Until recently, researchers have utilized and applied various techniques for intrusion detection system (IDS), including DNA encoding and clustering that are widely used for this purpose. In addition to the other two major techniques for detection are anomaly and misuse detection, where anomaly detection is done based on user behavior, while misuse detection is done based on known attacks signatures. However, both techniques have some drawbacks, such as a high false alarm rate. Therefore, hybrid IDS takes advantage of combining the strength of both techniques to overcome their limitations. In this paper, a hybrid IDS is proposed based on the DNA encoding and clustering method. The proposed DNA encoding is done based on the UNSW-NB15

The current study presents an experimental investigation of heat transfer and flow characteristic for subcooled flow boiling of deionized water in the microchannel heat sink. The test section consisted of a single microchannel having 300μm wide nominal dimensions and 300μm height (hydraulic diameter of 300μm). The test section formed of oxygen-free copper with 72mm length and 12mm width. Experimental operation conditions spanned the heat flux (78-800) kW/m², mass flux (1700 and 2100) kg/m².s at 31˚C subcooled inlet temperature. The boiling heat transfer coefficient is measured and compared with existing correlations. Also, the experimental pressure drop is measured and compared with microscale p

Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d

The communication inspiration formed an essential foundations for contribute the influence individuals and recipients, whether negatively or positively, through the messages that were published and presented in them with multiple themes and viewpoints that covered all parts of the world and all age groups; it is directed to children addressing the various stages of childhood, as it simulates many goals, including what is directed through the digital use of educational data in television production, as it is considered an intellectual and mental bag to deliver ideas and expressive and aesthetic connotations to children, where the songs and cartoons carrying data on education; within adjacent relations and in a mutual direction, both of th

The digital dermatoglyphics were studied in 120 females derived from northern region of Iraq (60 Arabs and 60 Kurds). Two kinds of analyses were perfomed : Quantitative and Qualtative. The unilateral and bilateral analyses for dermal ridge counts in each digital and the overall did not reveal any significant difference when t-test was used. A high correlation coefficients were revealed in this study between homologous and adjacent digits, moreover, significant differences were revealed between Arabian and Kurdish samples in both analyses when Fisher Z transform test was used, but the significant differences in the bilateral analysis exceed the ones in the unilateral. This indicates the importance of the former analysis in detecting the vari

Determining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You on