Publications

Unmanned Aircraft Systems require an ability to sense and avoid other air traffic to gain access to civil airspace and meet requirements in civil aviation regulations. One sense and avoid function is self separation, which requires that aircraft remain well clear. An approach is proposed in this paper to treat...

The development and evaluation process of the Tower Flight Data Manager prototype at Dallas Ft. Worth airport is described. Key results from the first field evaluation are presented, including lessons learned about making electronic flight information acceptable to controllers. Iteration of the field evaluation methods are discussed for practitioner benefit.

A concept of operations for the Integrated Departure Route Planner (IDRP) tool is proposed to address issues in the area of departure route management. By combining information about weather and departure demand, IDRP can both identify potential demand/capacity imbalances and recommend a rerouting option, if appropriate. To effectively implement IDRP...

High-sensitivity (ng/cm2) optical detection of the explosive 2,4,6- trinitrotoluene (TNT) is demonstrated using photodissociation followed by laser-induced fluorescence (PD-LIF). Detection occurs rapidly, within 6 laser pulses (~7 ns each) at a range of 15 cm. Dropcasting is used to create calibrated samples covering a wide range of TNT concentrations; and...

This paper summarizes progress of a project to develop and advance the maturity of photon-counting detectors for NASA exoplanet missions. The project, funded by NASA ROSES TDEM program, uses a 256x256 pixel silicon Geiger-mode avalanche photodiode (GM-APD) array, bump-bonded to a silicon readout circuit. Each pixel independently registers the arrival...

We present a new perspective on the subspace compensation techniques that currently dominate the field of speaker recognition using Gaussian Mixture Models (GMMs). Rather than the traditional factor analysis approach, we use Gaussian modeling in the sufficient statistic supervector space combined with Probabilistic Principal Component Analysis (PPCA) within-class and shared...

In this paper, a new language identification system is presented based on the total variability approach previously developed in the field of speaker identification. Various techniques are employed to extract the most salient features in the lower dimensional i-vector space and the system developed results in excellent performance on the...

Regions of nonmodal phonation, exhibiting deviations from uniform glottal-pulse periods and amplitudes, occur often and convey information about speaker- and linguistic-dependent factors. Such waveforms pose challenges for speech modeling, analysis/synthesis, and processing. In this paper, we investigate the representation of nonmodal pulse trains as a sum of harmonically-related sinewaves with...

Of increasing importance in the civilian and military population is the recognition of Major Depressive Disorder at its earliest stages and intervention before the onset of severe symptoms. Toward the goal of more effective monitoring of depression severity, we investigate automatic classifiers of depression state, that have the important property...

This work presents techniques for automatically summarizing the topical content of an audio corpus. Probabilistic latent semantic analysis (PLSA) is used to learn a set of latent topics in an unsupervised fashion. These latent topics are ranked by their relative importance in the corpus and a summary of each topic...