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.
Structural buildings consist of concrete and steel, and these buildings have confronted many challenges from various aggressive environments against the materials manufactured from them. It contains high water levels and buildings whose concrete cover may be damaged and thus lead to the deterioration and corrosion of steel. It was important to have an alternative to steel, such as the glass fiber reinforced polymer (GFRP), which is distinguished by its great effectiveness in resisting corrosion, as well as its strong tensile resistance. Still, one of its drawbacks is that it has a low modulus of elasticity. This research article aims to conduct a numerical study using the nonlinear fi
Digital Elevation Model (DEM) is one of the developed techniques for relief representation. The definition of a DEM construction is the modeling technique of earth surface from existing data. DEM plays a role as one of the fundamental information requirement that has been generally utilized in GIS data structures. The main aim of this research is to present a methodology for assessing DEMs generation methods. The DEMs data will be extracted from open source data e.g. Google Earth. The tested data will be compared with data produced from formal institutions such as General Directorate of Surveying. The study area has been chosen in south of Iraq (Al-Gharraf / Dhi Qar governorate. The methods of DEMs creation are kriging, IDW (inver
... Show MoreSingle mode-no core-single mode fiber structure with a section of tuned no-core fiber diameter to sense changes in relative humidity has been experimentally demonstrated. The sensor performance with tuned NCF diameter was investigated to maximize the evanescent fields. Different tuned diameters of of (100, 80, and 60)μm were obtained by chemical etching process based on hydrofluoric acid immersion. The highest wavelength sensitivity was obtained 184.57 pm/RH% in the RH range of 30% –100% when the no-core fiber diameter diameter was 60 μm and the sensor response was in real-time measurements
As a reservoir is depleted due to production, pore pressure decreases leading to increased effective stress which causes a reduction in permeability, porosity, and possible pore collapse or compaction. Permeability is a key factor in tight reservoir development; therefore, understanding the loss of permeability in these reservoirs due to depletion is vital for effective reservoir management. The paper presents a case history on a tight carbonate reservoir in Iraq which demonstrates the behavior of rock permeability and porosity as a function of increasing effective stress simulating a depleting mode over given production time. The experimental results show unique models for the decline of permeability and porosity as function effective str
... Show MoreIn this study, gold nanoparticles (AuNPs) were synthesized using a plasma jet system at different exposure times. Using ultraviolet, visible spectra, X-ray diffraction, the nanoparticles were characterized (XRD). A Plasmon surface resonance concentrated at 530, 540, and 533 nm for the prepared AuNPs. The pattern of XRD showed that the extreme peaks of the film reflect crystalline existence. The face-centered cubic structure of the gold nanoparticles was prepared for all samples, with an average crystallite size of 25-40 nm. The effect of AuNPs in vivo on liver function levels was measured. For all doses, we notice an increase in the ranks of liver function in the blood during the period of dosing, and it begins to decrease when the dosi
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