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.
This study aimed to incorporate hydroxyapatite nanoparticles (nHA) or amorphous calcium phosphate nanoparticles (nACP) into a self-etch primer (SEP) to develop a simplified orthodontic bonding system with remineralizing and enamel preserving properties.
nHA and nACP were incorporated into a commercial SEP (Transbond™ plus) in 7% weight ratio and compared with the plain SEP as a control. Shear bond strengths (SBS), enamel damage, and adhesive remnant index (ARI) scores were evaluated at 24 h
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Inundation floodingmap aimedto find outearly warningsto avoidenvironmental damageandhumanin terms of theheight ofthe wave ofwater, speed time arrival, effects of inundation sideanddepth of the water/ distanceand reduce the impact of the flood wave after obtaining the process of collapse of the dam in the lower part of the river to the dam area. The study has been using a numerical model one-dimensional depends on the development of equations (Saint-Venant) so that parts of the river, any river channel main banks of the right and left treated as separate parts, that’s the difference in the characteristics of the hydraulic and engineering, along the line of the flow will take into account in each section of the sections and flow in the riv
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In this work, the modified Lyapunov-Schmidt reduction is used to find a nonlinear Ritz approximation of Fredholm functional defined by the nonhomogeneous Camassa-Holm equation and Benjamin-Bona-Mahony. We introduced the modified Lyapunov-Schmidt reduction for nonhomogeneous problems when the dimension of the null space is equal to two. The nonlinear Ritz approximation for the nonhomogeneous Camassa-Holm equation has been found as a function of codimension twenty-four.
The present study was aimed to screen the ability of local isolates of Bacillus spp. (56 isolates) for nattokinase production using solid state fermentation, then optimize the nutritional conditions for enzyme production. The isolates were subjected to the primary and secondary screening process to select the Bacillus isolate which give the highest production of enzyme. It was found that Bacillus sp. B24 had the highest productivity of the enzyme (25.58U/mg protein). The optimum conditions for nattokinase production were performed by the solid state fermentation and found that the wheat bran was the best medium at initial moisture ratio 1.0:1.0 (w/v) using distilled water as moisturizing solution with initial pH of 7.0 after inoculation
... Show MoreCorona Virus Disease-2019 (COVID-19) is a novel virus belongs to the corona virus's family. It spreads very quickly and causes many deaths around the world. The early diagnosis of the disease can help in providing the proper therapy and saving the humans' life. However, it founded that the diagnosis of chest radiography can give an indicator of coronavirus. Thus, a Corner-based Weber Local Descriptor (CWLD) for COVID-19 diagnostics based on chest X-Ray image analysis is presented in this article. The histogram of Weber differential excitation and gradient orientation of the local regions surrounding points of interest are proposed to represent the patterns of the chest X-Ray image. Support Vector Machine (SVM) and Deep Belief Network (DBN)
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The logistic regression model of the most important regression models a non-linear which aim getting estimators have a high of efficiency, taking character more advanced in the process of statistical analysis for being a models appropriate form of Binary Data.
Among the problems that appear as a result of the use of some statistical methods I
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