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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
Tue Dec 12 2017
Journal Name
Al-khwarizmi Engineering Journal
Model Reference Adaptive Control based on a Self-Recurrent Wavelet Neural Network Utilizing Micro Artificial Immune Systems
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Abstract 

This paper presents an intelligent model reference adaptive control (MRAC) utilizing a self-recurrent wavelet neural network (SRWNN) to control nonlinear systems. The proposed SRWNN is an improved version of a previously reported wavelet neural network (WNN). In particular, this improvement was achieved by adopting two modifications to the original WNN structure. These modifications include, firstly, the utilization of a specific initialization phase to improve the convergence to the optimal weight values, and secondly, the inclusion of self-feedback weights to the wavelons of the wavelet layer. Furthermore, an on-line training procedure was proposed to enhance the control per

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Publication Date
Wed Dec 01 2021
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Some Semi-parametric Methods in Partial Linear Single-Index Model
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The research dealt with a comparative study between some semi-parametric estimation methods to the Partial linear Single Index Model using simulation. There are two approaches to model estimation two-stage procedure and MADE to estimate this model. Simulations were used to study the finite sample performance of estimating methods based on different Single Index models, error variances, and different sample sizes , and the mean average squared errors were used as a comparison criterion between the methods were used. The results showed a preference for the two-stage procedure depending on all the cases that were used

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Publication Date
Tue Oct 11 2022
Journal Name
College Of Islamic Sciences
Hanbali's approach to building long and short travel provisions with issues attached to their provisions
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The problem with research lies in hiding the Hanbali approach in building long and short travel provisions, as well as hiding some provisions relating to short travel that are not provided for by the jurists of Hanbali (in their books).

The research aims to demonstrate the approach and standards on which they based the long and short travel provisions, as well as to reflect the provisions of some of the issues that are silent on long and short travel, with evidence and significance.

The research included a preface and two researches, the researcher in the preface talked about the reality of long and short travel, in the first research on the approach of ha

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Publication Date
Mon Feb 04 2019
Journal Name
Journal Of The College Of Education For Women
Classification of Rural Road Network in Al-Najaf Governorate
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This study has dealt with, the issue of classification of rural road network , in addition to prepare a suggested for the classification for this network in Iraq , this classification account , the specifications and characteristics of rural roads, population, and the range taking of settlements , then this classification was applied on the rural road network in the Najaf province there are four categories of classification ,the first is major arterial rural roads divided into two major arterial and minor arterial roads , while the second category collected roads which was divided into minor arterial roads and main collected roads. The third category was represented by Local Roads , it has been divided into paved roads and unpaved, the f

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Intelligent Systems
A study on predicting crime rates through machine learning and data mining using text
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Abstract<p>Crime is a threat to any nation’s security administration and jurisdiction. Therefore, crime analysis becomes increasingly important because it assigns the time and place based on the collected spatial and temporal data. However, old techniques, such as paperwork, investigative judges, and statistical analysis, are not efficient enough to predict the accurate time and location where the crime had taken place. But when machine learning and data mining methods were deployed in crime analysis, crime analysis and predication accuracy increased dramatically. In this study, various types of criminal analysis and prediction using several machine learning and data mining techniques, based o</p> ... Show More
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Publication Date
Mon Jan 02 2017
Journal Name
European Journal Of Scientific Research
Fast approach for arabic text encryption using genetic algorithm
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As s widely use of exchanging private information in various communication applications, the issue to secure it became top urgent. In this research, a new approach to encrypt text message based on genetic algorithm operators has been proposed. The proposed approach follows a new algorithm of generating 8 bit chromosome to encrypt plain text after selecting randomly crossover point. The resulted child code is flipped by one bit using mutation operation. Two simulations are conducted to evaluate the performance of the proposed approach including execution time of encryption/decryption and throughput computations. Simulations results prove the robustness of the proposed approach to produce better performance for all evaluation metrics with res

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Publication Date
Thu Jun 01 2023
Journal Name
Baghdad Science Journal
Some Subclasses of Univalent and Bi-Univalent Functions Related to K-Fibonacci Numbers and Modified Sigmoid Function
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            This paper is interested in certain  subclasses of univalent and bi-univalent functions concerning  to shell- like curves connected with k-Fibonacci numbers involving modified Sigmoid activation function θ(t)=2/(1+e^(-t) ) ,t ≥0 in unit disk |z|<1 . For estimating of the initial coefficients |c_2 | , |c_3 |, Fekete-Szego ̈ inequality and the  second Hankel determinant have been investigated for the functions in our classes. 

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Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
Diagnosing COVID-19 Infection in Chest X-Ray Images Using Neural Network
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With its rapid spread, the coronavirus infection shocked the world and had a huge effect on billions of peoples' lives. The problem is to find a safe method to diagnose the infections with fewer casualties. It has been shown that X-Ray images are an important method for the identification, quantification, and monitoring of diseases. Deep learning algorithms can be utilized to help analyze potentially huge numbers of X-Ray examinations. This research conducted a retrospective multi-test analysis system to detect suspicious COVID-19 performance, and use of chest X-Ray features to assess the progress of the illness in each patient, resulting in a "corona score." where the results were satisfactory compared to the benchmarked techniques.  T

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Publication Date
Thu Mar 30 2023
Journal Name
Journal Of Economics And Administrative Sciences
An Artificial Intelligence Algorithm to Optimize the Classification of the Hepatitis Type
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Hepatitis is one of the diseases that has become more developed in recent years in terms of the high number of infections. Hepatitis causes inflammation that destroys liver cells, and it occurs as a result of viruses, bacteria, blood transfusions, and others. There are five types of hepatitis viruses, which are (A, B, C, D, E) according to their severity. The disease varies by type. Accurate and early diagnosis is the best way to prevent disease, as it allows infected people to take preventive steps so that they do not transmit the difference to other people, and diagnosis using artificial intelligence gives an accurate and rapid diagnostic result. Where the analytical method of the data relied on the radial basis network to diagnose the

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Publication Date
Fri Apr 12 2019
Journal Name
Journal Of Economics And Administrative Sciences
Split and Merge Regions of Satellite Images using the Non-Hierarchical Algorithm of Cluster Analysis
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يعد التقطيع الصوري من الاهداف الرئيسة والضرورية في المعالجات الصورية للصور الرقمية، فهو يسعى الى تجزئة الصور المدروسة الى مناطق متعددة اكثر نفعاً تلخص فيها المناطق ذات الافادة لصور الاقمار الصناعية، وهي صور متعددة الاطياف ومجهزة من الاقمار الصناعية باستخدام مبدأ الاستشعار عن بعد والذي اصبح من المفاهيم المهمة التي تُعتمد تطبيقاته في اغلب ضروريات الحياة اليومية، وخاصة بعد التطورات المتسارعة التي شهد

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