In recent years, the world witnessed a rapid growth in attacks on the internet which resulted in deficiencies in networks performances. The growth was in both quantity and versatility of the attacks. To cope with this, new detection techniques are required especially the ones that use Artificial Intelligence techniques such as machine learning based intrusion detection and prevention systems. Many machine learning models are used to deal with intrusion detection and each has its own pros and cons and this is where this paper falls in, performance analysis of different Machine Learning Models for Intrusion Detection Systems based on supervised machine learning algorithms. Using Python Scikit-Learn library KNN, Support Ve

Information systems and data exchange between government institutions are growing rapidly around the world, and with it, the threats to information within government departments are growing. In recent years, research into the development and construction of secure information systems in government institutions seems to be very effective. Based on information system principles, this study proposes a model for providing and evaluating security for all of the departments of government institutions. The requirements of any information system begin with the organization's surroundings and objectives. Most prior techniques did not take into account the organizational component on which the information system runs, despite the relevance of

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.

Today the NOMA has exponential growth in the use of Optical Visible Light Communication (OVLC) due to good features such as high spectral efficiency, low BER, and flexibility. Moreover, it creates a huge demand for electronic devices with high-speed processing and data rates, which leads to more FPGA power consumption. Therefore; it is a big challenge for scientists and researchers today to recover this problem by reducing the FPGA power and size of the devices. The subject matter of this article is producing an algorithm model to reduce the power consumption of (Field Programmable Gate Array) FPGA used in the design of the Non-Orthogonal Multiple Access (NOMA) techniques applied in (OVLC) systems combined with a blue laser. However, The po

This study was design to investigate the dimensional stability of heat-activated acrylic resin with different methods of flask cooling (15 minutes rapid cooling, one hour bench cooling, four hours delayed deflasking, and 24 hours delayed deflasking) at different time intervals (immediately, two days, seven days, 30 days) after deflasking. Heat-activated acrylic resin was used to prepare acrylic samples. Then, measurement of the distances where achieved between the centers of selected marks in the acrylic samples. They were measured at different time intervals for different methods of flask cooling. The results showed that the group samples of the four hours and 24 hours of delayed deflasking was insignificantly different from the control an

In this study, chemical oxidation was employed for the synthesis of polypyrrole (PPy) nanofiber. Furthermore, PPy has been subjected to treatment using nanoparticles of neodymium oxide (Nd2O3), which were produced and added in a certain ratio. The inquiry centered on the structural characteristics of the blend of polypyrrole and neodymium oxide after their combination. The investigation utilises X-ray diffraction (XRD), FTIR, and Field Emission Scanning Electron Microscopy (FE-SEM) for PPy, 10%, 30%, and 50% by volume of Nd2O3. According to the electrochemical tests, it has been noted that the nanocomposites exhibit a substantial amount of pseudocapacitive activity.

Background: to evaluate the effect of different dentifrices on the surface roughness of two composite resins (nanofilled-based and nanoceramic – based composite resins). Materials and methods: Forty specimens (diameter 12 mm and height of 2mm) prepared from different composite resin materials: Z350 (nanofilled composite, and Ceram-X (nanoceramic) .they were subjected to brushing simulation equivalent to the period of 1 year. The groups assessed were a control group brushed with distilled water (G1), Opalescence whitening toothpasteR (G2), Colgate sensitive pro-relief (G3) and Biomed Charcoal Toothpaste (G4). The initial and final roughness of each group was tested by surface roughness tester. The results were statistically analyzed using