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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
Tue Feb 02 2021
Journal Name
جامعة واسط مجلة كلية التربية
استعمال الانموذج اللوجستي ثنائي المعلم في بناء وتدريج مقياس الشخصية الافتراضية المتعدد الابعاد لطلبة الجامعة وفقا لنظرية الاستجابة للفقرة
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تهدف الدراسة الحالية الى استعمال الانموذج اللوجستي ثنائي المعلم في تدريج مقياس الشخصية الافتراضية المتعدد الابعاد لطلبة الجامعة وفقا لنظرية الاستجابة للفقرة، والخروج بتعميم لنتائج البحث والوقوف على الاجراءات العلمية المناسبة وتوفير تطبيق عملي علمي صحيح لاعتمادها من قبل الباحثين. وقد اتبعث الباحثة الاسلوب العلمي من خطوات واجراءات في عملية بناء المقياس حيث حدت ابعاد الشخصية الافتراضية المتمثلة بسبع ابعا

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Publication Date
Tue Dec 31 2019
Journal Name
Journal Of Economics And Administrative Sciences
The Impact of Emotional Intelligence on Employee Performance in Saudi Arabia Banking Sector
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Saudi Arabia’s banking sector plays an important role in the country’s development as it is among the leading sectors in the financial sector. Considering, two main Saudi banks (The National Commercial Bank and Saudi American bank), the present study aims to observe the impact of emotional intelligence on employee performance. The components of emotional intelligence affecting employee performance include self-management, relationship management, self-awareness, and social awareness. A quantitative methodology was applied to analyse the survey results of 300 respondents over the period from 2018 to 2019. The results show that there was a significant positive impact of self-management, self-awareness, and relationship manageme

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Publication Date
Wed Nov 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Dry Canal in Iraq and Mutual Growth in International Economic Environment
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In this paper, an attempt was made to measure and interpret the impact of several variables on global maritime transport, including: OECD industrial productions, high growth rates of some developing countries, and growth in world GDP. These variables contribute to higher rates of maritime transport revenues of 800 billion dollars annually; in the form of numerical sequences. The dry canal in Iraq was assumed to transfer 99 million tons of goods annually. This was made sure through the economic feasibility of the difference between maritime and land transport through railways. The effect of geographical and anthropological nature of Iraq on this project was studied too. Our findings indicated that the project will not drive growth

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Publication Date
Sat Jul 01 2023
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Auditing the performance of the structural capital according to standards of e-learning and its reflection on the performance of universities: applied research
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The developments and transformations taking place in the era and the growth of knowledge economies and communication technology led this development to compel higher education institutions in Iraq to reconsider their objectives to keep pace with development. And one of the most important tools of development was the application of e-learning standards and its long-term impact on the performance of the educational institution. Performance auditing plays an important role in verifying the extent to which these institutions have implemented their activities and programs that auditing performance by adopting e-learning standards helps the institutions’ management by providing appropriate information on the extent to which they achieve thei

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

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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
Thu Apr 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Rainwater Drainage Service Improvement Using a Number Of Quality Tools at the Directorate of Karbala Sewage
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The basic objective of the research is to study the quality of the water flow service in the Directorate of Karbala sewage and how to improve it after identifying the deviations of the processes and the final product and then providing the possible solutions in addressing the causes of the deviations and the associated quality gaps. A number of quality tools were used and applied to all data Stations with areas and activities related to the drainage of rainwater, as the research community determines the stations of lifting rainwater in the Directorate of the streams of Karbala holy, and the station was chosen Western station to apply the non-random sampling method intended after meeting a number of. It is one of the largest and m

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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
Wed Mar 20 2019
Journal Name
Al-khwarizmi Engineering Journal
Improvement of Mechanical and Fatigue Properties for Aluminum Alloy 7049 By Using Nano Composites Technique
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The aim of present work is to improve mechanical and fatigue properties for Aluminum alloy7049 by using Nano composites technique. The ZrO2 with an average grain diameter of 30-40 nm, was selected as Nano particles, to reinforce Aluminum alloy7049 with different percentage as, 2, 4, 6 and 7 %. The Stir casting method was used to fabricate the Nano composites materials due to economical route for improvement and processing of metal matrix composites. The experimental results were shown that the adding of zirconium oxide (ZrO2) as reinforced material leads to improve mechanical properties. The best percentage of improvement of mechanical properties of 7049 AA was with 4% wt. of ZrO2 about (7.76% ) for ultim

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