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Comparison of ML/DL Approaches for Detecting DDoS Attacks in SDN
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Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an SVM-based DDoS detection model shows superior performance. This comparative analysis offers a valuable insight into the development of efficient and accurate techniques for detecting DDoS attacks in SDN environments with less complexity and time.

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Publication Date
Fri Sep 01 2023
Journal Name
Asian Pacific Journal Of Cancer Prevention
Development of a T-ARMS-PCR Assay for Detecting Genetic Polymorphism in the Catalase (rs7943316) Gene in the Iraqi Population with Breast Cancer
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Publication Date
Wed Mar 27 2019
Journal Name
Iraqi Journal Of Science
Efficiency of Thematic Mapper Data for Detecting the Changes of Land Use -Land Cover in Mosul Lake and Surrounding Area Northern Iraq
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The study area lies in the northern part of Iraq, This study depends on one scene of Thematic Mapper (TM5) data of Landsat, these data are subset by using region of interest (ROI) file within the ERDAS 9.2 software. RS and GIS have been used as tools for detecting the desertification during the periods 1990-2000-2009 by using Normalized Difference Vegetation Index NDVI, Water Index WI and Barren Land Index BLI. The indicators of Desertification which used in this study for period  1990-2000 and 2000-2009 are represented by decrease the vegetation cover and increase water body and barren land.

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
A Crime Data Analysis of Prediction Based on Classification Approaches
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Crime is considered as an unlawful activity of all kinds and it is punished by law. Crimes have an impact on a society's quality of life and economic development. With a large rise in crime globally, there is a necessity to analyze crime data to bring down the rate of crime. This encourages the police and people to occupy the required measures and more effectively restricting the crimes. The purpose of this research is to develop predictive models that can aid in crime pattern analysis and thus support the Boston department's crime prevention efforts. The geographical location factor has been adopted in our model, and this is due to its being an influential factor in several situations, whether it is traveling to a specific area or livin

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Publication Date
Wed Oct 25 2023
Journal Name
2023 Ieee 8th International Conference On Engineering Technologies And Applied Sciences (icetas)
Vibration Characteristics of Perforated Plate using Experimental and Numerical Approaches
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Vibration analysis plays a vital role in understanding and analyzing the behavior of the structure. Where, it can be utilized from this analysis in the design process of the structures in different engineering applications, check the quality and safety of the structure under different working conditions. This work presents experimental measurements and numerical solutions to an out of plane vibration of a rectangular plate with a circular hole. Free edges rectangular plates with different circular holes diameters were studied. The effects of hole location on the plate natural frequencies were also investigated. A finite element modeling (using ANSYS Software) has been used to analyze the vibration characteristics of the plates. A good agree

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Publication Date
Wed Jan 06 2021
Journal Name
Pierm
ULTRA-WIDEBAND FEATURING ENHANCED DELAY AND SUM ALGORITHM AND ORIENTED FOR DETECTING EARLY STAGE BREAST CANCER
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Abstract—In this study, we present the experimental results of ultra-wideband (UWB) imaging oriented for detecting small malignant breast tumors at an early stage. The technique is based on radar sensing, whereby tissues are differentiated based on the dielectric contrast between the disease and its surrounding healthy tissues. The image reconstruction algorithm referred to herein as the enhanced version of delay and sum (EDAS) algorithm is used to identify the malignant tissue in a cluttered environment and noisy data. The methods and procedures are tested using MRI-derived breast phantoms, and the results are compared with images obtained from classical DAS variant. Incorporating a new filtering technique and multiplication procedure, t

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Publication Date
Sat Sep 30 2023
Journal Name
Iraqi Journal Of Science
Comparing the Random Forest vs. Extreme Gradient Boosting using Cuckoo Search Optimizer for Detecting Arabic Cyberbullying
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   Cyberbullying is one of the major electronic problems, and it is not a new phenomenon. It was present in the traditional form before the emergence of social networks, and cyberbullying has many consequences, including emotional and physiological states such as depression and anxiety. Given the prevalence of this phenomenon and the importance of the topic in society and its negative impact on all age groups, especially adolescents, this work aims to build a model that detects cyberbullying in the comments on social media (Twitter) written in the Arabic language using Extreme Gradient Boosting (XGBoost) and Random Forest methods in building the models. After a series of pre-processing, we found that the accuracy of classification of t

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Publication Date
Wed Jan 16 2019
Journal Name
Applied Physics A
Detecting the thermoplasmonic effect using ellipsometry parameters for self-assembled gold nanoparticles within a polydimethylsiloxane matrix
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Publication Date
Thu Jul 20 2023
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Comparison of Some Numerical Simulation Techniques for COVID-19 Model in Iraq
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The aim of our study is to solve a nonlinear epidemic model, which is the COVID-19 epidemic model in Iraq, through the application of initial value problems in the current study. The model has been presented as a system of ordinary differential equations that has parameters that change with time. Two numerical simulation methods are proposed to solve this model as suitable methods for solving systems whose coefficients change over time. These methods are the Mean Monte Carlo Runge-Kutta method (MMC_RK) and the Mean Latin Hypercube Runge-Kutta method (MLH_RK). The results of numerical simulation methods are compared with the results of the numerical Runge-Kutta 4th order method (RK4) from 2021 to 2025 using the absolute error, which prove

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Publication Date
Sun Oct 30 2022
Journal Name
Iraqi Journal Of Science
Climatic Water Balance Comparison for Selected areas in The Middle of Iraq
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     The climate parameters annual rainfall and average mean temperature are investigated from 2000 to 2019 for Kut, Hilla and Iskandaryia. Evidence of climate change is noticed by decreasing the mean annual rainfall and relative humidity with an increase in the annual mean temperature. The climate water balance has been calculated. Due to high temperature, increased evaporation, and low precipitation rates, there was a large water deficit. The total water surplus in the Kut area is 32.86 mm from November to February, and in  Hilla and Iskandaryia is 20.4 and 27.8 mm from December to February, respectively. The climate classification for the three stations was semi-dry to dry climates. The region has a significant water deficit of u

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Publication Date
Fri Jun 30 2023
Journal Name
Iraqi Journal Of Science
Review on Vision Based Real Time Fingertip Detection Approaches
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    Computer vision is an emerging area with a huge number of applications. Identification of the fingertip is one of the major parts of those areas. Augmented reality and virtual reality are the most recent technological advancements that use fingertip identification. The interaction between computers and humans can be performed easily by this technique. Virtual reality, robotics, smart gaming are the main application domains of these fingertip detection techniques. Gesture recognition is one of the most fascinating fields of fingertip detection. Gestures are the easiest and productive methods of communication with regard to collaboration with the computer. This analysis examines the different studies done in the field of

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