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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.
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A data dictionary and additional information is located on the Data Resource Page. Files are refreshed monthly.
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SBC: Kord Technologies, Inc. Topic: N19BT027
Accurate prediction heat transfer in gas turbine components subject to cooling requires high fidelity modeling of heat transfer in the presence of high Reynolds number turbulent flow. The cooling internal to the blades results in sustained temperature gradients within the structural parts, from low temperature in the interior of the structure to increasingly higher temperature closer to the surfac ...STTR Phase I 2019 Department of DefenseNavy
SBC: REAL-TIME INNOVATIONS, INC. Topic: N19AT012
We propose to develop an open, highly scalable, extensible and secure unified logging architecture for performance and cybersecurity monitoring for Naval Control Systems (NCSs). The primary goal of this architecture is to realize a centralized logging infrastructure for monitoring the status of the entire NCS through collecting and aggregating logs from all subsystems. It will be built upon widely ...STTR Phase I 2019 Department of DefenseNavy
SBC: ULTRA-LOW LOSS TECHNOLOGIES LLC Topic: N19AT023
Ultra-Low Loss Technologies (ULL Technologies) is proposing in collaboration with Prof. Arka Majumdar from University of Washington (UW), to develop a compact, low-cost spectrometer module to be used for chemical sensing applications and to be fabricated using the process design kit (PDK) available through AIM Photonics multi-project wafer run (MPW). The team will combine ULL Technologies expertis ...STTR Phase I 2019 Department of DefenseNavy
SBC: Perceptronics Solutions, Inc. Topic: N19BT029
Mission and planning is a difficult and time-consuming process that places a heavy burden on manpower and critical thinking and is performed under significant pressure. Existing and emerging artificial intelligence (AI) and machine learning (ML) techniques are well-suited to assisting humans with these challenges. While the promise of AI/ML is great, there are significant obstacles to operationali ...STTR Phase I 2019 Department of DefenseNavy
SBC: BCL Technologies Topic: N19AT024
In this SBIR, BCL proposes developing a Multi-lingual Social-media Crowd Manipulation Detector (MSCMD). The MSCMD will use natural language processing techniques to detect terms that arouse emotion using information out of context to trigger reaction from the audience and move them to act.The MSCMD will operate in Asian languages using a Natural Language Processor for each language. The MSCMD will ...STTR Phase I 2019 Department of DefenseNavy
SBC: Arete Associates Topic: N19AT017
The US Navy’s mission to maintain, train and equip combat-ready Naval forces requires that decision makers have situational awareness of the capabilities, limitations, vulnerabilities/opportunities for adversarial and allied forces. An incomplete or inaccurate understanding of the current landscape and associated trends could lead to suboptimal mission readiness and outcomes. Analysts need tools ...STTR Phase I 2019 Department of DefenseNavy
SBC: GCAS, Inc. Topic: N19AT002
This proposal describes the use of machine learning, data mining and Bayesian inference algorithms for incorporation into a surveillance aircraft cognitive radar system. The need for incorporation of higher-order uncertainty distributions will also be assessed. This will result in enhanced sensor resource management capability for surveillance aircraft radar.STTR Phase I 2019 Department of DefenseNavy
SBC: OCEANIT LABORATORIES INC Topic: AF18AT001
Oceanit proposes to develop a system to characterize weak electromagnetic fields for the investigation of the effect of both thermal and non-thermal RF/magnetic fields on biological material, and to detect resulting biological impact of the energy deposited.STTR Phase I 2018 Department of DefenseAir Force
SBC: Information Systems Laboratories, Inc. Topic: AF19AT010
Recent advances and successes of deep learning neural networks (DLNN) techniques and architectures have been well publicized over the last several years. Voluminous, high-quality and annotated training data, or trial and error in a realistic environment, is required to achieve the promised performance potential of DLNNs. Unfortunately for DoD and/or Intelligence Community (IC) applications of mult ...STTR Phase I 2019 Department of DefenseAir Force
SBC: POLARIS SENSOR TECHNOLOGIES INC Topic: SOCOM18A001
The objective of this proposal is to develop instrumentation and algorithms for acquiring facial features for facial recognition in low- and no-light conditions.We will use cross-spectrum matching by exploiting infrared polarimetric imagery which tends to show features that match more closely visible imagery than conventional infrared.In addition to thermal infrared, we will also test subjects in ...STTR Phase I 2018 Department of DefenseSpecial Operations Command