Granular synthesis for display of time-varying probability densities

We present a method for displaying time-varying probabilistic information to users using an asynchronous granular synthesis technique. We extend the basic synthesis technique to include distribution over waveform source, spatial position, pitch and time inside waveforms. To enhance the synthesis in interactive contexts, we "quicken" the display by integrating predictions of user behaviour into the sonification. This includes summing the derivatives of the distribution during exploration of static densities, and using Monte-Carlo sampling to predict future user states in nonlinear dynamic systems. These techniques can be used to improve user performance in continuous control systems and in the interactive exploration of high dimensional spaces. This technique provides feedback from users potential goals, and their progress toward achieving them; modulating the feedback with quickening can help shape the users actions toward achieving these goals. We have applied these techniques to a simple nonlinear control problem as well as to the sonification of on-line probabilistic gesture recognition. We are applying these displays to mobile, gestural interfaces, where visual display is often impractical. The granular synthesis approach is theoretically elegant and easily applied in contexts where dynamic probabilistic displays are required

Pointing Without a Pointer

We present a method for performing selection tasks based on continuous control of multiple, competing agents who try to determine the user's intentions from their control behaviour without requiring an explicit pointer. The entropy in the selection process decreases in a continuous fashion -- we provide experimental evidence of selection from 500 initial targets. The approach allows adaptation over time to best make use of the multimodal communication channel between the human and the system. This general approach is well suited to mobile and wearable applications, shared displays and security conscious settings

Sonification of probabilistic feedback through granular synthesis

We describe a method to improve user feedback, specifically the display of time-varying probabilistic information, through asynchronous granular synthesis. We have applied these techniques to challenging control problems as well as to the sonification of online probabilistic gesture recognition. We're using these displays in mobile, gestural interfaces where visual display is often impractical

The pupillary response of cephalopods

This paper provides the first detailed description of the time courses of light-evoked pupillary constriction for two species of cephalopods, Sepia officinalis (a cuttlefish) and Eledone cirrhosa (an octopus). The responses are much faster than hitherto reported, full contraction in Sepia taking less than 1 s, indicating it is among the most rapid pupillary responses in the animal kingdom. We also describe the dependence of the degree of pupil constriction on the level of ambient illumination and show considerable variability between animals. Furthermore, both Sepia and Eledone lack a consensual light-evoked pupil response. Pupil dilation following darkness in Sepia is shown to be very variable, often occurring within a second but at other times taking considerably longer. This may be the result of extensive light-independent variations in pupil diameter in low levels of illumination

Radio-wave propagation in the non-Gaussian interstellar medium

Radio waves propagating from distant pulsars in the interstellar medium (ISM), are refracted by electron density inhomogeneities, so that the intensity of observed pulses fluctuates with time. The theory relating the observed pulse time-shapes to the electron-density correlation function has developed for 30 years, however, two puzzles have remained. First, observational scaling of pulse broadening with the pulsar distance is anomalously strong; it is consistent with the standard model only when non-uniform statistics of electron fluctuations along the line of sight are assumed. Second, the observed pulse shapes are consistent with the standard model only when the scattering material is concentrated in a narrow slab between the pulsar and the Earth. We propose that both paradoxes are resolved at once if one assumes stationary and uniform, but non-Gaussian statistics of the electron-density distribution. Such statistics must be of Levy type, and the propagating ray should exhibit a Levy flight. We propose that a natural realization of such statistics may be provided by the interstellar medium with random electron-density discontinuities. We develop a theory of wave propagation in such a non-Gaussian random medium, and demonstrate its good agreement with observations. The qualitative introduction of the approach and the resolution of the anomalous-scaling paradox was presented earlier in [PRL 91, 131101 (2003); ApJ 584, 791 (2003)].Comment: 27 pages, changes to match published versio

NASA automatic subject analysis technique for extracting retrievable multi-terms (NASA TERM) system

Current methods for information processing and retrieval used at the NASA Scientific and Technical Information Facility are reviewed. A more cost effective computer aided indexing system is proposed which automatically generates print terms (phrases) from the natural text. Satisfactory print terms can be generated in a primarily automatic manner to produce a thesaurus (NASA TERMS) which extends all the mappings presently applied by indexers, specifies the worth of each posting term in the thesaurus, and indicates the areas of use of the thesaurus entry phrase. These print terms enable the computer to determine which of several terms in a hierarchy is desirable and to differentiate ambiguous terms. Steps in the NASA TERMS algorithm are discussed and the processing of surrogate entry phrases is demonstrated using four previously manually indexed STAR abstracts for comparison. The simulation shows phrase isolation, text phrase reduction, NASA terms selection, and RECON display

A Sunyaev-Zel'Dovich-Selected Sample of the Most Massive Galaxy Clusters in the 2500 deg^2 South Pole Telescope Survey

The South Pole Telescope (SPT) is currently surveying 2500 deg^2 of the southern sky to detect massive galaxy clusters out to the epoch of their formation using the Sunyaev-Zel'dovich (SZ) effect. This paper presents a catalog of the 26 most significant SZ cluster detections in the full survey region. The catalog includes 14 clusters which have been previously identified and 12 that are new discoveries. These clusters were identified in fields observed to two differing noise depths: 1500 deg^2 at the final SPT survey depth of 18 μK arcmin at 150 GHz and 1000 deg^2 at a depth of 54 μK arcmin. Clusters were selected on the basis of their SZ signal-to-noise ratio (S/N) in SPT maps, a quantity which has been demonstrated to correlate tightly with cluster mass. The S/N thresholds were chosen to achieve a comparable mass selection across survey fields of both depths. Cluster redshifts were obtained with optical and infrared imaging and spectroscopy from a variety of ground- and space-based facilities. The redshifts range from 0.098 ≤ z ≤ 1.132 with a median of z_(med) = 0.40. The measured SZ S/N and redshifts lead to unbiased mass estimates ranging from 9.8 × 10^(14) M_☉ h^(–1)_(70) ≤ M _(200(ρmean)) ≤ 3.1 × 10^(15) M_☉ h^(–1)_(70). Based on the SZ mass estimates, we find that none of the clusters are individually in significant tension with the ΛCDM cosmological model. We also test for evidence of non-Gaussianity based on the cluster sample and find the data show no preference for non-Gaussian perturbations

It’s a long way to Monte-Carlo: probabilistic display in GPS navigation

We present a mobile, GPS-based multimodal navigation system, equipped with inertial control that allows users to explore and navigate through an augmented physical space, incorporating and displaying the uncertainty resulting from inaccurate sensing and unknown user intentions. The system propagates uncertainty appropriately via Monte Carlo sampling and predicts at a user-controllable time horizon. Control of the Monte Carlo exploration is entirely tilt-based. The system output is displayed both visually and in audio. Audio is rendered via granular synthesis to accurately display the probability of the user reaching targets in the space. We also demonstrate the use of uncertain prediction in a trajectory following task, where a section of music is modulated according to the changing predictions of user position with respect to the target trajectory. We show that appropriate display of the full distribution of potential future users positions with respect to sites-of-interest can improve the quality of interaction over a simplistic interpretation of the sensed data

Show me the way to Monte Carlo: density-based trajectory navigation

We demonstrate the use of uncertain prediction in a system for pedestrian navigation via audio with a combination of Global Positioning System data, a music player, inertial sensing, magnetic bearing data and Monte Carlo sampling for a density following task, where a listener’s music is modulated according to the changing predictions of user position with respect to a target density, in this case a trajectory or path. We show that this system enables eyes-free navigation around set trajectories or paths unfamiliar to the user and demonstrate that the system may be used effectively for varying trajectory width and context

Rehabilitation robot cell for multimodal standing-up motion augmentation

The paper presents a robot cell for multimodal standing-up motion augmentation. The robot cell is aimed at augmenting the standing-up capabilities of impaired or paraplegic subjects. The setup incorporates the rehabilitation robot device, functional electrical stimulation system, measurement instrumentation and cognitive feedback system. For controlling the standing-up process a novel approach was developed integrating the voluntary activity of a person in the control scheme of the rehabilitation robot. The simulation results demonstrate the possibility of “patient-driven” robot-assisted standing-up training. Moreover, to extend the system capabilities, the audio cognitive feedback is aimed to guide the subject throughout rising. For the feedback generation a granular synthesis method is utilized displaying high-dimensional, dynamic data. The principle of operation and example sonification in standing-up are presented. In this manner, by integrating the cognitive feedback and “patient-driven” actuation systems, an effective motion augmentation system is proposed in which the motion coordination is under the voluntary control of the user