Cybersecurity refers to the actions that are used by people and companies to protect themselves and their information from cyber threats. Different security methods have been proposed for detecting network abnormal behavior, but some effective attacks are still a major concern in the computer community. Many security gaps, like Denial of Service, spam, phishing, and other types of attacks, are reported daily, and the attack numbers are growing. Intrusion detection is a security protection method that is used to detect and report any abnormal traffic automatically that may affect network security, such as internal attacks, external attacks, and maloperations. This paper proposed an anomaly intrusion detection system method based on a

The power generation of solar photovoltaic (PV) technology is being implemented in every nation worldwide due to its environmentally clean characteristics. Therefore, PV technology is significantly growing in the present applications and usage of PV power systems. Despite the strength of the PV arrays in power systems, the arrays remain susceptible to certain faults. An effective supply requires economic returns, the security of the equipment and humans, precise fault identification, diagnosis, and interruption tools. Meanwhile, the faults in unidentified arc lead to serious fire hazards to commercial, residential, and utility-scale PV systems. To ensure secure and dependable distribution of electricity, the detection of such ha

Self-repairing technology based on micro-capsules is an efficient solution for repairing cracked cementitious composites. Self-repairing based on microcapsules begins with the occurrence of cracks and develops by releasing self-repairing factors in the cracks located in concrete. Based on previous comprehensive studies, this paper provides an overview of various repairing factors and investigative methodologies. There has recently been a lack of consensus on the most efficient criteria for assessing self-repairing based on microcapsules and the smart solutions for improving capsule survival ratios during mixing. The most commonly utilized self-repairing efficiency assessment indicators are mechanical resistance and durab

Fractal geometry is receiving increase attention as a quantitative and qualitative model for natural phenomena description, which can establish an active classification technique when applied on satellite images. In this paper, a satellite image is used which was taken by Quick Bird that contains different visible classes. After pre-processing, this image passes through two stages: segmentation and classification. The segmentation carried out by hybrid two methods used to produce effective results; the two methods are Quadtree method that operated inside Horizontal-Vertical method. The hybrid method is segmented the image into two rectangular blocks, either horizontally or vertically depending on spectral uniformity crit

One of the most Interesting natural phenomena is clouds that have a very strong effect on the climate, weather and the earth's energy balance. Also clouds consider the key regulator for the average temperature of the plant. In this research monitoring and studying the cloud cover to know the clouds types and whether they are rainy or not rainy using visible and infrared satellite images. In order to interpret and know the types of the clouds visually without using any techniques, by comparing between the brightness and the shape of clouds in the same area for both the visible and infrared satellite images, where the differences in the contrasts of visible image are the albedo differences, while in the infrared images is the temperature d

Image pattern classification is considered a significant step for image and video processing.Although various image pattern algorithms have been proposed so far that achieved adequate classification,achieving higher accuracy while reducing the computation time remains challenging to date. A robust imagepattern classification method is essential to obtain the desired accuracy. This method can be accuratelyclassify image blocks into plain, edge, and texture (PET) using an efficient feature extraction mechanism.Moreover, to date, most of the existing studies are focused on evaluating their methods based on specificorthogonal moments, which limits the understanding of their potential application to various DiscreteOrthogonal Moments (DOMs). The

Image pattern classification is considered a significant step for image and video processing. Although various image pattern algorithms have been proposed so far that achieved adequate classification, achieving higher accuracy while reducing the computation time remains challenging to date. A robust image pattern classification method is essential to obtain the desired accuracy. This method can be accurately classify image blocks into plain, edge, and texture (PET) using an efficient feature extraction mechanism. Moreover, to date, most of the existing studies are focused on evaluating their methods based on specific orthogonal moments, which limits the understanding of their potential application to various Discrete Orthogonal Moments (DOM