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A Proposed Agent System for Network Monitoring
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The traditional centralized network management approach presents severe efficiency and scalability limitations in large scale networks. The process of data collection and analysis typically involves huge transfers of management data to the manager which cause considerable network throughput and bottlenecks at the manager side. All these problems processed using the Agent technology as a solution to distribute the management functionality over the network elements. The proposed system consists of the server agent that is working together with clients agents to monitor the logging (off, on) of the clients computers and which user is working on it. file system watcher mechanism is used to indicate any change in files. The results were presented in real time which is minimizing the cost that represents the important factor to successful management of networks that was achieved using agents.

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Publication Date
Fri Dec 23 2011
Journal Name
International Journal Of The Physical Sciences
Fast prediction of power transfer stability index based on radial basis function neural network
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Publication Date
Sat Jan 01 2022
Journal Name
International Middle Eastern Simulation And Modelling Conference 2022, Mesm 2022,
MECHANICS OF COMPOSITE PLATE STRUCTURE REINFORCED WITH HYBRID NANO MATERIALS USING ARTIFICIAL NEURAL NETWORK
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Publication Date
Wed Jul 31 2019
Journal Name
Journal Of Engineering
River Water Salinity Impact on Drinking Water Treatment Plant Performance Using Artificial neural network
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The river water salinity is a major concern in many countries, and salinity can be expressed as total dissolved solids. So, the water salinity impact of the river is one of the major factors effects of water quality. Tigris river water salinity increase with streamline and time due to the decrease in the river flow and dam construction from neighboring countries. The major objective of this research to developed salinity model to study the change of salinity and its impact on the Al-Karkh, Sharq Dijla, Al-Karama, Al-Wathba, Al-Dora, and Al-Wihda water treatment plant along Tigris River in Baghdad city using artificial neural network model (ANN). The parameter used in a model built is (Turbidity, Ec, T.s, S.s, and TDS in)

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Publication Date
Mon Feb 04 2019
Journal Name
Iraqi Journal Of Physics
Evaluation the water quality of the potable water network in Al-Shuala/ Baghdad City
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In this research, the water quality of the potable water network in
Al-Shuala Baghdad city were evaluated and compare them with the
Iraqi standards (IQS) for drinking water and World Health
Organization standards (WHO), then water quality index (WQI) were
calculator: pH, heavy metals (lead, cadmium and iron), chlorides,
total hardness, turbidity, dissolved oxygen, total dissolved solid and
electrical conductivity. Water samples are collected weekly during
the period from February 2015 to April 2015 from ten sites. Results
show that the chlorides, total dissolved solid and electrical
conductivity less than acceptable limit of standards, but total
hardness and heavy metals in some samples higher than acceptabl

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Publication Date
Fri Dec 30 2022
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Comparison of Estimation Sonic Shear Wave Time Using Empirical Correlations and Artificial Neural Network
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Wellbore instability and sand production onset modeling are very affected by Sonic Shear Wave Time (SSW). In any field, SSW is not available for all wells due to the high cost of measuring. Many authors developed empirical correlations using information from selected worldwide fields for SSW prediction. Recently, researchers have used different Artificial Intelligence methods for estimating SSW. Three existing empirical correlations of Carroll, Freund, and Brocher are used to estimate SSW in this paper, while a fourth new empirical correlation is established. For comparing with the empirical correlation results, another study's Artificial Neural Network (ANN) was used. The same data t

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Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
Modeling of Corrosion Rate Under Two Phase Flow in Horizontal Pipe Using Neural Network
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The present study develops an artificial neural network (ANN) to model an analysis and a simulation of the correlation between the average corrosion rate carbon steel and the effective parameter Reynolds number (Re), water concentration (Wc) % temperature (T o) with constant of PH 7 . The water, produced fom oil in Kirkuk oil field in Iraq from well no. k184-Depth2200ft., has been used as a corrosive media and specimen area (400 mm2) for the materials that were used as low carbon steel pipe. The pipes are supplied by Doura Refinery . The used flow system is all made of Q.V.F glass, and the circulation of the two –phase (liquid – liquid ) is affected using a Q.V.F pump .The input parameters of the model consists of Reynolds number , w

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Publication Date
Fri Oct 31 2025
Journal Name
Mathematical Modelling Of Engineering Problems
Heterogeneous Traffic Management in SDN-Enabled Data Center Network Using Machine Learning-SPIKE Model
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Software-Defined Networking (SDN) has evolved network management by detaching the control plane from the data forwarding plane, resulting in unparalleled flexibility and efficiency in network administration. However, the heterogeneity of traffic in SDN presents issues in achieving Quality of Service (QoS) demands and efficiently managing network resources. SDN traffic flows are often divided into elephant flows (EFs) and mice flows (MFs). EFs, which are distinguished by their huge packet sizes and long durations, account for a small amount of total traffic but require disproportionate network resources, thus causing congestion and delays for smaller MFs. MFs, on the other hand, have a short lifetime and are latency-sensitive, but they accou

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Publication Date
Wed Jun 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Compared with Genetic Algorithm Fast – MCD – Nested Extension and Neural Network Multilayer Back propagation
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The study using Nonparametric methods for roubust to estimate a location and scatter it is depending  minimum covariance determinant of multivariate regression model , due to the presence of outliear values and increase the sample size and presence of more than after the model regression multivariate therefore be difficult to find a median location .       

It has been the use of genetic algorithm Fast – MCD – Nested Extension and compared with neural Network Back Propagation of multilayer in terms of accuracy of the results and speed in finding median location ,while the best sample to be determined by relying on less distance (Mahalanobis distance)has the stu

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Publication Date
Mon Dec 01 2025
Journal Name
Journal Of University Of Anbar For Pure Science
Mobile ad hoc network wireless security: problems, solutions, and application: state-of-the-art
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Publication Date
Mon Feb 28 2022
Journal Name
Journal Of Educational And Psychological Researches
The Effectiveness of a Proposed Unite in Voluntary Work in Enhancing Critical Thinking Skills and The Attitudes towards Responsible Citizenship among Eighth Grade Female Students in the Governorate in Sultanate of Oman North Batinah
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The aim of the present study is to examine the effectiveness of a proposed unite in voluntary work in enhancing critical thinking skills and the attitudes towards responsible citizenship among eighth grade female students in the Sultanate of Oman. In order to collect the study data, the researchers employed a quasi-experimental research design with twenty female students from Al-Sideeqah bint Al-Sideeq for basic education school. The research data were collected via a critical thinking test that consisted of twenty-five items and a scale of twenty items under three different dimensions, which aimed to measure students' attitudes towards responsible citizenship. The researchers implemented these two instruments as pre- and post the experi

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