34,107 research outputs found
Hierarchical modularity in human brain functional networks
The idea that complex systems have a hierarchical modular organization
originates in the early 1960s and has recently attracted fresh support from
quantitative studies of large scale, real-life networks. Here we investigate
the hierarchical modular (or "modules-within-modules") decomposition of human
brain functional networks, measured using functional magnetic resonance imaging
(fMRI) in 18 healthy volunteers under no-task or resting conditions. We used a
customized template to extract networks with more than 1800 regional nodes, and
we applied a fast algorithm to identify nested modular structure at several
hierarchical levels. We used mutual information, 0 < I < 1, to estimate the
similarity of community structure of networks in different subjects, and to
identify the individual network that is most representative of the group.
Results show that human brain functional networks have a hierarchical modular
organization with a fair degree of similarity between subjects, I=0.63. The
largest 5 modules at the highest level of the hierarchy were medial occipital,
lateral occipital, central, parieto-frontal and fronto-temporal systems;
occipital modules demonstrated less sub-modular organization than modules
comprising regions of multimodal association cortex. Connector nodes and hubs,
with a key role in inter-modular connectivity, were also concentrated in
association cortical areas. We conclude that methods are available for
hierarchical modular decomposition of large numbers of high resolution brain
functional networks using computationally expedient algorithms. This could
enable future investigations of Simon's original hypothesis that hierarchy or
near-decomposability of physical symbol systems is a critical design feature
for their fast adaptivity to changing environmental conditions
A Formal Framework for Linguistic Annotation
`Linguistic annotation' covers any descriptive or analytic notations applied
to raw language data. The basic data may be in the form of time functions --
audio, video and/or physiological recordings -- or it may be textual. The added
notations may include transcriptions of all sorts (from phonetic features to
discourse structures), part-of-speech and sense tagging, syntactic analysis,
`named entity' identification, co-reference annotation, and so on. While there
are several ongoing efforts to provide formats and tools for such annotations
and to publish annotated linguistic databases, the lack of widely accepted
standards is becoming a critical problem. Proposed standards, to the extent
they exist, have focussed on file formats. This paper focuses instead on the
logical structure of linguistic annotations. We survey a wide variety of
existing annotation formats and demonstrate a common conceptual core, the
annotation graph. This provides a formal framework for constructing,
maintaining and searching linguistic annotations, while remaining consistent
with many alternative data structures and file formats.Comment: 49 page
A Taxonomy of Workflow Management Systems for Grid Computing
With the advent of Grid and application technologies, scientists and
engineers are building more and more complex applications to manage and process
large data sets, and execute scientific experiments on distributed resources.
Such application scenarios require means for composing and executing complex
workflows. Therefore, many efforts have been made towards the development of
workflow management systems for Grid computing. In this paper, we propose a
taxonomy that characterizes and classifies various approaches for building and
executing workflows on Grids. We also survey several representative Grid
workflow systems developed by various projects world-wide to demonstrate the
comprehensiveness of the taxonomy. The taxonomy not only highlights the design
and engineering similarities and differences of state-of-the-art in Grid
workflow systems, but also identifies the areas that need further research.Comment: 29 pages, 15 figure
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