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The Award database is continually updated throughout the year. As a result, data for FY23 is not expected to be complete until September, 2024.

Download all SBIR.gov award data either with award abstracts (290MB) or without award abstracts (65MB). A data dictionary and additional information is located on the Data Resource Page. Files are refreshed monthly.

The SBIR.gov award data files now contain the required fields to calculate award timeliness for individual awards or for an agency or branch. Additional information on calculating award timeliness is available on the Data Resource Page.

  1. Target Discrimination for Subsurface Ordance Characterization

    SBC: BARRON ASSOCIATES, INC.            Topic: N/A

    The Cesium vapor magnotometer and ground-penetrating radar senors currently used to identify subsurface Unexploded Ordnance locations also respond to underground clutter and anomalies. The ultimate objective of this project is to develop a classifier or discriminator that has the potential of providing significantly improved performance on target discrimination for subsurface ordnance ...

    SBIR Phase I 1996 Department of DefenseAir Force
  2. Statistical Techniques for Simulation Model Validation

    SBC: BARRON ASSOCIATES, INC.            Topic: N/A

    Statistically sound approaches to making interfrences regarding simulation model validation, rather than reliance upon subjective appeal, are needed. Fundamentally, the question of interest is whether a model reflects reality to the required degree of accuracy. The utility (and hence validity) of a simulation model relies on how well it captures those aspects of the phenonmenon under study that ...

    SBIR Phase I 1996 Department of DefenseArmy
  3. Reinforcement Learning for Avionics Applications

    SBC: BARRON ASSOCIATES, INC.            Topic: N/A

    Simulation-based optimization techniques that enlist reinforcement learning controllers are ideally suited for complex and multi-objective optimization problems that cannot be solved easily using traditional techniques, especially when the stochastic natures or the environment, resources, and external interactive entities are taken into account. Reinforcement learning based on incremental value i ...

    SBIR Phase I 1997 Department of DefenseAir Force
  4. Algorithms for Health Care Quality Management and Outcomes Assessment

    SBC: BARRON ASSOCIATES, INC.            Topic: N/A

    American health care is in the midst of momentous change. Quality improvement principles are being used increasingly to enhance productivity and efficiency of health care delivery and to help contain costs. In producing patient outcomes and resource utilization measures, it is vital to control appropriately for case mix (i.e., differences in patients due, e.g., to illness severity) in the predicti ...

    SBIR Phase I 1997 Department of Commerce
  5. Fast Dynamical Simulations Of Power Electronic Circuits

    SBC: BARRON ASSOCIATES, INC.            Topic: N/A

    N/A

    SBIR Phase I 1997 National Aeronautics and Space Administration
  6. Neural Network Medical Decision Algorithms for Pre-Hospital Injury Severity and Risk Assessment

    SBC: BARRON ASSOCIATES, INC.            Topic: N/A

    N/A

    SBIR Phase I 1996 Department of DefenseArmy
  7. Saturable Self-Sensing Magnetic Bearings

    SBC: BARRON ASSOCIATES, INC.            Topic: N/A

    N/A

    SBIR Phase I 1997 National Aeronautics and Space Administration
  8. OPTIMAL ENERGY MANAGEMENT FOR KINETIC ENERGY WEAPONS

    SBC: BARRON ASSOCIATES, INC.            Topic: N/A

    N/A

    SBIR Phase I 1990 Department of DefenseMissile Defense Agency
  9. Improved Guidance of Autonomous Munitions and Submunitions

    SBC: BARRON ASSOCIATES, INC.            Topic: N/A

    N/A

    SBIR Phase I 1996 Department of DefenseAir Force
  10. Operational Training for FFG-7 Anti Air Warfare (AAW) Combat System

    SBC: BASIC COMMERCE & INDUSTRIES INC            Topic: N/A

    A need exists to develop an embedded training capability for AAW teams for the FFG-7 class to support the Navy's program of moving training to the operator's console on the ship. This method of using embedded training to "self-train" has been adopted as the prescribed means of accomplishing individual and team proficiency for all surface combatants. For various reasons, embedded training capabili ...

    SBIR Phase I 1996 Department of DefenseNavy
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