Award Data

Fog and smog reduce visibility at sea, greatly impacting ship navigation and safety. Low visibility marine conditions decrease speed and safety of commercial fleets and increase costs through poor fuel load planning. The COVID-19 pandemic underscored the importance of maritime operations to the supply chain; therefore, decreasing associated cost and risk are of the utmost importance. Applied Ocean ...

"Metron proposes to develop user-friendly software to promote understanding of impacts due to cascading climate hazards and extreme weather events, in collaboration with George Mason University (GMU). Climate and extreme weather (CEW) hazards pose significant risks to life and property. As extreme events become more prevalent, risks associated with cascading, compound events come to the fore, such ...

Face masks and respirators are frequently deployed in critical protective applications (such as medical and construction environments) where fit testing is not routinely performed before each shift. N95 and related testing protocols effectively assess filtration efficiency for respirators that remain tightly fitted throughout activity, but since these protocols prescribe sealing the tested product ...

The 21st century is the Age of the Network. Operators and clients of critical infrastructure networks are now vulnerable to cascading failures that they could not have seen coming. “Cascading” failure events remain a vital unsolved challenge as critical infrastructure network operators and regulators struggle to define and operationalize resilience, and measurement of interdependent network re ...

This research aims to develop decision support tools for better maintenance and planning of renewable energy generation and storage assets using atmospheric, local weather, and on-ground environmental data blended with site-, regional- and national-generation data. The study will use a combination of these data to understand the relationship between non-cloud cover based atmospheric conditions and ...

The primary objective of this project is to improve awareness, safety and enjoyment for mariners in coastal and inland waters by the creation of a participatory sensor network (PSN) that facilitates sharing of marine observations with other mariners. We are adding a new degree of temporal fidelity to nautical charts and maps. The approach leverages volunteered geographic information to augment con ...

We propose to use Aerosol Optical Depth (AOD) measurements as an early warning system, to cue on-site validation of the soiling station and any available meteorological (MET) station data to validate if a work order to clean deposited particulate matter is necessary. This would move from reactive maintenance – often weeks delayed, to proactive maintenance – getting ahead of the weather impact ...

CoVar’s DOCTRINAIRE is a new approach to computer aided object annotation that is modeled after the way expert end-users leverage generic, robust background information (e.g., what wheels look like) and known doctrine (the size and shape of components on a pickup truck) to perform reliable, explainable object detection and annotation. Our approach solves the robustness problem by training a reli ...

The primary goal of this proposed project is to develop a general-purpose technique for the problem of algorithm parameter selection (APS) that achieves the best performance of the algorithm and demonstrates its effectiveness within graph analysis, for the problem of community detection, or clustering.  Cell Matrix Corporation (CMC) will develop a means to greatly simplify the tweaking typically ...

LUCID (Land Use Classification Intelligence Discovery) is a novel artificial intelligence (AI) system that achieves on-demand classification of fine-grained Land Use and Land Cover (LULC) categories to create detailed LULC-annotated geospatial grid maps by orchestrating seamless fusion of satellite imagery, remote sensing, and non-imagery geospatial data layers. LUCID fuses multiple data sources/m ...