2,776 research outputs found
Absorbing-state phase transitions on percolating lattices
We study nonequilibrium phase transitions of reaction-diffusion systems
defined on randomly diluted lattices, focusing on the transition across the
lattice percolation threshold. To develop a theory for this transition, we
combine classical percolation theory with the properties of the supercritical
nonequilibrium system on a finite-size cluster. In the case of the contact
process, the interplay between geometric criticality due to percolation and
dynamical fluctuations of the nonequilibrium system leads to a new universality
class. The critical point is characterized by ultraslow activated dynamical
scaling and accompanied by strong Griffiths singularities. To confirm the
universality of this exotic scaling scenario we also study the generalized
contact process with several (symmetric) absorbing states, and we support our
theory by extensive Monte-Carlo simulations.Comment: 11 pages, 10 eps figures included, final version as publishe
Statistical Mechanics and Information-Theoretic Perspectives on Complexity in the Earth System
Peer reviewedPublisher PD
Multivariate Approaches to Classification in Extragalactic Astronomy
Clustering objects into synthetic groups is a natural activity of any
science. Astrophysics is not an exception and is now facing a deluge of data.
For galaxies, the one-century old Hubble classification and the Hubble tuning
fork are still largely in use, together with numerous mono-or bivariate
classifications most often made by eye. However, a classification must be
driven by the data, and sophisticated multivariate statistical tools are used
more and more often. In this paper we review these different approaches in
order to situate them in the general context of unsupervised and supervised
learning. We insist on the astrophysical outcomes of these studies to show that
multivariate analyses provide an obvious path toward a renewal of our
classification of galaxies and are invaluable tools to investigate the physics
and evolution of galaxies.Comment: Open Access paper.
http://www.frontiersin.org/milky\_way\_and\_galaxies/10.3389/fspas.2015.00003/abstract\>.
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Hollywood in Homes: Crowdsourcing Data Collection for Activity Understanding
Computer vision has a great potential to help our daily lives by searching
for lost keys, watering flowers or reminding us to take a pill. To succeed with
such tasks, computer vision methods need to be trained from real and diverse
examples of our daily dynamic scenes. While most of such scenes are not
particularly exciting, they typically do not appear on YouTube, in movies or TV
broadcasts. So how do we collect sufficiently many diverse but boring samples
representing our lives? We propose a novel Hollywood in Homes approach to
collect such data. Instead of shooting videos in the lab, we ensure diversity
by distributing and crowdsourcing the whole process of video creation from
script writing to video recording and annotation. Following this procedure we
collect a new dataset, Charades, with hundreds of people recording videos in
their own homes, acting out casual everyday activities. The dataset is composed
of 9,848 annotated videos with an average length of 30 seconds, showing
activities of 267 people from three continents. Each video is annotated by
multiple free-text descriptions, action labels, action intervals and classes of
interacted objects. In total, Charades provides 27,847 video descriptions,
66,500 temporally localized intervals for 157 action classes and 41,104 labels
for 46 object classes. Using this rich data, we evaluate and provide baseline
results for several tasks including action recognition and automatic
description generation. We believe that the realism, diversity, and casual
nature of this dataset will present unique challenges and new opportunities for
computer vision community
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