Award Data

Decontamination of military personnel, equipment and facilities that have been exposed to deadly biological and / or chemical warfare agents is of critical concern to U.S. Armed Forces. Conventional technologies used for decontamination and sterilization suffer from drawbacks that include toxic effluents, radiation hazards to personnel, and very long time scales for the decontamination process pr ...

An efficient blue laser concept is proposed based on two-photon upconversion of diode laser near-IR radiation into the blue in a doped-crystal fiber. The upconversion process offers certain performance advantages not readily realized from a system containing nonlinear elements, such as resistance to damage and more relaxed requirements on the laser medium. With thulmium as the doping ion, wavelen ...

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 ...

An optical pulse generator based on photorefractive effect and optical bistability is proposed for applications in all-0ptical pulse coupled neural networks. The novel device employs the dynamic memory function of photorefractive crystal and the regenerative pulsation property of optical bistable devices (OBDs). It consists of a photorefractive crystal, and OBD and an optical feedback loop. It ...

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 ...

Methods for interconversion between cell types (cellular reprogramming) are currently discovered through resource intensive trial and error. Experiments may test a multitude of transcription factors to identify correct combinations that influence cell fate. In addition, reprogramming approaches commonly use stem cell intermediates such as induced pluripotent stem cells (iPSCs), which are generated ...

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 ...

CONCUR develops a computational framework for assessing and characterizing urban environments stability or fragility in response to volatility and stress, identifying specific weaknesses as well as key tipping points which could lead to rapid systemic failure. CONCUR explicitly models urban environments as emergent complex systems, focusing attention on the critical triggers that could lead to rap ...