Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
An Aspect Ratio Controlled New Mesh Enhancement Method Based On Statistical Mathematics
Date
2002-10-01
Author
Sorguç, Arzu
Hagiwara, Ichiro
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
33
views
0
downloads
Cite This
In this study, a non-conventional statistical mathematics based on method to mesh enhancement is introduced. The method explained here, is flexible in application i.e. it can be applied to planar and spatial meshes, as well as by choosing any quality parameter to evaluate the mesh architecture and enhance accordingly. In this statistical mathematics based approach, mesh generation is considered as a statistical problem rather than its geometric features and Monte Carlo technique is adopted for this random process. Geometry of mesh architecture involved only in so called 'template' to insert the new points. In the present paper, method is explained in a planar triangular mesh architecture and aspect ratio is chosen as the parameter to evaluate the mesh quality.
Subject Keywords
Mesh enhancement
,
Statistical mathematics
,
Random analysis
,
Monte Carlo technique
URI
https://hdl.handle.net/11511/41076
DOI
https://doi.org/10.1299/jsmeoptis.2002.5.235
Collections
Department of Architecture, Conference / Seminar
Suggestions
OpenMETU
Core
A GENERALIZED CORRELATED RANDOM WALK APPROXIMATION TO FRACTIONAL BROWNIAN MOTION
Vardar Acar, Ceren (null; 2018-04-30)
In this study, we mainly propose an algorithm to generate correlated random walk converging to fractional Brownian motion, with Hurst parameter, H∈ [1/2,1]. The increments of this random walk are simulated from Bernoulli distribution with proportion p, whose density is constructed using the link between correlation of multivariate Gaussian random variables and correlation of their dichotomized binary variables. We prove that the normalized sum of trajectories of this proposed random walk yields a Gaussian p...
An analysis of teacher background indices and their relation to the eighth grade Turkish students’ mathematics achievement in TIMSS 2007
Mihyap, Kübra; Berberoğlu, Halil Giray; Department of Secondary Science and Mathematics Education (2011)
The purpose of this study is to investigate teacher background indices and their relation to mathematics achievement. For this purpose, the data collected from 146 Turkish mathematics teachers and 4498 8th grade Turkish students with the instruments - mathematics teacher background questionnaire and mathematics achievement test in the Trends in International Mathematics and Science Study (TIMSS 2007) were analyzed by using the Pearson’s Product Moment Correlation. The teacher background indices, constructed...
An Investigation of 7th grade students’ statistical literacy about the concepts of average and variation on bar and line graphs
Çatman Aksoy, Emine; Işıksal Bostan, Mine; Department of Elementary Science and Mathematics Education (2018)
The aim of the present study was to analyze statistical literacy of seventh grade students on the concepts of “average” and “variation” on bar and line graphs related to the data obtained from social or scientific contexts. More specifically, seventh grade students’ statistical literacy levels in terms of the concepts of “average” and “variation” on bar and line graphs related to the data obtained from social or scientific contexts were determined and how students at different statistical literacy levels de...
A matheuristic for binary classification of data sets using hyperboxes
Akbulut, Derya; İyigün, Cem; Özdemirel, Nur Evin (null; 2018-07-08)
In this study, an optimization approach is proposed for the binary classification problem. A Mixed Integer Programming (MIP) model formulation is used to construct hyperboxes as classifiers, minimizing the number of misclassified and unclassified samples as well as overlapping of hyperboxes. The hyperboxes are determined by some lower and upper bounds on the feature values, and overlapping of these hyperboxes is allowed to keep a balance between misclassification and overfitting. A matheuristic, namely Iter...
An algorithm to analyze stability of gene-expression patterns
Gebert, J; Latsch, M; Pickl, SW; Weber, Gerhard Wilhelm; Wunschiers, R (Elsevier BV, 2006-05-01)
Many problems in the field of computational biology consist of the analysis of so-called gene-expression data. The successful application of approximation and optimization techniques, dynamical systems, algorithms and the utilization of the underlying combinatorial structures lead to a better understanding in that field. For the concrete example of gene-expression data we extend an algorithm, which exploits discrete information. This is lying in extremal points of polyhedra, which grow step by step, up to a...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
A. Sorguç and I. Hagiwara, “An Aspect Ratio Controlled New Mesh Enhancement Method Based On Statistical Mathematics,” 2002, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/41076.
