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Performance Evaluation of SDN DDoS Attack Detection and Mitigation Based Random Forest and K-Nearest Neighbors Machine Learning Algorithms
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of network topology have been generated to observe the effectiveness of proposed algorithms on different network architectures. The results reveal that RF performs better than KNN in a single topology, and both have close performance in other topologies.

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Publication Date
Sun Dec 01 2013
Journal Name
Baghdad Science Journal
Linear Increasing in Radial Electronic Density Distribution for K and L Shells throughout Some Be-Like Ions
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Maximum values of one particle radial electronic density distribution has been calculated by using Hartree-Fock (HF)wave function with data published by[A. Sarsa et al. Atomic Data and Nuclear Data Tables 88 (2004) 163–202] for K and L shells for some Be-like ions. The Results confirm that there is a linear behavior restricted the increasing of maximum points of one particle radial electronic density distribution for K and L shells throughout some Be-like ions. This linear behavior can be described by using the nth term formula of arithmetic sequence, that can be used to calculate the maximum radial electronic density distribution for any ion within Be like ions for Z<20.

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Publication Date
Thu May 04 2023
Journal Name
Biomedicine
Relationship between cathepsin K and total oxidative state in diabetes mellitus female patients with osteoporosis in Iraq
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Introduction and Aim: Diabetes mellitus patients almost always struggle with a metabolic condition known as chronic hyperglycemia. According to the World Health Organization, osteoporosis is a progressive systemic skeletal disorder that is characterized by decreasing bone mass and microstructural breakdown of bone tissue that increases susceptibility to fracture and increased risk of breaking a bone. Here, we aimed to compare the levels of CatK and total oxidative state in patients with diabetes and osteoporosis among the female Iraqi population and study the possible relationship between them.   Materials and Methods: This study included 40 females with diabetes (Group G1), 40 with diabetes and osteoporosis (Group G2) and 40 norma

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Publication Date
Thu Aug 18 2022
Journal Name
Dental Hypotheses
Microleakage Evaluation of Glass Hybrid Restoration Following Usage of Papain-Based Gel and Ceramic Bur for Caries Removal: An in Vitro Study
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Publication Date
Sat Sep 30 2023
Journal Name
Wasit Journal Of Computer And Mathematics Science
Real time handwriting recognition system using CNN algorithms
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Abstract— The growing use of digital technologies across various sectors and daily activities has made handwriting recognition a popular research topic. Despite the continued relevance of handwriting, people still require the conversion of handwritten copies into digital versions that can be stored and shared digitally. Handwriting recognition involves the computer's strength to identify and understand legible handwriting input data from various sources, including document, photo-graphs and others. Handwriting recognition pose a complexity challenge due to the diversity in handwriting styles among different individuals especially in real time applications. In this paper, an automatic system was designed to handwriting recognition

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Publication Date
Thu Jun 16 2022
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Optimization algorithms for transportation problems with stochastic demand
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The purpose of this paper is to solve the stochastic demand for the unbalanced transport problem using heuristic algorithms to obtain the optimum solution, by minimizing the costs of transporting the gasoline product for the Oil Products Distribution Company of the Iraqi Ministry of Oil. The most important conclusions that were reached are the results prove the possibility of solving the random transportation problem when the demand is uncertain by the stochastic programming model. The most obvious finding to emerge from this work is that the genetic algorithm was able to address the problems of unbalanced transport, And the possibility of applying the model approved by the oil products distribution company in the Iraqi Ministry of Oil to m

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Publication Date
Sun Oct 01 2023
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Intelligence framework dust forecasting using regression algorithms models
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<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, c

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Publication Date
Mon Apr 05 2021
Journal Name
Solid State Technology
Genetic Algorithms in Construction Project Management: A Review
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Genetic algorithms (GA) are a helpful instrument for planning and controlling the activities of a project. It is based on the technique of survival of the fittest and natural selection. GA has been used in different sectors of construction and building however that is rarely documented. This research aimed to examine the utilisation of genetic algorithms in construction project management. For this purpose, the research focused on the benefits and challenges of genetic algorithms, and the extent to which genetic algorithms is utilised in construction project management. Results showed that GA provides an ability of generating near optimal solutions which can be adopted to reduce complexity in project management and resolve difficult problem

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Publication Date
Mon Dec 11 2017
Journal Name
Al-khwarizmi Engineering Journal
Proposed Hybrid Sparse Adaptive Algorithms for System Identification
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Abstract 

For sparse system identification,recent suggested algorithms are  -norm Least Mean Square (  -LMS), Zero-Attracting LMS (ZA-LMS), Reweighted Zero-Attracting LMS (RZA-LMS), and p-norm LMS (p-LMS) algorithms, that have modified the cost function of the conventional LMS algorithm by adding a constraint of coefficients sparsity. And so, the proposed algorithms are named  -ZA-LMS, 

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Publication Date
Wed May 16 2018
Journal Name
Asian Journal Of Chemistery
Study of Physical and Spectral Properties of Quaternary System of 2,5-Hexadione+Cyclopentanol+Cyclohexanol+3-Heptanol Mixture at 298 K
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Publication Date
Tue Dec 03 2024
Journal Name
Adab Al-basrah
The Time Machine: Scientific Advances and Social Milieus in H. G. Well's Vision of the Future
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This study is qualitative, it illustrates H.G. Wells\\'s The Time Machine through the scientific and social framework of the Victorian Era. Wells\\'s portrayal of future societies examines the rapid technological progress and social changes of the 19th century. The analysis scrutinizes the division between the Eloi and the Morlocks, tracing the consequences of social division. To meet the objective of the study, Victorian frame of mind is utilized to examine the class struggle that is symbolized by the Eloi and the Morlocks. The analysis highlights the economic and social effects of industrialization and how Wells examines the capitalist system and its impact on human relationships and class division. The study also utilizes concepts from D

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