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The Award database is continually updated throughout the year. As a result, data for FY22 is not expected to be complete until September, 2023.
Neurofeedback Training and Hyperscanning for Mission Readiness and Return-to-Duty via Functional Near-Infrared Spectrometry (fNIRS)SBC: SOAR TECHNOLOGY INC Topic: DHA19B001
Until now,much of theresearch usingfunctional near-infrared spectroscopy (fNIRS) has focused on tailoringasystem to detect onlyafew cognitivestatesand theapplication of theseapproaches outsidethe laboratory is not well tested. This solution provides severely limited coverage of thespacethat this technology could beapplied to,and is notarealistic path for developing neuroimagingasan operational ass ...STTR Phase I 2020 Department of DefenseDefense Health Agency
SBC: Intelligent Automation, Inc. Topic: DTRA19B002
Current state-of-the-art object detection algorithms are almost exclusively based on Deep Convolutional Neural Network (DCNN). These algorithms all require a large amount of labeled examples for each of the object categories they can recognize. These algorithms will fail for novel objects that only very few or even no prior examples are available. These algorithms are also far less accurate when c ...STTR Phase I 2020 Department of DefenseDefense Threat Reduction Agency
Fully Metallic Self-Fragmenting Structural Reactive Materials Using Composites and Alloys Comprised of Aluminum, Lithium, and MagnesiumSBC: Adranos Energetics LLC Topic: DTRA16A002
While aluminum casing materials provide some enhanced performance and thermal loading to explosive ordinance, their overall effectiveness is highly limited by incomplete combustion and long residence times. In order to reduce these problems, the casing material must be designed to facilitate rapid fragmentation through either specialized casing geometries or greatly refined initial particle sizes. ...STTR Phase I 2016 Department of DefenseDefense Threat Reduction Agency