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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
Thu Jun 23 2022
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Flow Injection Spectrophotometric Technique for Determining of Genistein in Pure and Supplements Formulations Through Diazotization Coupling Reaction
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Genistein (GEN) is The major isoflavone found in soybeans, has a number of cardiovascular health benefits, Postmenopausal syndrome and osteoporosis. A direct flow injection analysis method for estimation of (GEN) in pure and supplements formulation . This system is based on diazotization coupling reactions between procaine penciline (PR) and genistein in basic medium, they formed yellow dyes have maximum absorption at 416 nm. Calibration curve were constructed over different GEN concentrations, linearity for GEN was 10-100 µg.mL-1 and detection limits of 1.51 ?g/mL. In the FIA technique, all analytical factors were analyzed and optimized. The established method was successfully used to determine GEN in the formulations of its supplement

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Publication Date
Fri Dec 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
A Comparison between Methods of Laplace Estimators and the Robust Huber for Estimate parameters logistic regression model
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The logistic regression model regarded as the important regression Models ,where of the most interesting subjects in recent studies due to taking character more advanced in the process of statistical analysis .                                                

The ordinary estimating methods is failed in dealing with data that consist of the presence of outlier values and hence on the absence of such that have undesirable effect on the result.    &nbs

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Publication Date
Sat Feb 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Concept And Importance Of Detection Failureś Possibilities Of Corporation Proposed Model For Application In The Iraqi Environment
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Research aims to shed light on the concept of corporate failures , display and analysis the most distinctive models used to predicting corporate failure; with suggesting  a model to reveal the probabilities of corporate failures which including internal and external financial and non-financial indicators, A tested is made for the research objectivity and its indicators weight and by a  number of academics professionals experts, in addition to  financial analysts  and have concluded a set of conclusions ,  the most distinctive of them that failure is not considered a sudden phenomena for the company and its stakeholders , it is an Event passes through numerous stages; each have their symptoms that lead eve

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Publication Date
Wed Aug 01 2012
Journal Name
International Journal Of Geographical Information Science
Assessing similarity matching for possible integration of feature classifications of geospatial data from official and informal sources
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Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
Comparison between RSA and CAST-128 with Adaptive Key for Video Frames Encryption with Highest Average Entropy
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Encryption of data is translating data to another shape or symbol which enables people only with an access to the secret key or a password that can read it. The data which are encrypted are generally referred to as cipher text, while data which are unencrypted are known plain text. Entropy can be used as a measure which gives the number of bits that are needed for coding the data of an image. As the values of pixel within an image are dispensed through further gray-levels, the entropy increases. The aim of this research is to compare between CAST-128 with proposed adaptive key and RSA encryption methods for video frames to determine the more accurate method with highest entropy. The first method is achieved by applying the "CAST-128" and

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Publication Date
Tue Jan 01 2019
Journal Name
Ieee Access
Intelligent EMG Pattern Recognition Control Method for Upper-Limb Multifunctional Prostheses: Advances, Current Challenges, and Future Prospects
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Publication Date
Thu Oct 09 2025
Journal Name
Frontiers In Dental Medicine
The role of neurogenic inflammation in pulp repair and the techniques used for its assessment (narrative review)
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Neurogenic inflammation is pivotal in dental pulp repair, involving complex interactions between sensory nerves, immune cells, and dental pulp stem cells (DPSCs). This review aimed to identify the favorable pathways of neurogenic inflammation and neurogenic differentiation of DPSCs in the pulpal healing process. Also, to identify the techniques used to evaluate these inflammatory and differentiation processes. Both PubMed and Google Scholar databases were employed in the search strategy using keyword combinations based on MeSH terms. The search was performed for published articles in English from January 2014 to November 2024, including studies with histological and molecular findings. 29 articles only met the inclusion criteria. Neurogenic

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Publication Date
Mon Nov 28 2016
Journal Name
Separation Science And Technology
Using sewage sludge as a permeable reactive barrier for remediation of groundwater contaminated with lead and phenol
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Publication Date
Wed Dec 18 2024
Journal Name
International Journal Of Environmental Analytical Chemistry
Biocomposite adsorbent (cross-linked chitosan + algae + montmorillonite) for methyl violet 2B dye removal: statistical modelling and optimisation
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Herein, a biocomposite of crosslinked chitosan polyethylene glycol diglycidyl ether (CS-PEDGE), montmorillonite (MMT), and foodgrade algae (FGA) was successfully prepared by a hydrothermal technique. The resulting absorbent (CS-PEDGE/FGA/MMT) was assessed for its adsorption property with methyl violet 2B (MV 2B) a toxic cationic dye. The physicochemical properties of CS-EDGE/ FGA/MMT were assessed via various analytical techniques, including BET, Elemental analysis, pHpzc, and spectroscopy (FTIR, XRD, SEM-EDX). The influence of three adsorption variables, namely adsorbent dose (A: 0.02–0.1 g/100 mL), solution pH (B: 4–10), and contact time (C: 10–420 min) on the rate of MV 2B dye removal was examined using the Box-Behnken design (RSM-

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Publication Date
Tue Sep 07 2021
Journal Name
Journal Of Petroleum Exploration And Production Technology
Wellbore instability management using geomechanical modeling and wellbore stability analysis for Zubair shale formation in Southern Iraq
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Abstract<p>Wellbore instability problems cause nonproductive time, especially during drilling operations in the shale formations. These problems include stuck pipe, caving, lost circulation, and the tight hole, requiring more time to treat and therefore additional costs. The extensive hole collapse problem is considered one of the main challenges experienced when drilling in the Zubair shale formation. In turn, it is caused by nonproductive time and increasing well drilling expenditure. In this study, geomechanical modeling was used to determine a suitable mud weight window to overpass these problems and improve drilling performance for well development. Three failure criteria, including Mohr–Coulomb, modifie</p> ... Show More
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