Living analytics methods for the social web

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The accretion disk in the post period-minimum cataclysmic variable SDSS J080434.20+510349.2

This study of SDSS0804 is primarily concerned with the double-hump shape in the light curve and its connection with the accretion disk in this bounce-back system. Time-resolved photometric and spectroscopic observations were obtained to analyze the behavior of the system between superoutbursts. A geometric model of a binary system containing a disk with two outer annuli spiral density waves was applied to explain the light curve and the Doppler tomography. Observations were carried out during 2008-2009, after the object's magnitude decreased to V~17.7(0.1) from the March 2006 eruption. The light curve clearly shows a sinusoid-like variability with a 0.07 mag amplitude and a 42.48 min periodicity, which is half of the orbital period of the system. In Sept. 2010, the system underwent yet another superoutburst and returned to its quiescent level by the beginning of 2012. This light curve once again showed a double-humps, but with a significantly smaller ~0.01mag amplitude. Other types of variability like a "mini-outburst" or SDSS1238-like features were not detected. Doppler tomograms, obtained from spectroscopic data during the same period of time, show a large accretion disk with uneven brightness, implying the presence of spiral waves. We constructed a geometric model of a bounce-back system containing two spiral density waves in the outer annuli of the disk to reproduce the observed light curves. The Doppler tomograms and the double-hump-shape light curves in quiescence can be explained by a model system containing a massive >0.7Msun white dwarf with a surface temperature of ~12000K, a late-type brown dwarf, and an accretion disk with two outer annuli spirals. According to this model, the accretion disk should be large, extending to the 2:1 resonance radius, and cool (~2500K). The inner parts of the disk should be optically thin in the continuum or totally void.Comment: 12 pages, 15 figures, accepted for publication in A&

Personalized Event-Based Surveillance and Alerting Support for the Assessment of Risk

In a typical Event-Based Surveillance setting, a stream of web documents is continuously monitored for disease reporting. A structured representation of the disease reporting events is extracted from the raw text, and the events are then aggregated to produce signals, which are intended to represent early warnings against potential public health threats. To public health officials, these warnings represent an overwhelming list of "one-size-fits-all" information for risk assessment. To reduce this overload, two techniques are proposed. First, filtering signals according to the user's preferences (e.g., location, disease, symptoms, etc.) helps reduce the undesired noise. Second, re-ranking the filtered signals, according to an individual's feedback and annotation, allows a user-specific, prioritized ranking of the most relevant warnings. We introduce an approach that takes into account this two-step process of: 1) filtering and 2) re-ranking the results of reporting signals. For this, Collaborative Filtering and Personalization are common techniques used to support users in dealing with the large amount of information that they face.Comment: International Meeting on Emerging Diseases and Surveillance. IMED 2011 - Poster Session - Vienna, Austria. February 4-7, 201