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Academic Achievement Level and Its Relationship with Some Fundamental Skills in Fencing for Third Year College Students
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Publication Date
Sat Feb 26 2022
Journal Name
Sport Tk-revista Euroamericana De Ciencias Del Deporte
Effect of physical exertion training on bio-kinetic abilities in weightlifting among students of Physical Education and Sports Sciences
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The objective of this research was to study the effect of physical exertion training on bio-kinetic abilities in weightlifting among students of Physical Education and Sports Sciences. The present study had a pre-posttest experimental design in which participants were recruited in two groups: experimental group and control group. A total of 30 students of Physical Education and Sports Sciences constituted the sample of the study. The sample selection was done by a comprehensive inventory method. Participants were equally allocated into two groups with n=15 in each group. Participants of experimental group were made to perform special physical exercises with three training units per week during eight weeks. The statisti

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Publication Date
Mon Apr 03 2023
Journal Name
Journal Of Educational And Psychological Researches
The Effectiveness of Using Cubing Technique in the Iraqi EFL Secondary Students' Composition Writing, Vocabulary, and Meta-Cognitive Awareness
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Abstract

The aim of this research is to determine how well the Cubing Technique affects the Iraqi EFL students' composition writing, vocabulary, and meta-cognitive awareness of writing strategies. The sample of (64) secondary-school female students in the fifth grade is drawn from two classrooms and split into two equal groups: the experimental group and the control group, each of which consists of (32) students. A quasi-experimental design is applied. The performance test and Meta-cognitive Writing Strategies questionnaire are given as a pre-test for equalizing the two groups after ensuring their validity and reliability. Then, they are administrated as a posttest in both groups. According to the results, the si

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Publication Date
Sun Jan 01 2023
Journal Name
Revista Iberoamericana De PsicologĂ­a Del Ejercicio Y El Deporte
THE IMPACT OF ENGINEERING ANXIETY ON STUDENTS: A COMPREHENSIVE STUDY IN THE FIELDS OF SPORT, ECONOMICS, AND TEACHING METHODS
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Publication Date
Sat Nov 01 2014
Journal Name
International Journal Of Statistics
Single and Double Stage Shrinkage Estimators for the Normal Mean with the Variance Cases
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Publication Date
Wed Mar 29 2023
Journal Name
Aspac J. Mol. Biol. Biotechnol.
Utilizing waste mango and avocado seeds for highly effective dye removal with activated carbon
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Activated carbon (AC) is a highly important adsorbent material, as it is a solid form of pure carbon that boasts a porous structure and a large surface area, making it effective for capturing pollutants. Thanks to its exceptional features, AC is widely used for purifying water that is contaminated with odors and removing dyes in a cost-effective manner. A variety of carbonic materials have been employed to prepare AC, and this study aimed to evaluate the suitability of utilizing waste mango and avocado seeds for this purpose, followed by testing their efficacy in removing dye from aqueous solutions. The results indicate that using waste mango and avocado as AC is technically feasible, achieving dye removal percentages of 98% and 93%,

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Scopus
Publication Date
Wed Apr 08 2020
Journal Name
Periodicals Of Engineering And Natural Sciences
Bayes estimators for reliability and hazard function of Rayleigh-Logarithmic (RL) distribution with application
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In this paper, we derived an estimators and parameters of Reliability and Hazard function of new mix distribution ( Rayleigh- Logarithmic) with two parameters and increasing failure rate using Bayes Method with Square Error Loss function and Jeffery and conditional probability random variable of observation. The main objective of this study is to find the efficiency of the derived of Bayesian estimator compared to the to the Maximum Likelihood of this function using Simulation technique by Monte Carlo method under different Rayleigh- Logarithmic parameter and sample sizes. The consequences have shown that Bayes estimator has been more efficient than the maximum likelihood estimator in all sample sizes with application

Publication Date
Tue Apr 02 2024
Journal Name
Engineering, Technology & Applied Science Research
Two Proposed Models for Face Recognition: Achieving High Accuracy and Speed with Artificial Intelligence
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In light of the development in computer science and modern technologies, the impersonation crime rate has increased. Consequently, face recognition technology and biometric systems have been employed for security purposes in a variety of applications including human-computer interaction, surveillance systems, etc. Building an advanced sophisticated model to tackle impersonation-related crimes is essential. This study proposes classification Machine Learning (ML) and Deep Learning (DL) models, utilizing Viola-Jones, Linear Discriminant Analysis (LDA), Mutual Information (MI), and Analysis of Variance (ANOVA) techniques. The two proposed facial classification systems are J48 with LDA feature extraction method as input, and a one-dimen

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Publication Date
Mon Jan 01 2018
Journal Name
International Journal Of Agricultural And Statistical Sciences
Response of growth and yield of zea maize for foliar spraying with humic acid
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Scopus (3)
Scopus
Publication Date
Sun Jul 01 2018
Journal Name
International Journal Of Engineering Research And Management
The first and Second Order Polynomial Models with Double Scalar Quantization for Image Compression
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Publication Date
Sun Dec 30 2018
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of penetration Rate and cost with Artificial Neural Network for Alhafaya Oil Field
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Prediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered

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