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.
Carbon dioxide (CO2) capture and storage is a critical issue for mitigating climate change. Porous aromatic Schiff base complexes have emerged as a promising class of materials for CO2 capture due to their high surface area, porosity, and stability. In this study, we investigate the potential of Schiff base complexes as an effective media for CO2 storage. We review the synthesis and characterization of porous aromatic Schiff bases materials complexes and examine their CO2 sorption properties. We find that Schiff base complexes exhibit high CO2 adsorption capacity and selectivity, making them a promising candidate for use in carbon capture applications. Moreover, we investigate the effect of various parameters such as temperature, and pressu
... Show MoreIn this article, a numerical method integrated with statistical data simulation technique is introduced to solve a nonlinear system of ordinary differential equations with multiple random variable coefficients. The utilization of Monte Carlo simulation with central divided difference formula of finite difference (FD) method is repeated n times to simulate values of the variable coefficients as random sampling instead being limited as real values with respect to time. The mean of the n final solutions via this integrated technique, named in short as mean Monte Carlo finite difference (MMCFD) method, represents the final solution of the system. This method is proposed for the first time to calculate the numerical solution obtained fo
... Show More
(15)
(9)
(15)
(16)
(107)
(108)
An eco-epidemiological system incorporating a vertically transmitted infectious disease is proposed and investigated. Micheal-Mentence type of harvesting is utilized to study the harvesting effort imposed on the predator. All the properties of the solution of the system are discussed. The dynamical behaviour of the system, involving local stability, global stability, and local bifurcation, is investigated. The work is finalized with the numerical simulation to observe the global behaviour of the solution.
(2)
A partial temporary immunity SIR epidemic model involv nonlinear treatment rate is proposed and studied. The basic reproduction number is determined. The local and global stability of all equilibria of the model are analyzed. The conditions for occurrence of local bifurcation in the proposed epidemic model are established. Finally, numerical simulation is used to confirm our obtained analytical results and specify the control set of parameters that affect the dynamics of the model.
(7)
(3)
In this work, a chemical optical fiber sensor based on Surface Plasmon Resonance (SPR) was designed and implemented using plastic optical fiber. The sensor is used for estimating refractive indices and concentrations of various chemical materials (methanol, distilled water, ethanol, kerosene) as well as for evaluating the performance parameters such as sensitivity, signal to noise ratio, resolution and the figure of merit of the fabricated sensor. It was found that the value of the sensitivity of the optical fiber-based SPR sensor, with 40 nm thick and 10 mm long Au metal film of exposed sensing region, was 3μm/RIU, while the SNR was 0.24, the figure of merit was 20, and the resolution was 0.00066. The sort of optical fiber utilized i
... Show More
(14)
(10)
In this research paper, we explain the use of the convexity and the starlikness properties of a given function to generate special properties of differential subordination and superordination functions in the classes of analytic functions that have the form in the unit disk. We also show the significant of these properties to derive sandwich results when the Srivastava- Attiya operator is used.
(4)
(3)
The authors introduced and addressed several new subclasses of the family of meromorphically multivalent -star-like functions in the punctured unit disk in this study, which makes use of several higher order -derivatives. Many fascinating properties and characteristics are extracted systematically for each of these newly identified function classes. Distortion theorems and radius problems are among these characteristics and functions. A number of coefficient inequalities for functions belonging to the subclasses are studied, and discussed, as well as a suitable condition for them is set. The numerous results are presented in this study and the previous works on this
... Show More
(7)
(3)