3,998 research outputs found
A Revision Control System for Image Editing in Collaborative Multimedia Design
Revision control is a vital component in the collaborative development of
artifacts such as software code and multimedia. While revision control has been
widely deployed for text files, very few attempts to control the versioning of
binary files can be found in the literature. This can be inconvenient for
graphics applications that use a significant amount of binary data, such as
images, videos, meshes, and animations. Existing strategies such as storing
whole files for individual revisions or simple binary deltas, respectively
consume significant storage and obscure semantic information. To overcome these
limitations, in this paper we present a revision control system for digital
images that stores revisions in form of graphs. Besides, being integrated with
Git, our revision control system also facilitates artistic creation processes
in common image editing and digital painting workflows. A preliminary user
study demonstrates the usability of the proposed system.Comment: pp. 512-517 (6 pages
The Weight Function in the Subtree Kernel is Decisive
Tree data are ubiquitous because they model a large variety of situations,
e.g., the architecture of plants, the secondary structure of RNA, or the
hierarchy of XML files. Nevertheless, the analysis of these non-Euclidean data
is difficult per se. In this paper, we focus on the subtree kernel that is a
convolution kernel for tree data introduced by Vishwanathan and Smola in the
early 2000's. More precisely, we investigate the influence of the weight
function from a theoretical perspective and in real data applications. We
establish on a 2-classes stochastic model that the performance of the subtree
kernel is improved when the weight of leaves vanishes, which motivates the
definition of a new weight function, learned from the data and not fixed by the
user as usually done. To this end, we define a unified framework for computing
the subtree kernel from ordered or unordered trees, that is particularly
suitable for tuning parameters. We show through eight real data classification
problems the great efficiency of our approach, in particular for small
datasets, which also states the high importance of the weight function.
Finally, a visualization tool of the significant features is derived.Comment: 36 page
Reconceptualizing major policy change in the advocacy coalition framework: a discourse network analysis of German pension politics
How does major policy change come about? This article identifies and rectifies weaknesses in the conceptualization of innovative policy change in the Advocacy Coalition Framework. In a case study of policy belief change preceding an innovative reform in the German subsystem of old-age security, important new aspects of major policy change are carved out. In particular, the analysis traces a transition from one single hegemonic advocacy coalition to another stable coalition, with a transition phase between the two equilibria. The transition phase is characterized (i) by a bipolarization of policy beliefs in the subsystem and (ii) by state actors with shifting coalition memberships due to policy learning across coalitions or due to executive turnover. Apparently, there are subsystems with specific characteristics (presumably redistributive rather than regulative subsystems) in which one hegemonic coalition is the default, or the "normal state." In these subsystems, polarization and shifting coalition memberships seem to interact to produce coalition turnover and major policy change. The case study is based on discourse network analysis, a combination of qualitative content analysis and social network analysis, which provides an intertemporal measurement of advocacy coalition realignment at the level of policy beliefs in a subsystem
Providing visualisation support for the analysis of anatomy ontology data
BACKGROUND: Improvements in technology have been accompanied by the generation of large amounts of complex data. This same technology must be harnessed effectively if the knowledge stored within the data is to be retrieved. Storing data in ontologies aids its management; ontologies serve as controlled vocabularies that promote data exchange and re-use, improving analysis. The Edinburgh Mouse Atlas Project stores the developmental stages of the mouse embryo in anatomy ontologies. This project is looking at the use of visual data overviews for intuitive analysis of the ontology data. RESULTS: A prototype has been developed that visualises the ontologies using directed acyclic graphs in two dimensions, with the ability to study detail in regions of interest in isolation or within the context of the overview. This is followed by the development of a technique that layers individual anatomy ontologies in three-dimensional space, so that relationships across multiple data sets may be mapped using physical links drawn along the third axis. CONCLUSION: Usability evaluations of the applications confirmed advantages in visual analysis of complex data. This project will look next at data input from multiple sources, and continue to develop the techniques presented to provide intuitive identification of relationships that span multiple ontologies
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