Growth in voice-based applications and personalized systems has led to increasing demand for speech- analytics technologies that estimate the state of a speaker from speech. Such systems support a wide range of applications, from more traditional call-center monitoring, to health monitoring, to human-robot interactions, and more. To work seamlessly in real-world contexts, such systems must meet certain requirements, including for speed, customizability, ease of use, robustness, and live integration of both acoustic and lexical cues. This demo introduces SenSay AnalyticsTM, a platform that performs real-time speaker-state classification from spoken audio. SenSay is easily configured and is customizable to new domains, while its underlying architecture offers extensibility and scalability.
Oceans & space publications
We develop an effective medium model of thermal conductivity that accounts for both percolation and interface scattering. This model accurately explains the measured increase and decrease of thermal conductivity with loading in composites dominated by percolation and interface scattering, respectively. Our model further predicts that strong interface scattering leads to a sharp decrease in thermal conductivity, or an insulator transition, at high loadings when conduction through the matrix is restricted and heat is forced to diffuse through particles with large interface resistance. The accuracy of our model and its ability to predict transitions between insulating and conducting states suggest it can be a useful tool for designing materials with low or high thermal conductivity for a variety of applications.
Radar Detectability Studies of Slow and Small Zodiacal Dust Cloud Particles. II. A Study of Three Radars with Different Sensitivity
The sensitivity of radar systems to detect different velocity populations of the incoming micrometeoroid flux is often the first argument considered to explain disagreements between models of the Near-Earth dust environment and observations. Recently, this was argued by Nesvorný et al. to support the main conclusions of a Zodiacal Dust Cloud (ZDC) model which predicts a flux of meteoric material into the Earth’s upper atmosphere mostly composed of small and very slow particles. In this paper, we expand on a new methodology developed by Janches et al. to test the ability of powerful radars to detect the meteoroid populations in question. In our previous work, we focused on Arecibo 430 MHz observations since it is the most sensitive radar that has been used for this type of observation to date. In this paper, we apply our methodology to two other systems, the 440 MHz Poker Flat Incoherent Scatter Radar and the 46.5 Middle and Upper Atmosphere radar. We show that even with the less sensitive radars, the current ZDC model over-predicts radar observations. We discuss our results in light of new measurements by the Planck satellite which suggest that the ZDC particle population may be characterized by smaller sizes than previously believed. We conclude that the solution to finding agreement between the ZDC model and sensitive high power and large aperture meteor observations must be a combination of a re-examination not only of our knowledge of radar detection biases, but also the physical assumptions of the ZDC model itself.
Oil spills caused by accidents from oil tankers and blowouts of oil and gas from offshore platforms cause tremendous damage to the environment as well as to marine and human life. To prevent oil and gas accidentally released from deep water from spreading and causing further damage over time to the environment, early detection and monitoring systems can be deployed to the area where underwater releases of oil and gas first occurred. Monitoring systems can provide a rapid inspection of the area by detecting chemical substances and collecting oceanography data necessary for enhancing the accuracy of simulation of behavior of oil and gas. An autonomous underwater vehicle (AUV) called the Spilled Oil and Gas Tracking Autonomous Buoy system (SOTAB-I) is being developed to perform onsite measurements of oceanographic data as well as dissolved chemical substances using underwater mass spectrometry. The scope of this paper is limited to the surveying abilities of SOTAB-I in shallow water, although it also has functions for surveying in deep water. The experiment results obtained during the early deployments of SOTAB-I in the shallow water of the Gulf of Mexico in the United States are provided. Oceanographic data, such as the water column distribution of temperature, salinity, and density, as well as the dissolution of chemical substances were measured. In addition, a high-resolution water current profile was obtainable near the seabed.
A presentation of SRI research to meet the need of a thermochemical process that allows economic conversion of wet biomass to liquid fuels.
Poster presented at Bioenergy 2015, Washington D.C., June 23-24, 2015.
Winds in the thermosphere are highly important for transporting mass, momentum, and energy over the globe. In the high-latitude region, observations show that ion and neutral motions are strongly coupled when the aurora is present but the coupling is less evident when there is no aurora. In this study, we investigate the ability of the Global Ionosphere-Thermosphere Model (GITM) to simulate the mesoscale wind structure over Alaska during a substorm. Thirteen distinct numerical simulations of a substorm event that occurred between 02:00 and 17:00 Universal Time on 24 November 2012 have been performed. Distinct drivers considered include the Weimer and SuperDARN potential patterns and the OVATION Prime and OVATION-SME auroral models. The effects of the boundary between the neutral wind dynamo calculation and the high-latitude imposed electric potential were also considered. Neutral wind velocities and thermospheric temperatures measured by the Scanning Doppler Imager instruments located at three locations in Alaska were compared to GITM simulation results, and electron densities within GITM were compared to data from the Poker Flat Incoherent Scatter Radar. It was found that the different drivers used between multiple simulations lead to various amounts of momentum coupling within the simulation, affecting the accuracy of the modeled neutral and ion flow patterns and the strength of electron precipitation at high latitudes. This affirms that better observations of auroral precipitation and electric fields are required to accurately understand and consistently reproduce the mesoscale neutral wind flow patterns and temperature structure in the high-latitude thermosphere.
Direct Measurement of Lower Thermospheric Neutral Density Using Multifrequency Incoherent Scattering
Incoherent scatter (IS) is sensitive to collisional properties of the ion gas when the mean free path is close to the radar wave number. However, it has been traditionally difficult to infer the rate of collisions from IS measurements because of ambiguities in the theory for measurements at a single wave number (k). We demonstrate that multifrequency measurements to achieve diversity in k can allow for direct inference of the composition-weighted ion-neutral collision frequency in the upper mesosphere and lower thermosphere. By direct, we mean that no significant constraints are imposed on the interpretation of the IS spectra and that interpretation relies only on the IS formalism (rather than a steady state ion-momentum equation, for example). The technique is demonstrated using measurements from the European Incoherent Scatter VHF and UHF radar systems. This technique can be used to investigate neutral atmosphere variations as well as the validity of collision models commonly used in the IS formalism.
Observations in the E Region Ionosphere of Kappa Distribution Functions Associated with Precipitating Auroral Electrons and Discrete Aurorae
Precipitating auroral electrons can produce discrete auroral arcs that contain signatures of the magnetospheric auroral source region. Differential number flux observations over two discrete aurorae were obtained by the Auroral Currents and Electrodynamics Structure sounding rocket mission, which successfully launched in 2009. These observations were made at E region altitudes of approximately 130 km. A model of precipitating auroral electrons as described by Evans (1974) was fit to the electron differential number flux obtained by the payloads, and parameters from the model were used to infer properties of the auroral source region. It is shown that the field-aligned precipitating electrons were better fit by a kappa distribution function versus a Maxwellian distribution function for the equatorward side of the first, quasi-stable, auroral arc crossing. The latter half of the first auroral arc crossing and second auroral crossing show that the precipitating electrons were better fit by a Maxwellian distribution function, which provides additional observational confirmation of previous studies. The low-energy electron population determined by the Evans (1974) model was within a factor of 2 of the observed differential number flux. The source region parameters determined from fitting the model to the data were compared with relevant studies from sounding rockets and satellites. Our observations are consistent with the results of Kletzing et al. (2003) that the plasma sheet electrons mapping to auroral zone invariant latitudes are characterized by kappa distribution functions.
The Effect of Solar Flares, Coronal Mass Ejections, and Solar Wind Streams on Venus’ 5577 Angstrom Oxygen Green Line
We observed the Venusian 5577.3 Å OI (1S-1D) (oxygen green line) nightglow emission feature after solar flares, coronal mass ejections (CMEs), and solar wind streams from December 2010 to July 2012 using the high resolution Astrophysical Research Consortium Echelle Spectrograph on the Apache Point Observatory 3.5 m telescope. For the first time since 2004, we detected the green line. The emission is highly temporally variable, with the strongest emission detected being comparable to the previously known brightest detection, and to occur after each of the three types of solar events. We find the greatest emission occurs after CMEs and suggest that particle precipitation is the main contributor to green line emission.