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Comparison between Epsilon Normalized Least Means Square (ϵ-NLMS) and Recursive Least Squares (RLS) Adaptive Algorithms
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There is an evidence that channel estimation in communication systems plays a crucial issue in recovering the transmitted data. In recent years, there has been an increasing interest to solve problems due to channel estimation and equalization especially when the channel impulse response is fast time varying Rician fading distribution that means channel impulse response change rapidly. Therefore, there must be an optimal channel estimation and equalization to recover transmitted data. However. this paper attempt to compare epsilon normalized least mean square (ε-NLMS) and recursive least squares (RLS) algorithms by computing their performance ability to track multiple fast time varying Rician fading channel with different values of Doppler frequency, as well as mean square deviation (MSD) has simulated to measure the difference between original channel and what is estimated. The simulation results of this study showed that (ε-NLMS) tend to perform fast time varying Rician fading channel better than (RLS) adaptive filter.

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Publication Date
Mon Jun 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
Partnership between Public-Private secters between legislation and practice in IRAQ
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The topic of the partnership between the public and private sectors with great interest by researchers around the world after making sure that the process of economic and social development depends on a combination of resources and energies and expertise of both the public and private sectors in the creation and operation of the various projects , the economic development of the growing proved the failure of both sectors in achieving greater economic growth Klaaly separately in many countries , especially developing countries with a socialist approach , led one way or another to adopt most of the countries economic reform programs promoted by international organizations and institutions ( such as the IMF and the World Bank ) of i

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Publication Date
Fri Nov 01 2024
Journal Name
Journal Of Kufa Legal And Political Science
The Legal Regime of Mandatory Mediation as a Means of Dispute Resolution – A Comparative Analytical Study
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The mediation system is based on settling the dispute amicably through the intervention of a third party by bringing views closer away from the judiciary, which is an amicable way to settle disputes, which disputants resort to voluntarily, but some Western legislation has begun to impose resorting to mediation to settle disputes compulsorily, to take advantage of its advantages, get rid of the disadvantages of resorting to the judiciary in some disputes, and relieve pressure on the courts.

Publication Date
Mon Nov 11 2019
Journal Name
Day 3 Wed, November 13, 2019
Drill Bit Selection Optimization Based on Rate of Penetration: Application of Artificial Neural Networks and Genetic Algorithms
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Abstract<p>The drill bit is the most essential tool in drilling operation and optimum bit selection is one of the main challenges in planning and designing new wells. Conventional bit selections are mostly based on the historical performance of similar bits from offset wells. In addition, it is done by different techniques based on offset well logs. However, these methods are time consuming and they are not dependent on actual drilling parameters. The main objective of this study is to optimize bit selection in order to achieve maximum rate of penetration (ROP). In this work, a model that predicts the ROP was developed using artificial neural networks (ANNs) based on 19 input parameters. For the</p> ... Show More
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Publication Date
Sat Apr 12 2025
Journal Name
Mustansiriyah Journal Of Sports Science
A Review of the Use of Artificial Intelligence Algorithms for Predicting Injuries and Performance in Football Players
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The purpose of this study is to investigate the research on artificial intelligence algorithms in football, specifically in relation to player performance prediction and injury prevention. To accomplish this goal, scholarly resources including Google Scholar, ResearchGate, Springer, and Scopus were used to provide a systematic examination of research done during the last ten years (2015–2025). Through a systematic procedure that included data collection, study selection based on predetermined criteria, categorisation based on AI applications in football, and assessment of major research problems, trends, and prospects, almost fifty papers were found and analysed. Summarising AI applications in football for performance and injury p

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Publication Date
Sun Sep 03 2023
Journal Name
Wireless Personal Communications
Application of Healthcare Management Technologies for COVID-19 Pandemic Using Internet of Things and Machine Learning Algorithms
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Publication Date
Fri Jan 01 2021
Journal Name
Journal Of Mechanical Engineering Research And Developments
Numerical investigation for Natural Convection in a square Enclosure with partially active thermal sides' wall
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Three-dimensional cavity was investigated numerical in the current study filled with porous medium from a saturated fluid. The problem configuration consists of two insulated bottom and right wall and left vertical wall maintained at constant temperatures at variable locations, using two discretized heaters. The porous cavity fluid motion was represented by the momentum equation generalized model. The present investigation thermophysical parameters included the local thermal equilibrium condition. The isotherms and streamlines was used to examine energy transport and momentum. The meaning of changing parameters on the established average Nusselt number, temperature and velocity distribution are highlighted and discussed.

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Publication Date
Sat Apr 30 2022
Journal Name
Revue D'intelligence Artificielle
Performance Evaluation of SDN DDoS Attack Detection and Mitigation Based Random Forest and K-Nearest Neighbors Machine Learning Algorithms
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

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Publication Date
Thu Apr 01 2021
Journal Name
Telkomnika (telecommunication Computing Electronics And Control)
Automatic human ear detection approach using modified adaptive search window technique
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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
Sun Oct 01 2023
Journal Name
Int. J. Nonlinear Anal. Appl
Adaptive 1-D polynomial coding to compress color image with C421
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