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Shared Congestion Detection: A Comparative Study
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Most Internet-tomography problems such as shared congestion detection depend on network measurements. Usually, such measurements are carried out in multiple locations inside the network and relied on local clocks. These clocks usually skewed with time making these measurements unsynchronized and thereby degrading the performance of most techniques. Recently, shared congestion detection has become an important issue in many computer networked applications such as multimedia streaming and
peer-to-peer file sharing. One of the most powerful techniques that employed in literature is based on Discrete Wavelet Transform (DWT) with cross-correlation operation to determine the state of the congestion. Wavelet transform is used as a de-noising tool to reduce the effects of both clock skew and queuing delay fluctuations on the decision of congestion type. Since, classical Discrete Wavelet Transform (DWT) is not shift-invariant transform which is a very useful property particularly in signal de-noising problems. Therefore, another transform called Stationary Wavelet Transform (SWT) that possesses shiftinvariant property is suggested and used instead of DWT. The modified technique exhibits a better performance in terms of the time required to correctly detect the state of congestion especially with the existence of clock skew problem. The suggested technique is tested using simulations under different
environments.

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Engineering
Artificial Neural Network Models to Predict the Cost and Time of Wastewater Projects
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Infrastructure, especially wastewater projects, plays an important role in the life of residential communities. Due to the increasing population growth, there is also a significant increase in residential and commercial facilities. This research aims to develop two models for predicting the cost and time of wastewater projects according to independent variables affecting them. These variables have been determined through a questionnaire distributed to 20 projects under construction in Al-Kut City/ Wasit Governorate/Iraq. The researcher used artificial neural network technology to develop the models. The results showed that the coefficient of correlation R between actual and predicted values were 99.4% and 99 %, MAPE was

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Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
Stable Semisimple Modules, Stable t- Semisimple Modules and Strongly Stable t-Semisimple Modules
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        Throughout this paper, three concepts are introduced namely stable semisimple modules, stable t-semisimple modules and strongly stable t-semisimple. Many features co-related with these concepts are presented. Also many connections between these concepts are given. Moreover several relationships between these classes of modules and other co-related classes and other related concepts are introduced.

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Publication Date
Tue Jan 01 2019
Journal Name
Aip Conference Proceedings
Temperature dependence energy distribution function for proton-tritium fusion reaction
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The physical behavior for the energy distribution function (EDF) of the reactant particles depending upon the gases (fuel) temperature are completely described by a physical model covering the global formulas controlling the EDF profile. Results about the energy distribution for the reactant system indicate a standard EDF, in which it’s arrive a steady state form shape and intern lead to fix the optimum selected temperature.

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Publication Date
Wed May 17 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Evaluation of Thermal Reactor Fission Products Cross Sections
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      The production of fission products during reactor operation has a very important effect on  reactor reactivity .Results of neutron cross section evaluations are presented for the main product nuclides considered as being the most important  for reactor calculation and burn-up consideration . Data from the main international libraries considered as containing the most up-to-date nuclear data   and the latest experimental measurements are considered in the evaluation processes, we describe the evaluated cross sections of the fission product nuclides by making inter comparison of the data and point out the discrepancies among libraries.

 

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Publication Date
Thu Sep 01 2022
Journal Name
Iraqi Journal Of Physics
Positron Interactions with Some Human Body Organs Using Monte Carlo Probability Method
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In this study, mean free path and positron elastic-inelastic scattering are modeled for the elements hydrogen (H), carbon (C), nitrogen (N), oxygen (O), phosphorus (P), sulfur (S), chlorine (Cl), potassium (K) and iodine (I). Despite the enormous amounts of data required, the Monte Carlo (MC) method was applied, allowing for a very accurate simulation of positron interaction collisions in live cells. Here, the MC simulation of the interaction of positrons was reported with breast, liver, and thyroid at normal incidence angles, with energies ranging from 45 eV to 0.2 MeV. The model provides a straightforward analytic formula for the random sampling of positron scattering. ICRU44 was used to compile the elemental composition data. In this

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Publication Date
Wed Sep 01 2021
Journal Name
Iraqi Journal Of Physics
Theoretical Calculations of the Cross-sections for (n,α) and (n,xα) reactions on the Structural Material for Fusion Reactor 46-50Ti
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The biggest problem of structural materials for fusion reactor is the damage caused by the fusion product neutrons to the structural material. If this problem is overcomed, an important milestone will be left behind in fusion energy. One of the important problems of the structural material is that nuclei forming the structural material interacting with fusion neutrons are transmuted to stable or radioactive nuclei via (n, x) (x; alpha, proton, gamma etc.) reactions. In particular, the concentration of helium gas in the structural material increases through deuteron- tritium (D-T) and (n, α) reactions, and this increase significantly changes the microstructure and the properties of the structural materials. T

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Publication Date
Tue Mar 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
Using Iterative Reweighting Algorithm and Genetic Algorithm to Calculate The Estimation of The Parameters Of The Maximum Likelihood of The Skew Normal Distribution
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Excessive skewness which occurs sometimes in the data is represented as an obstacle against normal distribution. So, recent studies have witnessed activity in studying the skew-normal distribution (SND) that matches the skewness data which is regarded as a special case of the normal distribution with additional skewness parameter (α), which gives more flexibility to the normal distribution. When estimating the parameters of (SND), we face the problem of the non-linear equation and by using the method of Maximum Likelihood estimation (ML) their solutions will be inaccurate and unreliable. To solve this problem, two methods can be used that are: the genetic algorithm (GA) and the iterative reweighting algorithm (IR) based on the M

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Publication Date
Thu Mar 01 2018
Journal Name
Journal Of Engineering
Permeability Estimation by Using the Modified and Conventional FZI Methods
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There many methods for estimation of permeability. In this Paper, permeability has been estimated by two methods. The conventional and modified methods are used to calculate flow zone indicator (FZI). The hydraulic flow unit (HU) was identified by FZI technique. This technique is effective in predicting the permeability in un-cored intervals/wells. HU is related with FZI and rock quality index (RQI). All available cores from 7 wells (Su -4, Su -5, Su -7, Su -8, Su -9, Su -12, and Su -14) were used to be database for HU classification. The plot of probability cumulative of FZI is used. The plot of core-derived probability FZI for both modified and conventional method which indicates 4 Hu (A, B, C and D) for Nahr Umr forma

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Publication Date
Mon Sep 30 2024
Journal Name
Iraqi Journal Of Science
Attention-Deficit Hyperactivity Disorder Prediction by Artificial Intelligence Techniques
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Attention-Deficit Hyperactivity Disorder (ADHD), a neurodevelopmental disorder affecting millions of people globally, is defined by symptoms of hyperactivity, impulsivity, and inattention that can significantly affect an individual's daily life. The diagnostic process for ADHD is complex, requiring a combination of clinical assessments and subjective evaluations. However, recent advances in artificial intelligence (AI) techniques have shown promise in predicting ADHD and providing an early diagnosis. In this study, we will explore the application of two AI techniques, K-Nearest Neighbors (KNN) and Adaptive Boosting (AdaBoost), in predicting ADHD using the Python programming language. The classification accuracies obtained w

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Publication Date
Tue Mar 31 2015
Journal Name
Al-khwarizmi Engineering Journal
Profiles and Geotechnical Properties for some Basra Soils
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 Abstract

Basra province is known for its logistic location for trading activity and oil industry. By geological point of view, Basra areas are believed to consist mainly of alternation of (clay, silty clay, clayey silt, silt and sand) type of soil. Any development of industry in this area should be affected by the occurrence of the clay soil. That is why the investigation to the soil is more than necessary. In this case, a vast testing program was carried out by the author to evaluate the various formations constituting the of some Basra soils. An attempt to characterize and discuss the nature, minerals, engineering behavior and field properties of soil samples extracted from more than one thousand and one

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