Presenting in Virtual Worlds: An Architecture for a 3D Anthropomorphic Presenter

Multiparty-interaction technology is changing entertainment, education, and training. Deployed examples of such technology include embodied agents and robots that act as a museum guide, a news presenter, a teacher, a receptionist, or someone trying to sell you insurance, homes, or tickets. In all these cases, the embodied agent needs to explain and describe. This article describes the design of a 3D virtual presenter that uses different output channels (including speech and animation of posture, pointing, and involuntary movements) to present and explain. The behavior is scripted and synchronized with a 2D display containing associated text and regions (slides, drawings, and paintings) at which the presenter can point. This article is part of a special issue on interactive entertainment

Brief Mindfulness Meditation Improves Attention In Novices: Evidence From ERPs And Moderation By Neuroticism

Past research has found that mindfulness meditation training improves executive attention. Event-related potentials (ERPs) have indicated that this effect could be driven by more efficient allocation of resources on demanding attentional tasks, such as the Flanker Task and the Attention Network Test (ANT). However, it is not clear whether these changes depend on long-term practice. In two studies, we sought to investigate the effects of a brief, 10-min meditation session on attention in novice meditators, compared to a control activity. We also tested moderation by individual differences in neuroticism and the possible underlying neural mechanisms driving these effects, using ERPs. In Study 1, participants randomly assigned to listen to a 10-min meditation tape had better accuracy on incongruent trials on a Flanker task, with no detriment in reaction times (RTs), indicating better allocation of resources. In Study 2, those assigned to listen to a meditation tape performed an ANT more quickly than control participants, with no detriment in performance. Neuroticism moderated both of these effects, and ERPs showed that those individuals lower in neuroticism who meditated for 10 min exhibited a larger N2 to incongruent trials compared to those who listened to a control tape; whereas those individuals higher in neuroticism did not. Together, our results support the hypothesis that even brief meditation improves allocation of attentional resources in some novices

Homogeneous Analysis of the Dust Morphology of Transition Disks Observed with ALMA: Investigating Dust Trapping and the Origin of the Cavities

We analyze the dust morphology of 29 transition disks (TDs) observed with ALMA at (sub-) millimeter-emission. We perform the analysis in the visibility plane to characterize the total flux, cavity size, and shape of the ring-like structure. First, we found that the $M_{\rm{dust}}-M_\star$ relation is much flatter for TDs than the observed trends from samples of class II sources in different star forming regions. This relation demonstrates that cavities open in high (dust) mass disks, independent of the stellar mass. The flatness of this relation contradicts the idea that TDs are a more evolved set of disks. Two potential reasons (not mutually exclusive) may explain this flat relation: the emission is optically thick or/and millimeter-sized particles are trapped in a pressure bump. Second, we discuss our results of the cavity size and ring width in the context of different physical processes for cavity formation. Photoevaporation is an unlikely leading mechanism for the origin of the cavity of any of the targets in the sample. Embedded giant planets or dead zones remain as potential explanations. Although both models predict correlations between the cavity size and the ring shape for different stellar and disk properties, we demonstrate that with the current resolution of the observations, it is difficult to obtain these correlations. Future observations with higher angular resolution observations of TDs with ALMA will help to discern between different potential origins of cavities in TDs

Mathematical practice, crowdsourcing, and social machines

The highest level of mathematics has traditionally been seen as a solitary endeavour, to produce a proof for review and acceptance by research peers. Mathematics is now at a remarkable inflexion point, with new technology radically extending the power and limits of individuals. Crowdsourcing pulls together diverse experts to solve problems; symbolic computation tackles huge routine calculations; and computers check proofs too long and complicated for humans to comprehend. Mathematical practice is an emerging interdisciplinary field which draws on philosophy and social science to understand how mathematics is produced. Online mathematical activity provides a novel and rich source of data for empirical investigation of mathematical practice - for example the community question answering system {\it mathoverflow} contains around 40,000 mathematical conversations, and {\it polymath} collaborations provide transcripts of the process of discovering proofs. Our preliminary investigations have demonstrated the importance of "soft" aspects such as analogy and creativity, alongside deduction and proof, in the production of mathematics, and have given us new ways to think about the roles of people and machines in creating new mathematical knowledge. We discuss further investigation of these resources and what it might reveal. Crowdsourced mathematical activity is an example of a "social machine", a new paradigm, identified by Berners-Lee, for viewing a combination of people and computers as a single problem-solving entity, and the subject of major international research endeavours. We outline a future research agenda for mathematics social machines, a combination of people, computers, and mathematical archives to create and apply mathematics, with the potential to change the way people do mathematics, and to transform the reach, pace, and impact of mathematics research.Comment: To appear, Springer LNCS, Proceedings of Conferences on Intelligent Computer Mathematics, CICM 2013, July 2013 Bath, U

The Challenges of Real-Time AI

The research agendas of two major areas of computer science are converging: Artificial Intelligence (AI) methods are moving towards more realistic domains requiring real-time responses, and real-time systems are moving towards more complex applications requiring intelligent behavior. Together, they meet at the crossroads of interest in "real-time intelligent control," or "real-time AI." This subfield is still being defined by the common interests of researchers from both real-time and AI systems. As a result, the precise goals for various real-time AI systems are still in flux. This paper describes an organizing conceptual structure for current real-time AI research, clarifying the different meanings this term has acquired for various researchers. Having identified the various goals of real-time AI research, we then specify some of the necessary steps towards reaching those goals. This in turn enables us to identify promising areas for future research in both AI and real-time systems techniques. (Also cross-referenced as UMIACS-TR-94-69