Topological mappings between graphs, trees and generalized trees

We present novel topological mappings between graphs, trees and generalized trees that means between structured objects with different properties. The two major contributions of this paper are, first, to clarify the relation between graphs, trees and generalized trees, a graph class recently introduced. Second, these transformations provide a unique opportunity to transform structured objects into a representation that might be beneficial for a processing, e.g., by machine learning techniques for graph classification. (c) 2006 Elsevier Inc. All rights reserved.

Counter-Mappings: Cartography and Difference

Introduction to the co-edited book 'Cartographies of Differences: Interdisciplinary Perspectives

Cities of God? Medieval urban forms and their Christian Symbolism

Situated in the context of recent geographical engagements with 'landscape', this paper combines 'morphological' and 'iconographic' landscape interpretations to examine how urban forms were perceived in late medieval Europe. To date, morphological studies have mapped the medieval city either by classifying urban layouts according to particular types, or by analysing plan forms of particular towns and cities to reveal their spatial evolution. This paper outlines a third way, an 'iconographic' approach, which shows how urban forms in the Middle Ages conveyed Christian symbolism. Three such 'mappings' explore this thesis: the first uses textual and visual representations which show that the city was understood as a scaled-down world â?? a microcosm â?? linking city and cosmos in the medieval mind; the second 'mapping' develops this theme further and suggests that urban landscapes were inscribed with symbolic form through their layout on the ground; while the third looks at how Christian symbolism of urban forms was performed through the urban landscape in perennial religious processions. Each of these 'mappings' points to the symbolic, mystical significance urban form had in the Middle Ages, based on religious faith, and they thus offer a deepened appreciation of how urban landscapes were represented, constructed and experienced at the time.

Generalisation between opposing visuomotor rotations when each is associated with visual targets and movements of different amplitude

Previous studies have attempted to identify sources of contextual information which can facilitate dual adaptation to two variants of a novel environment, which are normally prone to interference. The type of contextual information previously used can be grouped into two broad categories: that which is arbitrary to the motor system, such as a colour cue, and that which is based on an internal property of the motor system, such as a change in movement effector. The experiments reported here examined whether associating visuomotor rotations to visual targets and movements of different amplitude would serve as an appropriate source of contextual information to enable dual adaptation. The results indicated that visual target and movement amplitude is not a suitable source of contextual information to enable dual adaptation in our task. Interference was observed in groups who were exposed to opposing visuomotor rotations, or a visuomotor rotation and no rotation, both when the onset of the visuomotor rotations was sudden, or occurred gradually over the course of training. Furthermore, the pattern of interference indicated that the inability to dual adapt was a result of the generalisation of learning between the two visuomotor mappings associated with each of the visual target and movement amplitudes. (C) 2008 Elsevier B.V. All rights reserved.

An extended framework for evidential reasoning systems.

Use of the Dempster-Shafer (D-S) theory of evidence to deal with uncertainty in knowledge-based systems has been widely addressed. Several AI implementations have been undertaken based on the D-S theory of evidence or the extended theory. But the representation of uncertain relationships between evidence and hypothesis groups (heuristic knowledge) is still a major problem. This paper presents an approach to representing such knowledge, in which Yen’s probabilistic multi-set mappings have been extended to evidential mappings, and Shafer’s partition technique is used to get the mass function in a complex evidence space. Then, a new graphic method for describing the knowledge is introduced which is an extension of the graphic model by Lowrance et al. Finally, an extended framework for evidential reasoning systems is specified.