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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
Wed Nov 20 2024
Journal Name
Naunyn-schmiedeberg's Archives Of Pharmacology
The potential role of targeting the leptin receptor as a treatment for breast cancer in the context of hyperleptinemia: a literature review
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Since cancer is becoming a leading cause of death worldwide, efforts should be concentrated on understanding its underlying biological alterations that would be utilized in disease management, especially prevention strategies. Within this context, multiple bodies of evidence have highlighted leptin’s practical and promising role, a peptide hormone extracted from adipose and fatty tissues with other adipokines, in promoting the proliferation, migration, and metastatic invasion of breast carcinoma cells. Excessive blood leptin levels and hyperleptinemia increase body fat content and stimulate appetite. Also, high leptin level is believed to be associated with several conditions, including overeating, emotional stress, inflammation, obesity,

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Publication Date
Sun Aug 07 2022
Journal Name
Hiv Nursing
Assessment of ApoE Gene Variants and Apob-100 R3500q Mutation as Genetic Risks for Dyslipidemia: A Case-Control Study
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Background: Dyslipidemia is defined as an abnormally high level of various lipids in the blood. It is considered a major risk for atherosclerosis and coronary artery disease. Genetic susceptibility can have a significant influence on the development and progression of dyslipidemia. ApoB-100 R3500Q mutation and ApoE variants are among those genetic risks for dyslipidemia. This study aims to assess the possible contribution of ApoB and ApoE variants on lipid profile among a group of early-onset ischemic heart disease (IHD) patients in comparison to a group of controls. Methods: Forty patients with dyslipidemia and early-onset IHD without chronic conditions likely to cause derangement of lipid levels were recruited to this case-control study

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Publication Date
Mon May 01 2023
Journal Name
Journal Of Engineering
Measuring the Attribute Accuracy and Completeness for the OpenStreetMap Roads Networks for Two Regions in Iraq
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The OpenStreetMap (OSM) project aims to establish a free geospatial database for the entire world which is editable by international volunteers. The OSM database contains a wide range of different types of geographical data and characteristics, including highways, buildings, and land use regions. The varying scientific backgrounds of the volunteers can affect the quality of the spatial data that is produced and shared on the internet as an OSM dataset. This study aims to compare the completeness and attribute accuracy of the OSM road networks with the data supplied by a digitizing process for areas in the Baghdad and Thi-Qar governorates. The analyses are primarily based on calculating the portion of the commission (extr

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Publication Date
Mon May 01 2023
Journal Name
Journal Of Engineering
Measuring the Attribute Accuracy and Completeness for the OpenStreetMap Roads Networks for Two Regions in Iraq
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The OpenStreetMap (OSM) project aims to establish a free geospatial database for the entire world which is editable by international volunteers. The OSM database contains a wide range of different types of geographical data and characteristics, including highways, buildings, and land use regions. The varying scientific backgrounds of the volunteers can affect the quality of the spatial data that is produced and shared on the internet as an OSM dataset. This study aims to compare the completeness and attribute accuracy of the OSM road networks with the data supplied by a digitizing process for areas in the Baghdad and Thi-Qar governorates. The analyses are primarily based on calculating the portion of the commission (extra road) and

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Publication Date
Sat Oct 01 2011
Journal Name
Journal Of Engineering
MODIFIED TRAINING METHOD FOR FEEDFORWARD NEURAL NETWORKS AND ITS APPLICATION in 4-LINK SCARA ROBOT IDENTIFICATION
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In this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func

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Publication Date
Mon Oct 17 2011
Journal Name
Journal Of Engineering
MODIFIED TRAINING METHOD FOR FEEDFORWARD NEURAL NETWORKS AND ITS APPLICATION in 4-LINK SCARA ROBOT IDENTIFICATION
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In this research the results of applying Artificial Neural Networks with modified activation function to perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of identification strategy consists of a feed-forward neural network with a modified activation function that operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have been trained online and offline have been used, without requiring any previous knowledge about the system to be identified. The activation function that is used in the hidden layer in FFNN is a modified version of the wavelet function. This approach ha

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Publication Date
Wed Jan 01 2020
Journal Name
Ieee Access
Smart Routing Management Framework Exploiting Dynamic Data Resources of Cross-Layer Design and Machine Learning Approaches for Mobile Cognitive Radio Networks: A Survey
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Publication Date
Wed Jun 01 2022
Journal Name
Journal Of Engineering
Assessment Strategies of Fixed Firefighting system in Residential Multi-Story Building for Improving Fire Safety: A Review
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A fixed firefighting system is a key component of fire safeguarding and reducing fire danger. It is installed as a permanent component in a structure to protect the entire or a portion of the building and its contents. The study aims to review the previous studies that deal with the evaluation of fire safety measures and their use in resolving problems associated with fire threats in buildings. For this reason, a number of previous studies in this field were reviewed compared with the NFPA code. The findings revealed that regulatory developments over the last several decades had created an atmosphere conducive to innovation. This has resulted in a growth in the number of fixed firefighting system types now obtainable. Th

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Publication Date
Sun Apr 01 2018
Journal Name
Journal Of Educational And Psychological Researches
Forgiveness and its relation to the social intelligence among elementary school students
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The study aims to identify the relationship between forgiveness and social intelligence among elementary school students. The study employed a descriptive analytical approach, whereby a total of (500) elementary school student were selected randomly regarding the variable of gender and economical status. Two scales were prepared: one to measure the forgiveness depending on Albort’s theory that consist of (20) item, and the other to measure the social intelligence according to Tony’s theory which composed of (20) item as well. The result revealed that 6th grade students have interested level of the forgiveness and social intelligence, the girl showed significant differences according to the forgiveness variable, the sample

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Publication Date
Wed Mar 18 2020
Journal Name
Baghdad Science Journal
Solutions and Recent Challenges Related to Energy in Wireless Body Area Networks with Integrated Technologies: Applications and Perspectives
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          In this paper, we have investigated some of the most recent energy efficient routing protocols for wireless body area networks. This technology has seen advancements in recent times where wireless sensors are injected in the human body to sense and measure body parameters like temperature, heartbeat and glucose level. These tiny wireless sensors gather body data information and send it over a wireless network to the base station. The data measurements are examined by the doctor or   physician and the suitable cure is suggested. The whole communication is done through routing protocols in a network environment. Routing protocol consumes energy while helping non-stop communic

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Scopus (11)
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