The current research aims at detecting Brain Dominance Learning Styles distinguished
and ordinary secondary school students (males and females).The researcher adopted Torrance
measure, known as ‘the style of your learning and thinking to measure Brain Dominance
Learning Styles’, the codified version of Joseph Qitami (1986); picture (a). The researcher
verified the standard properties of tool. The final application sample was 352 distinguished
and ordinary students; 176 distinguished male and female students and 176 ordinary male and
female students at the scientific fifth level of secondary school from schools in the province of
Baghdad, AL- KarKh Education Directorates in the First and Second . and who have been
selected in a stratified random sampling . After the application the tool of research and
analysis of the data statistically by using statistical methods ( Chi- Square, ,Guttman
Correlation), the Researcher arrived at the following results:
1.The right learning style is the dominant brain style among Individuals the research sample
Applied .
2.The presence of statistically significant differences in the right Brain Dominance Learning
Style among the sample Individuals at distinguished and ordinary in favor of distinguished
students .
3. The lack of statistically significant differences in the Brain Dominance Learning Styles can
be attributed to the sex variable.
Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
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A new and hybrid deep learning-based approach for diagnosing faults in electric vehicle (EV) drive motors is proposed in this article. This article presents a new and hybrid deep learning-based method of diagnosing faults in the drive motors of electric vehicles (EV). In contrast to standard CNNLSTM approaches that depend on SoftMax classification, the introduced framework combines a Random Forest (RF) classifier to enhance the generalization, interpretability, and robustness of fault prediction. Furthermore meant for use on edge computing equipment with IoT integration, the design allows for real-time monitoring in resource-limited settings. The introduced algorithm utilizes a Random Forest (RF) classifier for accurate fault classification
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Background Due to the intermittent, nonlinear, and uncertain behavior of renewable energy sources (res) such as solar and wind, grid stability and reliability require very high forecasting and optimization skills as widely reported in the literature. Traditional optimization methods work very well in small or static systems but are suffer difficulty on large-scale, dynamic and stochastic renewable environment due to their NP-hard nature. Methods The framework introduces the concept of a Machine Learning-Assisted Hybrid Cuckoo Search (ML-HCS) that combines CS with a hybrid metaheuristic and integrates Long Short-Term Memory (LSTM) networks for forecasting based on both regression models of LSTMs and hybrid optimization algorithm
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
... Show More
(6)
(6)
Breast cancer is highlighted in recent research as one of the most prevalent types of cancer. Timely identification is essential for enhancing patient results and decreasing fatality rates. Utilizing computer-assisted detection and diagnosis early on may greatly improve the chances of recovery by accurately predicting outcomes and developing suitable treatment plans. Grading breast cancer properly, especially evaluating nuclear atypia, is difficult owing to faults and inconsistencies in slide preparation and the intricate nature of tissue patterns. This work explores the capability of deep learning to extract characteristics from histopathology photos of breast cancer. The research introduces a new method called SMOTE-based Convolut
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The current research involves psychological pressure (educational,environment andemotionly) for secondary level to 2013-2014.This research includes comparison among students who are trained and not trained in physical education .The sample is(126) students from each gender from first education.Al-Karkh and the research found out that physical education has an effect in lessing emotional and educational in a big degree in student in secondary which affect them positively in their study. &n
... Show MoreThe research aims at showing the media awareness for Students, especially for the students of the preparatory schools through their following the mass media in forming the cultural, educational and political database. It also aims at building a content and prospectives that make them a wide awake stratum that safeguard the society which has faced huge effects of terrorist actions.
Furthermore, it aims at knowing to what extent that students have been acquainted with the printed and electronic newspapers. Finally, it aims at knowing to what extent that they are content with the mass media in covering and
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This research is based on the study of common praise in Mutanabbi and Ibn Hani Al-Andalusi as the main purpose in poetry poets, and balance between them;
The research was divided into two topics, presented by introductory introduction for the purpose of praise, and the concept of budget in Arab criticism, and then presented a brief overview of the lives of poets.
In the first section, I dealt with the common objectivity of the poets, such as the subject of sincerity in praise, hyperbole in the person of Mamdouh, and self-esteem when asked, in addition to the most common characteristics in t
... Show MoreBackground: Mental health of children has recently been
receiving increased attention in many parts of the world.
However, such attention has been lacking in developing
countries, particularly in the form of systematic research
Aim: The study aimed to find out the frequency of
behavior disorders in a sample of primary school children
and the different social and demographic factors that might
be related to this disorder.
Methods: The study is a cross-sectional one that included
918 primary school pupils in both urban and rural areas of
Baghdad. Rutter's questionnaire teacher's version was used
to assess the pupils, and the demographic data was obtained
by special questionnaire sent to the parents to be