Award Data

Cyber Risk Assessments for Threatened Environments (CRATE) is a system that produces actionable, mission-level alerts when anomalous behaviors indicative of cyber-attack are discovered within deployed mission-critical cyber-systems. CRATE is particularly relevant to deployment scenarios involving third-party infrastructure, such as deployment to a Platform as a Service (PaaS) provider or other clo ...

Research is currently identifying new biochemical markers to help monitor cognition and stress in the human body and enhance human performance. Traditional biometric markers like heart rate, temperature, oxygen partial pressure, blood glucose, electrolyte concentration, and others have been correlated with cognition and stress states. However, the correlation is indirect. Molecular biomarkers with ...

This effort will investigate the use MALDI (matrix assisted laser desorption/ionization)-TOF (time-of-flight) mass spectrometer as a platform for rapid analysis of biomarkers in operational and training environments. In Phase I samples, will be acquired from human subjects under stress. These samples will be processed for analysis using our prototype portable MALDI TOF mass spectrometer. Samples w ...

The objective of this effort matures a technology called EagleEye Sentinel Hosted – Secure Overlay System Protect (ESH-SOSP), to provide a new security layer for normal cyber physical system (CPS) operations as the basis for detecting system anomalies and cyber-attacks for the U.S. Air Force. ESH-SOSP technology provides the security analyst the means to have all the necessary and relevant ...

The objective is to develop zonal multi-physics capability for turbulent combustion simulations. The foundation of the proposed work is a novel Pareto-Efficient Combustion (PEC) framework for fidelity-adaptive combustion modeling. The PEC model utilizes a combustion submodel assignment, combining the low-cost flamelet-based models with the more expensive finite rate chemistry models where necessar ...

For this STTR Intelligent Automation, Inc. teams with researchers from University of Maryland, College Park to develop SLA, a self-learned agent system for collective human activities and events in aerial videos. Aerial video analytics often faces challenges such as low resolution, shadows, varied spatio-temporal dynamics, etc. The traditional methods depending on the object detection and tracking ...

Accurate knowledge of heat flux is critical in assessing the design, performance, and survivability of hypersonic flight vehicles. Despite decades of research and testing, much is still unknown regarding hypersonic instabilities and transition mechanisms that define the state of the boundary layer. While the existence of these features is known, the ability to accurately measure them remains a cha ...

The machine learning and artificial intelligence community has recently garnered much attention for ground breaking performance of novel neural network architectures for self-driving cars. One of the machine learning methods used in self-driving cars is semantic segmentation. In this fashion each pixel in an image is label with a class, allowing for contour-based image segmentation which is differ ...

Faraday and Utah State University propose to demonstrate the feasibility of utilizing electrophoretic deposition to develop graphene features with controlled functional properties in order to address the DoD need for a spacecraft charging mitigation. Implementation of such materials in DoD mission areas is anticipated to lower costs, improve sustainability, and increase readiness. The proposed Pha ...

The project will develop and validate a geometry scalable CNTFET compact model for HF circuit design and extract the model parameters from the measured characteristics of the fabricated devices. The ballistic and quasi-ballistic transport, quantum and parasitic effects will be accounted for the predicted performance will be compared to 130 nm RF Si-CMOS to determine the conditions for breaking eve ...