In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve

      The Arabic Language is the native tongue of more than 400 million people around the world,  it is also a language that carries an important religious and international weight.  The Arabic language has taken its share of the huge technological explosion that has swept the world, and therefore it needs to be addressed with natural language processing applications and tasks.

This paper aims to survey and gather the most recent research related to Arabic Part of Speech (APoS), pointing to tagger methods used for the Arabic language, which ought to aim to constructing corpus for Arabic tongue. Many AI investigators and researchers have worked and performed POS utilizing various machine-learning methods, such as Hidden-Mark

The purpose of this research is to suggest a model which may be used by law enforcement to broaden individual and organizational creativity while providing a more inclusive, holistic view of management within our internal and external organizational structures. This project introduces alternatives to traditional management, leadership styles and problem solving strategies. Law enforcement organizations in the 21st century will face many challenges. Much like community policing impacted the nation in the mid 1980's through the 1990's, the systems thinking approach offers a philosophy for the new millennium.

Most organizations will face many challenges in the next decade of the twentieth first century. Just

In this paper, we used four classification methods to classify objects and compareamong these methods, these are K Nearest Neighbor's (KNN), Stochastic Gradient Descentlearning (SGD), Logistic Regression Algorithm(LR), and Multi-Layer Perceptron (MLP). Weused MCOCO dataset for classification and detection the objects, these dataset image wererandomly divided into training and testing datasets at a ratio of 7:3, respectively. In randomlyselect training and testing dataset images, converted the color images to the gray level, thenenhancement these gray images using the histogram equalization method, resize (20 x 20) fordataset image. Principal component analysis (PCA) was used for feature extraction, andfinally apply four classification metho

Classification of network traffic is an important topic for network management, traffic routing, safe traffic discrimination, and better service delivery. Traffic examination is the entire process of examining traffic data, from intercepting traffic data to discovering patterns, relationships, misconfigurations, and anomalies in a network. Between them, traffic classification is a sub-domain of this field, the purpose of which is to classify network traffic into predefined classes such as usual or abnormal traffic and application type. Most Internet applications encrypt data during traffic, and classifying encrypted data during traffic is not possible with traditional methods. Statistical and intelligence methods can find and model traff

Online learning is not a new concept in education, but it has been used extensively since the Covid-19 pandemic and is still in use now. Every student in the world has gone through this learning process from the primary to the college levels, with both teachers and students conducting instruction online (at home). The goal of the current study is to investigate college students’ attitudes towards online learning. To accomplish the goal of the current study, a questionnaire is developed and adjusted before being administered to a sample of 155 students. Additionally, validity and reliability are attained. Some conclusions, recommendations, and suggestions are offered in the end.

     Agriculture improvement is a national economic issue that extremely depends on productivity. The explanation of disease detection in plants plays a significant role in the agriculture field. Accurate prediction of the plant disease can help treat the leaf as early as possible, which controls the economic loss. This paper aims to use the Image processing techniques with Convolutional Neural Network (CNN). It is one of the deep learning techniques to classify and detect plant leaf diseases. A publicly available Plant village dataset was used, which consists of 15 classes, including 12 diseases classes and 3 healthy classes.  The data augmentation techniques have been used. In addition to dropout and weight reg

التعلم هو المظهر الرئيسي في حياة البشرية المتحضرة ،الذي يعبر عن نشاطهم العقلي الذي وهبه الله سبحانه وتعالى ، وما على الإنسان ألا إن يستغل هذه إلهية الإلهية بأقصى ما يمكن للاستفادة منها, ومن هذا المنطلق لابد أن يعتمد المتعلم على طرق وأساليب منطقية في اكتساب المعرفة والتعامل مع المعلومات ومعالجتها ، وتعرف هذه (بأساليب التعلم styles learning) وهي الفروق الفردية في طرق التلقي والإدراك والتذكر وا

Background: Cardiovascular disease (CVD) is the number one cause of death worldwide. Objective: To determine of coronary care unit nurses' knowledge regarding patient rehabilitation after myocardial infarction. Methodology: A cross- sectional study was designed in the Cardiac Care Unit of Al-Diwaniyah Teaching Hospital and the Specialized Center for Cardiac Surgery and Catheterization for the period from (November 7, 2022) to (May 12, 2023). A non-probability (purposive) sample consisting of (75 nurses) working in the above-mentioned study site. To determination of coronary care unit Nurses' knowledge regarding patient rehabilitation after myocardial infarction, the researcher used a tool that consists of two parts: The first part: