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.
The objective of this study is to examine the properties of Bayes estimators of the shape parameter of the Power Function Distribution (PFD-I), by using two different prior distributions for the parameter θ and different loss functions that were compared with the maximum likelihood estimators. In many practical applications, we may have two different prior information about the prior distribution for the shape parameter of the Power Function Distribution, which influences the parameter estimation. So, we used two different kinds of conjugate priors of shape parameter θ of the <
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In the present study, a total of 272 freshwater fishes belonging to three species namely: Cyprinus carpio, Barbus xanthopterus and Aspius vorax, were collected from Euphrates river at Al-Haklania distrct, Al-Anbar province during the period from August 2008 till the end of July 2009, by using gill nets and cast nets. Fishes were survyed for intestinal parasitic worms. The investigation revealed the infectation of these fishes with four parasitic species: the digenetic trematode Aspidogaster limacoides from the intestine of C. carpio, B. xanthopterus and A. vorax, larval nematode Contracaecum spp. from the body cavity of C. carpio and the external surface of intestine of B
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The predatory bush crickets Saga ephippigera Fischer Von Waldheim, 1846 is the largest Iraqi orthopterans and one of the most active and successful predators in the Kurdistan region. The nymphs and adults prey on all the stages of various species of insects. Twelve adult specimens were collected from Erbil Province during May 2018 and June 2021. Morphological structures of the adult insects were described and illustrated in details; important taxonomic characteristics of body regions with their appendages were chosen; and the results indicated the importance of morphological characteristics which confirmed the identification of this species correctly.
The research included preparation of new iron(II) complexes with mixed ligands including benzilazine(BA) and semicarbazone ligands {benzilsemicarbazone- BSCH or benzilbis(semicarba-zone)- BBSCH2 or salicylaldehydesemicarbazone- SSCH2 or benzoinsemicarbazone- B'SCH2}.by classical and microwave methods. The resulted complexes have been characterized using chemical and physical methods. The study suggested that the above ligands form ionic complexes having formulae [Fe(SCHi)(BA)(Cl)m](Cl)2-m {where SCH, BSCH, BBSCH2, SSCH¬2 or B'SCH2 ligands; m=1 or 2}. Hexacoordinated mononuclear complexes have been investigated by this study and having octahedral geometries. The effect of laser ray type visible region have been studied on solid ligands and
... Show MoreNonlinear time series analysis is one of the most complex problems ; especially the nonlinear autoregressive with exogenous variable (NARX) .Then ; the problem of model identification and the correct orders determination considered the most important problem in the analysis of time series . In this paper , we proposed splines estimation method for model identification , then we used three criterions for the correct orders determination. Where ; proposed method used to estimate the additive splines for model identification , And the rank determination depends on the additive property to avoid the problem of curse dimensionally . The proposed method is one of the nonparametric methods , and the simulation results give a
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