The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample

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 com

This research aims to knowledge the extent of the application of Tuz General Hospital to the concept of tacit knowledge dimensions (mental models, intuition, experience, skill) and methods of acquiring knowledge dimensions (training, job rotation, work teams) and the measurement and analysis of the link and the kind of impact between the methods of acquiring knowledge and tacit knowledge of the Angels nursing in the researched hospital, and was the questionnaire primary means of collecting information adopted by the researcher that, the research sample of (90) individuals, including the Angels nursing, has been using the statistical program spss for the purpose of conducting statistical treatments, and through the diagnosis and m

The rapid change in economic is a serious challenge facing all countries around the world, even developed ones. This challenge is increasing as the world enters the age of knowledge in which different knowledge and technologies have emerged and the distance between the emergence of scientific knowledge and its actual application on the ground has been reduced as well as the growing role of science and technology in community development. One of the most important technology amongst these technologies is nanotechnology, where this technology plays a major role in the development of products and modern devices and reduces cost with quality improvement. This technology is cross-cultural, requires a comprehensive knowledge structure and depe

A novel analytical method is developed for the determination of azithromycin. The method utilizes continuous flow injection analysis to enhance the chemiluminescence system of luminol, H2O2, and Cr(III). The method demonstrated a linear dynamic range of 0.001–100 mmol L-1 with a high correlation coefficient (r) of 0.9978, and 0.001–150 mmol L-1 with a correlation coefficient (r) of 0.9769 for the chemiluminescence emission versus azithromycin concentration. The limit of detection (L.O.D.) of the method was found to be 18.725 ng.50 µL−1 based on the stepwise dilution method for the lowest concentration within the linear dynamic range of the calibration graph. The relative standard deviation (R.S.D. %) for n = 6 was less than 1.2%