Obesity-related deaths continue to rise, and thus losing weight in overweight and obese patients is critical to prevent complications. Anredera cordifolia (Ten,) Steenis, species of succulent plant of the genus Basellaceae, is widely used in herbal medicine to decrease body weight. This study evaluated the potential benefits of Anredera cordifolia ethanol extract to reduce body weight in high-fat diet-induced obesity rat model. This was an experimental with post-test only control group design study involving 36 obese rats. They were divided into two groups: three control groups (K1, K2, K3) and three treatment groups (P1, P2, P3). All the groups were induced with high-fat diet, except K1 control group that received a standard di

The study aimed to identify the E-leadership practice at Princess Nora Bint Abdul Rahman University and to explore the obstacles that are facing the leaders in the implementation of E-leadership, in addition to find mechanisms to improve the practice of electronic driving at the university in light of the Corona pandemic. A descriptive analytical approach was used by depending on a questionnaire to collect the needed data. The study sample consisted of (139) heads of departments, attorneys' colleges and support Deanships universities. The study results showed that E-leadership employment recorded a medium to high degree. Especially at university, that publishing decisions electronically and uses technical means in providing its services.

    Text categorization refers to the process of grouping text or documents into classes or categories according to their content. Text categorization process consists of three phases which are: preprocessing, feature extraction and classification. In comparison to the English language, just few studies have been done to categorize and classify the Arabic language. For a variety of applications, such as text classification and clustering, Arabic text representation is a difficult task because Arabic language is noted for its richness, diversity, and complicated morphology. This paper presents a comprehensive analysis and a comparison for researchers in the last five years based on the dataset, year, algorithms and the accuracy th

Whenever, the Internet of Things (IoT) applications and devices increased, the capability of the its access frequently stressed. That can lead a significant bottleneck problem for network performance in different layers of an end point to end point (P2P) communication route. So, an appropriate characteristic (i.e., classification) of the time changing traffic prediction has been used to solve this issue. Nevertheless, stills remain at great an open defy. Due to of the most of the presenting solutions depend on machine learning (ML) methods, that though give high calculation cost, where they are not taking into account the fine-accurately flow classification of the IoT devices is needed. Therefore, this paper presents a new model bas

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

       In the pandemic era of COVID19, software engineering and artificial intelligence tools played a major role in monitoring, managing, and predicting the spread of the virus. According to reports released by the World Health Organization, all attempts to prevent any form of infection are highly recommended among people. One side of avoiding infection is requiring people to wear face masks. The problem is that some people do not incline to wear a face mask, and guiding them manually by police is not easy especially in a large or public area to avoid this infection. The purpose of this paper is to construct a software tool called Face Mask Detection (FMD) to detect any face that does not wear a mask in a specific