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bsj-2631
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
Sat Dec 01 2012
Journal Name
Iraqi Journal Of Science,
Monitoring Vegetation Growth of Spectrally Landsat Satellite Imagery ETM+ 7 & TM 5 for Western Region of Iraq by Using Remote Sensing Techniques.
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Landsat-5 Thematic Mapper (TM) has been imaging the Earth since March 1984 and Landsat-7 Enhanced Thematic Mapper Plus (ETM+) was added to the series of Landsat instruments in April 1999. In this paper the two sensors are used to monitoring the agriculture condition and detection the changing in the area of plant covers, the stability and calibration of the ETM+ has been monitored extensively since launch although it is not monitored for many years, TM now has a similar system in place to monitor stability and calibration. By referring to statistical values for the classification process, the results indicated that the state of vegetation in 1990 was in the proportion of 42.8%, while this percentage rose to 52.5% for the same study area in

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Publication Date
Sun Jun 05 2011
Journal Name
Baghdad Science Journal
A Study of Some Physical Properties for Binary System of Cyclohexane with n-decane and 1-pentanol at Different Temperatures
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mixtures of cyclohexane + n-decane and cyclohexane + 1-pentanol have been measured at 298.15, 308.15, 318.15, and 328.15 K over the whole mole fraction range. From these results, excess molar volumes, VE , have been calculated and fitted to the Flory equations. The VE values are negative and positive over the whole mole fraction range and at all temperatures. The excess refractive indices nE and excess viscosities ?E have been calculated from experimental refractive indices and viscosity measurements at different temperature and fitted to the mixing rules equations and Heric – Coursey equation respectively to predict theoretical refractive indices, we found good agreement between them for binary mixtures in this study. The variation of th

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Publication Date
Mon Apr 04 2022
Journal Name
Journal Of Educational And Psychological Researches
The Effectiveness of a Proposed Study Unit Based on the Funds of Knowledge Theory in Developing the Attitudes Towards Cultural Identity and the Proposed Study Unit among Students of Basic Education in the Sultanate of Oman
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The present study aims to explore the effectiveness of a proposed study unit based on the funds of knowledge theory in developing the attitudes towards cultural identity and the proposed study unit. In order to achieve the goal of the study, the two researchers followed the quasi-experimental approach, where the study sample consisted of (28) female students of the fifth-grade at Al-Jeelah Basic Education School, Al-Dakhiliyah Governorate in the Sultanate of Oman. The data were collected by two scales: the first is a scale of attitudes towards cultural identity consisting of (26) items. The second was a scale of attitudes towards the proposed study unit, which consisted of (24) items. The results of the study revealed that the effect of

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
Data Classification using Quantum Neural Network
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In this paper, integrated quantum neural network (QNN), which is a class of feedforward

neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that

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Publication Date
Thu Dec 01 2011
Journal Name
Iraqi Journal Of Physics
Electronic diagnostics system for the analysis of laser beam profile
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In this work the analysis of laser beam profile system ,using a two dimensional CCD (Charge Coupled Device) arrays, is established. The system is capable of producing video graphics that give a two dimensional image of laser beam. The video graphics system creates color distribution that represent the intensity distribution of the laser beam or the energy profile of the beam. The software used is capable of analyzing and displaying the profile in four different methods that is , color code intensity contouring , intensity shareholding, intensity cross section along two dimension x-y, and three dimensional plot of the beam intensity given in the same display.

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Publication Date
Mon Jun 09 2025
Journal Name
Intelligent Decision Technologies
Safety assessment model for DoS attacks detection in wireless communication and network OS environments
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Wireless networks and communications have witnessed tremendous development and growth in recent periods and up until now, as there is a group of diverse networks such as the well-known wireless communication networks and others that are not linked to an infrastructure such as telephone networks, sensors and wireless networks, especially in important applications that work to send and receive important data and information in relatively unsafe environments, cybersecurity technologies pose an important challenge in protecting unsafe networks in terms of their impact on reducing crime. Detecting hacking in electronic networks and penetration testing. Therefore, these environments must be monitored and protected from hacking and malicio

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Publication Date
Sat Jan 01 2022
Journal Name
Aip Conference Proceedings
Artificial neural network model for predicting the desulfurization efficiency of Al-Ahdab crude oil
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Publication Date
Sat May 09 2015
Journal Name
International Journal Of Innovations In Scientific Engineering
USING ARTIFICIAL NEURAL NETWORK TECHNIQUE FOR THE ESTIMATION OF CD CONCENTRATION IN CONTAMINATED SOILS
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The aim of this paper is to design artificial neural network as an alternative accurate tool to estimate concentration of Cadmium in contaminated soils for any depth and time. First, fifty soil samples were harvested from a phytoremediated contaminated site located in Qanat Aljaeesh in Baghdad city in Iraq. Second, a series of measurements were performed on the soil samples. The inputs are the soil depth, the time, and the soil parameters but the output is the concentration of Cu in the soil for depth x and time t. Third, design an ANN and its performance was evaluated using a test data set and then applied to estimate the concentration of Cadmium. The performance of the ANN technique was compared with the traditional laboratory inspecting

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Publication Date
Wed Jan 01 2020
Journal Name
International Conference Of Numerical Analysis And Applied Mathematics Icnaam 2019
Functionalized multi-walled carbon nanotubes network sensor for NO2 gas detection at room temperature
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Publication Date
Tue Dec 31 2024
Journal Name
Iraqi Geological Journal
Geomechanical Modeling and Artificial Neural Network Technique for Predicting Breakout Failure in Nasiriyah Oilfield
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Wellbore instability is one of the major issues observed throughout the drilling operation. Various wellbore instability issues may occur during drilling operations, including tight holes, borehole collapse, stuck pipe, and shale caving. Rock failure criteria are important in geomechanical analysis since they predict shear and tensile failures. A suitable failure criterion must match the rock failure, which a caliper log can detect to estimate the optimal mud weight. Lack of data makes certain wells' caliper logs unavailable. This makes it difficult to validate the performance of each failure criterion. This paper proposes an approach for predicting the breakout zones in the Nasiriyah oil field using an artificial neural network. It

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