Award Data

Current Army logistics systems contain massive amounts of data that need to be effectively extracted into actionable information. But, the databases themselves do not contain all that is needed to make it actionable. The Army needs an effective Enterprise Intelligence System to find data from many sources, process it in an integrated fashion, and disseminate actionable information on the readiness ...

The ability to see and understand the data is critical to situational awareness. As data becomes more prevalent, the need to link causal data into actionable information becomes paramount. Analysts are faced with mountains of data, and finding that piece of relevant information is the proverbial needle in a haystack, only with dozens of haystacks. Analysis tools that facilitate identifying causal ...

Accurate real-time waterborne pathogen detection is of paramount importance to security of U.S. military forces and installations. Fieldable high-throughput pathogen concentration is a critical analytical need for enhanced detection performance. Existing concentration methods are time-consuming, bulky, labor-intensive, power- and reagent-hungry, and consequently ill-suited for battlefield deployme ...

Current methods for detecting toxicity in food are labor intensive, time-consuming and require access to sophisticated laboratory equipment. To overcome these limitations we propose to develop a novel, microfluidics yeast-based sensor system for detection of Toxic Industrial Chemicals (TICs) in food. Robust yeast cell wires and membrane patches will be assembled on-demand and in-situ from suspensi ...

The goal of this project is to develop a computational algorithm/model to detect subtle changes in neurobiology of sleep-wake cycle due to mild TBI. We aim to quantify early enough the subtle changes in sleep-wake disorder by correlating objective sleep quality measurements as model inputs to the “Injury Leonardo” framework that

Including radiative heat transfer in full-vehicle thermal analysis simulations results in nonlinear equations with coefficient matrices that are dense, poorly conditioned, and difficult to solve. Further, calculating and storing view factors¯needed for surface-to-surface radiative fluxes¯is computationally prohibitive on fine grids. In the proposed SBIR project, CFDRC will develop, validate and ...

This Phase I SBIR program will develop an information system and design a nano-Toolkit with data-mining and predictive models for accelerated risk assessment of engineered nanomaterial attributes. It was recently shown that nanomaterials used in warfighter technologies may be responsible for significant human health and environmental risks. For example, researchers at the Army’s Engineer Resear ...

The goal of this project is to develop and deliver a rugged and portable human head/brain physical phantom that could be used for evaluation of existing and next generation EEG equipment. We will also develop, validate and deliver a virtual computational head phantom that could be used for evaluation of source localization. Computational models will be used to design both simple and anatomical hea ...

The objective of this SBIR program is to integrate scientific programs and associated databases within a Graphical User Interface (GUI)-driven wrapper to facilitate their use by the Army to assess the fate and transport of munitions and their effect on human health. The GUI will help ease data transfer between the programs, reducing the scope of user error and increasing productivity. In Phase I, ...

During the process of using Model Based Design and Implementation (MBDI), challenges have been identified with the loss of traceability between the higher level model of the system and the lower level implementation. This results in difficulty to optimize the system since feedback from the system is related to the lower level constructions. CohesionForce proposes a Model Annotation Tool (MAT) that ...