The biometric-based keys generation represents the utilization of the extracted features from the human anatomical (physiological) traits like a fingerprint, retina, etc. or behavioral traits like a signature. The retina biometric has inherent robustness, therefore, it is capable of generating random keys with a higher security level compared to the other biometric traits. In this paper, an effective system to generate secure, robust and unique random keys based on retina features has been proposed for cryptographic applications. The retina features are extracted by using the algorithm of glowworm swarm optimization (GSO) that provides promising results through the experiments using the standard retina databases. Additionally, in order t

The green synthesis of nickel oxide nanoparticles (NiO-NP) was investigated using Ni(NO3)2 as a precursor, olive tree leaves as a reducing agent, and D-sorbitol as a capping agent. The structural, optical, and morphology of the synthesized NiO-NP have been characterized using ultraviolet–visible spectroscopy (UV-Vis), X-ray crystallography (XRD) pattern, Fourier transform infrared spectroscopy (FT-IR) and scanning electron microscope (SEM) analysis. The SEM analysis showed that the nanoparticles have a spherical shape and highly crystalline as well as highly agglomerated and appear as cluster of nanoparticles with a size range of (30 to 65 nm). The Scherrer relation has been used to estimate the crystallite size of NiO-NP which ha

Support vector machine (SVM) is a popular supervised learning algorithm based on margin maximization. It has a high training cost and does not scale well to a large number of data points. We propose a multiresolution algorithm MRH-SVM that trains SVM on a hierarchical data aggregation structure, which also serves as a common data input to other learning algorithms. The proposed algorithm learns SVM models using high-level data aggregates and only visits data aggregates at more detailed levels where support vectors reside. In addition to performance improvements, the algorithm has advantages such as the ability to handle data streams and datasets with imbalanced classes. Experimental results show significant performance improvements in compa

Intrusion detection systems detect attacks inside computers and networks, where the detection of the attacks must be in fast time and high rate. Various methods proposed achieved high detection rate, this was done either by improving the algorithm or hybridizing with another algorithm. However, they are suffering from the time, especially after the improvement of the algorithm and dealing with large traffic data. On the other hand, past researches have been successfully applied to the DNA sequences detection approaches for intrusion detection system; the achieved detection rate results were very low, on other hand, the processing time was fast. Also, feature selection used to reduce the computation and complexity lead to speed up the system

This research aims to test the ability of glass waste powder to adsorb cadmium from aqueous solutions. The glass wastes were collected from the Glass Manufacturing Factory in Ramadi. The effect of concentration and reaction time on sorption was tested through a series of laboratory experiments. Four Cd concentrations (20, 40, 60, and 80) as each concentration was tested ten times for 5, 10, 15, 20, 25, 30, 35, 40, 45, and 50 min. Solid (glass wastes) to liquid was 2g to 30ml was fixed in each experiment where the total volume of the solution was 30ml. The pH, total dissolved salts and electrical conductivity were measured at 30ºC. The equilibrium concentration was determined at 25 minutes, thereafter it was noted that the sorption