to Determine the optimal Strategy for The Mobile Phone Networks in The Baghdad And Basra governorates
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      The objective of this research is employ the special cases of  function  trapezoid in the composition of fuzzy sets to make decision within the framework of the theory of games traditional to determine the best strategy for the mobile phone networks in the province of  Baghdad and Basra, has been the adoption of different periods of the  functions belonging to see the change happening in the matrix matches and the impact  that the strategies  and decision-making  available to each player and the impact on  societ

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Publication Date
Tue May 01 2018
Journal Name
2018 2nd Ieee Advanced Information Management,communicates,electronic And Automation Control Conference (imcec)
Hybrid Regressor and Approximation-Based Adaptive Control of Robotic Manipulators with Contact-Free Motion
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Publication Date
Sat Oct 04 2025
Journal Name
Mesopotamian Journal Of Computer Science
Enhanced IOT Cyber-Attack Detection Using Grey Wolf Optimized Feature Selection and Adaptive SMOTE
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The Internet of Things (IoT) has significantly transformed modern systems through extensive connectivity but has also concurrently introduced considerable cybersecurity risks. Traditional rule-based methods are becoming increasingly insufficient in the face of evolving cyber threats.  This study proposes an enhanced methodology utilizing a hybrid machine-learning framework for IoT cyber-attack detection. The framework integrates a Grey Wolf Optimizer (GWO) for optimal feature selection, a customized synthetic minority oversampling technique (SMOTE) for data balancing, and a systematic approach to hyperparameter tuning of ensemble algorithms: Random Forest (RF), XGBoost, and CatBoost. Evaluations on the RT-IoT2022 dataset demonstrat

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