in this paper, we propose a new definition of intuitionistic fuzzyquasi-metric and pseudo-metric spaces based on intuitionistic fuzzy points. weprove some properties of intuitionistic fuzzy quasi- metric and pseudo-metricspaces, and show that every intuitionistic fuzzy pseudo-metric space is intuitionisticfuzzy regular and intuitionistic fuzzy completely normal and henceintuitionistic fuzzy nor...

We formalize the notion of a cryptographic counter, which allows a group of participants to increment and decrement a cryptographic representation of a (hidden) numerical value privately and robustly. The value of the counter can only be determined by a trusted authority (or group of authorities, which may include participants themselves), and participants cannot determine any information about...

In this paper we shall be concerned with generalizing the ideas of ’metric’ and geodesic for a complex manifold M : we emphasize that our curves will be complex ones; a metric will be, informally speaking, a symmetric quadratic form on the holomorphic tangent space at each point p ∈ M , holomorphically depending on the point itself; of course, it couldn’t have any ’signature’, but, by simmetry,...

We apply the multiple point criticality principle to inflationary model building and study Coleman-Weinberg inflation when scalar potential is quadratic in logarithmic correction. analyze also impact of a non-minimal coupling gravity under two possible formulation: metric or Palatini. compare eventual compatibility results with final data release Planck mission.

We investigate the existence of Liouville integrable cosmological models in hybrid metric-Palatini theory. Specifically we use symmetry conditions for quadratic momentum conservation laws field equations as constraint determination unknown functional form The exact and analytic solutions systems which found this study are presented terms quadratics Laurent expansions.

introduction: appropriate definition of the distance measure between diffusion tensors has a deep impact on diffusion tensor image (dti) segmentation results. the geodesic metric is the best distance measure since it yields high-quality segmentation results. however, the important problem with the geodesic metric is a high computational cost of the algorithms based on it. the main goal of this ...

The purpose of this chapter is to describe recent progress in the study of Teichmüller geometry. We focus entirely on the Teichmüller metric. A survey of the very important Weil-Petersson metric can be found in [W]. The study of the Teichmüller metric has different aspects. One major theme in the subject is to what extent Teichmüller space with the Teichmüller metric resembles a metric of negat...

Learning a good distance metric in feature space potentially improves the performance of the KNN classifier and is useful in many real-world applications. Many metric learning algorithms are however based on the point estimation of a quadratic optimization problem, which is time-consuming, susceptible to overfitting, and lack a natural mechanism to reason with parameter uncertainty, an importan...

Detecting the densest subgraph is one of the most important problems in graph mining and has a variety of applications. Although there are many possible metrics for subgraph density, there is no consensus on which density metric we should use. In this paper, we provide formal guidelines to choose an appropriate density metric using four axioms. These axioms capture the necessary conditions any ...