Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr

Thermal energy storage is an important component in energy units to decrease the gap between energy supply and demand. Free convection and the locations of the tubes carrying the heat-transfer fluid (HTF) have a significant influence on both the energy discharging potential and the buoyancy effect during the solidification mode. In the present study, the impact of the tube position was examined during the discharging process. Liquid-fraction evolution and energy removal rate with thermo-fluid contour profiles were used to examine the performance of the unit. Heat exchanger tubes are proposed with different numbers and positions in the unit for various cases including uniform and non-uniform tubes distribution. The results show that

ولاء طارق حميد, Mustansiriyah Journal of Sports Science, 2021

The turning process has various factors, which affecting machinability and should be investigated. These are surface roughness, tool life, power consumption, cutting temperature, machining force components, tool wear, and chip thickness ratio. These factors made the process nonlinear and complicated. This work aims to build neural network models to correlate the cutting parameters, namely cutting speed, depth of cut and feed rate, to the machining force and chip thickness ratio. The turning process was performed on high strength aluminum alloy 7075-T6. Three radial basis neural networks are constructed for cutting force, passive force, and feed force. In addition, a radial basis network is constructed to model the chip thickness ratio. T

In this paper, we derive and prove the stability bounds of the momentum coefficient µ and the learning rate ? of the back propagation updating rule in Artificial Neural Networks .The theoretical upper bound of learning rate ? is derived and its practical approximation is obtained

Artificial Neural Networks (ANN) is one of the important statistical methods that are widely used in a range of applications in various fields, which simulates the work of the human brain in terms of receiving a signal, processing data in a human cell and sending to the next cell. It is a system consisting of a number of modules (layers) linked together (input, hidden, output). A comparison was made between three types of neural networks (Feed Forward Neural Network (FFNN), Back propagation network (BPL), Recurrent Neural Network (RNN). he study found that the lowest false prediction rate was for the recurrentt network architecture and using the Data on graduate students at the College of Administration and Economics, Univer

Given the importance of ecology and its entry into various fields in general and the urban environment particularly; ecological cities take wide ranges of application at multiple regional and global levels. However, it repeatedly noted that there was a state of cognitive confusion and overlapping in the term ecology comes from the diversity of implementation within several disciplines. Architects, designers, and planners have instilled biological development directly into the formal principles as well as the social structures of the ecological cities. Therefore, the research presents a rapid review of the most relevant areas that dealt with the ecological cities by research and analysis at various levels, from the concept and definition of

For Spanish learners who are not immersed in everyday contexts, such as students of Spanish as a foreign language, interaction with native speakers is an enriching experience that allows them to contrast their knowledge in a meaningful way. For its part, understanding the cognitive and grammatical functions of the so-called verbs of change plays an essential role in the development of everyday conversation,including the management of aspects such as dialectal variations.In relation to this important function, the central theme of our proposal is verbs of change. The latter have been the research base of several linguists who highlight, amidst their complex functioning in Spanish, positive communicative bases. By observing these perspecti