Award Data

This SBIR addresses EPA’s need for improved sampling and analysis technologies to detect Per- and Polyfluoroalkyl Substances (PFAS). PFAS are used in firefighting sprays, at airports, and for wild fires, and have been used in textile treatments (e.g., it is a component in Scotchgard). It is estimated that 65 million Americans are at risk of PFAS exposure in their drinking water. Seacoast propose ...

Advances in materials and automation are rapidly reshaping the American manufacturing economy. These advances must be embraced to sustain a strong manufacturing sector in the United States. Additive manufacturing is possibly the fastest growing example of this trend, growing at an astonishing compound annual growth rate of 25.7%. The plastic materials market for additive manufacturing, valued at $ ...

Need: People are exposed to formaldehyde, a carcinogen found in building materials. Highly sensitive, real-time formaldehyde sensors would improve human safety by alerting users to harmful concentrations. _x000D_ _x000D_ Technical Feasibility: Vaporsens produces chemical sensors based on novel organic nanofiber technology. Phase 1 results demonstrated high selectivity, rapid-response time, and dem ...

Recognizing the need to monitor formaldehyde gas in residential and industrial buildings,_x000D_ Giner, Inc. (Giner) will continue the successful work started in Phase I and will develop,_x000D_ fabricate and demonstrate a formaldehyde gas monitor that is capable of continuously_x000D_ measuring formaldehyde in the range of 0-2000 parts per billion (ppb) with a resolution of 10 ppb. The wireless c ...

Of the 300 million tons of plastic produced per year most will require 500 years to biodegrade. Currently only 9% is recycled, and 50 million tons of thermoset plastic produced annually that can't be recycled. _x000D_ _x000D_ This project will develop a sustainable and easily biodegradable polycarbonate plastic that is uniquely a recyclable thermoset resin. We call it a thermosetting thermoplastic ...

On this effort Toyon Research Corp. and The Pennsylvania State University are developing deep learning-based algorithms for object recognition and new class discovery in look-down infrared (IR) imagery. Our approach involves the development of a hybrid classifier that exploits both transfer learning and semi-supervised paradigms in order to maintain good generalization accuracy, especially when li ...

Toyon Research Corporation proposes to research and develop algorithms for low-shot object detection, adapting popular techniques to address the complexities inherent in ATR for remote sensing. Traditional object detection algorithms rely on large corpora of data which may not be available for more exotic targets (such as foreign military assets), and therefore, traditional Convolutional Neural Ne ...

Ground vehicles with navigation capability (e.g., GPS) can index into foundation data (e.g., Google Maps) to gain situational awareness abouttheir surroundings. When GPS and RF navigation sources are degraded, maintaining situational awareness requires an alternative navigationsource. One alternative source is the foundation data itself. The data contain objects at known 3D locations, which projec ...

To address the National Geospatial-Intelligence Agency (NGA) need for overhead imagery analysis algorithms that provide uncertaintymeasures for object recognition and aggregation, Intellisense Systems, Inc. (ISS) proposes to develop a new Variational Object Recognition andGrouping Network (VORGNet) system. It is based on the innovation of implementing a Bayesian convolutional neural network (CNN) ...

We propose to build ARGON, the ARet Ground-to-Overhead Network. The network will ingest analyst-supplied ground-level imagery ofobjects and retrieve instances of those objects in overhead collections, providing tips back to the analysts. A proprietary method of trainingthe network, leveraging in-house capabilities, data sources, and tools, will be critical to its success. During Phase I, we will p ...