In this article, Convolution Neural Network (CNN) is used to detect damage and no damage images form satellite imagery using different classifiers. These classifiers are well-known models that are used with CNN to detect and classify images using a specific dataset. The dataset used belongs to the Huston hurricane that caused several damages in the nearby areas. In addition, a transfer learning property is used to store the knowledge (weights) and reuse it in the next task. Moreover, each applied classifier is used to detect the images from the dataset after it is split into training, testing and validation. Keras library is used to apply the CNN algorithm with each selected classifier to detect the images. Furthermore, the performa

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

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 moral aspect is an important one in the structure of personality , and the lack of moral aspect is responsible for what we suffering today from problems . there is no exaggeration to say that many of our current problems are moral problems , and reflects the lack of moral growth.                            

 The goal of research is to build scale in order to detect the level of moral reasoning among junior high school students in Baghdad , The researcher followed the procedures in the construction of scientific standards in order to measur

Art education is one among the fundamental subjects for elementary school students, because it contributes to assembling learners’ personalities and developing their technical skills. For this reason, this research comes, which aims to understand the effect of the task groups’ strategy in developing the performance of elementary school students in art education. to realize the goal of the research, the researcher put the subsequent hypotheses:
-There is not any statistically significant difference at the amount (5%) between the typical many students between the experimental group that studied consistent with the strategy of task groups and therefore the control group that studied in keeping with the same old method that they obt

To assess cultural competence among nursing students from nine countries to provide an international perspective on cultural competence.