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Commuting Involution Graphs for Certain Exceptional Groups of Lie Type
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Abstract<p>Suppose that <italic>G</italic> is a finite group and <italic>X</italic> is a <italic>G</italic>-conjugacy classes of involutions. The commuting involution graph <inline-formula><alternatives><tex-math>$${\mathcal {C}}(G,X)$$</tex-math><math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mrow> <mi>C</mi> <mo>(</mo> <mi>G</mi> <mo>,</mo> <mi>X</mi> <mo>)</mo> </mrow> </math></alternatives></inline-formula> is the graph whose vertex set is <italic>X</italic> with <inline-formula><alternatives><tex-math>$$x, y \in X$$</tex-math><math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mrow> <mi>x</mi> <mo>,</mo> <mi>y</mi> <mo>∈</mo> <mi>X</mi> </mrow> </math></alternatives></inline-formula> being joined if <inline-formula><alternatives><tex-math>$$x \ne y$$</tex-math><math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mrow> <mi>x</mi> <mo>≠</mo> <mi>y</mi> </mrow> </math></alternatives></inline-formula> and <inline-formula><alternatives><tex-math>$$xy = yx$$</tex-math><math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mrow> <mi>x</mi> <mi>y</mi> <mo>=</mo> <mi>y</mi> <mi>x</mi> </mrow> </math></alternatives></inline-formula>. Here for various exceptional Lie type groups of characteristic two we investigate their commuting involution graphs.</p>
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Publication Date
Sat Apr 01 2017
Journal Name
25th Gis Research Uk Conference
VGI data collection for supplementing official land administration systems
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This article explores the process of VGI collection by assessing the relative usability and accuracy of a range of different methods (Smartphone GPS, Tablet, and analogue maps) for data collection amongst different demographic and educational groups, and in different geographical contexts. Assessments are made of positional accuracy, completeness, and data collectors’ experiences with reference to the official cadastral data and the administration system in a case-study region of Iraq. Ownership data was validated by crowd agreement. The result shows that successful VGI projects have access to varying data collection methods.

Publication Date
Mon Mar 31 2025
Journal Name
Iraqi Statisticians Journal
Hypothesis Testing for Non-Normal Multiple Compact Regression Model
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Generalized multivariate transmuted Bessel distribution belongs to the family of probability distributions with a symmetric heavy tail. It is considered a mixed continuous probability distribution. It is the result of mixing the multivariate Gaussian mixture distribution with the generalized inverse normal distribution. On this basis, the paper will study a multiple compact regression model when the random error follows a generalized multivariate transmuted Bessel distribution. Assuming that the shape parameters are known, the parameters of the multiple compact regression model will be estimated using the maximum likelihood method and Bayesian approach depending on non-informative prior information. In addition, the Bayes factor was used

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Publication Date
Fri Feb 08 2019
Journal Name
Iraqi Journal Of Laser
Nano Fluid Detection for HPHE System Using Different Lasers
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Among the different passive techniques heat pipe heat exchanger (HPHE) seems to be the most effective one for energy saving in heating ventilation and air conditioning system (HVAC). The applications for nanofluids with high conductivity are favorable to increase the thermal performance in HPHE. Even though the nanofluid has the higher heat conduction coefficient that dispels more heat theoretically but the higher concentration will make clustering .Clustering is a problem that must be solved before nanofluids can be considered for long-term practical uses. Results showed that the maximum value of relative power is 0.13 mW at nanofluid compared with other concentrations due to the low density of nanofluid at this concentration. For highe

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Publication Date
Tue Nov 19 2024
Journal Name
Aip Conference Proceedings
CT scan and deep learning for COVID-19 detection
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Publication Date
Sat Jan 02 2021
Journal Name
The International Journal Of Nonlinear Analysis And Application
Atan regularized for the high dimensional Poisson regression model
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Variable selection in Poisson regression with high dimensional data has been widely used in recent years. we proposed in this paper using a penalty function that depends on a function named a penalty. An Atan estimator was compared with Lasso and adaptive lasso. A simulation and application show that an Atan estimator has the advantage in the estimation of coefficient and variables selection.

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Publication Date
Tue Jan 01 2008
Journal Name
2008 15th Asia-pacific Software Engineering Conference
G2Way A Backtracking Strategy for Pairwise Test Data Generation
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Publication Date
Sat Aug 01 2015
Journal Name
International Journal Of Advanced Research In Computer Science And Software Engineering
Partial Encryption for Colored Images Based on Face Detection
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Publication Date
Thu Jun 15 2017
Journal Name
Ieee Sensors Journal
Calibrating Distance Sensors for Terrestrial Applications Without Groundtruth Information
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Publication Date
Sun Mar 01 2020
Journal Name
Gazi University Journal Of Science
Reliable Iterative Methods for Solving the Falkner-Skan Equation
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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
1-DOF Model for Fluid-Structure-Interaction Vibration Analysis
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In this paper an attempt to provide a single degree of freedom lumped model for fluid structure interaction (FSI) dynamical analysis will be presented. The model can be used to clarify some important concept in the FSI dynamics such as the added mass, added stiffness, added damping, wave coupling ,influence mass coefficient and critical fluid depth . The numerical results of the model show that the natural frequency decrease with the increasing of many parameters related to the structure and the fluid .It is found that the interaction phenomena can become weak or strong depending on the depth of the containing fluid .The damped and un damped free response are plotted in time domain and phase plane for different model parameters It is fou

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