The Next-generation networks, such as 5G and 6G, need capacity and requirements for low latency, and high dependability. According to experts, one of the most important features of (5 and 6) G networks is network slicing. To enhance the Quality of Service (QoS), network operators may now operate many instances on the same infrastructure due to configuring able slicing QoS. Each virtualized network resource, such as connection bandwidth, buffer size, and computing functions, may have a varied number of virtualized network resources. Because network resources are limited, virtual resources of the slices must be carefully coordinated to meet the different QoS requirements of users and services. These networks may be modified to achieve QoS using Artificial Intelligence (AI) and machine learning (ML). Developing an intelligent decision-making system for network management and reducing network slice failures requires reconfigurable wireless network solutions with machine learning capabilities. Using Spiking Neural Network (SNN) and prediction, we have developed a 'Buffer-Size Management' model for controlling network load efficiency by managing the slice's buffer size. To analyze incoming traffic and predict the network slice buffer size; our proposed Buffer-Size Management model can intelligently choose the best amount of buffer size for each slice to reduce packet loss ratio, increase throughput to 95% and reduce network failure by about 97%.
The sports institutions in general are affected and contact with sport in particular the environmental factor, whether political or economic, which makes them in constant need to consider their administrative applications to increase the confidence of their employees because of their suitability or consistency with the new reality according to the sports activities that relate to it, The stalemate in administrative and technical aspects of the administrative work method in the majority of the Olympic sports federations makes the achievement of most of the goals far from the present reality, and the selection of suitable alternatives to achieve the objectives by those who disagree with the concepts of modern dictatorial standards It leads to
... Show MoreThe investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti
... Show MoreMyriophyllum spicatum distribution in Al-Burgga marsh, Hor Al-Hammar was described in relation to some of the physical-chemical properties for its habitat (water depth, light penetration, water temperature, water salinity, pH, dissolved oxygen, Ca+2, Mg+2, reactive NO2=, reactive NO3-1, and reactive PO4-3) during 2011, seasonally. CANOCO ordination program (CCA) was used to analyse the data. Its vegetation cover percentage was with its peak at summer, its value was 90 %, while the lowest value was 20 % in winter. Statistically, Positive relationships for WT, sal., Ca+2, Mg+2, reactive NO2=, reactive NO3-1, and reactive PO4-3 with the vegetation cover percentage were observed. While, negative relationships for WD, pH, and DO with the ve
... Show MoreAn experimental and numerical investigation of the effect of using two types of nanofluids with suspending of (Al2O3 and CuO) nanoparticles in deionized water with a volume fraction of (0.1% vol.), in addition to use three types of fin plate configurations of (smooth, perforated, and dimple plate) to study the heat transfer enhancement characteristics of commercial fin plate heat sink for cooling computer processing unit. All experimental tests under simulated conditions by using heat flux heater element with input power range of (5, 16, 35, 70, and 100 W). The experimental parameters calculated are such as water and nanofluid as coolant with Reynolds number of (7000, 8000, 9400 and 11300); the air
... Show MoreThe relationship between costs of environment and costs of product life – cycle. Boubtlessly when the economical unit exercise their productive works, they lead to pollution in water, air and soil as well as all stages of product life- cycle from Rans Dstage, production stage, packaging stage and finally abandonment stage- Pollution causes environmental costs. Lgnoring or hiding environmental costs and no taking them in consideration with product cost lead to a wrong account of preduot cost.
Therefore, environmental costs should be included and matched for all stages with in product costs to know which activities, processes
... Show MoreThe Iraqi economy has suffered for a long period of inflation because of the Iraq war and the resolutions and the sanctions that were imposed on Iraq, this phenomenon overshadowed at various aspects of the economy including the tax revenue that the State seeks to optimize the total income for the budget, the research covers the years 1990-2010, these years have been divided according to the country's economic variables.
The research adopted on econometrics analysis that is based on the information and data available on topics and has been using statistical methods to test functions are formulated.
Research concluded that rates of inflation and GDP impact is limited to direct taxation and indirect in current prices a
... Show MoreA high percentage of existing buildings in Iraq are traditional buildings, yet there is approximately no such green building in Baghdad or other governorates. Most of these buildings require urgent upgrading to increase their performance (operationally, economically, and environmentally), also the building owners looking for identifying and implementing many of the green building measures to reduce the operational and maintenance costs of their buildings. The decision-makers need to support the possibility of achieving sustainable measures of existing building rating systems such as LEED or BREEAM, and that would require an optimization model. The goal of this study is to maximize the
Total dissolved solids are at the top of the parameters list of water quality that requires investigations for planning and management, especially for irrigation and drinking purposes. If the quality of water is sufficiently predictable, then appropriate management is possible. In the current study, Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) models were used as indicators of water quality and for the prediction of Total Dissolved Solids (TDS) along the Tigris River, in Baghdad city. To build these models five water parameters were selected from the intakes of four water treatment plants on the Tigris River, for the period between 2013 and 2017. The selected water parameters were Total Dissolved Solids (TDS
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