Award Data

To achieve the requisite fast, dynamic thermal switching times, we postulate the use of a Photonic Crystal (PC) filament operating at l=1-2mm. Our electrically biased PC design will be super thin to allow for fast on-off intensity-switching. It will have a small thermal mass and exhibit laser-like input-output characteristics, i.e. “Planck laser”. We will provide a theoretical framework for ou ...

The team of Signature Research, Inc. and Michigan Technological University will develop and demonstrate methods and metrics to evaluate the performance of machine learning-based computer vision algorithms with low numbers of samples of labeled EO imagery. We will use the existing xView panchromatic dataset to demonstrate a proof-of-concept set of tools. If successful, in Phase II, we will extend t ...

The focus of this STTR phase I component is on proof-of-concept studies demonstrating applicability of technical approaches for identificationof circulatory diagnostic markers for infectious disease. Therefore, the primary objective of this project is to determine feasibility of one suchtechnical approach called Proteomics-based Expression Library Screening (PELS), for identification of pathogen-d ...

Methods for interconversion between cell types (cellular reprogramming) are currently discovered through resource intensive trial and error. Experiments may test a multitude of transcription factors to identify correct combinations that influence cell fate. In addition, reprogramming approaches commonly use stem cell intermediates such as induced pluripotent stem cells (iPSCs), which are generated ...

Signature Research, Inc. (SGR) and Michigan Technological University (MTU) propose a Phase I STTR effort to develop a learning algorithm which exploits the spatio-spectral characteristics inherent within IR imagery and motion imagery.Our archive of modelled and labeled data sets will allow our team to thoroughly capture the variable elements that will drive machine learning performance.The overall ...

Investigates and explores the solution space for physiologically-based emotion detection within the design and development of a Physiology-based Operator Confidence Assessment System (PhOCAS). The PhOCAS project uses UCF ISTs experience as experts on augmented cognition and physiological assessment for determining user state (such as workload) combined with SoarTechs intelligent systems capabiliti ...

In this project, Sonalysts will team with the University of North Dakota to establish the feasibility of a deployable, unobtrusive suite of sensors and data processing approaches collectively known as Cognitively-Oriented Physiological Indicators of Load, Operational performance, and Tension (CO-PILOT). CO-PILOT will provide real-time indicators of operator state that can be used to inform adaptiv ...

computer vision, image processing, scene recognition, scene understanding, object recognition, image segmentation, gisting

Granville has designed a new satellite/spacecraft propulsion engine, GREP, delivering over 100.mN/1.0 kW of force from strong electromagnetic energy… more force magnitude and efficiency than existing propellant limited ion thrusters. And, because it uses renewable power from on-board solar/electric panels, GREP offers extended propulsion maneuver life, up to 15 years or more, substantially lon ...

A new method of manufacturing of deep brain stimulation devices is proposed. We will use proprietary method of processing of carbon nanotubes into ultrastrong and highly conductive thin sheets. Flexibility of the sheets and special electrode design will make possible effective integration of the designed implants into the brain tissues. This will greatly reduce inflammation which will be tested ...