Model Based Estimation of Geometric Characteristics of Open Foams

Open cell foams are a class of modern materials which is interesting for a wide variety of applications and which is not accessible to classical materialography based on 2d images. 3d imaging by micro computed tomography is a practicable alternative. Analysis of the resulting volume images is either based on a simple binarisation of the image or on so-called cell reconstruction by image processing. The first approach allows to estimate mean characteristics like the mean cell volume using the typical cell of a random spatial tessellation as model for the cell shape. The cell reconstruction allows estimation of empirical distributions of cell characteristics. This paper summarises the theoretical background for the first method, in particular estimation of the intrinsic volumes and their densities from discretized data and models for random spatial tessellations. The accuracy of the estimation method is assessed using the dilated edge systems of simulated random spatial tessellations.     

Second-Order Characteristics of the Edge System of Random Tessellations and the PPI Value of Foams

The mean number of pores per inch (PPI) is widely used as a pore size characteristic for foams. Nevertheless, there is still a lack of fast and reliable methods for estimating this quantity. We propose a method for estimating the PPI value based on the Bartlett spectrum of a dark field image of the material. To this end, second-order properties of the edge systems of random tessellations are investigated in detail. In particular, we study the spectral density of the random length measure of the edges. It turns out that the location of its first local maximum is proportional to the PPI value. To determine the factor of proportionality, several random tessellation models as well as examples of real foams are investigated. To mimic the image acquisition process, 2D sections and projections of 3D tessellations are considered.     

Distributional properties of the typical cell of stationary iterated tessellations

Distributional properties are considered of the typical cell of stationary iterated tessellations (SIT), which are generated by stationary Poisson-Voronoi tessellations (SPVT) and stationary Poisson line tessellations (SPLT), respectively. Using Neveus exchange formula, the typical cell of SIT can be represented by those cells of its component tessellation hitting the typical cell of its initial tessellation. This provides a simulation algorithm without consideration of limits in space. It has been applied in order to estimate the probability densities of geometric characteristics of the typical cell of SIT generated by SPVT and SPLT. In particular, the probability densities of the number of vertices, the perimeter, and the area of the typical cell of such SIT have been determined.Acknowledgement. This work was supported by France Telecom R&D through research grant no. 001B130.     

The Combinatorial Structure of Spatial STIT Tessellations

Spatially homogeneous random tessellations that are stable under iteration (nesting) in the $3$ 3 -dimensional Euclidean space are considered, so-called STIT tessellations. They arise as outcome of a space-time process of subsequent cell division and, consequently, they are not facet-to-facet. The intent of this paper is to develop a detailed analysis of the combinatorial structure of such tessellations and to determine a number of new geometric mean values, for example for the neighbourhood of the typical vertex. The heart of the results is a fine classification of tessellation edges based on the type of their endpoints or on the equality relationship with other types of line segments. In the background of the proofs are delicate distributional properties of spatial STIT tessellations.     

Exploration of Gibbs-Laguerre Tessellations for Three-Dimensional Stochastic Modeling

Random tessellations are well suited for probabilistic modeling of three-dimensional (3D) grain microstructures of polycrystalline materials. The present paper is focused on so-called Gibbs-Laguerre tessellations, in which the generators of the Laguerre tessellation form a Gibbs point process. The goal is to construct an energy function of the Gibbs point process such that the resulting tessellation matches some desired geometrical properties. Since the model is analytically intractable, our main tool of analysis is stochastic simulation based on Markov chain Monte Carlo. Such simulations enable us to investigate the properties of the models, and, in the next step, to apply the knowledge gained to the statistical reconstruction of the 3D microstructure of an aluminum alloy extracted from 3D tomographic image data.

     

The Poisson Voronoi Tessellation II. Edge Length Distribution Functions

This paper presents a method for the determination of the distribution function of the length of the 'typical' edge of the Poisson Voronoi tessellation. The method is based on distributional properties of the configuration of the centres in the neighbourhood of the 'typical' vertex. The distribution and density functions of the edge lengths are given in double integral form for various dimensions. Analogous characteristics are considered for two-dimensional sections through higher-dimensional Poisson Voronoi tessellations.     

A global construction of homogeneous random planar tessellations that are stable under iteration

Homogeneous (i.e. spatially stationary) random tessellations of the Euclidean plane are constructed which have the characteristic property to be stable under the operation of iteration (or nesting), STIT for short. It is based on a Poisson point process on the space of lines that are endowed with a time of birth. A new approach is presented that describes the tessellation in the whole plane. So far, an explicit geometrical construction for those tessellations was only known within bounded windows.     

How many T‐tessellations on k lines? Existence of associated Gibbs measures on bounded convex domains

The paper bounds the number of tessellations with T‐shaped vertices on a fixed set of k lines: tessellations are efficiently encoded, and algorithms retrieve them, proving injectivity. This yields existence of a completely random T‐tessellation, as defined by Kiêu et al. (Spat Stat 6 (2013) 118–138), and of its Gibbsian modifications. The combinatorial bound is sharp, but likely pessimistic in typical cases. © 2014 Wiley Periodicals, Inc. Random Struct. Alg., 47, 561–587, 2015     

Mathematical aspects of educating architecture designers: a college study

This paper considers a second-year Mathematical Aspects in Architectural Design course, which relies on a first-year mathematics course and offers mathematical learning as part of hands-on practice in architecture design studio. The 16-hour course consisted of seminar presentations of mathematics concepts, their application to covering the plane by regular shapes (tessellations), and an architecture design project. The course follow-up examined the features of mathematical learning in the studio environment using qualitative methods. It showed students’ curiosity and motivation to deepen in mathematical subjects and use them in their tessellation design projects. The majority of the students refreshed and practically applied their background mathematical knowledge, especially in calculus, on a need-to-know basis.     

Large correlation analysis

In this paper, a novel supervised dimensionality reduction method is developed based on both the correlation analysis and the idea of large margin learning. The method aims to maximize the minimal correlation between each dimensionality-reduced instance and its class label, thus named as large correlation analysis (LCA). Unlike most existing correlation analysis methods such as CCA, CCAs and CDA, which all maximize the total or ensemble correlation over all training instances, LCA devotes to maximizing the individual correlations between given instances and its associated labels and is established by solving a relaxed quadratic programming with box-constraints. Experimental results on real-world datasets from both UCI and USPS show its effectiveness compared to the existing canonical correlation analysis methods.     

Asymptotics for Statistical Distances Based on Voronoi Tessellations

We obtain an information-type inequality and a strong law for a wide class of statistical distances between empirical estimates and random measures based on Voronoi tessellations. This extends some basic results in the asymptotic theory of sample spacings, when the cells of the Voronoi tessellation are interpreted as d-dimensional spacings.     

Bernoulli Cluster Field: Voronoi Tessellations

A new point process is proposed which can be viewed either as a Boolean cluster model with two cluster modes or as a p-thinned Neyman-Scott cluster process with the retention of the original parent point. Voronoi tessellation generated by such a point process has extremely high coefficients of variation of cell volumes as well as of profile areas and lengths in the planar and line induced tessellations. An approximate numerical model of tessellation characteristics is developed for the case of small cluster size; its predictions are compared with the results of computer simulations. Tessellations of this type can be used as models of grain structures in steels.     

On hyperbolic once-punctured-torus bundles III: Comparing two tessellations of the complex plane

To each once-punctured-torus bundle, Tφ, over the circle with pseudo-Anosov monodromy φ, there are associated two tessellations of the complex plane: one, Δ(φ), is (the projection from ∞ of) the triangulation of a horosphere at ∞ induced by the canonical decomposition into ideal tetrahedra, and the other, CW(φ), is a fractal tessellation given by the Cannon-Thurston map of the fiber group switching back and forth between gray and white each time it passes through ∞. In this paper, we fully describe the relation between Δ(φ) and CW(φ).     

Poisson polyhedra in high dimensions

The zero cell of a parametric class of random hyperplane tessellations depending on a distance exponent and an intensity parameter is investigated, as the space dimension tends to infinity. The model includes the zero cell of stationary and isotropic Poisson hyperplane tessellations as well as the typical cell of a stationary Poisson Voronoi tessellation as special cases. It is shown that asymptotically in the space dimension, with overwhelming probability these cells satisfy the hyperplane conjecture, if the distance exponent and the intensity parameter are suitably chosen dimension-dependent functions. Also the high dimensional limits of the mean number of faces are explored and the asymptotic behaviour of an isoperimetric ratio is analysed. In the background are new identities linking the f-vector of the zero cell to certain dual intrinsic volumes.     

Representation complexity of adaptive 3D distance fields

In this paper we study the representation complexity of a kind of data structure that stores the information necessary to compute the distance from a point to a geometric body. These data structures called adaptive splitting based on cubature distance fields (ASBCDF), are binary search trees generated by the adaptive splitting based on cubature (ASBC) algorithm that adaptively subdivides the space surrounding the body into tetrahedra. Their representation complexity is measured by the number of nodes in the tree (two times the number of tetrahedra in the resulting tessellation). In the case of convex polyhedra we prove that this quantity remains bounded as the number of vertices of the polyhedra increases to infinity. Experimental results show that the number of tetrahedra in the tessellations is almost independent of the combinatorial complexity of the polyhedra. This means that the average compute time of the distance to arbitrary convex polyhedra is almost constant. Therefore, ASBCDFs are especially suitable for real time applications involving rapidly changing environments modelized with complex polyhedra.     

On the Arrangement of Cells in Planar STIT and Poisson Line Tessellations

It is well known that the distributions of the interiors of the typical cells of a Poisson line tessellation and a STIT tessellation with the same parameters coincide. In this paper, differences in the arrangement of the cells in these two tessellation models are investigated. In particular, characteristics of the set of cells neighbouring the typical cell are studied, mainly by simulation. Furthermore, the pair-correlation function and several mark correlation functions of the point processes of cell centres are estimated and compared.     

2D Centroidal Voronoi Tessellations with Constraints

<正>We tackle the problem of constructing 2D centroidal Voronoi tessellations with constraints through an efficient and robust construction of bounded Voronoi diagrams, the pseudo-dual of the constrained Delaunay triangulation.We exploit the fact that the cells of the bounded Voronoi diagram can be obtained by clipping the ordinary ones against the constrained Delaunay edges.The clipping itself is efficiently computed by identifying for each constrained edge the(connected) set of triangles whose dual Voronoi vertices are hidden by the constraint.The resulting construction is amenable to Lloyd relaxation so as to obtain a centroidal tessellation with constraints.     

统计相关性分析方法的进展

系统综述了自19世纪开始且至今常用统计相关性的方法,例如Pearson和Spearman相关系数,CorGc和CovGc 相关性及距离相关性方法。重点介绍了2011年提出的MIC方法以及由此引发的毁誉参半的大量评述,旨在揭示这一热点领域研究面貌。该领域不仅受到统计学家的关注,而且受到了分析大样本和异质数据的应用研究领域的学者们的追捧,例如基因组生物学家和网络信息研究者。这些研究者期望在众多已有方法的理解和剖析中更恰当地付诸应用,并提出新的应用问题来推动新的分析方法的创造。     

Gromov hyperbolicity of planar graphs

We prove that under appropriate assumptions adding or removing an infinite amount of edges to a given planar graph preserves its non-hyperbolicity, a result which is shown to be false in general. In particular, we make a conjecture that every tessellation graph of ?² with convex tiles is non-hyperbolic; it is shown that in order to prove this conjecture it suffices to consider tessellation graphs of ?² such that every tile is a triangle and a partial answer to this question is given. A weaker version of this conjecture stating that every tessellation graph of ?² with rectangular tiles is non-hyperbolic is given and partially answered. If this conjecture were true, many tessellation graphs of ?² with tiles which are parallelograms would be non-hyperbolic.     

Second‐order properties of the point process of nodes in a stationary Voronoi tessellation

In this paper we derive representation formulae for the second factorial moment measure of the point process of nodes and the second moment of the number of vertices of the typical cell associated with a stationary normal Voronoi tessellation in ?^d . In case the Voronoi tessellation is generated by a stationary Poisson process with intensity λ > 0 the corresponding pair correlation function g_V,λ (r) can be expressed by a weighted sum of d +2 (numerically tractable) multiple parameter integrals. The asymptotic variance of the number of nodes in an increasing cubic domain as well as the second moment of the number of vertices of the typical Poisson Voronoi cell are calculated exactly by means of these parameter integrals. The existence of a (d ? 1)st‐order pole of g_V,λ (r) at r = 0 is proved and the exact value of lim_{r →0} r^{d –1} g_V,λ (r) is determined. In the particular cases d = 2 and d = 3 the graph of g_V,1(r) including its local extreme points, the points of level 1 of gV, 1(r) and other characteristics are computed by numerical integration. Furthermore, an asymptotically exact confidence interval for the intensity of nodes is obtained. (© 2008 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)