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Development of an Optimized Botnet Detection Framework based on Filters of Features and Machine Learning Classifiers using CICIDS2017 Dataset
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Abstract<p>Botnet is a malicious activity that tries to disrupt traffic of service in a server or network and causes great harm to the network. In modern years, Botnets became one of the threads that constantly evolving. IDS (intrusion detection system) is one type of solutions used to detect anomalies of networks and played an increasing role in the computer security and information systems. It follows different events in computer to decide to occur an intrusion or not, and it used to build a strategic decision for security purposes. The current paper <italic>suggests</italic> a hybrid detection Botnet model using machine learning approach, performed and analyzed to detect Botnet attacks using CICIDS2017 dataset. The proposed model designed based on two types of filters to the botnet features; Correlation Attribute Eval and Principal Component deployed to reduce the dataset dimensions and to decrease the time complexity of the botnet detection process. The detection enhancement achieved by reducing the features of the dataset from 85 to 9. The training stage of classifiers is developed and compared based on six classifiers called (Random Forest, IBK, JRip, Multilayer Perceptron, Naive Bayes and OneR) evaluated to accomplish an optimized detection model. The performance and results of the proposed framework are validated using well-known metrics such as Accuracy (ACC), Precision (Pr), Recall (Rc) and F-Measure (F1). The consequence is that the combination of Correlation Attribute Eval (filter) with JRip (classifier) together can satisfy significant improvement in the Botnet detection process using CICIDS2017 dataset.</p>
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Publication Date
Tue Mar 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
Developing and Sustaining a Multilevel Competitive Learning Organization – A Behavioral and Cognitive Approach
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To maintain a sustained competitive position in the contemporary environment of  knowledge  economy,  organizations  as an open social systems must have an ability to learn and know  how to adapt to rapid changes  in a proper fashion so that organizational objectives will be achieved efficiently and effectively.  A multilevel approach is adopted proposing that organizational learning suffers from the lack of interest about the strategic competitive performance of the organization. This remains implicit almost in all models of organizational learning and there is little focus on how learning organizations achieve sustainable competitive advantage . A dynamic model that captures t

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Publication Date
Thu Oct 01 2020
Journal Name
Biochemical & Cellular Archives
STUDY ON ABILITY OF PROTEUS MIRABILIS ISOLATED FROM BURNS AND WOUNDS INFECTIONS TO BIOFILM FORMATION AND DETECTION URE C GENE RESPONSIBLE FOR PRODUCE UREASE ENZYME
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A total of 200 clinical samples included Burns and Wounds infections were collected from Baghdad Governorate. Results showed that rate all isolates of P. mirabilis was 31(15.5%) and rate of Burns infections was 14 (45%) and rate of wounds infection 17 (55%). Where was diagnostic based on conventional biochemical tests and confirmed by the Vitek-2 Compact system and the specific primer of the16SrRNA gene, the ability of bacterial isolates to biofilm formation to be studied. It's considered an important virulence factor in Incidence of diseases and play important role in increasing resistance to antibiotic of encased bacteria, by two methods Congo Red Agar method and Microtiter Plate method. The Congo Red Agar method showed that most isolates

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Publication Date
Sun Jan 01 2023
Journal Name
Dental Hypotheses
Effect of Amoxicillin and Azithromycin Suspensions on Microhardness of Sliver Reinforced and Nano Resin-Modified Glass Ionomers: An In Vitro Study
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We aimed to examine the effect of amoxicillin and azithromycin suspensions on the microhardness of sliver-reinforced glass ionomer and nano-resin modified glass ionomer (GI). Method: Thirty discs (2mm height x 4mm diameter) of each type of GI were prepared, which were randomly assigned to amoxicillin, azithromycin, and artificial saliva groups. Microhardness was evaluated by Vickers hardness test before and after three immersion cycles. Results: The overall model (P < 0.001), before/after intervention (P < 0.001), intervention group (type of antibiotic) (P=0.013), and type of glass ionomer (P < 0.001) showed significant differences among study groups (P < 0.001). Post hoc test showed only non-significant before/after difference for Azithrom

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Publication Date
Fri Mar 31 2023
Journal Name
Sport Tk-revista Euroamericana De Ciencias Del Deporte
Effect of an exercise program on physical-kinetic intelligence and the skills of dribbling and shooting in basketball among female students
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The current research aimed to study the effect of an exercise program on physical-kinetic intelligence and the skills of dribbling and shooting in basketball among female students. The research community was composed of 102 female students in the second stage of the Physical Education and Sports Sciences College for Girls of Baghdad University, in the academic year 2021-2022. A total of 40 female students were the sample of the study: 20 female students in the control group and 20 female students in the experimental group. After the implementation of the exercise program, there were significant improvements from pre-tests to post tests in the two groups (control and experimental groups), in physical-kinetic intelligenc

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Publication Date
Thu Aug 01 2019
Journal Name
Ieee Photonics Journal
Di-Iron Trioxide Hydrate-Multi-Walled Carbon Nanotube Nanocomposite for Arsenite Detection Using Surface Plasmon Resonance Technique
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Publication Date
Sun Nov 19 2017
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
Image Compression based on Fixed Predictor Multiresolution Thresholding of Linear Polynomial Nearlossless Techniques
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Image compression is a serious issue in computer storage and transmission,  that simply makes efficient use of redundancy embedded within an image itself; in addition, it may exploit human vision or perception limitations to reduce the imperceivable information Polynomial coding is a modern image compression technique based on modelling concept to remove the spatial redundancy embedded within the image effectively that composed of two parts, the  mathematical model and the residual. In this paper, two stages proposed technqies adopted, that starts by utilizing the lossy predictor model along with multiresolution base and thresholding techniques corresponding to first stage. Latter by incorporating the near lossless com

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Publication Date
Mon May 31 2021
Journal Name
Iraqi Journal Of Science
Simultaneous Approximation by a New Sequence of Integral Type Based on Two Parameters
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This paper introduces a generalization sequence of positive and linear operators of integral type based on two parameters to improve the order of approximation. First, the simultaneous approximation is studied and a Voronovskaja-type asymptotic formula is introduced. Next, an error of the estimation in the simultaneous approximation is found. Finally, a numerical example to approximate a test function and its first derivative of this function is given for some values of the parameters. 

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Publication Date
Sat Jun 27 2020
Journal Name
Iraqi Journal Of Science
Extractive Multi-Document Summarization Model Based On Different Integrations of Double Similarity Measures
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Currently, the prominence of automatic multi document summarization task belongs to the information rapid increasing on the Internet. Automatic document summarization technology is progressing and may offer a solution to the problem of information overload. 

Automatic text summarization system has the challenge of producing a high quality summary. In this study, the design of generic text summarization model based on sentence extraction has been redirected into a more semantic measure reflecting individually the two significant objectives: content coverage and diversity when generating summaries from multiple documents as an explicit optimization model. The proposed two models have been then coupled and def

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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Improve Akaike’s Information Criterion Estimation Based on Denoising of Quadrature Mirror Filter Bank
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Akaike’s Information Criterion (AIC) is a popular method for estimation the number of sources impinging on an array of sensors, which is a problem of great interest in several applications. The performance of AIC degrades under low Signal-to-Noise Ratio (SNR). This paper is concerned with the development and application of quadrature mirror filters (QMF) for improving the performance of AIC. A new system is proposed to estimate the number of sources by applying AIC to the outputs of filter bank consisting quadrature mirror filters (QMF). The proposed system can estimate the number of sources under low signal-to-noise ratio (SNR).

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Publication Date
Mon Apr 01 2019
Journal Name
Journal Of Engineering
Design of New Hybrid Neural Controller for Nonlinear CSTR System based on Identification
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This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

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