The paper proposes a methodology for predicting packet flow at the data plane in smart SDN based on the intelligent controller of spike neural networks(SNN). This methodology is applied to predict the subsequent step of the packet flow, consequently reducing the overcrowding that might happen. The centralized controller acts as a reactive controller for managing the clustering head process in the Software Defined Network data layer in the proposed model. The simulation results show the capability of Spike Neural Network controller in SDN control layer to improve the (QoS) in the whole network in terms of minimizing the packet loss ratio and increased the buffer utilization ratio.

   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

When searching for an answer to the following question: What are the reasons for the reluctance of female physical education teachers in secondary schools to referee sports competitions according to the variable of years of service? It was found that the research aimed to reveal the differences between the opinions of the research sample of physical education teachers in secondary schools (girls) about refereeing sports competitions according to the variable of years of service. To achieve the research goal, it is assumed that there are significant differences between the average opinions of the research sample of female teachers and their reluctance and the reasons for the differences in the practice of refereeing sports competitions accor

Integrating Renewable Energy (RE) into Distribution Power Networks (DPNs) is a choice for efficient and sustainable electricity. Controlling the power factor of these sources is one of the techniques employed to manage the power loss of the grid. Capacitor banks have been employed to control phantom power, improving voltage and reducing power losses for several decades. The voltage sag and the significant power losses in the Iraqi DPN make it good evidence to be a case study proving the efficiency enhancement by adjusting the RE power factor. Therefore, this paper studies a part of the Iraqi network in a windy and sunny region, the Badra-Zurbatya-11 kV feeder, in the Wasit governorate. A substation of hybrid RE sources is connected to this

The Cu2SiO3 composite has been prepared from the binary compounds (Cu2O, and SiO2) with high purity by solid state reaction. The Cu2SiO3 thin films were deposited at room temperature on glass and Si substrates with thickness 400 nm by pulsed laser deposition method. X-ray analysis showed that the powder of Cu2SiO3 has a polycrystalline structure with monoclinic phase and preferred orientation along (111) direction at 2θ around 38.670o which related to CuO phase. While as deposited and annealed Cu2SiO3 films have amorphous structure. The morphological study revealed that the grains have granular and elliptical shape, with average diameter of 163.63 nm. The electrical properties which represent Hall effect were investigated. Hall coeffici

Magnesium Phthalocyanine (MgPc) was deposited on a glass substrate by pulsed laser deposition (PLD) using Q-Switching Nd:YAG laser with wavelength 1064 nm, repetition rate 6 Hz, at room temperature (300K) and different annealing temperatures (373, 473, and 573)K under vacuum condition of 10-3 torr. All films were annealed for one hour to attain crystallinity. X-ray diffraction (XRD) of MgPc powder indicated that MgPc crystallizes in polycrystalline with a monoclinic structure. While comparing the MgPc films, it was observed that the intensity of the characteristic peak increases with temperature, and the crystallization exhibited a monoclinic structure typical of the β-form. The Miller indices, hkl, values for each diffraction peak