ON A DUALITY PROPERTY OF ISOTHERMIC SURFACES

2017 ◽  
Vol 20 (1) ◽  
pp. 85-90
Author(s):  
Magdalena Toda
Author(s):  
XIANG LI ◽  
BAODING LIU

Possibility measures and credibility measures are widely used in fuzzy set theory. Compared with possibility measures, the advantage of credibility measures is the self-duality property. This paper gives a relation between possibility measures and credibility measures, and proves a sufficient and necessary condition for credibility measures. Finally, the credibility extension theorem is shown.


2011 ◽  
Vol 77 (3-4) ◽  
pp. 513-524
Author(s):  
Belmesnaoui Aqzzouz ◽  
Aziz Elbour

2008 ◽  
Vol 80 (1) ◽  
pp. 3-19
Author(s):  
Shuguo Shi

In this paper, we introduce the fourth fundamental forms for hypersurfaces in Hn+1 and space-like hypersurfaces in S1n+1, and discuss the conformality of the normal Gauss map of the hypersurfaces in Hn+1 and S1n+1. Particularly, we discuss the surfaces with conformal normal Gauss map in H³ and S³1, and prove a duality property. We give a Weierstrass representation formula for space-like surfaces in S³1 with conformal normal Gauss map. We also state the similar results for time-like surfaces in S³1. Some examples of surfaces in S³1 with conformal normal Gauss map are given and a fully nonlinear equation of Monge-Ampère type for the graphs in S³1 with conformal normal Gauss map is derived.


2015 ◽  
Vol 2015 ◽  
pp. 1-16
Author(s):  
Tao Lei ◽  
Yi Wang ◽  
Weiwei Luo

Self-dual morphological operators (SDMO) do not rely on whether one starts the sequence with erosion or dilation; they treat the image foreground and background identically. However, it is difficult to extend SDMO to multichannel images. Based on the self-duality property of traditional morphological operators and the theory of extremum constraint, this paper gives a complete characterization for the construction of multivariate SDMO. We introduce a pair of symmetric vector orderings (SVO) to construct multivariate dual morphological operators. Furthermore, utilizing extremum constraint to optimize multivariate morphological operators, we construct multivariate SDMO. Finally, we illustrate the importance and effectiveness of the multivariate SDMO by applications of noise removal and segmentation performance. The experimental results show that the proposed multivariate SDMO achieves better results, and they suppress noises more efficiently without losing image details compared with other filtering methods. Moreover, the proposed multivariate SDMO is also shown to have the best segmentation performance after the filtered images via watershed transformation.


Author(s):  
Alexander I Bobenko ◽  
Yuri B Suris

We give an elaborated treatment of discrete isothermic surfaces and their analogues in different geometries (projective, Möbius, Laguerre and Lie). We find the core of the theory to be a novel characterization of discrete isothermic nets as Moutard nets. The latter are characterized by the existence of representatives in the space of homogeneous coordinates satisfying the discrete Moutard equation. Moutard nets admit also a projective geometric characterization as nets with planar faces with a five-point property: a vertex and its four diagonal neighbours span a three-dimensional space. Restricting the projective theory to quadrics, we obtain Moutard nets in sphere geometries. In particular, Moutard nets in Möbius geometry are shown to coincide with discrete isothermic nets. The five-point property, in this particular case, states that a vertex and its four diagonal neighbours lie on a common sphere, which is a novel characterization of discrete isothermic surfaces. Discrete Laguerre isothermic surfaces are defined through the corresponding five-plane property, which requires that a plane and its four diagonal neighbours share a common touching sphere. Equivalently, Laguerre isothermic surfaces are characterized by having an isothermic Gauss map. S-isothermic surfaces as an instance of Moutard nets in Lie geometry are also discussed.


2019 ◽  
Vol 2019 ◽  
pp. 1-8 ◽  
Author(s):  
Václav Kolář ◽  
Jakub Šístek

A new analysis of the vortex-identification Q-criterion and its recent modifications is presented. In this unified framework based on different approaches to averaging of the cross-sectional balance between vorticity and strain rate in 3D, new relations among the existing modifications are derived. In addition, a new method based on spherical averaging is proposed. It is applicable to compressible flows, and it inherits a duality property which allows its use for identifying high strain-rate zones together with vortices. The new quantity is applied to identification of vortices and high strain-rate zones in the flow around an inclined flat plate, in the flow past a sphere, and for the reconnection process of two Burgers vortices.


2020 ◽  
Vol 17 (06) ◽  
pp. 2050085
Author(s):  
José Antonio Belinchón ◽  
Danae Polychroni

We study a string inspired cosmological with variable potential through the Lagrangian invariance method in order to determine the form of the potential. We have studied four cases by combining the different fields, that is, the dilaton [Formula: see text] the potential [Formula: see text] the [Formula: see text]-field and the matter field (a perfect fluid). In all the studied cases, we found that the potential can only take two possible forms: [Formula: see text] and [Formula: see text] where [Formula: see text] and [Formula: see text] are numerical constants. We conclude that when we take into account the Kalb–Ramond field, i.e. the [Formula: see text]-field, then it is only possible to get a constant potential, [Formula: see text] Nevertheless, if this field is not considered, then we get two possible solutions for the potential: [Formula: see text] and [Formula: see text] In all the cases, if the potential is constant, [Formula: see text] then we get a de Sitter like solution for the scale factor of the metric, [Formula: see text], which verifies the [Formula: see text]-duality property, while if the potential varies, then we get a power-law solution for the scale factor, [Formula: see text] [Formula: see text]


Sign in / Sign up

Export Citation Format

Share Document