Active worms have posed a major security threat to the Internet, and many research efforts have focused on them. This paper is interested in internet worm that spreads via TCP, which accounts for the majority of internet traffic. It presents an approach that use a hybrid solution between two detection algorithms: behavior base detection and signature base detection to have the features of each of them. The aim of this study is to have a good solution of detecting worm and stealthy worm with the feature of the speed. This proposal was designed in distributed collaborative scheme based on the small-world network model to effectively improve the system performance.

To make iron oxide nanoparticles (IONPs), a simple chemical approach was used to combine iron chloride (FeCl₂+FeCl₃) salt with onion peel extract. According to the study, iron salts can be converted into IONPs by the biomolecules in onion peel extract. From FeCl₂+FeCl₃ to γ -Fe₂O₃, the approach changes iron oxide NPs' size, shape, purity and phases. In water treatment, γ -Fe₂O₃ NPs are critical for the removal of the color methylene blue (MB). X-ray diffraction (XRD), scanning electron microscopy (SEM), ultraviolet (UV-Vis) and photoluminescence (PL) spectroscopy were used to identify IONPs. Results from the XRD experiment showed crystals having a

Electromyogram (EMG)-based Pattern Recognition (PR) systems for upper-limb prosthesis control provide promising ways to enable an intuitive control of the prostheses with multiple degrees of freedom and fast reaction times. However, the lack of robustness of the PR systems may limit their usability. In this paper, a novel adaptive time windowing framework is proposed to enhance the performance of the PR systems by focusing on their windowing and classification steps. The proposed framework estimates the output probabilities of each class and outputs a movement only if a decision with a probability above a certain threshold is achieved. Otherwise (i.e., all probability values are below the threshold), the window size of the EMG signa

The enrollment of students in the university represents a new stage in their life that differ from the previous educational stages that student has previously established. It should be noted that students with special needs at the University of Baghdad are not large numbers. It appears that these students have an excel role in their colleges most often, That is, the handicap was not a barrier to their scientific progress, but rather an incentive for them to excel. The most important conclusion reached by the researcher is that the University of Baghdad had no role in caring for people with special needs and caring for them financially, socially, psychologically, healthily and economically, they need to pay attention to them and take care

Abstract

Robust controller design requires a proper definition of uncertainty bounds. These uncertainty bounds are commonly selected randomly and conservatively for certain stability, without regard for controller performance.  This issue becomes critically important for multivariable systems with high nonlinearities, as in Active Magnetic Bearings (AMB) System. Flexibility and advanced learning abilities of intelligent techniques make them appealing for uncertainty estimation. The aim of this paper is to describe the development of robust H₂/H_∞ controller for AMB based on intelligent estimation of uncertainty bounds using Adaptive Neuro Fuzzy Inference System (ANFIS).  Simulatio

Palynological characters of eleven cultivated species of the family Fabaceae
grown in Baghdad University campus has been presented in this work. The study
included two kind of single pollen grain. Tri.colporate in Bauhinia variegata L.,
Cassia fistula L., Lablab purpureus(L.)sweet, Vigna mungo(L.)Hepper , and Tri-
Colpate in Cassia acutifolia L., Mimosa pudica L., Vigna sinensis/L. Vicia faba L.
,and polyad in Acasia cyanophylla Lindl, Acasia famesiana(L.)wild, Albizia lebbeck
(L.)Benth.,A study focused on the shape of colpi and endoaperture are variable,
shape of pollen show variation in polar and equatorial view for single species and
for front and side view for polyad one, The study determind size of pollen gra

    Clustering is an unsupervised learning method that classified data according to similarity probabilities. DBScan as a high-quality algorithm has been introduced for clustering spatial data due to its ability to remove noise (outlier) and constructing arbitrarily shapes. However, it has a problem in determining a suitable value of Eps parameter. This paper proposes a new clustering method, termed as DBScanBAT, that it optimizes DBScan algorithm by BAT algorithm. The proposed method automatically sets the DBScan parameters (Eps) and finds the optimal value for it. The results of the proposed DBScanBAT automatically generates near original number of clusters better than DBScanPSO and original DBScan. Furthermore, the proposed method

Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo

The subject of social capital is of great importance, as it provides an analytical framework for researchers interested in understanding the impact of the Internet on many dimensions of human and social life. And because social networking sites have infiltrated societies and produced new variables at the level of human and social communication, this study came to examine the relationship between the use of the social networking site Facebook and the accumulation of social capital among a sample of University of Algeria 3 students, by researching the variables of intensity of use and patterns of use as independent variables and their relationship to social capital. The results of the field study revealed a strong relationship between the

This paper presents a comparative study of two learning algorithms for the nonlinear PID neural trajectory tracking controller for mobile robot in order to follow a pre-defined path. As simple and fast tuning technique, genetic and particle swarm optimization algorithms are used to tune the nonlinear PID neural controller's parameters to find the best velocities control actions of the right wheel and left wheel for the real mobile robot. Polywog wavelet activation function is used in the structure of the nonlinear PID neural controller. Simulation results (Matlab) and experimental work (LabVIEW) show that the proposed nonlinear PID controller with PSO
learning algorithm is more effective and robust than genetic learning algorithm; thi