The recent advancements in security approaches have significantly increased the ability to identify and mitigate any type of threat or attack in any network infrastructure, such as a software-defined network (SDN), and protect the internet security architecture against a variety of threats or attacks. Machine learning (ML) and deep learning (DL) are among the most popular techniques for preventing distributed denial-of-service (DDoS) attacks on any kind of network. The objective of this systematic review is to identify, evaluate, and discuss new efforts on ML/DL-based DDoS attack detection strategies in SDN networks. To reach our objective, we conducted a systematic review in which we looked for publications that used ML/DL approaches to identify DDoS attacks in SDN networks between 2018 and the beginning of November 2022. To search the contemporary literature, we have extensively utilized a number of digital libraries (including IEEE, ACM, Springer, and other digital libraries) and one academic search engine (Google Scholar). We have analyzed the relevant studies and categorized the results of the SLR into five areas: (i) The different types of DDoS attack detection in ML/DL approaches; (ii) the methodologies, strengths, and weaknesses of existing ML/DL approaches for DDoS attacks detection; (iii) benchmarked datasets and classes of attacks in datasets used in the existing literature; (iv) the preprocessing strategies, hyperparameter values, experimental setups, and performance metrics used in the existing literature; and (v) current research gaps and promising future directions.
Confocal microscope imaging has become popular in biotechnology labs. Confocal imaging technology utilizes fluorescence optics, where laser light is focused onto a specific spot at a defined depth in the sample. A considerable number of images are produced regularly during the process of research. These images require methods of unbiased quantification to have meaningful analyses. Increasing efforts to tie reimbursement to outcomes will likely increase the need for objective data in analyzing confocal microscope images in the coming years. Utilizing visual quantification methods to quantify confocal images with naked human eyes is an essential but often underreported outcome measure due to the time required for manual counting and e
... Show MoreThe research aims to achieve a set of objectives, the most important of which is determining the extent to which the auditors of the research sample in the Federal Bureau of Financial Supervision adhere to the requirements of the quality control system according to the Iraqi Audit Manual No. The federal financial / research sample with the quality control system according to the Iraqi audit guide No. 7), and the researcher seeks to test the main research hypothesis and sub-hypotheses, and to achieve this, a questionnaire was designed by (Google Form) and distributed electronically to the elements of the research sample, Through the statistical package program (SPSS), the results of the questionnaire were analysed. In light of the applied
... Show MoreFallacies are incorrect reasoning that make an argument seem less logically credible and easier to be identified as unsound. They are widespread; individuals commit them while engaging in various activities, including at work, at home, while creating advertisements, and in the media. This study aims to investigate the rhetorical strategies accompanied with producing the fallacious arguments selected from the American Film “12 Angry Men (1957)”. The study adopts Damer’s (2009) model for the identification of fallacy. As for rhetorical analysis, the study adopts Aristotle’s triangle of rhetoric and McGuigan’s (2007) taxonomy of rhetorical devices. The results uncover that the most violated criteria are relevance, acceptabili
... Show MoreThe interplay of species in a polluted environment is one of the most critical aspects of the ecosystem. This paper explores the dynamics of the two-species Lokta–Volterra competition model. According to the type I functional response, one species is affected by environmental pollution. Whilst the other degrades the toxin according to the type II functional response. All equilibrium points of the system are located, with their local and global stability being assessed. A numerical simulation examination is carried out to confirm the theoretical results. These results illustrate that competition and pollution can significantly change the coexistence and extinction of each species.
CNC machine is used to machine complex or simple shapes at higher speed with maximum accuracy and minimum error. In this paper a previously designed CNC control system is used to machine ellipses and polylines. The sample needs to be machined is drawn by using one of the drawing software like AUTOCAD® or 3D MAX and is saved in a well-known file format (DXF) then that file is fed to the CNC machine controller by the CNC operator then that part will be machined by the CNC machine. The CNC controller using developed algorithms that reads the DXF file feeds to the machine, extracts the shapes from the file and generates commands to move the CNC machine axes so that these shapes can be machined.
Shadow removal is crucial for robot and machine vision as the accuracy of object detection is greatly influenced by the uncertainty and ambiguity of the visual scene. In this paper, we introduce a new algorithm for shadow detection and removal based on different shapes, orientations, and spatial extents of Gaussian equations. Here, the contrast information of the visual scene is utilized for shadow detection and removal through five consecutive processing stages. In the first stage, contrast filtering is performed to obtain the contrast information of the image. The second stage involves a normalization process that suppresses noise and generates a balanced intensity at a specific position compared to the neighboring intensit
... Show MoreSupport vector machine (SVM) is a popular supervised learning algorithm based on margin maximization. It has a high training cost and does not scale well to a large number of data points. We propose a multiresolution algorithm MRH-SVM that trains SVM on a hierarchical data aggregation structure, which also serves as a common data input to other learning algorithms. The proposed algorithm learns SVM models using high-level data aggregates and only visits data aggregates at more detailed levels where support vectors reside. In addition to performance improvements, the algorithm has advantages such as the ability to handle data streams and datasets with imbalanced classes. Experimental results show significant performance improvements in compa
... Show MoreThe aim of this study to identify the effect of using two strategies for active learning ( Jigsaw Strategy & Problems Solving) in learning some balanced beam's skills in artistic gymnastics for women , as well as to identify the best of the three methods (jigsaw strategy , problems solving and the traditional method) in learning some skills balance beam , the research has used the experimental methodology, and the subject included the students of the college of Physical Education and Sports Sciences / University of Baghdad / third grade and by the lot was selected (10) students for each group of groups Search three and The statistical package for social sciences (SPSS) was used means, the standard deviation and the (T.test), the one way a n
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