ABSTRACT
The simulation of groundwater movement has been carried out by using MODFLOW model
in order to show the impact of change of water surface elevation of the Tigris river on layers of
the aquifer system for Nuclear Research Center at Al-Tuwaitha area, in addition to evaluate the
ability of the proposed pumping well to collect groundwater and change the direction of flow at
steady-state. The results of the study indicated that there is a good match between the values of
groundwater levels that calculated in the model and measured in the field, where mean error is
0.09 m.
The study also showed that the increasing of water surface elevation of the Tigris river led to
increase in the hydraulic head of observed wells, while the use proposed pumping well reduced
the hydraulic head and intercepted the movement of groundwater flow. The flow direction is
toward the Tigris river, and the velocity of flow is clear in the third layer identified medium sand
which is 0.0015 m/day. The using of the proposed pumping well has changed the direction of
groundwater, especially in the area around the well.
The game of volleyball is one of the competitive team games that took the lead in terms of its spread in the world, and the game of volleyball relies on basic skills as an important base on which this game is built to advance in the level of performance Performance and among these skills the skill of spiking and blocking wall, the research aims to identify the extent of the relationship of decision-making to the performance of spiking and blocking in volleyball for junior players. The sample was chosen from volleyball players for the Junior Specialized School of Sulaikh Sports Club / Baghdad Governorate for the season 2020 The researcher used the descriptive approach, and the research community was composed of (101) players. The two
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Due to the huge variety of 5G services, Network slicing is promising mechanism for dividing the physical network resources in to multiple logical network slices according to the requirements of each user. Highly accurate and fast traffic classification algorithm is required to ensure better Quality of Service (QoS) and effective network slicing. Fine-grained resource allocation can be realized by Software Defined Networking (SDN) with centralized controlling of network resources. However, the relevant research activities have concentrated on the deep learning systems which consume enormous computation and storage requirements of SDN controller that results in limitations of speed and accuracy of traffic classification mechanism. To fill thi
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