Award Data

Conflict hinges on human behavior, but today's combat simulations only represent behavior in terms of heuristics. Yet these rule-based representations. fail to include human variability earning, and being intelligently interactive. They do not take advantage of an adversary's mistakes. An empirical modeling of behavior is difficult because behavior is intent and situation dependent. In contrast, a ...

Exiting simulation, training, and agent-based systems either do not address the modeling of individual behavior, or assume normative performance, thereby failing to exhibit expected performance variations due to individual differences factors (i.e., cognitive, affective, and personality variables). This shortcoming seriously limits realism of the resulting simulations, thereby reducing their utili ...

Simulation environments offer a safe, inexpensive alternative to live exercises, but the entities which populate them lack many important human behavioral characteristics such as fear, frustration, anger, and fatigue. Such emotions influence how situations are interpereted, how attention is focused, which actions are considered and selected for execution, and how these actions are executed. The pr ...

We propose to develop a prototype of a novel spintronic spectrum analyzer using an array of nano-scale magnetic spin-torque detectors. The operation of the proposed spectrum analyzer is based on the recently discovered effects of spin-transfer torque and spin-diode effects in nano-scale magnetic multilayered elements, the fabrication of which became possible due to the recent advances in nano-fabr ...

This STTR project will develop a wearable sensor suite for accurate assessment of circadian and sleep rhythms with the goal to identify abnormalities in PTSD patients and enable personalized therapy to help restore their normal functional and quality of life. Phase I has already demonstrated proof-of-principle hardware. The primary Phase II objective is to successfully carry out a human subjects s ...

BaySpec Inc., in collaboration with Pacific Northwest National Laboratory, proposes to develop a new portable multi-order mass spectrometry system that can sequence peptides derived from biological agents including bacteria, viruses, and toxins. During Phase I stage, a fully functional prototype instrument, based on an innovative design concept, was successfully built and the performance evaluatio ...

On this effort Toyon Research Corp. and The Pennsylvania State University are developing deep learning-based algorithms for object recognition and new class discovery in look-down infrared (IR) imagery. Our approach involves the development of a hybrid classifier that exploits both transfer learning and semi-supervised paradigms in order to maintain good generalization accuracy, especially when li ...

Signature Research, Inc. (SGR) and Michigan Technological University (MTU) propose a Phase I STTR effort to develop a learning algorithm which exploits the spatio-spectral characteristics inherent within IR imagery and motion imagery.Our archive of modelled and labeled data sets will allow our team to thoroughly capture the variable elements that will drive machine learning performance.The overall ...

The Tunable Active HEterodyne Terahertz Imager (TAHETI) system will use Terahertz Quantum-Cascade Lasers (QCL) combined with a Schottky diode detector for ultra-high dynamic range heterodyne imaging. Distributed feedback (DFB) QCLs with milliwatt power levels are engineered to emit at slightly offset frequencies, and are used as local oscillator and illumination for imaging. The QCLs will be down ...

Scanning probe microscopy (SPM) is a technique used to detect near-field interaction when a sample is rater-scanned by a probe. Example include atomic force microscope (AFM) and scanning tunneling microscope (STM). It offers nanometric and atomic image resolution. In this field, an emerging technique, Near-Field Scanning Microwave Microscopy (SMM), utilizes microwave evanescent waves to attain the ...