In this paper, we propose a hierarchical approach to 3D scattered data interpolation with compactly supported basis functions. Our numerical experiments suggest that the approach integrates the best aspects of scattered data fitting with locally and globally supported basis functions. Employing locally supported functions leads to an efficient computational procedure, while a coarse-to-fine hie...

We present a new algorithm for terrain modeling based on Voronoi diagrams and Sibson’s interpolant. Starting with a set of scattered data sites in the plane with associated function values defining a height field, our algorithm constructs a top-down hierarchy of smooth approximations. We use the convex hull of given sites as domain for our hierarchical representation. Sibson’s interpolant is us...

In this paper, we propose a hierarchical approach to 3D scattered data interpolation with compactly supported basis functions. Our numerical experiments suggest that the approach integrates the best aspects of scattered data fitting with locally and globally supported basis functions. Employing locally supported functions leads to an efficient computational procedure, while a coarse-to-fine hie...

ÐWe describe MGV, an integrated visualization and exploration system for massive multidigraph navigation. It adheres to the Visual Information-Seeking Mantra: overview first, zoom and filter, then details on demand. MGV's only assumption is that the vertex set of the underlying digraph corresponds to the set of leaves of a predetermined tree T . MGV builds an out-of-core graph hierarchy and pro...

Machine learning techniques represent a powerful paradigm in side-channel analysis, but they come with a price. Selecting the appropriate algorithm as well as the parameters can sometimes be a difficult task. Nevertheless, the results obtained usually justify such an effort. However, a large part of those results use simplification of the data relation and in fact do not consider all the availa...

Given a large bipartite graph that represents objects and their properties, how can we automatically extract semantic information that provides an overview of the data and – at the same time – enables us to drill down to specific parts for an in-depth analysis? In this work in-progress paper, we propose extracting a taxonomy that models the relation between the properties via an is-a hierarchy....

The first data model was developed by Rockwell and IBM in the 1970s. It is known as the hierarchical model. The hierarchical database is a collection of records that is logically organized to conform to the upside-down tree (hierarchical) structure. Within the hierarchy, the top layer (the root) is perceived as the parent of the segment directly beneath it. While this model represents 1:M relat...

This paper is a survey of two kinds of “compressed” proof schemes, the matrix method and proof nets, as applied to a variety of logics ranging along the substructural hierarchy from classical all the way down to the nonassociative Lambek system. A novel treatment of proof nets for the latter is provided. Descriptions of proof nets and matrices are given in a uniform notation based on sequents, ...

We explore a generalized, stochastic seceder model of societal dynamics with variable size polling groups and higher-dimensional opinion vectors, revealing its essential modes of self-organized segregation. Renormalizing to a discrete, deterministic version, we pin down the upper critical size of the sampling group and analytically uncover a self-similar hierarchy of dynamically stable, multipl...

Control problems in the process industry are dominated by non-linear and time-varying behaviour, many inner loops, and much interaction between the control loops. Fuzzy controllers have in some cases nevertheless mimicked the control actions of a human operator. For high level control and supervisory control several simple controllers can be combined in a priority hierarchy such as the one deve...