ُعد الاضطهاد الديني في ميانمار من أبرز القضايا الإنسانية والسياسية في جنوب شرق آسيا، إذ تعاني بعض الأقليات الدينية، خصوصًا المسلمين والمسيحيين، من التمييز والقيود والانتهاكات المستمرة

التجربة الاتحادية في دولة الامارات العربية المتحدة

Many changes took place in a number of Arab countries, most of which ended with the change of the ruling leadership and a new coming. The same change brought about the hopes of the people to turn the page of the past into a democracy through which to overcome the grievances of previous years and achieve justice in all its aspects. The same new grievances have been added to that precedent and justice has not yet been achieved. Here we try to address the justice that is applied in the stages of change or transitional stages, which have been called, ie transitional justice, which has mechanisms and conditions of different application between countries, each of which the conditions applied in them and through a review of these mechanisms bet

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

With the vast usage of network services, Security became an important issue for all network types. Various techniques emerged to grant network security; among them is Network Intrusion Detection System (NIDS). Many extant NIDSs actively work against various intrusions, but there are still a number of performance issues including high false alarm rates, and numerous undetected attacks. To keep up with these attacks, some of the academic researchers turned towards machine learning (ML) techniques to create software that automatically predict intrusive and abnormal traffic, another approach is to utilize ML algorithms in enhancing Traditional NIDSs which is a more feasible solution since they are widely spread. To upgrade t

One study whose importance has significantly grown in recent years is lip-reading, particularly with the widespread of using deep learning techniques. Lip reading is essential for speech recognition in noisy environments or for those with hearing impairments. It refers to recognizing spoken sentences using visual information acquired from lip movements. Also, the lip area, especially for males, suffers from several problems, such as the mouth area containing the mustache and beard, which may cover the lip area. This paper proposes an automatic lip-reading system to recognize and classify short English sentences spoken by speakers using deep learning networks. The input video extracts frames and each frame is passed to the Viola-Jone