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.
A simulation study of using 2D tomography to reconstruction a 3D object is presented. The 2D Radon transform is used to create a 2D projection for each slice of the 3D object at different heights. The 2D back-projection and the Fourier slice theorem methods are used to reconstruction each 2D projection slice of the 3D object. The results showed the ability of the Fourier slice theorem method to reconstruct the general shape of the body with its internal structure, unlike the 2D Radon method, which was able to reconstruct the general shape of the body only because of the blurring artefact, Beside that the Fourier slice theorem could not remove all blurring artefact, therefore, this research, suggested the threshold technique to eliminate the
... Show MoreThis paper aims at exploring the impact of the Iraq-Iran war in the poetry of Adnan Al-Sayegh. Al-Sayegh participation in this war makes him a first hand witness to the atrocities of the trenches and fight in the first lines. This war did not only change his life and world view for good, it changes the nature of his poetry as well. As aresult, war becomes a central issue not only in the poetry Al-Sayegh wrote in the 1980s and 1990s Iraq, but also in the exile.
Key Words: War, Al-Sayegh, Poetry.
The using of the parametric models and the subsequent estimation methods require the presence of many of the primary conditions to be met by those models to represent the population under study adequately, these prompting researchers to search for more flexible models of parametric models and these models were nonparametric models.
In this manuscript were compared to the so-called Nadaraya-Watson estimator in two cases (use of fixed bandwidth and variable) through simulation with different models and samples sizes. Through simulation experiments and the results showed that for the first and second models preferred NW with fixed bandwidth fo
... Show MoreIn this work a chemical sensor was built by using Plane Wave Expansion (PWE) modeling technique by filling the core of 1550 hollow core photonic crystal fiber with chloroform that has different concentrations after being diluted with distilled water. The minimum photonic bandgap width is.0003 and .0005 rad/sec with 19 and 7 cells respectively and a concentration of chloroform that filled these two fibers is 75%.
KE Sharquie, AA Noaimi, AF Hameed, Journal of Cosmetics, Dermatological Sciences and Applications, 2013 - Cited by 11
An automatic text summarization system mimics how humans summarize by picking the most significant sentences in a source text. However, the complexities of the Arabic language have become challenging to obtain information quickly and effectively. The main disadvantage of the traditional approaches is that they are strictly constrained (especially for the Arabic language) by the accuracy of sentence feature functions, weighting schemes, and similarity calculations. On the other hand, the meta-heuristic search approaches have a feature tha
... Show MoreIn this paper, a new hybrid algorithm for linear programming model based on Aggregate production planning problems is proposed. The new hybrid algorithm of a simulated annealing (SA) and particle swarm optimization (PSO) algorithms. PSO algorithm employed for a good balance between exploration and exploitation in SA in order to be effective and efficient (speed and quality) for solving linear programming model. Finding results show that the proposed approach is achieving within a reasonable computational time comparing with PSO and SA algorithms.
A single-blind randomized controlled clinical trial in patients with deep caries and symptoms of reversible pulpitis compared outcomes from a self-limiting excavation protocol using chemomechanical Carisolv gel/operating microscope (self-limiting) versus selective removal to leathery dentin using rotary burs (control). This was followed by pulp protection with mineral trioxide aggregate (MTA) and restoration with glass ionomer cement and resin composite, all in a single visit. The pulp sensibility and periapical health of teeth were assessed after 12 mo, in addition to the differences in bacterial tissue concentration postexcavation. Apical radiolucencies were assessed using cone beam computed tomography/periapical radiographs (CBC
... Show More This research aims to estimate stock returns, according to the Rough Set Theory approach, test its effectiveness and accuracy in predicting stock returns and their potential in the field of financial markets, and rationalize investor decisions. The research sample is totaling (10) companies traded at Iraq Stock Exchange. The results showed a remarkable Rough Set Theory application in data reduction, contributing to the rationalization of investment decisions. The most prominent conclusions are the capability of rough set theory in dealing with financial data and applying it for forecasting stock returns.The research provides those interested in investing stocks in financial
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