Award Data

Our proposed second order uncertainty (SOU) product is a decision making software solution that addresses the problem of providing accurate and precisely defined decision courses of action (COAs) of complex, time-constrained problems in a fraction of the time required by alternative methods striving to achieve the same level of precision. Complex decision situations can deal with large volume of ...

The goal of this program is to design a lightweight optical bench capable of remaining stable under temperature and moisture changes, while isolating the precision optical array from vibrations such as engine noise and air turbulence. By integrating a customizable periodic stack in the bench, vibrations are attenuated more effectively than commercially available mounts. Additionally, the periodic ...

Physical Sciences Inc. (PSI) proposes to design, develop, and demonstrate a portable, non-invasive, real-time sensor to assess the chemical and physical health of solid rocket motors as a function of age without affecting the motors integrity nor having direct contact with the propellant. In Phase II, a sensor to monitor specific gas species that are markers of the chemical and mechanical aging pr ...

A critical step in the extraction of elements from ore, especially rare earth elements that are found in complex minerals, is separation. Froth flotation is a highly versatile method for physically separating particles based on differences in the ability of air bubbles to selectively adhere to specific mineral surfaces in a mineral/water slurry. The particles with attached air bubbles are then ca ...

Empirical-based mathematical framework and computer algorithms, for representing human perception and cognition processes and limitations, which influence the recognition of salient information about rapidly changing events.

Boston Fusion, together with our teammate Syracuse University, propose a program of research and development, Uncertainty Characterization Using Copulas (UC)2, that will result in a parametric framework based on the statistical theory of copulas for modeling uncertainties for the problem of object classification. (UC)2 will produce a mathematical framework, founded on rigorous theoretical analysis ...

In our Adaptive Management and Mitigation of Uncertainty in Fusion (AMMUF) project, we will model the entire multi-sensor fusion process as a probabilistic model and reason about the different design and algorithmic decisions that can be made by system engineers. This fusion model will use standard fusion system representations and ideas from statistical relational learning field to create flexibl ...

The ultimate goal of this proposed effort is to better utilize disparate sensor data to perform better correlations and lethality assessments through the development of a sensor data fusion system using artificial intelligence (AI) techniques and the concept of extracting features from raw sensor data and reasoning about those features and their hypothetical association with hypothesized objects. ...

Toyon developed a Phase I framework leveraging spatiotemporal image processing algorithms for non-stationary clutter estimation, and nonlinear filtering based Track-before-Detect algorithms for tracking targets. Information is fused across sensors without loss of information due to detection thresholds. Algorithms, when applied jointly, provide a near-optimal solution. In addition, algorithms a ...

The goal of the proposed work is to develop a human-centric training and assessment system for cyber situation awareness. The envisioned system will enable instructors to define training goals, design lesson plans, assign students roles in teams, and observe students performance, record events and interactions for scoring. The instructor/students can place tags (time or event) to roll back or repl ...