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Award Data

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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. Optimization of Fatigue Test Signal Compression Using the Wavelet Transform

    SBC: ATA Engineering, Inc.            Topic: N18BT029

    Traditional approaches to accelerated fatigue testing rely on heuristic methods with thresholds based mostly on experience and engineering judgment. These methods generally do not apply to the multiaxial dynamic loading situations characteristic of most aerospace applications and often result in uncharacteristic fatigue damage and failure modes during testing. To overcome the limitations of tradit ...

    STTR Phase I 2018 Department of DefenseNavy
  2. Hybrid DNN-based Transfer Learning and CNN-based Supervised Learning for Object Recognition in Multi-modal Infrared Imagery

    SBC: TOYON RESEARCH CORPORATION            Topic: 1

    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 ...

    STTR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency
  3. 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
  4. An Integrated Materials Informatics/Sequential Learning Framework to Predict the Effects of Defects in Metals Additive Manufacturing

    SBC: Citrine Informatics, Inc.            Topic: N18AT013

    In this project, Citrine Informatics and the ADAPT Center at the Colorado School of Mines propose to build an informatics-driven system to understand the effects of defects in additive manufactured parts. The entire history of each sample will be captured on this system; from specific printing parameters and details of precursor materials through to part characterizations and performance measureme ...

    STTR Phase I 2018 Department of DefenseNavy
  5. Novel Cooling System for Laser Enclosure

    SBC: Photonwares Corporation            Topic: N18AT001

    We propose to utilize a laser 3D printing manufacturing technique to realize an ultra high efficiency micro-channel laser head cooling system with high thermal load capacity in a small volume package. The new approach incorporates key technical innovations that drastically increase the forced water flow interaction surface area and the metal thermal conductivity. The approach enables conformal geo ...

    STTR Phase I 2018 Department of DefenseNavy
  6. Full Featured Low-Cost HMS for Combatant Craft

    SBC: QUALTECH SYSTEMS, INC.            Topic: N18AT015

    Qualtech Systems, Inc. (QSI), in collaboration with VU proposes to develop a state-of-the art HMS system featuring: (1) Low Hardware cost by leveraging industrial-grade computers ruggedized to military specifications (2) Low Software cost by leveraging QSI’s COTS TEAMS software with real-time monitoring and diagnosis capabilities (3) Vibration and Shock Analysis and its impact on vehicle and cre ...

    STTR Phase I 2018 Department of DefenseNavy
  7. Active Imaging through Fog

    SBC: SA Photonics, Inc.            Topic: N18AT021

    Active imaging systems are used to for imaging in degraded visual environments like that found in marine fog and other environments with a high level of attenuation and scattering from obscurants like fog, rain, smoke, and dust.These systems are still limited in range and resolution. SA Photonics is taking advantage of multiple image enhancement techniques, like wavelength tunability, pulse contro ...

    STTR Phase I 2018 Department of DefenseNavy
  8. Accurate Flow-Through Conductivity Sensor for Autonomous Systems

    SBC: D 2 INCORPORATED            Topic: N18AT022

    UUVs have become increasingly important tools in the collection of environmental data. Their unique ability to operate independent of surface vessel conditions allows oceanographic seawater measurements when traditional means is not possible. Historically sensor packages for UUVs have been based on adaptions of ship deployed equipment. Recent development in sensors, such as the Hybrid Flow Through ...

    STTR Phase I 2018 Department of DefenseNavy
  9. System for Nighttime and Low-Light Face Recognition

    SBC: Systems & Technology Research LLC            Topic: SOCOM18A001

    Face recognition performance using deep learning has seen dramatic improvements in recent years. This improvement has been fueled in part by the curation of large labeled training datasets with millions of images of hundreds of thousands of subjects.This results in effective generalization for matching over pose, illumination, expression and age variation, however these datasets have traditionally ...

    STTR Phase I 2018 Department of DefenseSpecial Operations Command
  10. Layered Inference for Cyber Network Knowledge Synthesis (LINKS)

    SBC: Charles River Analytics, Inc.            Topic: N18AT019

    Providing effective cyber defense for the DoD is compounded by the fact there is not a single physical or logical entity that defines cyberspace. In reality, DoD networks are often composed of three disparate but interacting layers: a physical layer that defines the structure of the network (e.g., computers and routers), a logical layer that represents the static or dynamic state of data within th ...

    STTR Phase I 2018 Department of DefenseNavy
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