Preferred Language
Articles
/
Nxazs4sBVTCNdQwCZdeM
Performance Evaluation of SDN DDoS Attack Detection and Mitigation Based Random Forest and K-Nearest Neighbors Machine Learning Algorithms
...Show More Authors

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.

Scopus Crossref
View Publication
Publication Date
Wed Jan 02 2019
Journal Name
Journal Of Educational And Psychological Researches
Evaluation Tasks of Performance Quality of the University Students According to the Developmental Environment
...Show More Authors

 Education is a process of learning and education at the same time. As the conditions of modern life necessitate every person to keep learning, education has become a necessity to meet life needs. The society today is concerned with the educational process and aims to live up the expectations. Since education is an integral part of education and its means, it has become as a mean to achieve its purposes. The educational environment was a traditional environment limited to specific inputs, possibilities and stimulus of both teacher and student. Due to the latest advancement, the educational environment has been expanded to become a rich, with strong connections. It has expanded to encompass the entire global environment. The current

... Show More
View Publication Preview PDF
Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Deep Learning-based Predictive Model of mRNA Vaccine Deterioration: An Analysis of the Stanford COVID-19 mRNA Vaccine Dataset
...Show More Authors

The emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA

... Show More
View Publication Preview PDF
Scopus (10)
Crossref (6)
Scopus Crossref
Publication Date
Sun Oct 31 2021
Journal Name
Eastern-european Journal Of Enterprise Technologies
Distinguishing of different tissue types using K-Means clustering of color segmentation
...Show More Authors

Millions of lives might be saved if stained tissues could be detected quickly. Image classification algorithms may be used to detect the shape of cancerous cells, which is crucial in determining the severity of the disease. With the rapid advancement of digital technology, digital images now play a critical role in the current day, with rapid applications in the medical and visualization fields. Tissue segmentation in whole-slide photographs is a crucial task in digital pathology, as it is necessary for fast and accurate computer-aided diagnoses. When a tissue picture is stained with eosin and hematoxylin, precise tissue segmentation is especially important for a successful diagnosis. This kind of staining aids pathologists in disti

... Show More
View Publication Preview PDF
Scopus (3)
Crossref (1)
Scopus Crossref
Publication Date
Fri Mar 01 2024
Journal Name
Iaes International Journal Of Artificial Intelligence (ij-ai)
Analyzing the behavior of different classification algorithms in diabetes prediction
...Show More Authors

<span lang="EN-US">Diabetes is one of the deadliest diseases in the world that can lead to stroke, blindness, organ failure, and amputation of lower limbs. Researches state that diabetes can be controlled if it is detected at an early stage. Scientists are becoming more interested in classification algorithms in diagnosing diseases. In this study, we have analyzed the performance of five classification algorithms namely naïve Bayes, support vector machine, multi layer perceptron artificial neural network, decision tree, and random forest using diabetes dataset that contains the information of 2000 female patients. Various metrics were applied in evaluating the performance of the classifiers such as precision, area under the c

... Show More
View Publication
Scopus (2)
Crossref (1)
Scopus Crossref
Publication Date
Tue Mar 01 2011
Journal Name
Al-khwarizmi Engineering Journal
Noise Removal of ECG Signal Using Recursive Least Square Algorithms
...Show More Authors

This paper shows an approach for Electromyography (ECG) signal processing based on linear and nonlinear adaptive filtering using Recursive Least Square (RLS) algorithm to remove two kinds of noise that affected the ECG signal. These are the High Frequency Noise (HFN) and Low Frequency Noise (LFN). Simulation is performed in Matlab. The ECG, HFN and LFN signals used in this study were downloaded from ftp://ftp.ieee.org/uploads/press/rangayyan/, and then the filtering process was obtained by using adaptive finite impulse response (FIR) that illustrated better results than infinite impulse response (IIR) filters did.

View Publication Preview PDF
Publication Date
Sat Dec 31 2022
Journal Name
Mathematical Modelling Of Engineering Problems
Investigation of Energy Efficient Clustering Algorithms in WSNs: A Review
...Show More Authors

In recent years, Wireless Sensor Networks (WSNs) are attracting more attention in many fields as they are extensively used in a wide range of applications, such as environment monitoring, the Internet of Things, industrial operation control, electric distribution, and the oil industry. One of the major concerns in these networks is the limited energy sources. Clustering and routing algorithms represent one of the critical issues that directly contribute to power consumption in WSNs. Therefore, optimization techniques and routing protocols for such networks have to be studied and developed. This paper focuses on the most recent studies and algorithms that handle energy-efficiency clustering and routing in WSNs. In addition, the prime

... Show More
View Publication
Scopus (9)
Crossref (2)
Scopus Crossref
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
...Show More Authors

Scopus (3)
Crossref (2)
Scopus Crossref
Publication Date
Thu May 30 2024
Journal Name
Journal Of Interdisciplinary Mathematics
Laplace transform-adomian decomposition approach for solving random partial differential equations
...Show More Authors

Market share is a major indication of business success. Understanding the impact of numerous economic factors on market share is critical to a company’s success. In this study, we examine the market shares of two manufacturers in a duopoly economy and present an optimal pricing approach for increasing a company’s market share. We create two numerical models based on ordinary differential equations to investigate market success. The first model takes into account quantity demand and investment in R&D, whereas the second model investigates a more realistic relationship between quantity demand and pricing.

Scopus (3)
Scopus
Publication Date
Mon Jan 01 2007
Journal Name
Iraqi Journal Of Agricultural Sciences
EVALUATION OF PARTIAL AND COMPLETE REPLACEMENT OF SOYBEAN MEAL BY FERMENTEED BROAD BEAN IN THE DIET OX THE PRODI ICTIVR PERFORMANCE OF BROILERS
...Show More Authors

AAA AL-NUAIMY, MH ABDLL-ABASS, Iraqi Journal of Agricultural Sciences, 2007

View Publication
Publication Date
Fri Jan 15 2016
Journal Name
The Iraqi Journal For Mechanical And Material Engineering
MACHINE VISION APPLICATION IN MANUFACTURING: INSPECTION OF DIMENSIONS
...Show More Authors

Computers have been used for numerous applications involving the automatic or semiautomatic recognition of patterns in image. Advanced manufacturing system requires automated inspection and test method to increase production and yield best quality of product. Methods are available today is machine vision. Machine vision systems are widely used today in the manufacturing industry for inspection and sorting application. The objective of this paper is to apply machine vision technology for measuring geometric dimension of an automotive part. Vision system usually requires reprogramming or parameterization of software when it has to be configured for a part or product. A web camera used to capture an image of an automotive part that has been ch

... Show More
Preview PDF