Botnet detection develops a challenging problem in numerous fields such as order, cybersecurity, law, finance, healthcare, and so on. The botnet signifies the group of co-operated Internet connected devices controlled by cyber criminals for starting co-ordinated attacks and applying various malicious events. While the botnet is seamlessly dynamic with developing counter-measures projected by both network and host-based detection techniques, the convention techniques are failed to attain sufficient safety to botnet threats. Thus, machine learning approaches are established for detecting and classifying botnets for cybersecurity. This article presents a novel dragonfly algorithm with multi-class support vector machines enabled botnet

Image pattern classification is considered a significant step for image and video processing. Although various image pattern algorithms have been proposed so far that achieved adequate classification, achieving higher accuracy while reducing the computation time remains challenging to date. A robust image pattern classification method is essential to obtain the desired accuracy. This method can be accurately classify image blocks into plain, edge, and texture (PET) using an efficient feature extraction mechanism. Moreover, to date, most of the existing studies are focused on evaluating their methods based on specific orthogonal moments, which limits the understanding of their potential application to various Discrete Orthogonal Moments (DOM

A Multiple System Biometric System Based on ECG Data

Live the present companies in a competitive business environment going on and try to achieve excellence in their industry through the marketing of their products and achieve greater market share as possible to ensure its continued existence, and perhaps the concept of time production, which confirms, in essence, on the need to reduce inventory to a minimum in the production process as well as the concept of the marketing information system which asserts, in essence, to document all the events that are related to the marketing of the product provided by the production process, together constitute the subject deserves research and investigation as they have raised well-known in the fields of production management and marketing management.

The research aims to test the effect of the behavioral factors (intangible) represented by an explanatory variable represented by organizational silence and a responsive variable of quality of Function life. The problem was the negative effects of the organizational silence on the morale of the employees and consequently their performance and the quality of function life. To collect the data and information needed to measure the two variables of research conducted in the health center / Sulaikh by taking a sample of (40) employees to test the hypotheses of research through the survey of their views, using statistical tools non parametric using the program. The most important recommendations were the establishment of training workshops fo

This study was undertaken to introduce a fast, accurate, selective, simple and environment-friendly colorimetric method to determine iron (II) concentration in different lipstick brands imported or manufactured locally in Baghdad, Iraq. The samples were collected from 500-Iraqi dinars stores to establish routine tests using the spectrophotometric method and compared with a new microfluidic paper-based analytical device (µPAD) platform as an alternative to cost-effective conventional instrumentation such as Atomic Absorption Spectroscopy (AAS). This method depends on the reaction between iron (II) with iron(II) selective chelator 1, 10-phenanthroline(phen) in the presence of reducing agent hydroxylamine (HOA) and sodium acetate (NaOAc) b