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.
The agent-based modeling is currently utilized extensively to analyze complex systems. It supported such growth, because it was able to convey distinct levels of interaction in a complex detailed environment. Meanwhile, agent-based models incline to be progressively complex. Thus, powerful modeling and simulation techniques are needed to address this rise in complexity. In recent years, a number of platforms for developing agent-based models have been developed. Actually, in most of the agents, often discrete representation of the environment, and one level of interaction are presented, where two or three are regarded hardly in various agent-based models. The key issue is that modellers work in these areas is not assisted by simulation plat
... Show MoreIn the present survey 18 species of endo and ecto-parasites were recorded during the examination of 50 Mus musculus (Linnaeus, 1758) among 10 localities in Erbil city, of which 7 species were protozoan and as follows : Chilomastix bettencourti (da Fonseca 1915)82%; Giardia muris (Filice, 1952) 68%; Tritrichomonas muris (Grassi,1879)36%; Entamoeba histolytica (Schaudinn,1903) 24%; Entamoeba coli (Grassi,1879)32%; Eimeria sp. 28% and Trypanosoma musculi (Kendall,1906)2%; and 8 species were helminthes as follows: 4 Cestodes: Rodentolepis nana (von Siebold, 1852) 8%; Hymenolepis diminuta (Rudolphi, 1819)2%; larval stage of Echinococcus granulosus (Batsch, 1786)8%, Cysticercus fasciolaris (Rudolphi, 1808)6%, 4 Nematodes: Aspiculuris tetrapter
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One of the main causes for concern is the widespread presence of pharmaceuticals in the environment, which may be harmful to living things. They are often referred to as emerging chemical pollutants in water bodies because they are either still unregulated or undergoing regulation. Pharmaceutical pollution of the environment may have detrimental effects on ecosystem viability, human health, and water quality. In this study, the amount of remaining pharmaceutical compounds in environmental waters was determined using a straightforward review. Pharmaceutical production and consumption have increased due to medical advancements, leading to concerns about their environmental impact and potential harm to living things due to their increa
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The COVID-19 pandemic has profoundly affected the healthcare sector and the productivity of medical staff and doctors. This study employs machine learning to analyze the post-COVID-19 impact on the productivity of medical staff and doctors across various specialties. A cross-sectional study was conducted on 960 participants from different specialties between June 1, 2022, and April 5, 2023. The study collected demographic data, including age, gender, and socioeconomic status, as well as information on participants' sleeping habits and any COVID-19 complications they experienced. The findings indicate a significant decline in the productivity of medical staff and doctors, with an average reduction of 23% during the post-COVID-19 period. T
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In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the License Plate (LP) detection is presented using canny edge detection
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In this research, we studied the multiple linear regression models for two variables in the presence of the autocorrelation problem for the error term observations and when the error is distributed with general logistic distribution. The auto regression model is involved in the studying and analyzing of the relationship between the variables, and through this relationship, the forecasting is completed with the variables as values. A simulation technique is used for comparison methods depending on the mean square error criteria in where the estimation methods that were used are (Generalized Least Squares, M Robust, and Laplace), and for different sizes of samples (20, 40, 60, 80, 100, 120). The M robust method is demonstrated the best metho
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In this research, we studied the multiple linear regression models for two variables in the presence of the autocorrelation problem for the error term observations and when the error is distributed with general logistic distribution. The auto regression model is involved in the studying and analyzing of the relationship between the variables, and through this relationship, the forecasting is completed with the variables as values. A simulation technique is used for comparison methods depending
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The "Nudge" Theory is considered one of the most recent theories, which is clear in the economic, health, and educational sectors, due to the intensity of studies on it and its applications, but it has not yet been included in crime prevention studies. The use of Nudge theory appears to enrich the theory in the field of crime prevention, and to provide modern, effective, and implementable mechanisms.
The study deals with the "integrative review" approach, which is a distinctive form of research that generates new knowledge on a topic through reviewing, criticizing, and synthesizing representative literature on the topic in an integrated manner so that new frameworks and perspectives are created around it.
The study is bas
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Business Ethics play a major role in explaining the behavior of those interested in the management of tourism enterprises in the field of management gains, which sometimes turn to manipulation in the specification of the service of tourism and influence in the technical characteristics at the expense of the brand and market share, as well as misleading beneficiaries about the fact that the performance of the service of tourism, may depend activities tourist dramatically when submitting and sharing various services on the types of mutual relations the framework for moral distinct, in interaction or direct contact between producers of tourism services and tourists or their beneficiaries, in order to provide comfort and recreation a
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