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Construct an efficient distributed denial of service attack detection system based on data mining techniques
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<span>Distributed denial-of-service (DDoS) attack is bluster to network security that purpose at exhausted the networks with malicious traffic. Although several techniques have been designed for DDoS attack detection, intrusion detection system (IDS) It has a great role in protecting the network system and has the ability to collect and analyze data from various network sources to discover any unauthorized access. The goal of IDS is to detect malicious traffic and defend the system against any fraudulent activity or illegal traffic. Therefore, IDS monitors outgoing and incoming network traffic. This paper contains a based intrusion detection system for DDoS attack, and has the ability to detect the attack intelligently, dynamically and periodically by evaluating the set of attackers of the current node with its neighbors. We use dataset named CICDDoS2019 that contains on binary classes benign and DDoS. Performance has evaluated by applying data mining algorithms as well as applying the best features to discover potential attack classes.</span>

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Publication Date
Sat Aug 01 2015
Journal Name
Journal Of Engineering
A Real-Time Fuzzy Load Flow and Contingency Analysis Based on Gaussian Distribution System
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Fuzzy logic is used to solve the load flow and contingency analysis problems, so decreasing computing time and its the best selection instead of the traditional methods. The proposed  method is very accurate with outstanding computation time, which made the fuzzy load flow (FLF) suitable for real time application for small- as well as large-scale power systems. In addition that, the FLF efficiently able to solve load flow problem of ill-conditioned power systems and contingency analysis. The FLF method using Gaussian membership function requires less number of iterations and less computing time than that required in the FLF method using triangular membership function. Using sparsity technique for the input Ybus sparse matrix data gi

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Publication Date
Mon Jan 04 2021
Journal Name
Multimedia Tools And Applications
Attention enhancement system for college students with brain biofeedback signals based on virtual reality
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Publication Date
Tue Jun 01 2021
Journal Name
Bulletin Of Electrical Engineering And Informatics
A new pseudorandom bits generator based on a 2D-chaotic system and diffusion property
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A remarkable correlation between chaotic systems and cryptography has been established with sensitivity to initial states, unpredictability, and complex behaviors. In one development, stages of a chaotic stream cipher are applied to a discrete chaotic dynamic system for the generation of pseudorandom bits. Some of these generators are based on 1D chaotic map and others on 2D ones. In the current study, a pseudorandom bit generator (PRBG) based on a new 2D chaotic logistic map is proposed that runs side-by-side and commences from random independent initial states. The structure of the proposed model consists of the three components of a mouse input device, the proposed 2D chaotic system, and an initial permutation (IP) table. Statist

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Publication Date
Fri Mar 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
The construction of Investment Portfolios in the Iraq Stock Exchange: Market Timing Vs. an Efficient Selection
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Abstract

         Uncertainty, the deeply-rooted fact that surrounding the investment environment, especially the stock market which just prices have taken a specific trend until they moved to another one for its up or down. This means that the volatility characteristic of financial market requires the rational investor an argument led towards the adoption of planned acts to gain greater benefit in the goal of wealth maximizing. There is no possibility to achieve this goal without the burden of uncertainty and the risk of systematic fluctuations of investment returns in the financial market after the facts of  efficient diversification have pro

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Publication Date
Sat Jan 01 2022
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science (ijeecs)
A new smart approach of an efficient energy consumption management by using a machine-learning technique
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Many consumers of electric power have excesses in their electric power consumptions that exceed the permissible limit by the electrical power distribution stations, and then we proposed a validation approach that works intelligently by applying machine learning (ML) technology to teach electrical consumers how to properly consume without wasting energy expended. The validation approach is one of a large combination of intelligent processes related to energy consumption which is called the efficient energy consumption management (EECM) approaches, and it connected with the internet of things (IoT) technology to be linked to Google Firebase Cloud where a utility center used to check whether the consumption of the efficient energy is s

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Publication Date
Sun Aug 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
The impact of service promotion on achieving leadership for business organizations
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The research problem lies in the fundamental questions that revolve around the role of each of the tools of promotion, namely advertising, personal sale, public relations, sales promotion, and direct marketing in achieving leadership for business organizations. Research to know the role of promoting the service in the researched company and whether the promotion of the service is qualified to lead the researched company to leadership, and for this purpose formulated research hypotheses of three hypotheses, the first hypothesis says that there is a significant impact relationship between promotion and entrepreneurship. The second hypothesis aimed to determine the role played by promotion in the researched company to achieve unique

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Publication Date
Fri Jul 12 2024
Journal Name
World Water Policy
The effect of natural factors on changing soil uses in the marshes: An experimental study using Landsat satellite data
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The study aimed to analyze the effect of meteorological factors (rainfall rate and temperature) on the change in land use in the marshes of the Al‐Majar Al‐Kabir region in southern Iraq. Satellite images from Landsat 7 for 2012 and Landsat 8 for 2022 were used to monitor changes in the land coverings, the images taken from the Enhanced Thematic Mapper Plus (ETM+) and Operational Land Imager (OLI) sensors of the Landsat satellite. Geometric correction was used to convert images into a format with precise geographic coordinates using ArcMap 10.5. The maximum likelihood classification method was used to examine satellite image data using a supervised approach, and the data were analyzed statistically. We obtained clear images of the area,

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Detection capability Alttafaria for some materials using a bacterial mutagenesis system
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Tested effective Alttafaria some materials used for different purposes, system a bacterial mutagenesis component of three bacterial isolates belonging to different races and materials tested included drug Briaktin

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Publication Date
Sun Jul 01 2018
Journal Name
Agronomy Journal
Use of Rainfall Data to Improve Ground-Based Active Optical Sensors Yield Estimates
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Ground-based active optical sensors (GBAOS) have been successfully used in agriculture to predict crop yield potential (YP) early in the season and to improvise N rates for optimal crop yield. However, the models were found weak or inconsistent due to environmental variation especially rainfall. The objectives of the study were to evaluate if GBAOS could predict YP across multiple locations, soil types, cultivation systems, and rainfall differences. This study was carried from 2011 to 2013 on corn (Zea mays L.) in North Dakota, and in 2017 in potatoes in Maine. Six N rates were used on 50 sites in North Dakota and 12 N rates on two sites, one dryland and one irrigated, in Maine. Two active GBAOS used for this study were GreenSeeker and Holl

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Publication Date
Fri Jul 14 2023
Journal Name
International Journal Of Information Technology &amp; Decision Making
A Decision Modeling Approach for Data Acquisition Systems of the Vehicle Industry Based on Interval-Valued Linear Diophantine Fuzzy Set
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Modeling data acquisition systems (DASs) can support the vehicle industry in the development and design of sophisticated driver assistance systems. Modeling DASs on the basis of multiple criteria is considered as a multicriteria decision-making (MCDM) problem. Although literature reviews have provided models for DASs, the issue of imprecise, unclear, and ambiguous information remains unresolved. Compared with existing MCDM methods, the robustness of the fuzzy decision by opinion score method II (FDOSM II) and fuzzy weighted with zero inconsistency II (FWZIC II) is demonstrated for modeling the DASs. However, these methods are implemented in an intuitionistic fuzzy set environment that restricts the ability of experts to provide mem

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