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Performance Evaluation of Intrusion Detection System using Selected Features and Machine Learning Classifiers
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Some of the main challenges in developing an effective network-based intrusion detection system (IDS) include analyzing large network traffic volumes and realizing the decision boundaries between normal and abnormal behaviors. Deploying feature selection together with efficient classifiers in the detection system can overcome these problems.  Feature selection finds the most relevant features, thus reduces the dimensionality and complexity to analyze the network traffic.  Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance.  In this study, two different sets of selected features have been adopted to train four machine-learning based classifiers.  The two sets of selected features are based on Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) approach respectively.  These evolutionary-based algorithms are known to be effective in solving optimization problems.  The classifiers used in this study are Naïve Bayes, k-Nearest Neighbor, Decision Tree and Support Vector Machine that have been trained and tested using the NSL-KDD dataset. The performance of the abovementioned classifiers using different features values was evaluated.  The experimental results indicate that the detection accuracy improves by approximately 1.55% when implemented using the PSO-based selected features than that of using GA-based selected features.  The Decision Tree classifier that was trained with PSO-based selected features outperformed other classifiers with accuracy, precision, recall, and f-score result of 99.38%, 99.36%, 99.32%, and 99.34% respectively.  The results show that using optimal features coupling with a good classifier in a detection system able to reduce the classifier model building time, reduce the computational burden to analyze data, and consequently attain high detection rate.

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Publication Date
Fri May 15 2009
Journal Name
Journal Of Planner And Development
Preservation of heritage markets within an integrated framework to preserve the urban heritage in the historical centers of cities (selected models and experiments)
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This research discusses the rehabilitation of heritage markets in the historical centers of Islamic Arab cities and their use in the field of cultural tourism as one of the most important tourist attractions and the subsequent revival of the national economy in addition to preserving the urban heritage as these markets part of the historical centers of cities. The research also discusses the preservation of the continuity of heritage markets as a product of cultural heritage value within an integrated framework to preserve the urban heritage in the historic centers of cities. The study then reviews a number of experiences of Arab and Islamic countries in the field of preserving and rehabilitating heritage markets, which qualify them to b

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Publication Date
Mon Apr 03 2023
Journal Name
Journal Of Educational And Psychological Researches
The Role of Digital Repositories in Developing Teacher Performance in the Primary Stage
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Abstract

Digital repositories are considered one of the integrated collaborative educational environments that help every researcher interested in developing the education and educational process. The learning resources provided by the repositories are suitable for every researcher, so digital information can be stored and exchanged by ensuring the participation and cooperation of researchers, teachers, and those who are interested, as well as curricula experts, teachers, and students, to exchange each other’s experiences in constantly updating that information as a reason for developing their performance in education. This reveals the importance of the role of educational digital institutions by providing and

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Publication Date
Tue May 01 2012
Journal Name
Iraqi Journal Of Physics
Early detection of breast cancer mass lesions by mammogram segmentation images based on texture features
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Mammography is at present one of the available method for early detection of masses or abnormalities which is related to breast cancer. The most common abnormalities that may indicate breast cancer are masses and calcifications. The challenge lies in early and accurate detection to overcome the development of breast cancer that affects more and more women throughout the world. Breast cancer is diagnosed at advanced stages with the help of the digital mammogram images. Masses appear in a mammogram as fine, granular clusters, which are often difficult to identify in a raw mammogram. The incidence of breast cancer in women has increased significantly in recent years.
This paper proposes a computer aided diagnostic system for the extracti

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Publication Date
Mon Jun 01 2009
Journal Name
Journal Of Economics And Administrative Sciences
Evaluation of performance of some industrial companies In the default reference comparison method Field study in the public companies of cement (Iraqi - North - South
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The increasing Global Competitive and the continuous improvement in information technology has led the way to the development of the modern systems and using modern techniques. One of these techniques is benchmarking style and Total Quality Management all of them are used to improve the production process and target rid from the losts on the other side.

The Benchmarking style has become a very important for all the industrial systems and the serving systems as well. And an instrument to improve their performance specially those which are suffering from the highness of the costs or waste in time on the other side.

This study aims to depend on virtual Benchmarking style in the eval

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Publication Date
Mon Sep 01 2014
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Electronic payments system and its relationship to the effectiveness of commercial banks: Applied Research
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      That the electronic payments system plays an important role in the effectiveness of commercial banks by attracting domestic or foreign investors, especially in the banking sector , It must keep abreast of global developments and technology in the field of banking that lead to the effectiveness of the bank by providing modern banking services and good customer service that improves the reputation of the bank, as well as develop its activities and promotes economic development at the country level , The technological progress of the bank will increase the speed of conducting banking operations, accuracy and safer , here should be laws and regulations related to electronic payment systems keep pace with the la

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Publication Date
Mon Jun 01 2009
Journal Name
Journal Of Economics And Administrative Sciences
Performance Series Performance Metrics (*) A case study in the General Company for Cotton Industries
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The problem of the research is focused on importance limited of Iraq industrial companies in application of scientific measurements of supply chains performance,  The research sought to achieve a group of goals, the most important are , identifying the strengths and weaknesses in the reality of supply chain in General Company for Cotton Industries, The data and information required are gathered from the dependence company, records through the field observations and personal interviews, the research used some quantitative indicators to measure of supply chain performance, The research reached to many conclusions , the most outstanding among them is the existence of a strong inverse correlatio

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Publication Date
Sun Dec 01 2024
Journal Name
Al-qadisiyah Journal For Agriculture Sciences
Effect of Holes Diameter and Speed of Die on the Performance of Machine and Feed Pellet Quality
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The aim of this study to evaluate the effects of die holes diameter and speed of die on the performance of machine and feed pellet quality. Machine productivity (Kg.h-1), consumed power (kW), pellet durability (%) and pellet bulk density (g.cm-3) was studied. The study factors consisted of three diameter of die holes (3, 4, and 5 mm), and three speeds die (280, 300, and 320 rpm). Results showed with increasing of die holes diameter from 3 to 4 and to 5 mm give a significant increase in machine productivity, while consumed power, pellet durability and pellet bulk density a significant decreased. By increasing the die speed, from 280 to 300 then to 320 rpm, the machine productivity increased significantly, while consumed power, pellet durabil

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
Assessment of surface water quality using statistical analysis methods: Orontes River (Case study)
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The study investigates the water quality of the Orontes River, which is considered one of the important water recourses in Syria, as it is used for drinking, irrigation, swimming and industrial needs. A database of 660 measurements for 13 parameters concentrations used, were taken from 11 monitoring points distributed along the Orontes River for a period of five years from 2015-2019, and to study the correlation between parameters and their impact on water quality, statistical analysis was applied using (SPSS) program. Cluster analysis was applied in order to classify the pollution areas along the river, and two groups were given: (low pollution - high pollution), where the areas were classified according to the sources of pollution to w

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Publication Date
Sun Mar 31 2024
Journal Name
Iraqi Geological Journal
Permeability Prediction and Facies Distribution for Yamama Reservoir in Faihaa Oil Field: Role of Machine Learning and Cluster Analysis Approach
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Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F

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Publication Date
Fri Feb 28 2025
Journal Name
Energies
Synergizing Machine Learning and Physical Models for Enhanced Gas Production Forecasting: A Comparative Study of Short- and Long-Term Feasibility
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Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m

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