7,552 research outputs found
One-Class Classification: Taxonomy of Study and Review of Techniques
One-class classification (OCC) algorithms aim to build classification models
when the negative class is either absent, poorly sampled or not well defined.
This unique situation constrains the learning of efficient classifiers by
defining class boundary just with the knowledge of positive class. The OCC
problem has been considered and applied under many research themes, such as
outlier/novelty detection and concept learning. In this paper we present a
unified view of the general problem of OCC by presenting a taxonomy of study
for OCC problems, which is based on the availability of training data,
algorithms used and the application domains applied. We further delve into each
of the categories of the proposed taxonomy and present a comprehensive
literature review of the OCC algorithms, techniques and methodologies with a
focus on their significance, limitations and applications. We conclude our
paper by discussing some open research problems in the field of OCC and present
our vision for future research.Comment: 24 pages + 11 pages of references, 8 figure
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A non-separable stochastic model for pulse-like ground motions
A phenomenological non-separable non-stationary stochastic model is proposed to represent near-fault pulse-like ground motions (PLGMs) by means of a parametrically defined evolutionary power spectrum (EPSD). Numerical data pertaining to ensembles of EPSD compatible realizations and considering statistical analysis of peak elastic and inelastic spectral ordinates demonstrate the applicability of the model to capture the salient effects of PLGMs to structural responses. To this aim, the model parameters are calibrated against a field recorded PLGM. Further numerical data considering stochastic processes compatible with the response spectrum of the European aseismic code (EC8) are furnished to demonstrate the potential of the proposed model for including near-fault effects to spectrum compatible representations of the seismic action. It is foreseen that this model can be a useful tool in accounting for the low-frequency content of PLGMs in both Monte Carlo simulation-based analyses and in statistical linearization based studies
Serverification of Molecular Modeling Applications: the Rosetta Online Server that Includes Everyone (ROSIE)
The Rosetta molecular modeling software package provides experimentally
tested and rapidly evolving tools for the 3D structure prediction and
high-resolution design of proteins, nucleic acids, and a growing number of
non-natural polymers. Despite its free availability to academic users and
improving documentation, use of Rosetta has largely remained confined to
developers and their immediate collaborators due to the code's difficulty of
use, the requirement for large computational resources, and the unavailability
of servers for most of the Rosetta applications. Here, we present a unified web
framework for Rosetta applications called ROSIE (Rosetta Online Server that
Includes Everyone). ROSIE provides (a) a common user interface for Rosetta
protocols, (b) a stable application programming interface for developers to add
additional protocols, (c) a flexible back-end to allow leveraging of computer
cluster resources shared by RosettaCommons member institutions, and (d)
centralized administration by the RosettaCommons to ensure continuous
maintenance. This paper describes the ROSIE server infrastructure, a
step-by-step 'serverification' protocol for use by Rosetta developers, and the
deployment of the first nine ROSIE applications by six separate developer
teams: Docking, RNA de novo, ERRASER, Antibody, Sequence Tolerance,
Supercharge, Beta peptide design, NCBB design, and VIP redesign. As illustrated
by the number and diversity of these applications, ROSIE offers a general and
speedy paradigm for serverification of Rosetta applications that incurs
negligible cost to developers and lowers barriers to Rosetta use for the
broader biological community. ROSIE is available at
http://rosie.rosettacommons.org
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