3,040 research outputs found
Electrified externally heated rotary calciner for calcination of cement raw meal
publishedVersio
Optimal non-circular fiber geometries for image scrambling in high-resolution spectrographs
Optical fibers are a key component for high-resolution spectrographs to
attain high precision in radial velocity measurements. We present a custom
fiber with a novel core geometry - a 'D'-shape. From a theoretical standpoint,
such a fiber should provide superior scrambling and modal noise mitigation,
since unlike the commonly used circular and polygonal fiber cross sections, it
shows chaotic scrambling. We report on the fabrication process of a test fiber
and compare the optical properties, scrambling performance, and modal noise
behavior of the D-fiber with those of common polygonal fibers.Comment: 7 pages, 6 figures, submitted to SPIE Astronomical Telescopes &
Instrumentation 2016 (9912-192
Quality control for terms and definitions in ontologies and taxonomies
BACKGROUND: Ontologies and taxonomies are among the most important computational resources for molecular biology and bioinformatics. A series of recent papers has shown that the Gene Ontology (GO), the most prominent taxonomic resource in these fields, is marked by flaws of certain characteristic types, which flow from a failure to address basic ontological principles. As yet, no methods have been proposed which would allow ontology curators to pinpoint flawed terms or definitions in ontologies in a systematic way. RESULTS: We present computational methods that automatically identify terms and definitions which are defined in a circular or unintelligible way. We further demonstrate the potential of these methods by applying them to isolate a subset of 6001 problematic GO terms. By automatically aligning GO with other ontologies and taxonomies we were able to propose alternative synonyms and definitions for some of these problematic terms. This allows us to demonstrate that these other resources do not contain definitions superior to those supplied by GO. CONCLUSION: Our methods provide reliable indications of the quality of terms and definitions in ontologies and taxonomies. Further, they are well suited to assist ontology curators in drawing their attention to those terms that are ill-defined. We have further shown the limitations of ontology mapping and alignment in assisting ontology curators in rectifying problems, thus pointing to the need for manual curation
Extragradient Type Methods for Riemannian Variational Inequality Problems
Riemannian convex optimization and minimax optimization have recently drawn
considerable attention. Their appeal lies in their capacity to adeptly manage
the non-convexity of the objective function as well as constraints inherent in
the feasible set in the Euclidean sense. In this work, we delve into monotone
Riemannian Variational Inequality Problems (RVIPs), which encompass both
Riemannian convex optimization and minimax optimization as particular cases. In
the context of Euclidean space, it is established that the last-iterates of
both the extragradient (EG) and past extragradient (PEG) methods converge to
the solution of monotone variational inequality problems at a rate of
(Cai et al., 2022). However, analogous
behavior on Riemannian manifolds remains an open question. To bridge this gap,
we introduce the Riemannian extragradient (REG) and Riemannian past
extragradient (RPEG) methods. We demonstrate that both exhibit
last-iterate convergence. Additionally, we
show that the average-iterate convergence of both REG and RPEG is
, aligning with observations in the Euclidean case
(Mokhtari et al., 2020). These results are enabled by judiciously addressing
the holonomy effect so that additional complications in Riemannian cases can be
reduced and the Euclidean proof inspired by the performance estimation problem
(PEP) technique or the sum-of-squares (SOS) technique can be applied again
Opening Access to Visual Exploration of Audiovisual Digital Biomarkers: an OpenDBM Analytics Tool
Digital biomarkers (DBMs) are a growing field and increasingly tested in the
therapeutic areas of psychiatric and neurodegenerative disorders. Meanwhile,
isolated silos of knowledge of audiovisual DBMs use in industry, academia, and
clinics hinder their widespread adoption in clinical research. How can we help
these non-technical domain experts to explore audiovisual digital biomarkers?
The use of open source software in biomedical research to extract patient
behavior changes is growing and inspiring a shift toward accessibility to
address this problem. OpenDBM integrates several popular audio and visual open
source behavior extraction toolkits. We present a visual analysis tool as an
extension of the growing open source software, OpenDBM, to promote the adoption
of audiovisual DBMs in basic and applied research. Our tool illustrates
patterns in behavioral data while supporting interactive visual analysis of any
subset of derived or raw DBM variables extracted through OpenDBM.Comment: 6 pages, 2 figures, 2022 IEEE VIS Workshop - Visualization in
BioMedical A
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