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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
Sun Jan 01 2023
Journal Name
Journal Of Engineering
Artificial Neural Network Models to Predict the Cost and Time of Wastewater Projects
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Infrastructure, especially wastewater projects, plays an important role in the life of residential communities. Due to the increasing population growth, there is also a significant increase in residential and commercial facilities. This research aims to develop two models for predicting the cost and time of wastewater projects according to independent variables affecting them. These variables have been determined through a questionnaire distributed to 20 projects under construction in Al-Kut City/ Wasit Governorate/Iraq. The researcher used artificial neural network technology to develop the models. The results showed that the coefficient of correlation R between actual and predicted values were 99.4% and 99 %, MAPE was

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Publication Date
Wed Apr 10 2019
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
QUALITY SYSTEMS.POSSIBILITY OF IMPLEMENTING IN SOME LOCAL FOOD ESTABLISHMENTS: QUALITY SYSTEMS.POSSIBILITY OF IMPLEMENTING IN SOME LOCAL FOOD ESTABLISHMENTS
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In order to have an idea about what happens in Iraqi food establishments in relation to implement quality management system ISO 9001, this study was performed to show the actual situation of Iraqi food establishments concerning quality management system (ISO 9001:2015), reasons of implementing, factors that hinder implementing and problems faced high administration for getting establishments certification ISO 9001:2015. The study demonstrated from the questionnaire some difficulties to implement ISO 9001 for both of establishments that implemented the quality system or which in implementing of this international standard. The most important problems during implementing were business culture and costs and the most important proble

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Publication Date
Wed Dec 13 2017
Journal Name
Al-khwarizmi Engineering Journal
Performance Enhancement of the South Baghdad Thermal Station
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Aim of the research is the study of improving the performance of the thermal station south Baghdad and the main reasons for reduced its efficiency. South Baghdad power planet comprises (6) steam turbine units and (18) gas turbine units .The gas turbine units are composed of two groups: the first group is made up of gas units (1,2), each of capacity (123) MW. The design efficiency of gas turbine units is 32%. The actual efficiency data of steam units is 18.3% instead of 45% which is the design efficiency. The main reason for efficiency reduction of gas units is the rejected thermal energy with the exhaust gases to atmosphere, that are (450-510) ℃.The bad type of fuel used (heavy) fuel. Another reason for the low efficiency and has a neg

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Publication Date
Sun Dec 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
Evaluate the performance of the agricultural initiative in the application of the Agricultural Cooperative Bank.
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       This paper deals with the process of evaluating the performance of agricultural activity in Iraq and in particular the agricultural initiative launched by Prime Minister Nuri al-Maliki, during the period from 2008 - 2011. Where it is possible to use criteria or indicators that are fabricated by a statement on the calendar and the results of which may be by comparing planned performance with actual performance or the evaluation of the actual performance of successive periods selected. With an emphasis on the agricultural initiative is subject to the evaluation process by implementing and destinations specialized loan funds its own projects as one of the agricultural lending. With the need to co

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Publication Date
Sat Jun 30 2018
Journal Name
Kufa Journal For Agricultural Sciences
Effect of numbers of blades and speed of tillage in the performance of the rotavator plow
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Experiment Factorial conducted with two factor in field texture silt clay loam soil, the first factor were Two Rotavator plow which different in number of rotary blades on flanges, weight, width, made and type, the second factor were four speeds tractor 2.62, 5.10, 7.55, 9.23 km/hr to compare performance two Rotavator under depth 12 cm and knowledge slippage, distance between beat blades, practical productivity, disturbed soil volume, percentage of the soil clods which have diameter less than 5 cm under complete block design with three replications using Least Significant Design 0.05. Results showed Galucho Rotavator recorder the higher practical productivity 0>7089 ha/hr, disturbed soil volume 809.8 m3/hr, percentage of the soil clods 96.1

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Publication Date
Sat Apr 30 2022
Journal Name
Eastern-european Journal Of Enterprise Technologies
Improvement of noisy images filtered by bilateral process using a multi-scale context aggregation network
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Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d

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Publication Date
Mon May 27 2019
Journal Name
Al-academy
Improvisation Effectiveness in the Performance of the Actor in the Theatrical Show: مصطفى عباس خلف
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Improvisation is that spontaneous automatic achievement which is formed by a new cognition that is not based on something prior to it or a previous cognition. It is instantaneous. Whereas in art, improvisation also inters in all types of applied and performance arts as a foundation for launching and initiating it in music, painting, cinema, television and theater. In order to study the improvisation of the actor, the researcher put forward a theoretical study that included two sections. The first section is (the improvisation concept) and the second section is (improvisation in the show). The researcher, in the research procedures, took an intentional sample that was represented by the theatrical show (Rehearsal in Hell Play) and after t

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Publication Date
Tue Apr 30 2024
Journal Name
Iraqi Journal Of Science
Crescent Moon Visibility: A New Criterion using Deep learned Artificial Neural-Network
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     Many authors investigated the problem of the early visibility of the new crescent moon after the conjunction and proposed many criteria addressing this issue in the literature. This article presented a proposed criterion for early crescent moon sighting based on a deep-learned pattern recognizer artificial neural network (ANN) performance. Moon sight datasets were collected from various sources and used to learn the ANN. The new criterion relied on the crescent width and the arc of vision from the edge of the crescent bright limb. The result of that criterion was a control value indicating the moon's visibility condition, which separated the datasets into four regions: invisible, telescope only, probably visible, and certai

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Publication Date
Thu Oct 31 2024
Journal Name
Iraqi Geological Journal
Artificial Neural Network Application to Permeability Prediction from Nuclear Magnetic Resonance Log
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Reservoir permeability plays a crucial role in characterizing reservoirs and predicting the present and future production of hydrocarbon reservoirs. Data logging is a good tool for assessing the entire oil well section's continuous permeability curve. Nuclear magnetic resonance logging measurements are minimally influenced by lithology and offer significant benefits in interpreting permeability. The Schlumberger-Doll-Research model utilizes nuclear magnetic resonance logging, which accurately estimates permeability values. The approach of this investigation is to apply artificial neural networks and core data to predict permeability in wells without a nuclear magnetic resonance log. The Schlumberger-Doll-Research permeability is use

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Publication Date
Wed Mar 01 2017
Journal Name
2017 Annual Conference On New Trends In Information & Communications Technology Applications (ntict)
Automatic Iraqi license plate recognition system using back propagation neural network (BPNN)
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