Coding and decoding representations of 3D shapes

The aim of this study is to examine students’ ability in interpreting and constructing plane representations of 3D shapes, and to trace categories of students that reflect different types of behaviour in representing 3D shapes. To achieve this goal, one test was administered to 279 students in grades 5–9, and forty of them were interviewed. The results of the study showed that the representation of 3D shapes is composed of two general representing/cognitive abilities, coding and decoding. Decoding refers to interpreting the structural elements and geometrical properties of 3D shapes in plane representations, while coding refers to constructing plane representations and nets of 3D shapes, and translating from one representational mode to another. A mixed-method analysis showed that four categories of students can be identified that describe four types of behaviour and explain students’ reasoning patterns in representing 3D shapes.     

An efficient and reliable quadrature algorithm for integration with respect to binomial measures

In this work numerical methods for integration with respect to binomial measures are considered. Binomial measures are examples of fractal measures and arise when multifractal properties are investigated. Interpolatory quadrature rules are considered. An automatic integrator with local quadrature rules that generalize the five points Newton Cotes formula and error estimates based on null rules is then described. Numerical tests are performed to verify the efficiency and accuracy of the method. These tests confirm that the automatic integrator turns out to be as good as one of the best known quadrature algorithms with respect to the Lebesgue measure. AMS subject classification (2000)  28A25, 60G18, 65D30, 65D32, 68M15     

Lemniscates 3D: a CAGD primitive?

A 3D lemniscate is an implicitly given surface which generalizes the well-known Bernoulli lemniscates curves and the Cassini ovals in 2D. It is characterized by placing a finite number of points in space (the foci) and choosing a constant (radius), its algebraic degree is twice the number of foci and it is always contained in the union of certain spheres centered at the foci. The distribution of the foci gives a rough idea of the 3D shapes that could be modeled with any of the connected components of the lemniscate. The position of the foci can be used to stretch and to produce knoblike features. Given a set of foci, for a small radius the lemniscate consists of a number of spherelike surfaces centered at the foci which do not touch each other. As the radius increases the disconnected pieces coalesce producing interesting surfaces. In order to make 3D lemniscates a potentially useful primitive for CAGD it is necessary to control the coalescing/splitting of the connected components of the lemniscate while we move the foci and change the radius, simultaneously. In this paper we offer tools towards this control. We look closely at the case of four noncoplanar foci. AMS subject classification 65D05, 65D17, 65D18This work was partially supported by grant G97 000651 of Fonacit, Venezuela.     

Two Sample Tests for Mean 3D Projective Shapes from Digital Camera Images

In this article, we extend mean 3D projective shape change in matched pairs to independent samples. We provide a brief introduction of projective shapes of spatial configurations obtained from their digital camera images, building on previous results of Crane and Patrangenaru (J Multivar Anal 102:225–237, 2011). The manifold of projective shapes of k-ads in 3D containing a projective frame at five given landmark indices has a natural Lie group structure, which is inherited from the quaternion multiplication. Here, given the small sample size, one estimates the mean 3D projective shape change in two populations, based on independent random samples of possibly different sizes using Efron’s nonparametric bootstrap. This methodology is applied in three relevant applications of analysis of 3D scenes from digital images: visual quality control, face recognition, and scene recognition.     

Unsupervised classification of children’s bodies using currents

Object classification according to their shape and size is of key importance in many scientific fields. This work focuses on the case where the size and shape of an object is characterized by a current. A current is a mathematical object which has been proved relevant to the modeling of geometrical data, like submanifolds, through integration of vector fields along them. As a consequence of the choice of a vector-valued reproducing kernel Hilbert space (RKHS) as a test space for integrating manifolds, it is possible to consider that shapes are embedded in this Hilbert Space. A vector-valued RKHS is a Hilbert space of vector fields; therefore, it is possible to compute a mean of shapes, or to calculate a distance between two manifolds. This embedding enables us to consider size-and-shape clustering algorithms. These algorithms are applied to a 3D database obtained from an anthropometric survey of the Spanish child population with a potential application to online sales of children’s wear.     

Identification of the Velocity Field of 2D and 3D Tunnel Models with Frequency Domain Full Waveform Inversion

Full Waveform Inversion (FWI see [1]) has capability to identify the velocity field of a domain with a good precision. Its power comes from the fact that this approach does not only try to fit travel times of waves, but it tries to fit the whole seismogram. This work is about the application of acoustic full waveform inversion to 2D and 3D tunnel models. The necessary boundary conditions are applied to the models and the acoustic equation is solved by higher-order Finite Elements Method. The Conjugate Gradient (CG) method is utilized to minimize the misfit function. The results were verified with synthetic models. The synthetic tunnel models contain few bodies with different shapes and locations. Starting from a homogeneous velocity field, the synthetic model is sought over iterations. To avoid the ill-posedness, the locations and numbers of the source and receiver points have to be successfully chosen. Apart from this, the frequency set has also to be carefully constructed. (© 2014 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

On the Coupling of 3D-1D Muscle Models for Lumbar Spine Mechanics

The aim of this research is to represent, within one modelling framework, selected parts of the musculoskeletal system using principles of continuum mechanics, while other parts are modelled using lumped-parameter models and principles of Multi-Body Dynamics. The most challenging part within such a framework will be to properly model the transition from 3D to 1D models for skeletal muscles as many of the skeletal muscles extend beyond the selected part. Hence, this paper focuses on an interface condition for the 3D-1D transition within a skeletal muscle. (© 2011 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Constructing the Tree of Shapes of an Image by Fusion of the Trees of Connected Components of Upper and Lower Level Sets

The tree of shapes of an image is an ordered structure which permits an efficient manipulation of the level sets of an image, modeled as a real continuous function defined on a rectangle of , N ≥ 2. In this paper we construct the tree of shapes of an image by fusing both trees of connected components of upper and lower level sets. We analyze the branch structure of both trees and we construct the tree of shapes by joining their branches in a suitable way. This was the algorithmic approach for 2D images introduced by F. Guichard and P. Monasse in their initial paper, though other efficient approaches were later developed in this case. In this paper, we prove the well-foundedness of this approach for the general case of multidimensional images. This approach can be effectively implemented in the case of 3D images and can be applied for segmentation, but this is not the object of this paper. Devoted to the memory of Professor H.H. Schaefer     

Students’ geometric thinking with cube representations: Assessment framework and empirical evidence

While representations of 3D shapes are used in the teaching of geometry in lower secondary school, it is known that such representations can provide difficulties for students. In order to assess students’ thinking about 3D shapes, we constructed an assessment framework based on existing research studies and data from G7-9 students (aged 12–15). We then applied our framework to assess students’ geometric thinking in lessons. We report two cases of qualitative findings from a classroom experiment in which Grade 7 students (aged 12–13) tackled a problem in 3D geometry that was, for them, quite challenging. We found that students who failed to answer given problems did not mentally manipulate representations effectively, while others could mentally manipulate representations and reason about them in order to reach correct solutions. We conclude with the proposition that this finding shows the framework can be used by teachers in instruction to assess their students’ 3D geometric thinking.     

Multiplicity Free Schur, Skew Schur, and Quasisymmetric Schur Functions

In this paper we classify all Schur functions and skew Schur functions that are multiplicity free when expanded in the basis of fundamental quasisymmetric functions, termed F-multiplicity free. Combinatorially, this is equivalent to classifying all skew shapes whose standard Young tableaux have distinct descent sets. We then generalize our setting, and classify all F-multiplicity free quasisymmetric Schur functions with one or two terms in the expansion, or one or two parts in the indexing composition. This identifies composition shapes such that all standard composition tableaux of that shape have distinct descent sets. We conclude by providing such a classification for quasisymmetric Schur function families, giving a classification of Schur functions that are in some sense almost F-multiplicity free.     

Generating numerical algorithms using a computer algebra system

An useful application of computer algebra systems is the generation of algorithms for numerical computations. We have shown in Gander and Gruntz (SIAM Rev., 1999) how computer algebra can be used in teaching to derive numerical methods. In this paper we extend this work, using essentially the capability of computer algebra system to construct and manipulate the interpolating polynomial and to compute a series expansion of a function. We will automatically generate formulas for integration and differentiation with error terms and also generate multistep methods for integrating differential equations. In memory of Germund Dahlquist (1925–2005).AMS subject classification (2000) 65D25, 65D30, 65D32, 65L06     

计算机图形学中3D打印研究进展

3D打印是一种加法加工制造技术,它改变了传统的减式加工技术,实现了许多传统加工制造技术无法完成的任务.3D打印不仅为给计算机图形学提出了新的研究内容与挑战,也有力地推动了计算机图形学相关技术的发展.文中首先介绍3D打印技术相对于传统制造技术的优势同时,简要介绍3D打印技术的分类、原理与过程.在此基础上,对3D打印在计算机图形学的研究进展进行综述,包括:结构强度分析、大物体打印、打印方向优化、自平衡优化、支撑结构设计与优化、降低打印成本、提高打印效率和质量等.最后对3D打印在计算机图形学领域的发展情况进行展望.     

Análise elastoplástica de estruturas aporticadas com superfícies de interação obtidas por regressão linear múltipla

The ultimate limit state criteria (yielding surfaces) applied to structural designs are easier in stress resultants. There are many difficulties to generating interaction surfaces with six sectional efforts obtained through to numerical or experimental models of a space-frame analysis. The approach, in the literature, to nonlinear analysis of structures with 3D beams is use of interaction surfaces with only three combined efforts in the cross-section. Therefore, a better understanding of load types, of interactions between the six efforts and of local and global stability of structure are necessary. The interaction surfaces with three efforts are presented in planes, quadrics, more complex, or a mixture of them shapes, so that techniques which use analytical formulations with combined efforts and several section shapes are more or less complex. Multiple linear regression allows to treat the resultant efforts of several analyses for obtaining a yielding surface with the combined efforts. In this paper, the formulation to obtaining of the surfaces and their applications in the analysis of elasto-plastic frame structures are presented.     

r-regular shape reconstruction from unorganized points

In this paper, the problem of reconstructing a surface, given a set of scattered data points is addressed. First, a precise formulation of the reconstruction problem is proposed. The solution is mathematically defined as a particular mesh of the surface called the normalized mesh. This solution has the property to be included inside the Delaunay graph. A criterion to detect faces of the normalized mesh inside the Delaunay graph is proposed. This criterion is proved to provide the exact solution in 2D for points sampling a r-regular shapes with a sampling path < sin(π/8)r. In 3D, this result cannot be extended and the criterion cannot retrieve every face. A heuristic is proposed in order to complete the surface.     

Singularity of Lotka‐Volterra models under unfoldings

In this paper, we classify the singularity of a Lotka‐Volterra competitive model with a Gaussian competition function and non‐Gaussian carrying capacity functions. These functions need not be completely different to affect adaptive dynamics of the model. For instance, it will be seen how ostensibly similar models can actually give rise to quite different behaviors due to their properties under unfolding. The use of Gaussian‐like carrying capacity functions can also show the sensitivity of the model to assumptions on the carrying capacity function's shapes. The classification is achieved using singularity theory of fitness functions under dimorphism equivalence. We also investigate the effect of the presence of unfolding and bifurcation parameters on the evolution of the system near its singular points. Particularly, we study the adaptive dynamics of the system near the singularity by focusing on ESS and CvSS types, and dimorphisms. Mutual invasibility plots are used to show regions of coexistence.     

Random change on a Lie group and mean glaucomatous projective shape change detection from stereo pair images

In this article we develop a nonparametric methodology for estimating the mean change for matched samples on a Lie group. We then notice that for k≥5, a manifold of projective shapes of k-ads in 3D has the structure of a 3k−15 dimensional Lie group that is equivariantly embedded in a Euclidean space, therefore testing for mean change amounts to a one sample test for extrinsic means on this Lie group. The Lie group technique leads to a large sample and a nonparametric bootstrap test for one population extrinsic mean on a projective shape space, as recently developed by Patrangenaru, Liu and Sughatadasa. On the other hand, in the absence of occlusions, the 3D projective shape of a spatial k-ad can be recovered from a stereo pair of images, thus allowing one to test for mean glaucomatous 3D projective shape change detection from standard stereo pair eye images.     

Exploration of a hybrid feature selection algorithm

In the Knowledge Discovery Process, classification algorithms are often used to help create models with training data that can be used to predict the classes of untested data instances. While there are several factors involved with classification algorithms that can influence classification results, such as the node splitting measures used in making decision trees, feature selection is often used as a pre-classification step when using large data sets to help eliminate irrelevant or redundant attributes in order to increase computational efficiency and possibly to increase classification accuracy. One important factor common to both feature selection as well as to classification using decision trees is attribute discretization, which is the process of dividing attribute values into a smaller number of discrete values. In this paper, we will present and explore a new hybrid approach, ChiBlur, which involves the use of concepts from both the blurring and χ²-based approaches to feature selection, as well as concepts from multi-objective optimization. We will compare this new algorithm with algorithms based on the blurring and χ²-based approaches.     

基于最大惩罚似然的高斯混合模型无监督分类研究

本文提出了一个基于高斯混合模型的无监督分类算法. 考虑到利用EM算法求解高斯混合模型的参数参数估计问题容易陷入局部最优解, 我们引入逆Wishart分布来代替传统的Jeffery先验. 几个实验数据的结果表明, 采用该方法估计无监督分类的成分数, 无论是估计的正确率, 还是运算速度, 都有较大提高.     

A new level-set technique for the crack-detection problem

We present a new technique for recovering key characteristics of defects such as snake-like cracks from boundary electrical measurements. We propose a shape-based reconstruction algorithm adapting the level set techniques to the situation of modelling very thin shapes. Two level set functions are employed: the first one models the location and form of the crack, and the second one models its length and connectivity. Two Hamilton-Jacobi type equations are derived to describe the evolution laws for these two level set functions in order to minimize the least squares data misfit. Numerical experiments in 2D show the efficiency of this method for reconstructing disconnected cracks in the presence of measurement noise. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Classification of abelian hereditary directed categories satisfying Serre duality

In an ongoing project to classify all hereditary abelian categories, we provide a classification of -finite directed hereditary abelian categories satisfying Serre duality up to derived equivalence.

In order to prove the classification, we will study the shapes of Auslander-Reiten components extensively and use appropriate generalizations of tilting objects and coordinates, namely partial tilting sets and probing of objects by quasi-simples.