Award Data

The Sonalysts Team proposes to investigate, design, and develop a training system leveraging state-of-the art game and agent-based technologies with"TRILOGY,"a Modeling, Simulation, and Training (MST) system capable of three core capabilities: training, rehearsal, and analysis/CONOPS development. Sonalysts will leverage their latest commercial-off-the-shelf (COTS) game engine, Simulation Engine I ...

ABSTRACT: In ISR applications, multiple sensors can be employed to achieve more accurate parameters of interest on targets, improving discrimination and detection. But, the proliferation of sensor systems has created a large volume of multi-sensor data across a number of physical spectra. These resulting measurements can be so disparate that traditional aggregation methods perform poorly given h ...

ABSTRACT: The Sonalysts team proposes to develop a solution that facilitates the flow of data between different levels of classification while improving and ensuring both security and data integrity. Our approach involves a set of protocols that provide a unique and disruptive combination of multichannel data dispersion and multi-classification data management techniques to meet our objectives. ...

Mathematical models of physical and biological systems contain parameters that need to be estimated from measured data. Models with parameters distributed probabilistically require the estimates of a probability measure over the set of admissible parameters. We propose to use frequentist-based approaches for non-parametrically estimating probability measures that describe the distribution of par ...

The broader impact/commercial potential of this project includes applications ranging from peak load shifting, grid buffering for renewable energy input, frequency regulation, and chemical conversions. As the percentage of energy from renewables on the grid increases, energy storage will be essential to stabilize the supply and demand. Currently, 20-40% of wind energy is often stranded due to the ...