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

This research aims to solve the problem of selection using clustering algorithm, in this research optimal portfolio is formation using the single index model, and the real data are consisting from the stocks Iraqi Stock Exchange in the period 1/1/2007 to 31/12/2019. because the data series have missing values ,we used the two-stage missing value compensation method, the knowledge gap was inability the portfolio models to reduce The estimation error , inaccuracy of the cut-off rate and the Treynor ratio combine stocks into the portfolio that caused to decline in their performance, all these problems required employing clustering technic to data mining and regrouping it within clusters with similar characteristics to outperform the portfolio

Aromatic Schiff-bases are known to have antibacterial activity, but most of these compounds are sparingly soluble in water. The present work describes the synthesis of new Schiff-bases derived from branched aminosugars. Treatment of 3-Amino-3-Cyano-3-Deoxy-1,2:5,6-Di-O-Isopropylene-α-D-Allofuranose (1) with the aldehydes (2) under reflux in methanol afforded the Schiff-bases (3) in good yields. The new Schiff-bases were in accord with their NMR, IR spectral data and elemental analysis.

The current study aimed the syntheses and characterizations of Gold nanoparticles (Au NPs) using a laser ablation Q-switched Nd: YAG laser with a wave-length of 355 nm at a variety of laser pulse energies (E) and deposited on porous silicon (PS). Optical emission spectrometer was used to diagnosed medium air to study gold plasma characteristics and prepared Au nanoparticles. The laser pulse energy influence has been studied on the plasma characteristics in air. The data showed the emergence of the ionic (Au II) spectral emission lines in the gold plasma emission spectrum. XRD has been utilized to examine structural characteristics. Moreover, AFM results 37.2 nm as the mean value of the diameter that is coordinated in a shape similar to the

a laser ablation Q-switched Nd: YAG laser with a wave-length of 355 nm at a variety of laser pulse energies (E) and deposited on porous silicon (PS). Optical emission spectrometer was used to diagnosed medium air to study gold plasma characteristics and prepared Au nanoparticles. The laser pulse energy influence has been studied on the plasma characteristics in air. The data showed the emergence of the ionic (Au II) spectral emission lines in the gold plasma emission spectrum. XRD has been utilized to examine structural characteristics. Moreover, AFM results 37.2 nm as the mean value of the diameter that is coordinated in a shape similar to the rod that appears for Au NPs, in addition to that, TEM has been an indication of the fact that syn