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The Award database is continually updated throughout the year. As a result, data for FY20 is not expected to be complete until September, 2021.

  1. Novel assay for the detection of water-born algae toxins

    SBC: Attogene Corporation            Topic: NOAAOAROARTPO201

    Ciguatera fish poisoning is an illness suffered by > 50,000 people yearly after consumption of fish containing ciguatoxins (CTXs) or exposure to a harmful algae bloom (HAB). Manufacturing of critical reagents to develop assays to detect ciguatoxin have been elusive due to the constraints in production of viable amounts of the toxin. Thankfully, a significant amount of work has been done to demonst ...

    SBIR Phase I 2020 Department of CommerceNational Oceanic and Atmospheric Administration
  2. Fluorescent Qdot-Antibody or Aptamer Test Strips for Ultrasensitive Algal Toxin Detection

    SBC: NANOHMICS INC            Topic: 9203

    Nanohmics, Inc. proposes to develop the most sensitive antibody and/or DNA aptamer‐quantum dot (Qdot)‐based lateral flow (LF) test strips possible for detection of harmful algal bloom (HAB) toxins in fresh or saltwater and seafood rinsates. Although commercial colloidal gold‐LF test strips for some HABs and anti‐HAB toxin aptamer DNA sequences already exist, Nanohmics’ innovation of inco ...

    SBIR Phase I 2020 Department of CommerceNational Oceanic and Atmospheric Administration
  3. Underwater Adhesive for Coral Restoration

    SBC: METNA CO            Topic: 9201

    Coral transplantation is a primary management option for rehabilitation of degraded reefs. Stabilization (via adhesion, etc.) of transplants on existing reef or artificial substrates notably improves their survival rate. Improved underwater adhesives are needed for expedient and convenient stabilization of coral transplants with improved survival rate. A new hybrid organic-inorganic adhesive is pr ...

    SBIR Phase I 2020 Department of CommerceNational Oceanic and Atmospheric Administration
  4. Coral Adhesive

    SBC: Texas Research Institute, Austin, Inc.            Topic: 9201

    Texas Research Institute Austin (TRI Austin) will develop a fast acting, strong, tough, adhesive that will bond underwater without extensive surface preparations. TRI Austin will formulate the adhesive to optimize setup time, establish charge weight for the adhesive to reduce adhesive underwater preparation time, and develop the procedures for using the adhesive to bond coral to reef substrates. A ...

    SBIR Phase I 2020 Department of CommerceNational Oceanic and Atmospheric Administration
  5. Rapid Point of Use Method to Identify Seafood Species

    SBC: Lynntech Inc.            Topic: 9202

    Species substitution with a product of lesser value has become an increasing problem within the seafood industry. Increased international trade, rising consumption rates, and high profit incentives have all contributed to the intentional mislabeling of seafood. While whole, unprocessed fish can generally be identified by their morphological features, processing of seafood makes identification chal ...

    SBIR Phase I 2020 Department of CommerceNational Oceanic and Atmospheric Administration
  6. Faster Optical Modem for Underwater Data Acquisition

    SBC: SONALYSTS, INC.            Topic: NGA182001

    To address NGA’s requirements, Sonalysts’ team of world-class experts in underwater optical communication proposes development and implementation of the Precision Optical Navigation Transceiver for Undersea Systems (PONTUS). PONTUS will transfer navigation information from an Underwater Navigation Beacon (UNB) to an Unmanned Undersea Vehicle (UUV) in an electromagnetic-spectrum-denied (e.g., G ...

    SBIR Phase I 2019 Department of DefenseNational Geospatial-Intelligence Agency
  7. Improved still frames and denoised motion imagery from distressed FMV

    SBC: NANOHMICS INC            Topic: NGA191004

    Producers of imagery intelligence must contend with the distortions and defects in available images. One approach to recovering some the lost spatiotemporal video content during single frame analysis is to use processing techniques that improve spatial quality and resolution of individual frames by exploiting inter-frame correlations. However, the assumptions, enhancement capabilities, and computa ...

    SBIR Phase I 2019 Department of DefenseNational Geospatial-Intelligence Agency
  8. Development of “Permit Wizard” Software for AssistedPermit Application Completion

    SBC: TOTAL QUALITY SYSTEMS, INC.            Topic: 833

    TECHNICAL ABSTRACT: The objective of this project is to research the technical feasibility of designing a software tool “Permit Wizard” that will automate the process for aquamarine permit application submittal, review, approval/disapproval and issue (including collection of fees). Aquaculture producers are currently faced with slow, complex, and often confusing permitting processes that must ...

    SBIR Phase I 2018 Department of CommerceNational Oceanic and Atmospheric Administration
  9. Densely Connected Neural Networks for Remote Sensing

    SBC: Lynntech Inc.            Topic: NGA181010

    The objective of this project is to design a software architecture based on densely-connected neural network to perform automatic targetsegmentation and recognition using training datasets of limited size (low-shot). Deep learning architectures have proved to be extremelyeffective at object detection and recognition, but such capability comes at the cost of having large labeled datasets. Such data ...

    SBIR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  10. Algorithms for Look-down Infrared Target Exploitation

    SBC: SIGNATURE RESEARCH, INC.            Topic: 1

    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 ...

    STTR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
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