Hot coronal loops associated with umbral brightenings

We analyzed AIA/SDO high-cadence images in all bands, HMI/SDO data, soft X-ray images from SXI/GOES-15, and Halpha images from the GONG network. We detected umbral brightenings that were visible in all AIA bands as well as in Halpha. Moreover, we identified hot coronal loops that connected the brightenings with nearby regions of opposite magnetic polarity. These loops were initially visible in the 94 A band, subsequently in the 335 A band, and in one case in the 211 A band. A differential emission measure analysis revealed plasma with an average temperature of about 6.5x10^6 K. This behavior suggests cooling of impulsively heated loops.Comment: A&A, 2013, in pres

Learning how to do things with imitation

In this paper we discuss how agents can learn to do things by imitating other agents. Especially we look at how the use of different metrics and sub-goal granularity can affect the imitation results. We use a computer model of a chess world as a test-bed to also illustrate issues that arise when there is dissimilar embodiment between the demonstrator and the imitator agents

Synoptic study of the corona at meter wavelength

The Mark III Nancay Radioheliograph is used to observe the Sun at 169 MHz with a time resolution of 25 East-West and North-South images per second. When the brightness distribution of the Sun is stable during the eight hours of daily observation, a two dimensional map can be produced using the technique of earth rotation synthesis. The best images are obtained during the period April to August, when the declination of the Sun is high to give a good coverage in the uv plane and a reasonable North-South resolution. The spatial resolution is 1.5' East-West and in summer, 3.5' North-South. The maps are calibrated using Cygnus A as a reference. Examples of the maps are given and discussed

Achieving Corresponding Effects on Multiple Robotic Platforms: Imitating in Context Using Different Effect Metrics

Original paper can be found at: www.aisb.org.uk/publications/proceedings/aisb05/3_Imitation_Final.pdfOne of the fundamental problems in imitation is the correspondence problem, how to map between the actions, states and effects of the model and imitator agents, when the embodiment of the agents is dissimilar. In our approach, the matching is according to different metrics and granularity. This paper presents JABBERWOCKY, a system that uses captured data from a human demonstrator to generate appropriate action commands, addressing the correspondence problem in imitation. Towards a characterization of the space of effect metrics, we are exploring absolute/relative angle and displacement aspects and focus on the overall arrangement and trajectory of manipulated objects. Using as an example a captured demonstration from a human, the system produces a correspondence solution given a selection of effect metrics and starting from dissimilar initial object positions, producing action commands that are then executed by two imitator target platforms (in simulation) to successfully imitate