Emotional competence, is relatively a new concept, stands for the ability of people to perceive their feelings and emotions, and sharing them with others. It also refers to capability in optimizing these feeling and emotions, and managing them over various situations. Thus, this study aims to examine the efficiency of counseling program in developing an emotional competence among intermediate school students in Baghdad city. The sample included group of female students at intermediate stage. The findings revealed none of experimental and control groups have statistically significant differences in pre-posttests of emotional competence efficiency.

Current research strives to achieve the following aims:

1. Develop a scale for dominant values of Tikrit university students.
2. Measuring the dominant of Tikrit university students.
3. Identifying the significant differences among dominant values of Tikrit university students according to(sex, specialty, time).
4. Measuring the dominant values of each one of the six fields of the scale.
5. Identifying the differences in dominant values of each field according to the sex variables.

The current research has limi

The need to constantly and consistently improve the quality and quantity of the educational system is essential. E-learning has emerged from the rapid cycle of change and the expansion of new technologies. Advances in information technology have increased network bandwidth, data access speed, and reduced data storage costs. In recent years, the implementation of cloud computing in educational settings has garnered the interest of major companies, leading to substantial investments in this area. Cloud computing improves engineering education by providing an environment that can be accessed from anywhere and allowing access to educational resources on demand. Cloud computing is a term used to describe the provision of hosting services

Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with

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