Distributed Denial of Service (DDoS) attacks on Web-based services have grown in both number and sophistication with the rise of advanced wireless technology and modern computing paradigms. Detecting these attacks in the sea of communication packets is very important. There were a lot of DDoS attacks that were directed at the network and transport layers at first. During the past few years, attackers have changed their strategies to try to get into the application layer. The application layer attacks could be more harmful and stealthier because the attack traffic and the normal traffic flows cannot be told apart. Distributed attacks are hard to fight because they can affect real computing resources as well as network bandwidth. DDoS attacks can also be made with smart devices that connect to the Internet, which can be infected and used as botnets. They use Deep Learning (D.L.) techniques like Convolutional Neural Network (C.N.N.) and variants of Recurrent Neural Networks (R.N.N.), such as Long Short-Term Memory (L.S.T.M.), Bidirectional L.S.T.M., Stacked L.S.T.M., and the Gat G.R.U.. These techniques have been used to detect (DDoS) attacks. The Portmap.csv file from the most recent DDoS dataset, CICDDoS2019, has been used to test D.L. approaches. Before giving the data to the D.L. approaches, the data is cleaned up. The pre-processed dataset is used to train and test the D.L. approaches. In the paper, we show how the D.L. approach works with multiple models and how they compare to each other.
Interface bonding between asphalt layers has been a topic of international investigation over the last thirty years. In this condition, a number of researchers have made their own techniques and used them to examine the characteristics of pavement interfaces. It is obvious that test findings won't always be comparable to the lack of a globally standard methodology for interface bonding. Also, several kinds of research have shown that factors like temperature, loading conditions, materials, and others have an impact on surface qualities. This study aims to solve this problem by thoroughly investigating interface bond testing that might serve as a basis for a uniform strategy. First, a general explanation of how
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Any harm done to genetic material, whether directly interacting with DNA or indirectly through biological systems, is referred to as genotoxicity. Such harm poses major risks to the health of people, animals, and plants as it is a primary source of carcinogenesis, mutagenesis, and teratogenesis. Because of their medicinal qualities, alkaloids—a family of naturally occurring phytochemicals made by plants from amino acids—are frequently utilized to treat ailments such newborn apnea, gout, and asthma. Recent research has sparked worries about their possible genotoxic consequences despite their therapeutic advantages. Through a variety of processes, including as the creation of DNA adducts, DNA–DNA cross-links, and DNA–protein c
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Interface bonding between asphalt layers has been a topic of international investigation over the last thirty years. In this condition, a number of researchers have made their own techniques and used them to examine the characteristics of pavement interfaces. It is obvious that test findings won't always be comparable to the lack of a globally standard methodology for interface bonding. Also, several kinds of research have shown that factors like temperature, loading conditions, materials, and others have an impact on surface qualities. This study aims to solve this problem by thoroughly investigating interface bond testing that might serve as a basis for a uniform strategy. First, a general explanation of how the bonding strength
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The research aims to statement the main obstacles that prevent the application of total quality management (TQM) in a number of Iraqi service organizations, and by one organization in each of the sectors (health, finance, education, higher education, tourism), which are, (Al-Yarmouk Teaching Hospital, Rafidain Bank/ Branch of Hay Al-Arabi Al-Jadid, Al-Karkh/1 Directorate of Education, College of administration and Economics/ Baghdad University, International Palestine Hotel). The research also, tries to classify the priority of the obstacles depending on the type of service organization surveyed. And diagnoses the extent to which or the difference of the research sample members views on the order of obstacles of TQM, and also proposes a
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In this work, the detection of zinc (Zn) ions that cause water pollution is studied using the CSNPs- Linker-alkaloids compound that was prepared by linking extracted alkaloids from Iraqi Catharanthus roseus plant with Chitosan nanoparticles (CSNPs) using maleic anhydride. This compound is characterized by an X-ray diffractometer (XRD) which shows that it has an orthorhombic structure with crystallite size in the nano dimension. Zeta Potential results show that the CSNPs-Linker-alkaloids carried a positive charge of 54.4 mV, which means it possesses high stability. The Fourier transform infrared spectroscopy (FTIR) shows a new distinct band at 1708.93 cm-1 due to C=O esterification. Scanning electron microscope (SEM) image
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
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This article presents the results of an experimental investigation of using carbon fiber–reinforced polymer sheets to enhance the behavior of reinforced concrete deep beams with large web openings in shear spans. A set of 18 specimens were fabricated and tested up to a failure to evaluate the structural performance in terms of cracking, deformation, and load-carrying capacity. All tested specimens were with 1500-mm length, 500-mm cross-sectional deep, and 150-mm wide. Parameters that studied were opening size, opening location, and the strengthening factor. Two deep beams were implemented as control specimens without opening and without strengthening. Eight deep beams were fabricated with openings but without strengthening, while
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This article presents the results of an experimental investigation of using carbon fiber–reinforced polymer sheets to enhance the behavior of reinforced concrete deep beams with large web openings in shear spans. A set of 18 specimens were fabricated and tested up to a failure to evaluate the structural performance in terms of cracking, deformation, and load-carrying capacity. All tested specimens were with 1500-mm length, 500-mm cross-sectional deep, and 150-mm wide. Parameters that studied were opening size, opening location, and the strengthening factor. Two deep beams were implemented as control specimens without opening and without strengthening. Eight deep beams were fabricated with openings but without strengthening, while
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The Braille Recognition System is the process of capturing a Braille document image and turning its content into its equivalent natural language characters. The Braille Recognition System's cell transcription and Braille cell recognition are the two basic phases that follow one another. The Braille Recognition System is a technique for locating and recognizing a Braille document stored as an image, such as a jpeg, jpg, tiff, or gif image, and converting the text into a machine-readable format, such as a text file. BCR translates an image's pixel representation into its character representation. As workers at visually impaired schools and institutes, we profit from Braille recognition in a variety of ways. The Braille Recognition S
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