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

--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

In information security, fingerprint verification is one of the most common recent approaches for verifying human identity through a distinctive pattern. The verification process works by comparing a pair of fingerprint templates and identifying the similarity/matching among them. Several research studies have utilized different techniques for the matching process such as fuzzy vault and image filtering approaches. Yet, these approaches are still suffering from the imprecise articulation of the biometrics’ interesting patterns. The emergence of deep learning architectures such as the Convolutional Neural Network (CNN) has been extensively used for image processing and object detection tasks and showed an outstanding performance compare

This work presents a novel technique for the detection of oil aging in electrical transformers using a single mode optical fiber sensor based on surface plasmon resonance (SPR). The aging of insulating oil is a critical issue in the maintenance and performance of electrical transformers, as it can lead to reduce insulation properties, increase risk of electrical breakdown, and decrease operational lifespan. Many parameters are calculated in this study in order to examine the efficiency of this sensor like sensitivity (S), signal to noise ratio (SNR), resolution (refractive index unit) and figure of merit (FOM) and the values are for figure of merit is 11.05, the signal to noise ratio is 20.3, the sensitivity is 6.63, and the resolution is 3

The aim of the current research is to know the degree to which middle school teachers and female teachers in the southern border schools use electronic educational alternatives in the field of education from their point of view and its relationship to some variables, and to achieve this goal, a random sample of (200) teachers was selected in southern border schools, and a questionnaire was prepared to collect The data, as well as the descriptive approach was used to achieve this goal. T-test and analysis of variance were used for the statistical treatment. The results concluded that the educational courses provided to male and female teachers are not sufficient. It has also been concluded that the use of electronic educational alternativ

Cryptocurrency became an important participant on the financial market as it attracts large investments and interests. With this vibrant setting, the proposed cryptocurrency price prediction tool stands as a pivotal element providing direction to both enthusiasts and investors in a market that presents itself grounded on numerous complexities of digital currency. Employing feature selection enchantment and dynamic trio of ARIMA, LSTM, Linear Regression techniques the tool creates a mosaic for users to analyze data using artificial intelligence towards forecasts in real-time crypto universe. While users navigate the algorithmic labyrinth, they are offered a vast and glittering selection of high-quality cryptocurrencies to select. The

The current research aims to examine the effect of the rapid learning method in developing creative thinking among second-grade female students in the subject of history. Thus, the researcher has adopted an experimental design of two groups to suit the nature of the research. The sample of the study consists of (36) randomly selected students from Al-Shafaq Secondary School for Women, which are divided randomly into two groups. The first group represents the experimental; it includes (31) students who studied the subject of history using the quick learning method. The second group, on the other hand, is the control group, which consists of (32) students, who studied the same subject using the traditional way. Before starting with the exp