Award Data

The goal of the proposed project is to create Kin-X, a novel software system to generate both rapid and deep intelligence from a wide variety of DNA types by inferring distant kinship relationships between individuals and reconstructing familial pedigrees. Kinship inference and pedigree reconstruction are both computationally intensive processes, and our proposed system is designed to achieve both ...

This STTR Phase II project proposes development of a statistical relational learning framework for identification of the function of laboratory equipment from imagery. The proposed framework uses semantic reasoning to incorporate evidence from multiple classifiers and feature extractors, domain knowledge, and scene context for scene understanding and labeling. The Phase II effort will focus on dev ...

The Defense Threat Reduction Agency, DTRA, currently uses technologies capable of detecting IEDs using airborne sensors that are demonstrated as reliable. These systems are only used for detection purposes and are not capable of neutralizing the IED. Due to IEDs being located in remote, dangerous, and hostile locations, there is high casualty risk for personnel to manually neutralize the target by ...

This is a proposal to develop a unique, Ultrashort Pulsed Off-axis Digital Holography (USPODH) system, enabling the high frequency imaging of detailed 3D structures within aerosol fields under harsh thermodynamic conditions and high optical depths where ordinary imaging is essentially useless. Many powerful imaging methods have failed to provide this capability because noise from multiple scatteri ...

To fully understand the combustion dynamics when chemical warfare agents are detonated, fast time-scale diagnostics are needed. While computational modeling may provide insight into the different processes, experimental measurements are needed to verify and validate these models. Since the detonation or combustion of chemical agents can result in optically thick fireballs, innovative techniques mu ...

Reliable automated pattern recognition in the current system is limited by excessive noise and clutter combined with insufficient and/or ambiguous features. Our team consisting of AcornSI and Leidos thus propose a multi-step approach based on the combined effects of improved detection, feature extraction, phase identification, and global association. A key innovation here is creating a new classif ...

In this project, we propose to identify and examine solution growth approaches for engineering perovskite single crystal for gamma spectrometry in a hand-held sensor format. We will demonstrate that the solution growth approach is able to produce perovskite single crystal in sufficient volume and quality to yield a detector crystal whose utilization presents no inherent environmental, health, or s ...

With the advent of high-density low-power sub-20nm technology processes and circuits with tens-of-billions of transistors, radiation-induced single-event effects present a new set of design challenges for terrestrial applications. Developing reliable single-event effect resilient microelectronics in these modern technology nodes is a resource and time-intensive endeavor that further requires valid ...

During the Phase I effort, Semandex Networks and its team developed a prototype capability to detect trends in research publications by automatically identifying emerging concepts within the data. The implemented capability provides insights into past and

DTRA uses High Fidelity Computer Codes (HFCC) to investigate weapon effects and techniques for countering Weapons of Mass Destruction (WMD). End-to-end HFCC simulations in support of the DTRA Agent Defeat Warfighter Capability will require calculations including multiple phenomena that occur in vastly different time scales (µ-sec to hours). As DTRA becomes increasingly reliant on computational mo ...