The aim of the research: To identify the trends of students of the College of Physical Education and Sports Sciences towards modern teaching methods. To determine the type of strategies used that students prefer in practical lessons. In light of the research results, the researcher adopted the descriptive method because it is appropriate for the study. The research community is represented by students of the College of Physical Education and Sports Sciences (fourth stage), amounting to (320) students. Conclusions: The research results indicate that students of the College of Physical Education and Sports Sciences have positive and strong attitudes towards using modern teaching methods, and they realize their reality in improving interaction

The aim of the research: To identify the trends of students of the College of Physical Education and Sports Sciences towards modern teaching methods. To determine the type of strategies used that students prefer in practical lessons. In light of the research results, the researcher adopted the descriptive method because it is appropriate for the study. The research community is represented by students of the College of Physical Education and Sports Sciences (fourth stage), amounting to (320) students. Conclusions: The research results indicate that students of the College of Physical Education and Sports Sciences have positive and strong attitudes towards using modern teaching methods, and they realize their reality in improving interaction

This study was conducted in the plant protection department/ College of Agriculture/ University of Baghdad to evaluate the efficiency of physical agents ozone, ultraviolet radiation, microwave for destroying afla produced in corn seeds. An isolate af A.flavus producing Aflatoxin B1 was obtained from plant protection dept. college of Agric. University of Baghdad. Results showed destroy toxin AFLA B1 the effect of radiation microwave in the media of Japex degree 80 and 100 c^o 57.14% and 85.71%, respectively, and for 20 sec, compared to the treatment comparison 0.00% as found significant differences were apparent between transactions and the treatment of comparison, as and notes the existence of a significant dif

Support vector machine (SVM) is a popular supervised learning algorithm based on margin maximization. It has a high training cost and does not scale well to a large number of data points. We propose a multiresolution algorithm MRH-SVM that trains SVM on a hierarchical data aggregation structure, which also serves as a common data input to other learning algorithms. The proposed algorithm learns SVM models using high-level data aggregates and only visits data aggregates at more detailed levels where support vectors reside. In addition to performance improvements, the algorithm has advantages such as the ability to handle data streams and datasets with imbalanced classes. Experimental results show significant performance improvements in compa

<span lang="EN-US">Diabetes is one of the deadliest diseases in the world that can lead to stroke, blindness, organ failure, and amputation of lower limbs. Researches state that diabetes can be controlled if it is detected at an early stage. Scientists are becoming more interested in classification algorithms in diagnosing diseases. In this study, we have analyzed the performance of five classification algorithms namely naïve Bayes, support vector machine, multi layer perceptron artificial neural network, decision tree, and random forest using diabetes dataset that contains the information of 2000 female patients. Various metrics were applied in evaluating the performance of the classifiers such as precision, area under the c

Objective: Breast cancer is regarded as a deadly disease in women causing lots of mortalities. Early diagnosis of breast cancer with appropriate tumor biomarkers may facilitate early treatment of the disease, thus reducing the mortality rate. The purpose of the current study is to improve early diagnosis of breast by proposing a two-stage classification of breast tumor biomarkers fora sample of Iraqi women.

Methods: In this study, a two-stage classification system is proposed and tested with four machine learning classifiers. In the first stage, breast features (demographic, blood and salivary-based attributes) are classified into normal or abnormal cases, while in the second stage the abnormal breast cases are

Linear discriminant analysis and logistic regression are the most widely used in multivariate statistical methods for analysis of data with categorical outcome variables .Both of them are appropriate for the development of linear  classification models .linear discriminant analysis has been that the data of explanatory variables must be distributed multivariate normal distribution. While logistic regression no assumptions on the distribution of the explanatory data. Hence ,It is assumed that logistic regression is the more flexible and more robust method in case of violations of these assumptions.

In this paper we have been focus for the comparison between three forms for classification data belongs

Knowledge of the mineralogical composition of a petroleum reservoir's formation is crucial for the petrophysical evaluation of the reservoir. The Mishrif formation, which is prevalent in the Middle East, is renowned for its mineralogical complexity. Multi-mineral inversion, which combines multiple logs and inversions for multiple minerals at once, can make it easier to figure out what minerals are in the Mishrif Formation. This method could help identify minerals better and give more information about the minerals that make up the formation. In this study, an error model is used to find a link between the measurements of the tools and the petrophysical parameters. An error minimization procedure is subsequently applied to determine