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 after integrating the convolutional neural networks (CNN) and long short-term memory (LSTM) networks to extract both spatial and temporal features from motor data. The presented mechanism shows higher accuracy (98.1%) and computational efficiency compared to the state-of-the-art algorithms, and it can be implemented in real time on edge computing systems, facilitating continuous motor condition monitoring in electric vehicles. © 2025 IEEE.
This paper presents the application of a framework of fast and efficient compressive sampling based on the concept of random sampling of sparse Audio signal. It provides four important features. (i) It is universal with a variety of sparse signals. (ii) The number of measurements required for exact reconstruction is nearly optimal and much less then the sampling frequency and below the Nyquist frequency. (iii) It has very low complexity and fast computation. (iv) It is developed on the provable mathematical model from which we are able to quantify trade-offs among streaming capability, computation/memory requirement and quality of reconstruction of the audio signal. Compressed sensing CS is an attractive compression scheme due to its uni
... Show MoreThe need for an efficient method to find the furthermost appropriate document corresponding to a particular search query has become crucial due to the exponential development in the number of papers that are now readily available to us on the web. The vector space model (VSM) a perfect model used in “information retrieval”, represents these words as a vector in space and gives them weights via a popular weighting method known as term frequency inverse document frequency (TF-IDF). In this research, work has been proposed to retrieve the most relevant document focused on representing documents and queries as vectors comprising average term term frequency inverse sentence frequency (TF-ISF) weights instead of representing them as v
... Show MoreThisstudy aims to determine the specifications of obese women accordingto the heightand type of obesity. It also aimstoidentify the significance of differences in choosing ready-made clothes for the research sample. Finally, the significance of differences in choosing ready-made clothes according to the variable of binaryclassification ofobesity is also identified.The study sample includes obese women: employees, non-employees and students with the age group (18-50) years.The weights and lengths of the sample have been taken to suit the group of obese women.Aquestionnaire in the form of an open question was distributed among (50) obese womenso as to extract the items of the questionnaire. After that, the questionnaire was distributed amo
... Show MoreNowadays, university education stands in front of both students who feel they are weak and teachers who are addicted to using traditional and dependent teaching. This has led to have negative repercussions on the learner from different aspects, including the mental aspect and the academic achievement process. Therefore, the present research is concerned with finding a new teaching method that adopts the motivation by the fear of failure technique. Thus, the study aims to examine the effect of adopting this method on students’ academic achievement. To achieve this aim, an experimental method was used, and an achievement test was built for the curriculum material of level two students. The pretest test was applied on 17 male and female s
... Show MoreJean-Paul Sartre and Badr Shakir al-Sayyabe are among the most prominent writers that critiqued the destructive role of capitalism and the patriarchal power system in the period of the Post-World War II crisis. Divided into three chapters, the present study examines two of the most eminent literary works in the history of the Western and Eastern societies in the fifties of the last decade: Jean Paul Sartre’s play : The Respectful Prostitute and Badr Shaker al-Sayyabe’s poem: The Blind Prostitute.
Chapter one discusses the position of the prostitute in a patriarchal societies. Chapter two linguistically analy
... Show MoreLegislative language is characterized by its complexity, specifically in the process of translating statutory terms from two quite different languages, and from totally two different legal systems as from Spanish into Arabic. The present study stresses the process of translating legislative terms used in Spanish wills into Arabic through high lightening the polysemy of such mentioned terms and explaining their use in other legislative grounds. Additionally, the present study elucidates, analyzes, underlines the difficulty and looks for the most appropriate procedures and techniques of translating some of the prominent inheritance expressions taking in account the legislative dif
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This paper tackles the theme of alienation as being a concurrent state of human being from birth to death; so extensive is the description of this state by writers. Alienation has been a product of their hard experiences and miserable lives. One such writer is Jean-Marie Gustave le Clézio who was so perfect in describing alienation in his works. Upon so many occasions, he imagined one or more of his characters as living in a chaotic world and so lived safely in alienation. The novel "Le Procès-Verbal" is one of the most important of his works. This paper deals with e the narrative structure of novel while shedding light on the hero's alienation: its essence and causes.
... Show MoreThe logistic regression model is an important statistical model showing the relationship between the binary variable and the explanatory variables. The large number of explanations that are usually used to illustrate the response led to the emergence of the problem of linear multiplicity between the explanatory variables that make estimating the parameters of the model not accurate.
... Show MoreThis book includes four main chapters: 1. Indefinite Integral. 2. Methods of Integration. 3. Definite Integral. 4. Multiple Integral. In addition to many examples and exercises for the purpose of acquiring the student's ability to think correctly in solving mathematical questions.
Applications of remote sensing are important in improving potato production through the broader adoption of precision agriculture. This technology could be useful in decreasing the potential contamination of soil and water due to the over-fertilization of agriculture crops. The objective of this study was to assess the utility of active sensors (Crop Circle™, Holland Scientific, Inc., Lincoln, NE, USA and GreenSeeker™, Trimble Navigation Limited, Sunnyvale, CA, USA) and passive sensors (multispectral imaging with Unmanned Arial Vehicles (UAVs)) to predict total potato yield and phosphorus (P) uptake. The experimental design was a randomized complete block with four replications and six P treatments, ranging from 0 to 280 kg P ha−1, as
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