In recent years, the field of research around the congestion problem of 4G and 5G networks has grown, especially those based on artificial intelligence (AI). Although 4G with LTE is seen as a mature technology, there is a continuous improvement in the infrastructure that led to the emergence of 5G networks. As a result of the large services provided in industries, Internet of Things (IoT) applications and smart cities, which have a large amount of exchanged data, a large number of connected devices per area, and high data rates, have brought their own problems and challenges, especially the problem of congestion. In this context, artificial intelligence (AI) models can be considered as one of the main techniques that can be used to solve network congestion problems. Since AI technologies are able to extract relevant features from data and deal with huge amounts of data, the integration of communication networks with AI to solve the congestion problem appears promising, and the research requires exploration. This paper provides a review of how AI technologies can be used to solve the congestion problem in 4G and 5G networks. We examined previous studies addressing the problem of congestion in networks, such as congestion prediction, congestion control, congestion avoidance, and TCP development for congestion control. Finally, we discuss the future vision of using AI technologies in 4G and 5G networks to solve congestion problems and identify research issues that need further study.
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Background: Multiple sclerosis (MS) is an inflammatory disease of the central nervous system, in which the myelin sheaths got injured. The prevalence of MS is on grow, as well as, it affects the young ages. Females are most common to have MS compared to males. Oxidative stress is the situation of imbalance between oxidants (free radicals and reactive oxygen species (ROS)) and antioxidants in a living system, in which either the oxidants are elevated or antioxidants are reduced, or sometimes both. ROS and oxidative stress have been implicated in the progression of many degenerative diseases, which is important in cracking the unrevealed mysteries of MS. In this review article, some of the proposed mechanisms that link oxidative stres
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حضيت القيادة باهتمام كبير من قبل الباحثين ودورها الإيجابي في التأثير على الموظفين ونجاح المنظمات، في الآونة الأخير بدأت الدراسات تركز على الجانب المظلم للقيادة وتأثيرها على التابعين وبيئة العمل، وقد تم تحديد القيادة السامة بأنها أخطر الأساليب القيادية التي تتسبب بتكاليف مادية ومعنوية على المنظمات بمختلف جوانبها، ان القيادة السامة تأثر على دوافع المرؤوسين وقدرتهم على انجاز المهام، ورغبتهم في الاستمرار في
... Show MoreOne of the recent significant but challenging research studies in computational biology and bioinformatics is to unveil protein complexes from protein-protein interaction networks (PPINs). However, the development of a reliable algorithm to detect more complexes with high quality is still ongoing in many studies. The main contribution of this paper is to improve the effectiveness of the well-known modularity density ( ) model when used as a single objective optimization function in the framework of the canonical evolutionary algorithm (EA). To this end, the design of the EA is modified with a gene ontology-based mutation operator, where the aim is to make a positive collaboration between the modularity density model and the proposed
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