In this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database

    Predicting the network traffic of web pages is one of the areas that has increased focus in recent years. Modeling traffic helps find strategies for distributing network loads, identifying user behaviors and malicious traffic, and predicting future trends. Many statistical and intelligent methods have been studied to predict web traffic using time series of network traffic. In this paper, the use of machine learning algorithms to model Wikipedia traffic using Google's time series dataset is studied. Two data sets were used for time series, data generalization, building a set of machine learning models (XGboost, Logistic Regression, Linear Regression, and Random Forest), and comparing the performance of the models using (SMAPE) and

     is at an all-time high in the modern period, and the majority of the population uses the Internet for all types of communication. It is great to be able to improvise like this. As a result of this trend, hackers have become increasingly focused on attacking the system/network in numerous ways. When a hacker commits a digital crime, it is examined in a reactive manner, which aids in the identification of the perpetrators. However, in the modern period, it is not expected to wait for an attack to occur. The user anticipates being able to predict a cyberattack before it causes damage to the system. This can be accomplished with the assistance of the proactive forensic framework presented in this study. The proposed system combines

Skin detection is classification the pixels of the image into two types of pixels skin and non-skin. Whereas, skin color affected by many issues like various races of people, various ages of people gender type. Some previous researchers attempted to solve these issues by applying a threshold that depends on certain ranges of skin colors. Despite, it is fast and simple implementation, it does not give a high detection for distinguishing all colors of the skin of people. In this paper suggests improved ID3 (Iterative Dichotomiser) to enhance the performance of skin detection. Three color spaces have been used a dataset of RGB obtained from machine learning repository, the University of California Irvine (UCI), RGB color space, HSV color sp

Drawbacks of Implementing Electronic Management in the Ministry of Education (A sample: Oman Educational Portal) from the Point of View of IT Staff. The study aimed at discovering the drawbacks of implementing electronic management in the Ministry of Education (a sample: Oman Educational Portal) from the point of view of IT staff, and that is by answering the following questions: - What are the main drawbacks (administrative, financial, technical and drawbacks related to human resources) that hinder implementing the electronic management in the Ministry of Education (a sample: Oman Educational Portal) from the point of view of IT staff? - Are there any statistical significance differences at the level (0.05) between study samples on the

    A prominent figure such as Yahya bin Khaldoun and a scholar of the moroccan countries in the medieval era, and had a special place in the history of the country and the state of Bani Zayan, and the positions he occupied in it and left his scientific, literary and historical traces, leaving him an imprint in the course of history and its events, and in this study
I dealt with the research: his personal life : his name and lineage, then his upbringing and his family.

    The aim of the study is to know this character in the details of his personal and scientific life, according to the historical descriptive research method, including description and presentation of events, and linking them in a

      Cyberbullying is one of the biggest electronic problems that takes multiple forms of harassment using various social media. Currently, this phenomenon has become very common and is increasing, especially for young people and adolescents. Negative comments have a significant and dangerous impact on society in general and on adolescents in particular. Therefore, one of the most successful prevention methods is to detect and block harmful messages and comments. In this research, negative Arabic comments that refer to cyberbullying will be detected using a support vector machine algorithm. The term frequency-inverse document frequency vectorizer and the count vectorizer methods were used for feature extraction, and the results wer

A new human-based heuristic optimization method, named the Snooker-Based Optimization Algorithm (SBOA), is introduced in this study. The inspiration for this method is drawn from the traits of sales elites—those qualities every salesperson aspires to possess. Typically, salespersons strive to enhance their skills through autonomous learning or by seeking guidance from others. Furthermore, they engage in regular communication with customers to gain approval for their products or services. Building upon this concept, SBOA aims to find the optimal solution within a given search space, traversing all positions to obtain all possible values. To assesses the feasibility and effectiveness of SBOA in comparison to other algorithms, we conducte

Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

ءأرﻘﻟا ةﺎﯾﺣﺑ ًﺎﻘﯾﺛو ًﻻﺎﺻﺗا لﺻﺗﺗ. نﻣ ﮫﺑﺗﺎﮐﻟﻟ ﻲﺻﺧﺷﻟا ﻊﺑﺎطﻟا ﻲﻔﺣﺻﻟا دوﻣﻌﻟا لﻣﺣﯾ ا فﻟﺗﺧﻣﻟ ﮫﻟوﺎﻧﺗ لﻼﺧ وا ﮫﺋارا وا هرظﻧ ﺔﮭﺟو لﻣﺣﺗ ﻲﺗﻟا ﺔﯾﻣوﯾﻟا ثادﺣﻻاو ﺎﯾﺎﺿﻘﻟ ﺢﺿﻔﺑ موﻘﯾو ثادﺣﻻاو ﺔﯾﺑﻟﺳﻟا رھاوظﻟﻟ ىدﺻﺗﯾ وا، ءيرﺎﻘﻟا ﯽﻟا ﮫﺑرﺎﺟﺗ وا هرﺎﮐﻓا ءﺎطﺧﻻا دﺻرﯾ بﯾﻗرﺑ ﮫﺑﺷا وھو، ءيرﺟﻟا دﻘﻧﻟا نﻋ مﻧﯾ بوﻟﺳﺎﺑ ﺔﺋطﺎﺧﻟا تﺎﺳرﺎﻣﻣﻟا ﺎﮭﺣدﻣﯾو تﺎﯾﺑﺎﺟﯾﻻا ﯽﻟﻋ