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

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

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

publishing has become a large space in the field of interactive education and modern pages have become dedicated to the service of the educational effort in this area as the research in this context of the urgent scientific necessities, especially as we consider in Iraq from the new countries in the exploitation of these new technologies and investment possibilities of the information network And the contents of different in the framework of so-called distance education Here lies the problem of research in the possibility of finding scientific solutions for the design of interactive inter active website for students of the preparatory stage in Iraq and to find out the scientific ways to find design The study, which included the problem of

Abstract

The current research aims to identify the psychological security of students in the kindergarten department and identify if there is a significant difference between stage one and stage four students. To do this, the researcher adopted the psychological research scale of (Al-mohamdawi, 2007) that consisted of (30) items. It was administered to (120) female students chosen randomly from the kindergarten department in the college of education for women for the academic year (2029-2021). The results revealed that students in the kindergarten department have psychological security. There is a significant difference between stage one and four students in favor of stage four students.

Teachers' self-efficacy plays a very important role in the process of teaching English language, and teachers have primary role in determining what is needed or what would work best with their students. The sample consists of eighty-seven English language teachers in secondary schools in Baghdad/Kaarkh2. Self-efficacy questionnaire of fifteen items was constructed. Face, content validity and reliability were verified. Then, pupils' marks for the first semester were taken as their achievement.The main finding of the study indicates that:
English language teachers' self-efficacy has effect on their pupils' achievement.
In the light of the findings of the present study, several conclusions, recommendations and suggestions for further

Los lingüistas no árabes suelen quedar perplejos a la hora de  interpretar el  fenómeno de Al-ḍdad, −normalmente traducido en español como palabras  autoantónimas (1)− en la lengua árabe, en el que los arabistas, y entre ellos los españoles, han quedado sombrosos ante este fenómeno. El jefe del tribunal de la defensa de mi tesis me pidió que le explicara este fenómeno según mi teoría “El esquema básico de la referencia”; pues me dijo que no podía  imaginar que una palabra tuviera dos significados opuestos, y en ese momento le expliqué la palabra albayn  البين que significa la separación,  o la relación o  el enlace que comentar

Philology is a science concerned with issues raised about language. It is a research into the mental aspects of its origin in its various sciences. The term (philology) appeared in the writings of Arab scholars in the fourth century AH. One of the most prominent topics of philology is research on the origin and development of language; Because it is one of the topics that preoccupied thinkers and many scholars, philosophers, and theologians, as well as linguists, have tackled research in it.