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The Effect of Constructive Learning Model on Cognitive Achievement and Learning dribbling Skill in Soccer for Secondary School Students
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The research aimed at identifying the effect of using constructive learning model on academic achievement and learning soccer dribbling Skill in 2nd grade secondary school students. The researcher used the experimental method on (30) secondary school students; 10 selected for pilot study, 20 were divided into two groups. The experimental group followed constructive learning model while the controlling group followed the traditional method. The experimental program lasted for eight weeks with two teaching sessions per week for each group. The data was collected and treated using SPSS to conclude the positive effect of using constructive learning model on developing academic achievement and learning soccer dribbling Skill in 2nd grade secondary school students. Finally the researchers recommended benefiting from constructive learning model in improving and learning dribbling Skill.

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Publication Date
Fri Dec 01 2023
Journal Name
Al-khwarizmi Engineering Journal
An Overview of Audio-Visual Source Separation Using Deep Learning
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    In this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to test A

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Publication Date
Tue Aug 11 2020
Journal Name
International Journal Of Psychosocial Rehabilitation
The effect of the maximum physical effort on some physiological variables, body components and achievement level in the effectiveness of air rifle shooting
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The job that confronts players with the effectiveness of shooting with an air rifle is high, so it requires necessary functional adaptations that differ in their degrees from other sports. Regular training in air rifle shooting leads to physiological changes in most of the body's internal systems, and changes and responses can be identified. The functional accompanying physical activity through the presence of body components that reflect these physiological changes in the form of changes in some components, and the importance of research lies in studying the physiological changes accompanying the maximum physical effort and the consequent development of the level of achievement in the effectiveness of shooting with air rifle and body

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Publication Date
Fri Jan 01 2021
Journal Name
Artificial Intelligence For Covid-19
An Efficient Mixture of Deep and Machine Learning Models for COVID-19 and Tuberculosis Detection Using X-Ray Images in Resource Limited Settings
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Publication Date
Tue Jun 17 2025
Journal Name
Revista Iberoamericana De Psicología Del Ejercicio Y El Deporte, Issn 1886-8576, Vol. 17, Nº. 6, 2022, Págs. 416-418
The Effect Of Katsu Exercises On Some Abilities Of Strength And Achievement Of Advanced Weight Lifters, Baghdad Clubs
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Autorías: Ghassan Adeeb Abdulhasan, Talib Faisal Shnawa, Yasir Wajih Qaddoori. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 6, 2022. Artículo de Revista en Dialnet.

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Scopus
Publication Date
Fri Feb 28 2025
Journal Name
Energies
Synergizing Machine Learning and Physical Models for Enhanced Gas Production Forecasting: A Comparative Study of Short- and Long-Term Feasibility
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Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m

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Publication Date
Wed Mar 02 2022
Journal Name
Journal Of Educational And Psychological Researches
The Effectiveness of the Educational Program to Develop Recall Habits of Late School Students in the Intermediate Stage
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The research aimed to explore the recall habits and developing the right recall habits at middle school students. A sample of (40) students were chosen intentionally from middle school students in two schools (almntzr- zany aleabdyn) with an average of (20) students from each school. They were evenly distributed in two experimental and control groups. To achieve the aims of the research, a scale was designed to measure the recall habits, and a preparation of an educational program to develop recall habits.

To process data statistically, the researcher used several statistical methods such as Pearson correlation coefficient, chi-square, T-test for one sample, T-test for two independent samples, Wilcoxon test, Mann-Whitney test, ET

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Development of an Optimized Botnet Detection Framework based on Filters of Features and Machine Learning Classifiers using CICIDS2017 Dataset
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Abstract<p>Botnet is a malicious activity that tries to disrupt traffic of service in a server or network and causes great harm to the network. In modern years, Botnets became one of the threads that constantly evolving. IDS (intrusion detection system) is one type of solutions used to detect anomalies of networks and played an increasing role in the computer security and information systems. It follows different events in computer to decide to occur an intrusion or not, and it used to build a strategic decision for security purposes. The current paper <italic>suggests</italic> a hybrid detection Botnet model using machine learning approach, performed and analyzed to detect Botnet atta</p> ... Show More
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Publication Date
Tue Jun 17 2025
Journal Name
Iraqi Journal Of Humanitarian, Social And Scientific Research
The effect of special exercises with training tools in teaching the skill of circular sloping on the parallel apparatus in men&#39;s artistic gymnastics
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Publication Date
Mon Jun 06 2022
Journal Name
International Journal Of Health Sciences
effect of a training curriculum for the development of some functional variables and the level of achievement in the effectiveness of air rifle shooting
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There are significant differences between the pre and post-tests in favor of the post-test in the tests) stroke volume (S.V), cardiac thrust (C.O.P), left ventricular volume, maximum oxygen consumption Vo2max), which indicates the effect of the proposed training approach.There are significant differences between the pre and post-tests in favor of the post-test in the achievement level test with air rifle shooting for young female shooters, which indicates the effect of the proposed training curriculum.There are no significant differences between the pre and post-tests in the tests (heart rate (HR) before exercise, heart rate (HR) after exercise, systolic blood pressure rate before exercise, systolic blood pressure rate after exercis

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Publication Date
Fri Dec 01 2023
Journal Name
Applied Energy
Deep clustering of Lagrangian trajectory for multi-task learning to energy saving in intelligent buildings using cooperative multi-agent
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The intelligent buildings provided various incentives to get highly inefficient energy-saving caused by the non-stationary building environments. In the presence of such dynamic excitation with higher levels of nonlinearity and coupling effect of temperature and humidity, the HVAC system transitions from underdamped to overdamped indoor conditions. This led to the promotion of highly inefficient energy use and fluctuating indoor thermal comfort. To address these concerns, this study develops a novel framework based on deep clustering of lagrangian trajectories for multi-task learning (DCLTML) and adding a pre-cooling coil in the air handling unit (AHU) to alleviate a coupling issue. The proposed DCLTML exhibits great overall control and is

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Scopus (23)
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