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An IoT and Machine Learning-Based Predictive Maintenance System for Electrical Motors
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The rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient communication between the sensors, gateway devices, and the cloud server. The system was tested on an operational motors dataset, five machine learning algorithms, namely k-nearest neighbor (KNN), supported vector machine (SVM), random forest (RF), linear regression (LR), and naive bayes (NB), are used to analyze and process the collected data to predict motor failures and offer maintenance recommendations. Results demonstrate the random forest model achieves the highest accuracy in failure prediction. The solution minimizes downtime and costs through optimized maintenance schedules and decisions. It represents an Industry 4.0 approach to sustainable smart manufacturing.

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Publication Date
Tue Nov 01 2022
Journal Name
Journal Of Photochemistry And Photobiology B: Biology
High efficiency of Ag0 decorated Cu2MoO4 nanoparticles for heterogeneous photocatalytic activation, bactericidal system, and detection of glucose from blood sample
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Publication Date
Mon Jul 01 2024
Journal Name
Ecological Engineering & Environmental Technology
Use of Nano Co-Ni-Mn Composite and Aluminum for Removal of Artificial Anionic Dye Congo Red by Combined System
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The removal of congo red (CR) is a critical issue in contemporary textile industry wastewater treatment. The current study introduces a combined electrochemical process of electrocoagulation (EC) and electro-oxidation (EO) to address the elimination of this dye. Moreover, it discusses the formation of a triple composite of Co, Mn, and Ni oxides by depositing fixed salt ratios (1:1:1) of these oxides in an electrolysis cell at a constant current density of 25 mA/cm2. The deposition ended within 3 hours at room temperature. X-ray diffractometer (XRD), field emission scanning electron microscopy (FESEM), atomic force microscopy (AFM), and energy dispersive X-ray (EDX) characterized the structural and surface morphology of the multi-oxide sedim

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Publication Date
Wed Jul 01 2020
Journal Name
Journal Of Engineering
An Analytical Solution for the Maximum Tensile Stress and Stress Concentration Factor Investigations for Standard, Asymmetric fillets, Asymmetric Pressure Angle and Profile Shifted Helical and Spur Gears
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This research introduces a developed analytical method to determine the nominal and maximum tensile stress and investigate the stress concentration factor. The required tooth fillets parametric equations and gears dimensions have been reformulated to take into account the asymmetric fillets radiuses, asymmetric pressure angle, and profile shifting non-standard modifications. An analytical technique has been developed for the determination of tooth weakest section location for standard, asymmetric fillet radiuses, asymmetric pressure angle and profile shifted involute helical and spur gears. Moreover, an analytical equation to evaluate gear tooth-loading angle at any radial distance on the involute profile of spur and hel

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Publication Date
Fri Jul 26 2024
Journal Name
Academia Open
Enhancing Pediatric Nursing Skills by Top Learning Strategies
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Background: The efficacy of educational strategies is crucial for nursing students to competently perform pediatric procedures like nasogastric tube insertion. Specific Background: This study evaluates the effectiveness of simulation, blended, and self-directed learning strategies in enhancing these skills among nursing students. Knowledge Gap: Previous research lacks a comprehensive comparison of these strategies' impacts on skill development in pediatric nursing contexts. Aims: The study aims to assess the effectiveness of different educational strategies on nursing students' ability to perform pediatric nasogastric tube insertions. Methods: A pre-experimental design was employed at the College of Nursing, University of Baghdad, i

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Publication Date
Sun Nov 01 2020
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Utilizing the ATM technology in e-distance learning
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<p>There is an Increasing demand for the education in the field of E-learning specially the higher education, and to keep contiuity between the user and the course director in any place and time. This research presents a proposed and simulation multimedia network design for distance learning utilizing ATM technique. The propsed framework determines the principle of ATM technology and shows how multimedia can be integrated within E- learning conteext. The first part of this research presents a theoretical design for the Electricity Department, university of technology. The purpose is to illustrate the usage of the ATM and Multimedia in distance learning process. In addition, this research composes two entities: Software entity

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Publication Date
Sun Jan 31 2016
Journal Name
International Journal Of Research In Humanities, Arts, And Literature
THE PROBLEMS FACING IRAQI CHILDREN IN LEARNING ENGLISH
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DBN Rashid, IMPAT: International Journal of Research in Humanities, Arts, and Literature, 2016 - Cited by 5

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Publication Date
Sun Nov 14 2021
Journal Name
Palarch's Journal Of Archaeology Of Egypt/egyptology
Blended Learning in Teaching English to University Students
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QJ Rashid, IH Abdul-Abbas, MR Younus, PalArch's Journal of Archaeology of Egypt/Egyptology, 2021 - Cited by 4

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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Engineering
Arabic Sentiment Analysis (ASA) Using Deep Learning Approach
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Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l

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Publication Date
Sat Dec 31 2022
Journal Name
International Journal On “technical And Physical Problems Of Engineering”
Age Estimation Utilizing Deep Learning Convolutional Neural Network
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Estimating an individual's age from a photograph of their face is critical in many applications, including intelligence and defense, border security and human-machine interaction, as well as soft biometric recognition. There has been recent progress in this discipline that focuses on the idea of deep learning. These solutions need the creation and training of deep neural networks for the sole purpose of resolving this issue. In addition, pre-trained deep neural networks are utilized in the research process for the purpose of facial recognition and fine-tuning for accurate outcomes. The purpose of this study was to offer a method for estimating human ages from the frontal view of the face in a manner that is as accurate as possible and takes

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Publication Date
Tue Jan 01 2019
Journal Name
Journal Of Human Sport And Exercise - 2019 - Spring Conferences Of Sports Science
The use of the electrical stimulation device for the muscles in the limit determines the elbow joint during the lifting of the disabled weightlifting players
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