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

With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se

--The objective of the current research is to identify: 1) Preparing a scale level for e-learning applications, 2) What is the relationship between the applications of e-learning and the students of the Department of Chemistry at the Faculty of Education for Pure Sciences/ Ibn Al-Haytham – University of Baghdad. To achieve the research objectives, the researcher used the descriptive approach because of its suitability to the nature of the study objectives. The researcher built a scale for e-learning applications that consists of (40) items on the five-point Likrat scale (I agree, strongly agree, neutral, disagree, strongly disagree). He also adopted the scale of scientific values, and it consists of (40) items on a five-point scale as wel

For over a decade, educational technology has been used sparingly in our schools and universities. Online training courses have been used since 2003 to fill the gaps in our learning system and to add extra program besides classroom learning. This paper aims to investigate the Iraqi EFL instructors’ participating in online training courses and its influence on the process of teaching and learning.

       The sample of present study consists of 30 instructors from University of Baghdad. The questionnaire of sixteen items was constructed. After ensuring validity and reliability of questionnaire, it was applied on March 2013 and the result shows that most of instructors improve their teaching methods b

This work aims at finding out the impact of teaching types blended learning strategies on academic students` achievement. A review of related literature indicates that almost no study has ever attempted to focus specifically on the effect of the different kinds of blended learning strategies on EFL students` achievement in the educational research writing, and the present study attempts to fill this gap. The study focused on the students at the Master's degree in Educational Research Writing in the first semester of the academic year 2020/2021. The sample has selected from the college of Education Ibn-Rushd (18) students. Material has been designed for the Master candidates’ participants of the study was divided into two groups: one an e

The study aims to follow modern methods in teaching rhythmic gymnastics skills by directing learners to develop their perceptions and absorb what the world deals with today and develop intelligence among learners, the researchers searched for the strengths of the learner by providing them with an opportunity to form their kinetic formation, hence the problem came by introducing a method of self-intelligence and social to guide the learner in the search for ways and solutions to overcome boredom and economy Time and effort in the educational process in learning and give them the freedom to express their ideas And their skills and here came the role of social and self-intelligence to teach the individual and collective kinetic formati

Permeability estimation is a vital step in reservoir engineering due to its effect on reservoir's characterization, planning for perforations, and economic efficiency of the reservoirs. The core and well-logging data are the main sources of permeability measuring and calculating respectively. There are multiple methods to predict permeability such as classic, empirical, and geostatistical methods. In this research, two statistical approaches have been applied and compared for permeability prediction: Multiple Linear Regression and Random Forest, given the (M) reservoir interval in the (BH) Oil Field in the northern part of Iraq. The dataset was separated into two subsets: Training and Testing in order to cross-validate the accuracy

Artificial intelligence techniques are reaching us in several forms, some of which are useful but can be exploited in a way that harms us. One of these forms is called deepfakes. Deepfakes is used to completely modify video (or image) content to display something that was not in it originally. The danger of deepfake technology impact on society through the loss of confidence in everything is published. Therefore, in this paper, we focus on deepfakedetection technology from the view of two concepts which are deep learning and forensic tools. The purpose of this survey is to give the reader a deeper overview of i) the environment of deepfake creation and detection, ii) how deep learning and forensic tools contributed to the detection