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.
Background: Iron homeostasis is crucial to many physiological functions in the human body, such as cellular activity, erythropoiesis, and the innate immune response. Iron deficiency anemia may occur from obesity's ability to disturb iron homeostasis. Obesity may be seen as a pre-inflammatory condition with mild, ongoing systemic inflammation. Additionally, an increase in hepcidin levels by chronic inflammation causes iron insufficiency in obese people. For this reason, this current experiment is designed to investigate the iron profile and some hematological and inflammatory parameters in obese adults in the Kurdistan region-Iraq.
Subjects and Methods: The cross-sectional study w
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In 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%.
Nanocrystalline ZnO/Zeolite type A composite was prepared by simple method of operation by . the precipitation of zinc oxide and loading on zeolite 5A in one step. Characterization was made by X-ray diffraction (XRD), X-ray fluorescence(XRF), N2 adsorption- desorption for BET surface area, and Atomic force microscopy (AFM). Results showed that zinc oxide was loaded on zeolite as noticed by the characteristic peaks and was of nano scale having an average diameter of 88.57nm. The percentage loading of ZnO on zeolite A was 28.37% and the surface area was 222m2/g. The activity of the prepared catalyst was examined in the desulfurization of double hydrogenated diesel fuel. The process was investigated in a
... Show MoreThis study proposed a biometric-based digital signature scheme proposed for facial recognition. The scheme is designed and built to verify the person’s identity during a registration process and retrieve their public and private keys stored in the database. The RSA algorithm has been used as asymmetric encryption method to encrypt hashes generated for digital documents. It uses the hash function (SHA-256) to generate digital signatures. In this study, local binary patterns histograms (LBPH) were used for facial recognition. The facial recognition method was evaluated on ORL faces retrieved from the database of Cambridge University. From the analysis, the LBPH algorithm achieved 97.5% accuracy; the real-time testing was done on thirty subj
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The main subject of this poem is a chance meeting between Baudelaire and unknown beautiful lady. Her presence represents the far-fetched, magnificent beauty. This beauty forms an aspect of idealism that takes its real existence and disappears immediately.
This emotional poem deals with the continuous despair that dates back to the Romantic age where it was a key topic; the passing woman embodies destiny. All this comes from constant experience and mad love through the poet’s view to a woman paving the way toward the unknown. Baudelaire, however, noticed this unknown through a passer-by that reflected the real and magical image of this unk
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With wireless sensor network (WSN) wide applications in popularity, securing its data becomes a requirement. This can be accomplished by encrypting sensor node data. In this paper a new an efficient symmetric cryptographic algorithm is presented. This algorithm is called wireless sensor network wavelet curve ciphering system (WSN-WCCS). The algorithm idea based on discrete wavelet transformation to generate keys for each node in WSN. It implements on hierarchical clustering WSN using LEACH protocol. Python programming language version 2.7 was used to create the simulator of WSN framework and implement a WSN-WCCS algorithm. The simulation result of the proposed WSN-WCCS with other symmetric algorithms has show
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In this paper we proposed a new method for selecting a smoothing parameter in kernel estimator to estimate a nonparametric regression function in the presence of missing values. The proposed method is based on work on the golden ratio and Surah AL-E-Imran in the Qur'an. Simulation experiments were conducted to study a small sample behavior. The results proved the superiority the proposed on the competition method for selecting smoothing parameter.
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