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bsj-4155
A Semi-Supervised Machine Learning Approach Using K-Means Algorithm to Prevent Burst Header Packet Flooding Attack in Optical Burst Switching Network
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Optical burst switching (OBS) network is a new generation optical communication technology. In an OBS network, an edge node first sends a control packet, called burst header packet (BHP) which reserves the necessary resources for the upcoming data burst (DB). Once the reservation is complete, the DB starts travelling to its destination through the reserved path. A notable attack on OBS network is BHP flooding attack where an edge node sends BHPs to reserve resources, but never actually sends the associated DB. As a result the reserved resources are wasted and when this happen in sufficiently large scale, a denial of service (DoS) may take place. In this study, we propose a semi-supervised machine learning approach using k-means algorithm, to detect malicious nodes in an OBS network. The proposed semi-supervised model was trained and validated with small amount data from a selected dataset. Experiments show that the model can classify the nodes into either behaving or not-behaving classes with 90% accuracy when trained with just 20% of data. When the nodes are classified into behaving, not-behaving and potentially not-behaving classes, the model shows 65.15% and 71.84% accuracy if trained with 20% and 30% of data respectively. Comparison with some notable works revealed that the proposed model outperforms them in many respects.

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Publication Date
Wed Dec 18 2019
Journal Name
Baghdad Science Journal
A Modified Approach by Using Prediction to Build a Best Threshold in ARX Model with Practical Application
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The proposal of nonlinear models is one of the most important methods in time series analysis, which has a wide potential for predicting various phenomena, including physical, engineering and economic, by studying the characteristics of random disturbances in order to arrive at accurate predictions.

In this, the autoregressive model with exogenous variable was built using a threshold as the first method, using two proposed approaches that were used to determine the best cutting point of [the predictability forward (forecasting) and the predictability in the time series (prediction), through the threshold point indicator]. B-J seasonal models are used as a second method based on the principle of the two proposed approaches in dete

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Publication Date
Sat Jun 01 2019
Journal Name
Journal Of Engineering And Applied Sciences
Enhancing LSB algorithm against brute-force attack using ASCII mapping technique
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Publication Date
Wed Apr 16 2025
Journal Name
International Journal Of Engineering Pedagogy (ijep)
Utilizing Machine Learning Techniques to Predict University Students' Digital Competence
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Given the importance of possessing the digital competence (DC) required by the technological age, whether for teachers or students and even communities and governments, educational institutions in most countries have sought to benefit from modern technologies brought about by the technological revolution in developing learning and teaching and using modern technologies in providing educational services to learners. Since university students will have the doors to work opened in all fields, the research aims to know their level of DC in artificial intelligence (AI) applications and systems utilizing machine learning (ML) techniques. The descriptive approach was used, as the research community consisted of students from the University

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Publication Date
Sat Oct 25 2025
Journal Name
Iet Networks
An Effective Technique of Zero‐Day Attack Detection in the Internet of Things Network Based on the Conventional Spike Neural Network Learning Method
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ABSTRACT<p>The fast evolution of cyberattacks in the Internet of Things (IoT) area, presents new security challenges concerning Zero Day (ZD) attacks, due to the growth of both numbers and the diversity of new cyberattacks. Furthermore, Intrusion Detection System (IDSs) relying on a dataset of historical or signature‐based datasets often perform poorly in ZD detection. A new technique for detecting zero‐day (ZD) attacks in IoT‐based Conventional Spiking Neural Networks (CSNN), termed ZD‐CSNN, is proposed. The model comprises three key levels: (1) Data Pre‐processing, in this level a thorough cleaning process is applied to the CIC IoT Dataset 2023, which contains both malicious and t</p> ... Show More
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Publication Date
Mon May 27 2019
Journal Name
Al-khwarizmi Engineering Journal
Prediction of Process Parameters That Affecting on Surface Roughness in Multi-Point Forming Process Using ANOVA Algorithm
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Multipoint forming process is an engineering concept which means that the working surface of the punch and die is produced as hemispherical ends of individual active elements (called pins), where each pin can be independently, vertically displaced using a geometrically reconfigurable die. Several different products can be made without changing tools saved precious production time. Also, the manufacturing of very expensive rigid dies is reduced, and a lot of expenses are saved. But the most important aspects of using such types of equipment are the flexibility of the tooling. This paper presents an experimental investigation of the effect of three main parameters which are blank holder, rubber thickness and forming speed th

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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Using the artificial TABU algorithm to estimate the semi-parametric regression function with measurement errors
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Artificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing artificial TABU algorithm to find the best estimate of the semi-parametric regression function with measurement errors in the explanatory variables and the dependent variable, where measurement errors appear frequently in fields such as sport, chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement.

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Publication Date
Thu Feb 07 2019
Journal Name
Journal Of The College Of Education For Women
Build and Implemented Learning Package for Prolog Programming Language Using Visual Basic.Net 2010
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E-Learning packages are content and instructional methods delivered on a computer
(whether on the Internet, or an intranet), and designed to build knowledge and skills related to
individual or organizational goals. This definition addresses: The what: Training delivered
in digital form. The how: By content and instructional methods, to help learn the content.
The why: Improve organizational performance by building job-relevant knowledge and
skills in workers.
This paper has been designed and implemented a learning package for Prolog Programming
Language. This is done by using Visual Basic.Net programming language 2010 in
conjunction with the Microsoft Office Access 2007. Also this package introduces several
fac

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Nurse Scheduling Problem Using Hybrid Simulated Annealing Algorithm
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Nurse scheduling problem is one of combinatorial optimization problems and it is one of NP-Hard problems which is difficult to be solved as optimal solution. In this paper, we had created an proposed algorithm which it is hybrid simulated annealing algorithm to solve nurse scheduling problem, developed the simulated annealing algorithm and Genetic algorithm. We can note that the proposed algorithm (Hybrid simulated Annealing Algorithm(GS-h)) is the best method among other methods which it is used in this paper because it satisfied minimum average of the total cost and maximum number of Solved , Best and Optimal problems. So we can note that the ratios of the optimal solution are 77% for the proposed algorithm(GS-h), 28.75% for Si

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Publication Date
Sun Mar 26 2023
Journal Name
Wasit Journal Of Pure Sciences
Covid-19 Prediction using Machine Learning Methods: An Article Review
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The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

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Publication Date
Sun Oct 03 2010
Journal Name
Journal Of Educational And Psychological Researches
The Effect of Applying K-W-L Technique on Teaching ESP Students
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         Over the last few decades, many instructors have been trying all kinds of teaching methods, but without benefit. Nevertheless, in the 1986, a new technique is appeared which called K-W-L technique, it  is specified for reading comprehension passages because reading  skill is not easy matter for students for specific purposes (ESP).therefore, the K-W-L technique is a good one for thinking and experiences. To fulfill the aims and verify the hypothesis which reads as follows" it is hypothesized that there are no significant differences between the achievements of students who are taught according to K-W-L technique and those who are taught according to the traditional method

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