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.
In their cross-sectional study, Al-Rubaye et al studied the extent of vitamin D (VD) deficiency/ insufficiency, factors affecting its degree, and the adverse outcomes of the altered VD status among a group of mothers and their neonates from Baghdad, Iraq. They found that 96.6% of the mothers had VD deficiency/ insufficiency compared to 86.4% in their neonates. Maternal VD levels and neonatal weights were significantly correlated with neonatal VD levels. We believe that the study results need to be revised. This is based two points listed in this letter to editor
The bile salt hydrolase gene (bshA), encoding bile salt hydrolase enzyme (EC 3.5.1.24) from probiotic isolate Lactobacillus acidophilus Ar strain which is responsible for assimilation cholesterol were studied in the present work. About 801 bp in length DNA fragment of Lb. acidophilus Ar strain was amplified by PCR techniques. Two restriction sites (PstI/SacI) were added to each end of that fragment for manipulation of DNA during cloning. Amplified fragment inserted into pJET1.2\blunt end vector and pMG36e vector respectively. pJET1.2\blunt end vector is overexpression plasmid for E. coli MC1022, and pMG36e vector is a shuttle vector which is able to replicate in both E. coli and lactic acid bacteria. The resulted constructs were named as pJ
... Show MoreBackground: Vitamin D deficiency/ insufficiency is common in different age groups in both genders especially among pregnant women and neonates where it is associated with several adverse outcomes including preeclampsia and preterm delivery.
Objectives: To assess the extent of vitamin D deficiency/ insufficiency among mothers and their neonates and some factors related to it and identify some adverse outcomes of the deficiency/ insufficiency on neonates (preterm birth and low birth weight).
Subject and Methods: A cross-sectional study was conducted on 88 Iraqi pregnant women and neonates admitted to “Al-Elwiya teaching hospital for maternity” in Baghdad- Al
... Show MoreThis paper reports test results and describes a numerical investigation of the effectiveness of using carbon fibre reinforced polymer (CFRP) fabrics for strengthening concrete cylinders that have been undamaged and damaged due to heating under preload. The purpose of this research was to investigate whether there is any difference in the performance of CFRP-wrapped cylinders if the wrapping is done under preload, and those for which neither heating, cooling nor wrapping was done under preload. The cylinders were exposed to 30% of maximum load at ambient temperature during heating and cooling before being wrapped under preload. Of 18 Ø 100 × 200 mm identical cylinders, 6 were left as control samples without heating, 12 were exposed t
... Show MoreIn this paper, we investigate the impact of fear on a food chain mathematical model with prey refuge and harvesting. The prey species reproduces by to the law of logistic growth. The model is adapted from version of the Holling type-II prey-first predator and Lotka-Volterra for first predator-second predator model. The conditions, have been examined that assurance the existence of equilibrium points. Uniqueness and boundedness of the solution of the system have been achieve. The local and global dynamical behaviors are discussed and analyzed. In the end, numerical simulations are confirmed the theoretical results that obtained and to display the effectiveness of varying each parameter
The objective of this research paper is two-fold. The first is a precise reading of the theoretical underpinnings of each of the strategic approaches: "Market approach" for (M. Porter), and the alternative resource-based approach (R B V), advocates for the idea that the two approaches are complementary. Secondly, we will discuss the possibility of combining the two competitive strategies: cost leadership and differentiation. Finally, we propose a consensual approach that we call "dual domination".
The study was aimed to evaluate the marketing efficiency of dry Onion crop in Salah al-Deen, as estimate the impact of some quality and quantity factors in the efficiency of marketing process of crop using Tobit regression model. The average marketing efficiency of the research sample was 71.3686%. The marketing margins differed according to the marketing channel followed in marketing the crop. The qualitative and quantitative variables in the model are productivity, family size, distance from the market, educational level. The estimated model revealed that a variable productivity is the most important and influential in marketing efficiency, followed by the variable of the distance between the farm and the market, then the variable
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