The increasing complexity of assaults necessitates the use of innovative intrusion detection systems (IDS) to safeguard critical assets and data. There is a higher risk of cyberattacks like data breaches and unauthorised access since cloud services have been used more frequently. The project's goal is to find out how Artificial Intelligence (AI) could enhance the IDS's ability to identify and classify network traffic and identify anomalous activities. Online dangers could be identified with IDS. An intrusion detection system, or IDS, is required to keep networks secure. We must create efficient IDS for the cloud platform as well, since it is constantly growing and permeating more aspects of our daily life. However, using standard intrusion

     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

      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.

This study deals with the role that social work profession plays in all its fields to reduce social extremismat home, or school or within society. The study aims to: examine the historical roots of social work in the Iraqi society, investigate the objectives of the developmental role of social work, review the theories of social extremism, its characteristics, and causes, and to analyze the developmental role of social work to limit social extremism. To meet the objectives of the study, a descriptive analytical approach has been adopted. It involves using the social sampling survey method, i.e., a questionnaire tool in the University of Baghdad community-College of Media. The sample was randomly selected to include (100) students from th

This study aims to predict the organic pollution produced from the presence of some polycyclic aromatic hydrocarbons (PAHs) and determination it's concentrations (µg/L , ppb) in Tigris river water by a collection twenty-seven water samples from a selected three stations with nine sampling sites and three depths of water (5 cm , 2 m and 4 m) each site for 4.6 km distance of a geographic studied area which is located between the ( Al-Senak and AL-Sarrafiah bridges ) at Baghdad city – Iraq on May, 2012. The geographic location was determined with a Global Positioning System (GPS) and Geographic Information System (GIS) software program. The concentrations of fourteen components (PAHs) were performed using the reverse phase

Influential, organized groups with natural antimicrobial and anti-biofilm broad-spectrum power exist within the food chain, like a hidden dormant mimic hygienic bio life nanobodies that can terminate multiple opportunistic disease entities owing multi-stress resistant forbidden recalcitrant power, such as Candida albicans. These wonderful dynamic forces created by ALLAH Almighty are the Mycophages or fungi-eating state of fungi foodborne phages, and this project was redirected to be a dare to leap from us towards the future. Multi-stress resistant C. albicans that are resistant to different antifungal agents with their genetic tolerance plasticity to thermal pasteurization decontamination module as well as to ultraviolet irradiation