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The Effect of Special Exercises for those with (Cognitive Concentration) in the Development of Motor Satisfaction and Learning Some Types of Scoring Basketball for Students
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The importance of the research in the preparation of special exercises to develop some types of basketball scoring as a contribution to help the physical education teacher to find successful educational alternatives. The purpose of the study was to prepare special exercises for the cognitive (cognitive) survey in the development of motor satisfaction and learning some types of Scoring for basketball for students. Learn about the effect of cognitive exercises in cognitive development in students. The survey included students from the first stage of the Faculty of Physical Education and Sports Science \ University of Diyala (159) divided into 6 people. The sample was randomized by (b) and (b) D) and after dispersion by the standard method In the (survey - focus) cognitive as the research sample consisted of (20) students per group. It took the curriculum using special exercises (9) weeks by two units per week in the unit time (90) minutes was invested the application part of each unit, The researchers found the following conclusions: - Special exercises have a high effectiveness in learning some types of Scoring basketball, and special exercises to teach students to develop motor satisfaction, the cognitive group outweighs the cognitive focus of learning the skills of lateral Scoring and peaceful Scoring, The study also recommends that students use special exercises to teach some types of Scoring in the basketball - to detect and differentiate between learners in the cognitive way (scanning the cognitive focus) before starting the learning process of some types Scoring basketball because of its impact in the process of learning - work on the development of motor satisfaction of students because of its importance.

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Publication Date
Sun Feb 27 2022
Journal Name
Iraqi Journal Of Science
Digital Speech Files Encryption based on Hénon and Gingerbread Chaotic Maps
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Speech encryption approaches are used to prevent eavesdropping, tracking, and other security concerns in speech communication. In this paper, a new cryptography algorithm is proposed to encrypt digital speech files. Initially, the digital speech files are rearranged as a cubic model with six sides to scatter speech data. Furthermore, each side is encrypted by random keys that are created by using two chaotic maps (Hénon and Gingerbread chaotic maps). Encryption for each side of the cube is achieved, using the based map vector that is generated randomly by using a simple random function. Map vector that consists of six bits, each bit refers to one of the specific chaotic maps that generate a random key to encrypt each face of the cube. R

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Publication Date
Wed Nov 30 2022
Journal Name
Iraqi Journal Of Science
Breast Cancer Detection using Decision Tree and K-Nearest Neighbour Classifiers
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      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimum err

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Publication Date
Wed Nov 30 2022
Journal Name
Iraqi Journal Of Science
Breast Cancer Detection using Decision Tree and K-Nearest Neighbour Classifiers
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      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu

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Scopus (9)
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Publication Date
Sat Jan 01 2022
Journal Name
Materials Today: Proceedings
Energy management and storage systems on electric vehicles: A comprehensive review
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Publication Date
Fri Mar 12 2021
Journal Name
Sensors
A Robust Handwritten Numeral Recognition Using Hybrid Orthogonal Polynomials and Moments
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Numeral recognition is considered an essential preliminary step for optical character recognition, document understanding, and others. Although several handwritten numeral recognition algorithms have been proposed so far, achieving adequate recognition accuracy and execution time remain challenging to date. In particular, recognition accuracy depends on the features extraction mechanism. As such, a fast and robust numeral recognition method is essential, which meets the desired accuracy by extracting the features efficiently while maintaining fast implementation time. Furthermore, to date most of the existing studies are focused on evaluating their methods based on clean environments, thus limiting understanding of their potential a

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
Regression shrinkage and selection variables via an adaptive elastic net model
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Abstract<p>In this paper, a new method of selection variables is presented to select some essential variables from large datasets. The new model is a modified version of the Elastic Net model. The modified Elastic Net variable selection model has been summarized in an algorithm. It is applied for Leukemia dataset that has 3051 variables (genes) and 72 samples. In reality, working with this kind of dataset is not accessible due to its large size. The modified model is compared to some standard variable selection methods. Perfect classification is achieved by applying the modified Elastic Net model because it has the best performance. All the calculations that have been done for this paper are in </p> ... Show More
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Publication Date
Fri Sep 15 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Determine, Predict and Map Soil pH Level by Fiber Optic Sensor
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Abstract<p>Soil pH is one of the main factors to consider before undertaking any agricultural operation. Methods for measuring soil pH vary, but all traditional methods require time, effort, and expertise. This study aimed to determine, predict, and map the spatial distribution of soil pH based on data taken from 50 sites using the Kriging geostatistical tool in ArcGIS as a first step. In the second step, the Support Vector Machines (SVM) machine learning algorithm was used to predict the soil pH based on the CIE-L*a*b values taken from the optical fiber sensor. The standard deviation of the soil pH values was 0.42, which indicates a more reliable measurement and the data distribution is normal.</p> ... Show More
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Publication Date
Wed Dec 12 2018
Journal Name
Iop Conference Series: Materials Science And Engineering
Preparation and characterization DLC thin films using atmospheric pressure plasma Jet
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Diamond-like carbon, amorphous hydrogenated films forms of carbon, were pretreated from cyclohexane (C6H12) liquid using plasma jet which operates with alternating voltage 7.5kv and frequency 28kHz. The plasma Separates molecules of cyclohexane and Transform it into carbon nanoparticles. The effect of argon flow rate (0.5, 1 and 1.5 L/min) on the optical and chemical bonding properties of the films were investigated. These films were characterized by UV-Visible spectrophotometer, X-ray diffractometer (XRD) Raman spectroscopy and scanning electron microscopy (SEM). The main absorption appears around 296, 299 and 309nm at the three flow rate of argon gas. The value of the optical energy gap is 3.37, 3.55 and 3.68 eV at a different flow rate o

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Publication Date
Tue May 30 2023
Journal Name
Iraqi Journal Of Science
Crude Oil Price Forecasts Using Support Vector Regression and Technical Indicators
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Oil price forecasting has captured the attention of both researchers and academics because of the unique characteristics of crude oil prices and how they have a big impact on a lot of different parts of the economic value of the product. As a result, most academics use a lot of different ways to predict the future. On the other hand, researchers have a hard time because crude oil prices are very unpredictable and can be affected by many different things. This study uses support vector regression (SVR) with technical indicators as a feature to improve the prediction of the monthly West Texas Intermediate (WTI) price of crude oil. The root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) measur

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Publication Date
Sat Apr 01 2023
Journal Name
Materials Today: Proceedings
Bimetallic (Fe/Zn-ZIF-8) crystals: Fabrication and adsorptive removal activity
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This work presents an investigation on the fabrication and characterization of Fe doped zeolitic imidazolate framework (ZIF-8) of 1:1 M ratio of Zn:Fe (Fe/Zn-ZIF-8) and adsorption performances of acquired materials. The synthesized Zn-ZIF-8, Fe-ZIF-8, and Fe/Zn-ZIF-8 materials were characterized for the phase structure, morphology, elemental analysis and surface area by using X-ray diffraction (XRD), Field emission scanning electron microscope (FESEM), Energy Dispersive X-Ray (EDX), and BET surface area, respectively. The results revealed the adsorption capacity was enhanced by incorporation of Fe into ZIF-8 structure. The CR dye adsorption capacities were 287, 219, and 412 mg/g for Zn-ZIF-8, Fe-ZIF-8, and Fe/Zn-ZIF-8 adsorbers, respectivel

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