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

Aphid Aphis spp (Hemiptera:Aphididae) and Thrips Thrips spp (Thysanoptera: Thripidae) an economically important pests on several crops in the world and Iraq, that transfer many viruses diseases to it. Field studies were conducted to assessment the population density of these insects and susceptibility of six varieties (Barin, Revera, Divela, Rudlph, Alazata and Pleny) to infestation during 2013 spring season. The results were showed that all Potato varieties were infested by Aphis and Thrips on spring plantation but with different percentage. The Divela variety was higher percentage of infestation and high population density of aphid which averaged 1.47 insect/ leaf while in Alazata was the lower population density which averaged 1.02 in

The plant Conyza canadensis, which belongs to Asteraceae (Compositae) family and known as Canadian horseweed. It was used as traditional medicine in China, Pakistan, India, and Africa for the treatment of various diseases causing by bacteria, fungi, or viruses. The plant has antimicrobial, antioxidant, anticoagulant, anti-inflammatory, and anticancer pharmacological activity. This study provides the first phytochemical investigation of the plant in Iraq and is concerned with extraction, fractionation, isolation, and purification of some of the important phytochemicals detected in the plant-like phenolic acids, flavonoids, and alkaloids. Also, the literature survey has revealed that the plant has a substantial antimicrobial activity, so it w

The current study was conducted to find out the effect of the sediment source (sedimentary of Iraqi-Iranian borderline and Tigris River) on the content and distribution of feldspar minerals and their effect on the optical properties of these minerals in some soils of Wasit and Maysan province. Eight pedons were chosen to represent the study area, five of them represented sediments coming from the borderline, which included pedons of (Badra, Taj Al-Din, Al-Shihabi, Jassan, and Galat), while two of them represent the sediments of the Tigris River (Essaouira, Al-Dabouni). Finally, the pedon of Ali Al-Gharbi represented the mixing area of sediments of all the torrents coming from borderline and the sediments of the Tigris River. The diagnostic

Linear regression is one of the most important statistical tools through which it is possible to know the relationship between the response variable and one variable (or more) of the independent variable(s), which is often used in various fields of science. Heteroscedastic is one of the linear regression problems, the effect of which leads to inaccurate conclusions. The problem of heteroscedastic may be accompanied by the presence of extreme outliers in the independent variables (High leverage points) (HLPs), the presence of (HLPs) in the data set result unrealistic estimates and misleading inferences. In this paper, we review some of the robust

      Detecting and subtracting the Motion objects from backgrounds is one of the most important areas. The development of cameras and their widespread use in most areas of security, surveillance, and others made face this problem. The difficulty of this area is unstable in the classification of the pixels (foreground or background). This paper proposed a suggested background subtraction algorithm based on the histogram. The classification threshold is adaptively calculated according to many tests. The performance of the proposed algorithms was compared with state-of-the-art methods in complex dynamic scenes.

Atmospheric transmission is disturbed by scintillation, where scintillation caused more beam divergence. In this work target image spot radius was calculated in presence of atmospheric scintillation. The calculation depend on few relevant equation based on atmospheric parameter (for Middle East), tracking range, expansion ratio of applied beam expander's, receiving unit lens F-number, and the laser wavelength besides photodetector parameter. At maximum target range Rmax =20 km, target image radius is at its maximum Rs=0.4 mm. As the range decreases spot radius decreases too, until the range reaches limit (4 km) at which target image spot radius at its minimum value (0.22 mm). Then as the range decreases, spot radius increases due to geom

A nonlinear filter for smoothing color and gray images
corrupted by Gaussian noise is presented in this paper. The proposed
filter designed to reduce the noise in the R,G, and B bands of the
color images and preserving the edges. This filter applied in order to
prepare images for further processing such as edge detection and
image segmentation.
The results of computer simulations show that the proposed
filter gave satisfactory results when compared with the results of
conventional filters such as Gaussian low pass filter and median filter
by using Cross Correlation Coefficient (ccc) criteria.