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 study aimed at accounting for the role of talents management in consolidating organizational learning process at the Yemeni General Corporation For telecommunication. To achieve the objective of the study, the researcher designed a questionnaire and administered it. The sample of the study consisted of (166) employees (General Manager, Manager and Department Head). They were selected randomly out of a total Population of (291) employees during the Year 2019. The descriptive analytic approach was used t reach conclusions.

The finding of the study revealed existence of effect of talents management dimensions, all together and alone, (talents polarization, talents development, talents maintenance and ma

The problem of slow learning in primary schools’ pupils is not a local or private one. It is also not related to a certain society other than others or has any relation to a particular culture, it is rather an international problem of global nature. It is one of the well-recognized issues in education field. Additionally, it is regarded as one of the old difficulties to which ancient people gave attention. It is discovered through the process of observing human behaviour and attempting to explain and predict it.
Through the work of the two researchers via frequent visits to primary schools that include special classes for slow learning pupils, in addition to the fact that one of the researcher has a child with slow learning issue, t

Abstract

Objective(s): To evaluate blended learning in nursing education at the Middle Region in Iraq.

Methodology: A descriptive study, using evaluation approach, is conducted to evaluate blended learning in nursing education in Middle Region in Iraq from September 26^th, 2021 to March 22^nd, 2022. The study is carried out at two Colleges of Nursing at the University of Baghdad and University of Tikrit in Iraq. A convenient, non-probability, sample of (60) undergraduate nursing students is selected. The sample is comprised of (30) student from each college of nursing, Self-report questionnaire is constructed from the literature, for e

Abstract

The current research aims to identify the effect of using a model of generative learning in the achievement of first-middle students of chemical concepts in science. The researcher adopted the null hypothesis, which is there is no statistically significant difference at the level (0.05) between the mean scores of the experimental group who study using the generative learning model and the average scores of the control group who study using the traditional method in the chemical concepts achievement test. The research consisted of (200) students of the first intermediate at Al-Farqadin Intermediate School for Boys affiliated with the Directorate of General Education in Baghdad Governorate / Al-Karkh 3 wit

Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m

Most of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B

The present study aims to identify the most and the least common teaching practices among faculty members in Northern Border University according to brain-based learning theory, as well as to identify the effect of sex, qualifications, faculty type, and years of experiences in teaching practices. The study sample consisted of (199) participants divided into 100 males and 99 females. The study results revealed that the most teaching practice among the study sample was ‘I am trying to create an Environment of encouragement and support within the classroom which found to be (4.4623). As for the least teaching practice was ‘I use a natural musical sounds to create student's mood to learn’ found to be (2.2965). The study results also in

Variation in DNA, and genes to a lesser or greater extent, can play an important role in most diseases; that is because this variation in will reflect and affect the function of DNA, and genes (combined genes and DNA or separately). This can be affected by environment, life style, as well as the inheriting from parents and previous generations. All these factors can contribute in human diseases. There are different alterations in genes, like imbalance and inequality in chromosomes, disorder in gene (deficiency in gene, which could be complex or single disorder), and cancer. In the last decades, scientists were focus on medicine and genetics; they pay an extensive attention to reach better understanding about diseases and their cause

          The aim of this paper is to present a new methodology to find the private key of RSA. A new initial value which is generated from a new equation is selected to speed up the process. In fact, after this value is found, brute force attack is chosen to discover the private key. In addition, for a proposed equation, the multiplier of Euler totient function to find both of the public key and the private key is assigned as 1. Then, it implies that an equation that estimates a new initial value is suitable for the small multiplier. The experimental results show that if all prime factors of the modulus are assigned larger than 3 and the multiplier is 1, the distance between an initial value and the private key