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 figure