Securboration has been selected by the Air Force Research Laboratory (AFRL) to explore, systematically study and develop technology that enables computers to proactively support analyst activity. The goal is to provide a bidirectional human and information technology partnership where the computer learns, adapts and informs analysts based on their typical practices, situational context, and available data content. The system under development, referred to as the Adaptive Data Immersion Environment or ADIEN, combines machine learning, text analytics, and semantic search to learn and evolve user preferences based on individual usage patterns. Additionally, as new data products become available they will be automatically identified and seamlessly added into analyst’s workspace. These capabilities in ADIEN will enable it to act as personalized, proactive assistant that can automatically tailor the workspace to the analyst’s needs while also automatically identifying and processing information potentially relevant to their missions.
Securboration was awarded a follow-on contract to continue development of the Semantic Enterprise Architecture (EA) for the Air Force Reserve Command (AFRC) at Robins AFB, Warner Robins, GA. The semantic EA utilizes an architecturally driven approach to manage AFRC’s current command systems IT portfolio with the objective of transforming current stovepipe IT systems to a loosely coupled, standards based, Service Oriented Architecture (SOA). This award is a continuation of the existing 5 year IDIQ contract with the Air Force Research Lab in Rome, NY.
The Army Corps of Engineers announced that Securboration was awarded a Phase II extension contracts for their research and development project MASM (MPICE Analytical Stability Model). This contract was awarded on June 10th, 2009 to cover the 2-year Phase II SBIR evolution.
MPICE and other metrics based approaches do not provide necessary insights and situational understanding with respects to how the US Government is progressing towards meeting its strategic, operational, and tactical objectives. MASM addresses these issues by formalizing the complex casual relationships through the use of advanced computation modeling techniques such as social network analysis, ontological modeling, and Bayesian-based reasoning. MASM will ultimately enable the situation understanding of MPICE metrics with respect to contributing, interrelated factors and in terms of addressing progress towards meeting US Government objectives.