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Performance Improvement of Neural Network Based RLS Channel Estimators in MIMO-OFDM Systems
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The objective of this study was tointroduce a recursive least squares (RLS) parameter estimatorenhanced by using a neural network (NN) to facilitate the computing of a bit error rate (BER) (error reduction) during channels estimation of a multiple input-multiple output orthogonal frequency division multiplexing (MIMO-OFDM) system over a Rayleigh multipath fading channel.Recursive least square is an efficient approach to neural network training:first, the neural network estimator learns to adapt to the channel variations then it estimates the channel frequency response. Simulation results show that the proposed method has better performance compared to the conventional methods least square (LS) and the original RLS and it is more robust at high speed mobility.

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Publication Date
Sat Dec 31 2011
Journal Name
Al-khwarizmi Engineering Journal
The Estimation of Vibrational Energy of Two Coupled (Welded) Plates Using Statistical Energy Analysis
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This paper deals with a method called Statistical Energy Analysis that can be applied to the mechanical and acoustical systems like buildings, bridges and aircrafts …etc. S.E.A as a tool can be applied to the resonant systems in the circumstances of high frequency or/and complex structure». The parameters of S.E.A such as coupling loss factor, internal loss factor, modal density and input power are clarified in this work ; coupled plate sub-systems and explanations are presented for these parameters. The developed system is assumed to be resonant, conservative, linear and there is an equipartition of energy between all the resonant modes within a given frequency band in a given sub-system. The aim of th

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Publication Date
Sat Jan 01 2022
Journal Name
Space International Journal Of Space Studies In Architecture And Urban Design
Adaptive Reuse of Traditional Architecture under the Influence of Intelligent Systems
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Publication Date
Fri Jul 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
The strengthening of strategic intelligence through an applied effective reality survey of strategic information systems An applied research in mobile companies in the Kurdistan Region
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Abstract

Purpose: The research attempts to Stand on the reality of the effective application of of strategic information systems in telecommunications companies in the Kurdistan Region, and what is the amount of the impact of such systems on promoting of Strategic Intelligence.

Design/Methodology/Approach: The Applied method has been used, In order to achieve the objectives of the research has been the development of a questionnaire prepared for this purpose and then distributed to (11) Company of Iraqi communications operating in Kurdistan Region companies, it has been used questionnaire to collect data in order to develop

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Publication Date
Wed Aug 18 2021
Journal Name
Palarch’s Journal Of Archaeology Of Egypt/egyptology
THE EFFECT OF LOCAL FINANCING UPON REALIZING THE FINANCIAL INDEPENDENCE OF LOCAL UNITS IN DECENTRALIZED ADMINISTRATIVE SYSTEMS
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The increasing level of residents’ requirements of the local community led to the necessity for sufficient local funding to satisfy the residents’ requirements and services of the local units affiliated with the decentralized administrative systems on the one hand, and to the role of local financing in the financial independence of local units on the other hand.With the presence of local financing, the financial independence of local units is achieved and is considered one of the conditions for financial independence, which is the provision of local financing to the units away from central support. The study focused in this research to clarify the concept of local financing for local units with a statement of its conditions and importan

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Publication Date
Tue Mar 01 2016
Journal Name
Journal Of Baghdad College Of Dentistry
A Comparison of the Effectiveness of Reciprocating System with Continuous Rotary Systems in Non-Surgical Endodontic Retreatment
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Background: Optimal root canal retreatment was required safe and efficient removal of filling material from root canal. The aim of this in vitro study was to compare the efficacy of reciprocating and continuous motion of four retreatment systems in removal of root canal filling material. Materials and Methods: Forty distal roots of the mandibular first molars teeth were used in this study, these roots were embedded in cold clear acrylic,roots were instrumented using crown down technique and rotary ProTaper systemize Sx to size F2 ,instrumentation were done with copiousirrigation of 2.5% sodium hypochlorite and 17% buffered solution of EDTA was used as final irrigant followed by distilledwater, roots were obturated with AH26 sealer and Prota

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Publication Date
Fri Feb 08 2019
Journal Name
Iraqi Journal Of Laser
Effects of 650 nm Diode Laser and 532 nm Frequency-Doubled Q-Switched Nd:YAG Laser on The Growth of Candida albicans, With and Without Photosensitizers
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This work describes an experimental setup to evaluate the photodynamictoxicity of 650 nm diode laser and 532 nm Frequency-doubled Q-Switched Nd:YAG laser on the growth of Candida albicans as well as the potential fungicidal effect when combining the laser irradiation with specific photosensitizers namely methylene blue, toluidine blue, acridine orange and safranin O. In this study the findings showed that the number of colony-forming units per millilitre (CFU/ml) of C. albicans decreased with increasing exposure time. In particular in the case of the frequency doubled Nd:YAG laser combined with safranin O, the best lethal effect occurred at 11 minutes exposure time with 2.26 J/cm² energy density (89.18% reduction) in comparison with the

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Publication Date
Mon Jan 01 2024
Journal Name
Fifth International Conference On Applied Sciences: Icas2023
A modified Mobilenetv2 architecture for fire detection systems in open areas by deep learning
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This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.

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Publication Date
Mon Sep 01 2025
Journal Name
Array
Enhanced zebra optimization algorithm for sustainable combined economic and emission dispatch in power systems
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The Combined Economic Emission Dispatch (CEED) problem is crucial for optimizing power system operation by minimizing costs and emissions while ensuring grid stability and meeting demand. This paper addresses the complex, nonlinear, and nonconvex nature of CEED, arising from factors like valve-point effects and transmission losses, which necessitates efficient metaheuristic algorithms. We introduce an Improved Zebra Optimization Algorithm (IMZOA), an enhanced bio-inspired technique integrating advanced adaptive foraging and dynamic defense mechanisms, along with a cubic function for CEED modeling, to improve search efficiency and convergence. IMZOA demonstrates significant numerical improvements, achieving up to a 0.80 % cost reduction for

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Publication Date
Sun Mar 30 2003
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Catalytic Pour Point Reduction and Viscosity Improvement of Lubricating Oil Fractions using Sulfided Nickel-Tungsten Catalysts
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Publication Date
Sat Oct 01 2011
Journal Name
Journal Of Engineering
MODIFIED TRAINING METHOD FOR FEEDFORWARD NEURAL NETWORKS AND ITS APPLICATION in 4-LINK SCARA ROBOT IDENTIFICATION
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In this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func

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