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A Review of TCP Congestion Control Using Artificial Intelligence in 4G and 5G Networks
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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.

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Publication Date
Sat Aug 01 2020
Journal Name
Journal Of Engineering Science And Technology (jestec)
Influence of A River Water Quality on The Efficiency of Water Treatment Using Artificial Neural Network
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Tigris River is the lifeline that supplies a great part of Iraq with water from north to south. Throughout its entire length, the river is battered by various types of pollutants such as wastewater effluents from municipal, industrial, agricultural activities, and others. Hence, the water quality assessment of the Tigris River is crucial in ensuring that appropriate and adequate measures are taken to save the river from as much pollution as possible. In this study, six water treatment plants (WTPs) situated on the two-banks of the Tigris within Baghdad City were Al Karkh; Sharq Dijla; Al Wathba; Al Karama; Al Doura, and Al Wahda from northern Baghdad to its south, that selected to determine the removal efficiency of turbidity and

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Publication Date
Wed Jan 01 2020
Journal Name
Nodes In Transport Networks – Research, Data Analysis And Modelling
Suggested Solutions to Reduce Traffic Congestion During Rush Hours in Al-Jadriya Intersection
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Publication Date
Thu Jan 11 2018
Journal Name
Al-khwarizmi Engineering Journal
Control on a 2-D Wing Flutter Using an Adaptive Nonlinear Neural Controller
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An adaptive nonlinear neural controller to reduce the nonlinear flutter in 2-D wing is proposed in the paper. The nonlinearities in the system come from the quasi steady aerodynamic model and torsional spring in pitch direction. Time domain simulations are used to examine the dynamic aero elastic instabilities of the system (e.g. the onset of flutter and limit cycle oscillation, LCO). The structure of the controller consists of two models :the modified Elman neural network (MENN) and the feed forward multi-layer Perceptron (MLP). The MENN model is trained with off-line and on-line stages to guarantee that the outputs of the model accurately represent the plunge and pitch motion of the wing and this neural model acts as the identifier. Th

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Publication Date
Fri Jul 24 2020
Journal Name
Al-kindy College Medical Journal
A review study of targeting of AAK1 and JAK1/2 using baricitinib in COVID-19 infected human cells
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     The outbreak of a current public health coronavirus 2019 disease is a causative agent of a serious acute respiratory syndrome and even death. COVID-19 has exposed to multi-suggested pharmaceutical agents to control this global disease. Baricitinib, a well-known antirheumatic agent, was one of them. This article reviews the likely pros and cons of baricitinib in attenuation of COVID-19 based on the mechanism of drug action as well as its pharmacokinetics. The inhibitory effect of baricitinib on receptor mediated endocytosis promoter, AKK1, and on JAK-STAT signaling pathway is benefacial in inhibition of both viral assembling and inflammation. Also, its pharmacokinetic has encouraged the physicians toward the drug

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Publication Date
Mon Mar 30 2009
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of bubble size in Bubble columns using Artificial Neural Network
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In the literature, several correlations have been proposed for bubble size prediction in bubble columns. However these correlations fail to predict bubble diameter over a wide range of conditions. Based on a data bank of around 230 measurements collected from the open literature, a correlation for bubble sizes in the homogenous region in bubble columns was derived using Artificial Neural Network (ANN) modeling. The bubble diameter was found to be a function of six parameters: gas velocity, column diameter, diameter of orifice, liquid density, liquid viscosity and liquid surface tension. Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 7.3 % and correlation coefficient of 92.2%. A

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Publication Date
Wed Jan 01 2025
Journal Name
Computers, Materials & Continua
A Comprehensive Review of Dynamic Community Detection: Taxonomy, Challenges, and Future Directions
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In recent years, the evolution of the community structure in social networks has gained significant attention. Due to the rapid and continuous evolution of real-world networks over time. This makes the process of identifying communities and tracking their topology changes challenging. To tackle these challenges, it is necessary to find efficient methodologies for analyzing the behavior patterns of dynamic communities. Several previous reviews have introduced algorithms and models for community detection. However, these methods have not been very accurate in identifying communities. Moreover, none of the reviewed papers made an apparent effort to link algorithms that can accurately detect dynamic communities. This review aims to present a ta

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Publication Date
Thu Mar 09 2023
Journal Name
Coatings
Nondestructive Evaluation of Fiber-Reinforced Polymer Using Microwave Techniques: A Review
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Carbon-fiber-reinforced polymer (CFRP) is widely acknowledged as a leading advanced material structure, offering superior properties compared to traditional materials, and has found diverse applications in several industrial sectors, such as that of automobiles, aircrafts, and power plants. However, the production of CFRP composites is prone to fabrication problems, leading to structural defects arising from cycling and aging processes. Identifying these defects at an early stage is crucial to prevent service issues that could result in catastrophic failures. Hence, routine inspection and maintenance are crucial to prevent system collapse. To achieve this objective, conventional nondestructive testing (NDT) methods are utilized to i

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Publication Date
Tue Dec 07 2021
Journal Name
Tencon 2021 - 2021 Ieee Region 10 Conference (tencon)
Robust State Feedback Control of Electric Heating Furnace Using a New Disturbance Observer
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As one type of heating furnaces, the electric heating furnace (EHF) typically suffers from time delay, non-linearity, time-varying parameters, system uncertainties, and harsh en-vironment of the furnace, which significantly deteriorate the temperature control process of the EHF system. In order to achieve accurate and robust temperature tracking performance, an integration of robust state feedback control (RSFC) and a novel sliding mode-based disturbance observer (SMDO) is proposed in this paper, where modeling errors and external disturbances are lumped as a lumped disturbance. To describe the characteristics of the EHF, by using convection laws, an integrated dynamic model is established and identified as an uncertain nonlinear second ord

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Publication Date
Wed Mar 12 2025
Journal Name
The Alarba'een Journal
Analyzing and tracking the data of the millions sized gatherings for the Arba'in visit and proposing alternative ways to relieve congestion using spatial analysis algorithms
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The city of Karbala is one of the most important holy places for visitors and pilgrims from the Islamic faith, especially through the Arabian visit, when crowds of millions gather to commemorate the martyrdom of Imam Hussein. Offering services and medical treatments during this time is very important, especially when the crowds head to their destination (the holy shrine of Imam Hussein (a.s)). In recent years, the Arba'in visit has witnessed an obvious growth in the number of participants. The biggest challenge is the health risks, and the preventive measures for both organizers and visitors. Researchers identified various challenges and factors to facilitating the Arba'in visit. The purpose of this research is to deal with the religious an

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Publication Date
Wed Oct 01 2014
Journal Name
Engineering And Technology Journal
Investigating Forward kinematic Analysis of a 5-axes Robotic Manipulator using Denavit-Hartenberg Method and Artificial Neural Network
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