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Development Artificial Neural Network (ANN) computing model to analyses men's 100¬meter sprint performance trends
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Coaches and analysts face a significant challenge of inaccurate estimation when analyzing Men's 100 Meter Sprint Performance, particularly when there is limited data available. This necessitates the use of modern technologies to address the problem of inaccurate estimation. Unfortunately, current methods used to estimate Men's 100 Meter Sprint Performance indexes in Iraq are ineffective, highlighting the need to adopt new and advanced technologies that are fast, accurate, and flexible. Therefore, the objective of this study was to utilize an advanced method known as artificial neural networks to estimate four key indexes: Accelerate First of 10 meters, Speed Rate, Time First of 10 meters, and Reaction Time. The application of artificial neural networks in the sports industry in the Republic of Iraq is crucial to ensure successful players. In this study, an artificial neural network model was built to predict Men's 100 meter indexes. Several factors related to the construction of artificial neural networks were studied, including network architecture and internal factors and their impact on the performance of the models. As a result, four easy equations were developed to calculate the four key indexes. The findings of the study indicate that these networks can predict Men's 100 Meter indexes with a high degree of reliability 98.034% and accounting coefficients R = 0.9143.

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Publication Date
Thu Oct 01 2020
Journal Name
Journal Of Engineering
Developing a Model to Estimate the Productivity of Ready Mixed Concrete Batch Plant
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Productivity estimating of ready mixed concrete batch plant is an essential tool for the successful completion of the construction process. It is defined as the output of the system per unit of time. Usually, the actual productivity values of construction equipment in the site are not consistent with the nominal ones. Therefore, it is necessary to make a comprehensive evaluation of the nominal productivity of equipment concerning the effected factors and then re-evaluate them according to the actual values.

In this paper, the forecasting system was employed is an Artificial Intelligence technique (AI). It is represented by Artificial Neural Network (ANN) to establish the predicted model to estimate wet ready mixe

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Publication Date
Sat Aug 01 2015
Journal Name
2015 Ieee Conference On Computational Intelligence In Bioinformatics And Computational Biology (cibcb)
Granular computing approach for the design of medical data classification systems
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Publication Date
Thu Oct 01 2020
Journal Name
Ieee Transactions On Very Large Scale Integration (vlsi) Systems
Low-Power, Highly Reliable Dynamic Thermal Management by Exploiting Approximate Computing
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With the continuous downscaling of semiconductor processes, the growing power density and thermal issues in multicore processors become more and more challenging, thus reliable dynamic thermal management (DTM) is required to prevent severe challenges in system performance. The accuracy of the thermal profile, delivered to the DTM manager, plays a critical role in the efficiency and reliability of DTM, different sources of noise and variations in deep submicron (DSM) technologies severely affecting the thermal data that can lead to significant degradation of DTM performance. In this article, we propose a novel fault-tolerance scheme exploiting approximate computing to mitigate the DSM effects on DTM efficiency. Approximate computing in hardw

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Publication Date
Thu Nov 01 2018
Journal Name
International Journal Of Computing And Digital Systems
The Perception of Information Security Threats Surrounding the Cloud Computing Environment
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Publication Date
Wed Jul 05 2017
Journal Name
Neural Computing And Applications
Hybrid soft computing approach for determining water quality indicator: Euphrates River
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Publication Date
Wed Aug 13 2025
Journal Name
Journal Of Administration And Economics
Bayesian Method in Classification Regression Tree to estimate nonparametric additive model compared with Logistic Model with Application
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The use of Bayesian approach has the promise of features indicative of regression analysis model classification tree to take advantage of the above information by, and ensemble trees for explanatory variables are all together and at every stage on the other. In addition to obtaining the subsequent information at each node in the construction of these classification tree. Although bayesian estimates is generally accurate, but it seems that the logistic model is still a good competitor in the field of binary responses through its flexibility and mathematical representation. So is the use of three research methods data processing is carried out, namely: logistic model, and model classification regression tree, and bayesian regression tree mode

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Publication Date
Tue Aug 08 2023
Journal Name
مجلة حمورابي للدراسات
adolescents exposure to the specialized satellite channel cartoon network and its relationship to their level of technological culture
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Publication Date
Thu Oct 01 2015
Journal Name
Journal Of Educational And Psychological Researches
Recent trends of Arabic language teaching methods in contemporary education environment
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Arabic language the timeless language of the Qur'an ((I made it read Arabic you may understand)) (Al-Zukhruf No 3). It is a way to express his thoughts and feelings and capable of giving constant absorbed the needs of the times and meet the General requirements and interactive needs of life to achieve social and intellectual aspects.    

The aim of current research to identify what teaching the contemporary trends in teaching, what the nature of knowledge and teaching methods, how do you rate the modern Arabic language teaching methods, the criteria for evaluating the effectiveness of teaching where the researcher has reached some recommendations: 1. establish the basics of environmental ed

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Publication Date
Thu Apr 25 2019
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
HARNESSING DIGITIZATION TO ACHIEVE THE GOALS OF SUSTAINABLE DEVELOPMENT 2030\ EXPERIENCE OF THE EMIRATE OF DUBAI.: HARNESSING DIGITIZATION TO ACHIEVE THE GOALS OF SUSTAINABLE DEVELOPMENT 2030\ EXPERIENCE OF THE EMIRATE OF DUBAI.
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Experienced economic environmentRadical changes at the end of the last century and the beginning of the present century, resulting in new concepts and expectations in all aspects of economic, political, social and even behavioral.Each of these concepts is the result of rapid developments in the intangible space. Competition is no longer limited to the mere possession of tangible material resources, but because of its link to knowledge and technology content and to the comprehensive quality standards and efficient and effective policies of States. With the increasing pace of growth and interdependence among the global economies, this resulted in the birth of a new economic system led by technological development and financial liberalizati

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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Using the artificial TABU algorithm to estimate the semi-parametric regression function with measurement errors
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Artificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing artificial TABU algorithm to find the best estimate of the semi-parametric regression function with measurement errors in the explanatory variables and the dependent variable, where measurement errors appear frequently in fields such as sport, chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement.

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