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

Pure nano Ferro fluid was synthesized by chemical co-precipitation method. The composite of polyaniline with nano sized Ferro fluid was prepared by In-situ–chemical oxidation polymerization method with ammonium per sulphate as an oxidant in aqueous hydrochloric acid under constant stirring at room temperature. The optical properties, absorption, transmission, optical energy gap (Eg) and optical constant refractive index (n) have been investigated. The value of the Eg decreased with increasing Ferro fluid concentration.

     In this paper, the botnet detection problem is defined as a feature selection problem and the genetic algorithm (GA) is used to search for the best significant combination of features from the entire search space of set of features. Furthermore, the Decision Tree (DT) classifier is used as an objective function to direct the ability of the proposed GA to locate the combination of features that can correctly classify the activities into normal traffics and botnet attacks. Two datasets  namely the UNSW-NB15 and the Canadian Institute for Cybersecurity Intrusion Detection System 2017 (CICIDS2017), are used as evaluation datasets. The results reveal that the proposed DT-aware GA can effectively find the relevant features from

Background: The estimation of ferritin and related variables by complete serum iron profile, for Iraqi hashimoto’s patients to see the effect of thyroid hormone insufficiency, which may lead to deficiency of ferritin iron stores, this may be quite useful during the diagnosis and treatment of hashimoto’s patients. Patients and Method: The study was performed at National Center of Teaching laboratories of Medical city institute in Baghdad. Fifty newly diagnosed patients with hashimoto’s and forty apparently healthy controls. Diagnosis based on thyroid profile analysis including:Thyroid Stimulating Hormone (TSH), Thyroxine (totalT4) and Triiodothyronine (total T3), estimation of antibodies against thyroperoxidase, iron profile including:

This study aims to show the  effectiveness of immobilization of Chlorella green algae biomass in the form of bead for the removal of lead ions from synthetic polluted water  at various operational parameters such as pH (2–6), biosorbent dosage (0.5–20 g/L) and initial concentration (10–100 mg/L). More than 90 % removal efficiency was achieved. FTIR and SEM-EDX analysis of the biosorbent before and after sorption show differences in the functional groups on the adsorbent surface. Langmuir and Freundlich equilibrium isotherm, pseudo-first-order and pseudo-second-order kinetic models were applied to the experimental and results and show good conformity with Langmuir isotherm model and pseudo-second-order kinetic model with c

 Research Summary

It highlights the importance of assessing the demand for money function in Iraq through the understanding of the relationship between him and affecting the variables by searching the stability of this function and the extent of their influence in the Iraqi dinar exchange rate in order to know the amount of their contribution to the monetary policies of the Iraqi economy fee, as well as through study behavior of the demand for money function in Iraq and analyze the determinants of the demand for money for the period 1991-2013 and the impact of these determinants in the demand for money in Iraq.

And that the problem that we face is how to estimate the total demand for money in

The designer must find the optimum match between the object's technical and economic needs and the performance and production requirements of the various material options when choosing material for an engineering application. This study proposes an integrated (hybrid) strategy for selecting the optimal material for an engineering design depending on design requirements. The primary objective is to determine the best candidate material for the drone wings based on Ashby's performance indices and then rank the result using a grey relational technique with the entropy weight method. Aluminum alloys, titanium alloys, composites, and wood have been suggested as suitable materials for manufacturing drone wings. The requirement