Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

Release of industrial effluents comprising dyes in water bodies is one of the foremost causes of water pollution. Therefore, the proper and proficient treatment of these dyes contaminated left-over material before their release is crucial. Herein, an eco-friendly biological macromolecule Gum-Acacia (GA) integrated Fe3O4 nanoparticles composite hydrogel was manufactured via co-precipitation technique for effective adsorption of Congo red (CR) dye existing in water bodies. The as-prepared magnetic GA/Fe3O4 composite hydrogel was characterized by FTIR, XRD, EDX, VSM, SEM, and BET techniques. These studies discovered the fruitful fabrication of biodegradable magnetic GA/Fe3O4 composite hydrogel possessing porous structure with large surface are

Background: The best material for dental implants is polyetherketoneketone (PEKK). However, this substance is neither osteoinductive nor osteoconductive, preventing direct bone apposition. Modifying the PEKK with bioactive elements like strontium hydroxyapatite is one method to overcome this (Sr-HA). Due to the technique's capacity to provide better control over the coating's properties, RF magnetron sputtering has been found to be a particularly useful technique for deposition.

Materials and methods : With specific sputtering conditions, the RF magnetron technique was employed to provide a homogeneous and thin coating on Polyetherketoneketone substrates.. the coatings were characterized by Contact angle, adhesion test, X-ray dif

The map of permeability distribution in the reservoirs is considered one of the most essential steps of the geologic model building due to its governing the fluid flow through the reservoir which makes it the most influential parameter on the history matching than other parameters. For that, it is the most petrophysical properties that are tuned during the history matching. Unfortunately, the prediction of the relationship between static petrophysics (porosity) and dynamic petrophysics (permeability) from conventional wells logs has a sophisticated problem to solve by conventional statistical methods for heterogeneous formations. For that, this paper examines the ability and performance of the artificial intelligence method in perme

Constructing a geologically realistic reservoir model and accurately evaluating petrophysical properties are critical components for effective reservoir management. Such efforts enable reliable assessment of hydrocarbon potential and support predictive development scenarios through numerical simulations. This study aims to characterize the Yamama carbonate reservoir in the Ratawi Field, southern Iraq, and to build a static geological model as a foundation for future dynamic simulation. Comprehensive well data, including wireline logs, core analysis, and geological reports, were integrated to interpret petrophysical parameters such as shale volume, effective porosity, and water saturation. Additionally, facies classification was performed us

This study investigates the impact of copper sulfate (CuSO4) doping and glycerin plasticization on the structural, electrical, dielectric, and optical properties of poly(vinyl alcohol) (PVA), polyvinyl pyrrolidone (PVP), and glycerin gel polymer electrolytes (GPEs). The GPEs were prepared using a solution casting method with varying CuSO4 concentrations (5 and 10 wt.%). X-ray diffraction analysis revealed the semi-crystalline nature of the polymer blend and also confirmed the presence of CuSO4. Fourier transform infrared spectroscopy confirmed the miscibility of PVA, PVP, and glycerin through interchain hydrogen bonding and indicated the successful incorporation of Cu2+ ions into the polymer blend matrix. The PVA/PVP/glycerin blend containi

Purpose: Current denture liner materials suffer from low tear strength, poor abrasion resistance, weak bond strength to denture material, and increasing risk of denture stomatitis due to adherence. The aim of this study was to evaluate the effects of the addition of cellulose nanofibers (CNFs) to commercial soft denture liner material on the adherence of and physical and mechanical properties. Materials and Methods: CNFs at concentrations of 0.0, 0.5, and 1.0 wt.% were incorporated into a soft liner material. Antifungal effects were assessed by quantifying the adherence of . The Shore A hardness, tensile strength, peel bond strength, and surface roughness tests were employed to assess the properties of the denture liner materials. Chemica