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Network Traffic Prediction Based on Boosting Learning

Classification of network traffic is an important topic for network management, traffic routing, safe traffic discrimination, and better service delivery. Traffic examination is the entire process of examining traffic data, from intercepting traffic data to discovering patterns, relationships, misconfigurations, and anomalies in a network. Between them, traffic classification is a sub-domain of this field, the purpose of which is to classify network traffic into predefined classes such as usual or abnormal traffic and application type. Most Internet applications encrypt data during traffic, and classifying encrypted data during traffic is not possible with traditional methods. Statistical and intelligence methods can find and model traffic patterns that can be categorized based on statistical characteristics. These methods help determine the type of traffic and protect user privacy at the same time. To classify encrypted traffic from end to end, this paper proposes using (XGboost) algorithms, finding the highest parameters using Bayesian optimization, and comparing the proposed model with machine learning algorithms (Nearest Neighbor, Logistic Regression, Decision Trees, Naive Bayes, Multilayer Neural Networks) to classify traffic from end to end. Network traffic has two classifications: whether the traffic is encrypted or not, and the target application. The research results showed the possibility of classifying dual and multiple traffic with high accuracy. The proposed model has a higher classification accuracy than the other models, and finding the optimal parameters increases the model accuracy.

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Publication Date
Wed Jan 13 2021
Journal Name
Iraqi Journal Of Science
Cost Effective Open Educational Platform to Face the Challenge of Massification in Cadi Ayyad University

This work presents the UC@MOOC project as a pedagogical innovation to face the effects of massification that are making Moroccan universities endure many constraints for the past ten years, as well as other African universities. It aims, among its objectives, to cope with the massification factor and to overcome the language difficulties encountered by students. In this project, our top priority is to reduce academic failure then we will get to the point of responding to the training' needs. Courses are scripted and posted online which did not require many resources, so their production cost is relatively low. Audiovisual digital content also helps us to save time, and go to a hybrid teaching or even flipped classrooms in some cases. The

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Publication Date
Tue Nov 09 2021
Journal Name
Abu Dhabi International Petroleum Exhibition & Conference
Numerical Simulation of Gas Lift Optimization Using Artificial Intelligence for a Middle Eastern Oil Field
Abstract<p>Artificial lift techniques are a highly effective solution to aid the deterioration of the production especially for mature oil fields, gas lift is one of the oldest and most applied artificial lift methods especially for large oil fields, the gas that is required for injection is quite scarce and expensive resource, optimally allocating the injection rate in each well is a high importance task and not easily applicable. Conventional methods faced some major problems in solving this problem in a network with large number of wells, multi-constrains, multi-objectives, and limited amount of gas. This paper focuses on utilizing the Genetic Algorithm (GA) as a gas lift optimization algorit</p> ... Show More
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Publication Date
Thu Dec 01 2011
Journal Name
Iraqi Journal Of Physics
Multilayer Perceptron for analyzing satellite data

Different ANN architectures of MLP have been trained by BP and used to analyze Landsat TM images. Two different approaches have been applied for training: an ordinary approach (for one hidden layer M-H1-L & two hidden layers M-H1-H2-L) and one-against-all strategy (for one hidden layer (M-H1-1)xL, & two hidden layers (M-H1-H2-1)xL). Classification accuracy up to 90% has been achieved using one-against-all strategy with two hidden layers architecture. The performance of one-against-all approach is slightly better than the ordinary approach

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Publication Date
Sun Feb 17 2019
Journal Name
Iraqi Journal Of Physics
Classification of the galaxy Milky Way using variable precision rough sets technique

Astronomy image is regarded main source of information to discover outer space, therefore to know the basic contain for galaxy (Milky way), it was classified using Variable Precision Rough Sets technique to determine the different region within galaxy according different color in the image. From classified image we can determined the percentage for each class and then what is the percentage mean. In this technique a good classified image result and faster time required to done the classification process.

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Publication Date
Wed Dec 26 2018
Journal Name
Iraqi Journal Of Science
Extraction of Vacant Lands for Baghdad City Using Two Classification Methods of Very High Resolution Satellite Images

The use of remote sensing technologies was gained more attention due to an increasing need to collect data for the environmental changes. Satellite image classification is a relatively recent type of remote sensing uses satellite imagery to indicate many key environment characteristics. This study aims at classifying and extracting vacant lands from high resolution satellite images of Baghdad city by supervised Classification tool in ENVI 5.3 program. The classification accuracy was 15%, which can be regarded as fairly acceptable given the difficulty of differentiating vacant land surfaces from other surfaces such as roof tops of buildings.

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Publication Date
Mon May 08 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Web Ranking and Rating Server Usng Web Service

The amount of information on the web is growing rapidly and number of web sites
becomes huge, so set of web applications used to help user and give him some information
about these sites, especially in e- business, news and sites introduce services.
Since Web site is built by comparatively free description, it is difficult to perform
absolute evaluation. So, rating of Web site is performed from various viewpoints.
In this paper we proposed method for ranking and rating using the web service and java
script to motivation remote server and return some public information to the site user and
other private information to owner.

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Publication Date
Sat Sep 30 2023
Journal Name
Iraqi Journal Of Science
Link Analysis in Web Information Retrieval: a Survey

     The analysis of the hyperlink structure of the web has led to significant improvements in web information retrieval. This survey study evaluates and analyzes relevant research publications on link analysis in web information retrieval utilizing diverse methods. These factors include the research year, the aims of the research article, the algorithms utilized to complete their study, and the findings received after using the algorithms. The findings revealed that Page Rank, Weighted Page Rank, and Weighted Page Content Rank are extensively employed by academics to properly analyze hyperlinks in web information retrieval. Finally, this paper analyzes the previous studies.

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Publication Date
Sat May 02 2020
Journal Name
Plant Archives
MEASUREMENT OF ASBESTOS FIBERS CONCENTRATIONS IN SOME DENSE AREAS IN BAGHDAD, IRAQ, IN WINTER 2020

Asbestos is a hazard pollutant to human health, exposure to asbestos cause serious health effects and wide range of asbestos-related diseases such as asbestosis, lung cancer and malignant mesothelioma and it has been classified as carcinogen by the World Health Organization WHO which cause a carcinogenic effects. Fibers of asbestos are mainly released from friction product in brakes and clutch linings and from reinforce agent in the asbestos cement industry. The aim of this was to evaluate the levels of asbestos fibers in surroundings air of some dense traffic points in Baghdad, through winter 2020. Materials and Methods: Samples of airs was carried out by directing air flow to a mixed cellulose ester membrane filter mounted on an open face

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Publication Date
Thu Dec 01 2011
Journal Name
Journal Of Engineering
OPTIMAL DESIGN OF MODERATE THICK LAMINATED COMPOSITE PLATES UNDER STATIC CONSTRAINTS USING REAL CODING GENETIC ALGORITHM

The objective of the current research is to find an optimum design of hybrid laminated moderate thick composite plates with static constraint. The stacking sequence and ply angle is required for optimization to achieve minimum deflection for hybrid laminated composite plates consist of glass and carbon long fibers reinforcements that impeded in epoxy matrix with known plates dimension and loading. The analysis of plate is by adopting the first-order shear deformation theory and using Navier's solution with Genetic Algorithm to approach the current objective. A program written with MATLAB to find best stacking sequence and ply angles that give minimum deflection, and the results comparing with ANSYS.

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Publication Date
Wed Jul 29 2020
Journal Name
Iraqi Journal Of Science
Automatic Vehicles Detection, Classification and Counting Techniques / Survey

Vehicle detection (VD) plays a very essential role in Intelligent Transportation Systems (ITS) that have been intensively studied within the past years. The need for intelligent facilities expanded because the total number of vehicles is increasing rapidly in urban zones. Traffic monitoring is an important element in the intelligent transportation system, which involves the detection, classification, tracking, and counting of vehicles. One of the key advantages of traffic video detection is that it provides traffic supervisors with the means to decrease congestion and improve highway planning. Vehicle detection in videos combines image processing in real-time with computerized pattern recognition in flexible stages. The real-time pro

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