54,223 research outputs found
Far infrared observations of crab-like supernova remnants
Using the Infrared Astronomy Satellite (IRAS) data, an investigation was begun of the far infrared properties of Crab-like supernova remnants and other synchrotron nebulae. Both the co-added scanning data and, where available, pointed observations were examined. To date infrared emission was found from two Crab-like remnants: G24.7+0.6 in which the infrared source near the center of the object was shown to be a compact HII region with EM greater than or approximately 10 to the 7th pc/cm(6); and G0.9+0.1 where a marginal detection of a 25 micron source coincident with the remnant core was used to set limits on the energetics of this synchrotron nebula. Further work, in progress under a second year of this program, should yield additional information concerning the distribution of initial pulsar spin periods and the evolution of synchrotron nebulae
Clustering Memes in Social Media
The increasing pervasiveness of social media creates new opportunities to
study human social behavior, while challenging our capability to analyze their
massive data streams. One of the emerging tasks is to distinguish between
different kinds of activities, for example engineered misinformation campaigns
versus spontaneous communication. Such detection problems require a formal
definition of meme, or unit of information that can spread from person to
person through the social network. Once a meme is identified, supervised
learning methods can be applied to classify different types of communication.
The appropriate granularity of a meme, however, is hardly captured from
existing entities such as tags and keywords. Here we present a framework for
the novel task of detecting memes by clustering messages from large streams of
social data. We evaluate various similarity measures that leverage content,
metadata, network features, and their combinations. We also explore the idea of
pre-clustering on the basis of existing entities. A systematic evaluation is
carried out using a manually curated dataset as ground truth. Our analysis
shows that pre-clustering and a combination of heterogeneous features yield the
best trade-off between number of clusters and their quality, demonstrating that
a simple combination based on pairwise maximization of similarity is as
effective as a non-trivial optimization of parameters. Our approach is fully
automatic, unsupervised, and scalable for real-time detection of memes in
streaming data.Comment: Proceedings of the 2013 IEEE/ACM International Conference on Advances
in Social Networks Analysis and Mining (ASONAM'13), 201
Not all the bots are created equal:the Ordering Turing Test for the labelling of bots in MMORPGs
This article contributes to the research on bots in Social Media. It takes as its starting point an emerging perspective which proposes that we should abandon the investigation of the Turing Test and the functional aspects of bots in favor of studying the authentic and cooperative relationship between humans and bots. Contrary to this view, this article argues that Turing Tests are one of the ways in which authentic relationships between humans and bots take place. To understand this, this article introduces the concept of Ordering Turing Tests: these are sort of Turing Tests proposed by social actors for purposes of achieving social order when bots produce deviant behavior. An Ordering Turing Test is method for labeling deviance, whereby social actors can use this test to tell apart rule-abiding humans and rule-breaking bots. Using examples from Massively Multiplayer Online Role-Playing Games, this article illustrates how Ordering Turing Tests are proposed and justified by players and service providers. Data for the research comes from scientific literature on Machine Learning proposed for the identification of bots and from game forums and other player produced paratexts from the case study of the game Runescape
Three-dimensional, transonic rotor flow field reconstructed from holographic interferogram data
Holographic interferometry and computer-assisted tomography (CAT) are used to determine the transonic flow field of a model rotor blade in hover. A pulsed ruby laser records 40 interferograms with a 61 cm-diam view field near the model rotor-blade tip operating at a tip Mach number of 0.90. After digitizing the interferograms and extracting fringe-order functions, the data are transferred to a CAT code. The CAT code then calculates pressure coefficients in several planes above the blade surface. The values from the holography-CAT method compare favorably with previously obtained numerical computations and laser velocimeter measurements at most locations near the blade tip. The results demonstrate the technique's potential for three-dimensional transonic rotor flow studies
Reconstruction of a 3-dimensional transonic rotor flow field from holographic interferogram data
Holographic interferometry and computer-assisted tomography (CAT) are used to determine the transonic velocity field of a model rotor blade in hover. A pulsed ruby laser recorded 40 interferograms with a 2-ft-diam view field near the model rotor-blade tip operating at a tip Mach number of 0.90. After digitizing the interferograms and extracting fringe-order functions, the data are transferred to a CAT code. The CAT code then calculates the perturbation velocity in seeral planes above the blade surface. The values from the holography-CAT method compare favorably with previously obtained numerical computations in most locations near the blade tip. The results demonstrate the technique's potential for three-dimensional transonic rotor flow studies
Star-Formation in Low Radio Luminosity AGN from the Sloan Digital Sky Survey
We investigate faint radio emission from low- to high-luminosity Active
Galactic Nuclei (AGN) selected from the Sloan Digital Sky Survey (SDSS). Their
radio properties are inferred by co-adding large ensembles of radio image
cut-outs from the FIRST survey, as almost all of the sources are individually
undetected. We correlate the median radio flux densities against a range of
other sample properties, including median values for redshift, [OIII]
luminosity, emission line ratios, and the strength of the 4000A break. We
detect a strong trend for sources that are actively undergoing star-formation
to have excess radio emission beyond the ~10^28 ergs/s/Hz level found for
sources without any discernible star-formation. Furthermore, this additional
radio emission correlates well with the strength of the 4000A break in the
optical spectrum, and may be used to assess the age of the star-forming
component. We examine two subsamples, one containing the systems with emission
line ratios most like star-forming systems, and one with the sources that have
characteristic AGN ratios. This division also separates the mechanism
responsible for the radio emission (star-formation vs. AGN). For both cases we
find a strong, almost identical, correlation between [OIII] and radio
luminosity, with the AGN sample extending toward lower, and the star-formation
sample toward higher luminosities. A clearer separation between the two
subsamples is seen as function of the central velocity dispersion of the host
galaxy. For systems with similar redshifts and velocity dispersions, the
star-formation subsample is brighter than the AGN in the radio by an order of
magnitude. This underlines the notion that the radio emission in star-forming
systems can dominate the emission associated with the AGN.Comment: Accepted for publication in Astronomical Journal; 15 pages, 8 color
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