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SBC: Euler Scientific Topic: NGA20A001
Deep Neural Networks have become ubiquitous in the modern analysis of voluminous datasets with geometric symmetries. In the field of Particle Physics, experiments such as DUNE require the detection of particle signatures interacting within the detector, with analyses of over a billion 3D event images per channel each year; with typical setups containing over 150,000 different channels. In an ...STTR Phase I 2020 Department of DefenseNational Geospatial-Intelligence Agency
SBC: TDA RESEARCH, INC. Topic: N19BT032
Webbing is strong, woven material that is used to secure cargo as well as for safety equipment such as seat belts, harnesses, and parachute rigging. Due to its extensive use in Military applications, the strength of the webbing is a key component of equipment design, especially in the case of safety gear that protects soldiers, as lives may be dependent on the strength and proper performance of th ...STTR Phase II 2021 Department of DefenseNavy
SBC: PC KRAUSE & ASSOCIATES INC Topic: N19BT025
Modern and next generation military aircraft face increasing challenges as thermal demands grow while available heat sinks reduce. Legacy platforms upgraded with advanced electrical systems are also encountering similar thermal constraints. Modeling and simulation (M&S) tools provide a cost-effective solution to the design, analysis, and optimization of growing thermal management challenges, but t ...STTR Phase II 2021 Department of DefenseNavy
SBC: INTELLIGENT OPTICAL SYSTEMS, INC. Topic: CBD20AT001
Intelligent Optical Systems, Inc., in collaboration with Bowling Green State University, proposes to develop a field-rugged, eye-readable indicating spray solution that can immediately detect synthetic opioids over a large area of contamination (i.e., military vehicles, individual protective equipment, clandestine labs, etc.). The proposed chemosensor in a spray solution format will detect multipl ...STTR Phase I 2021 Department of DefenseOffice for Chemical and Biological Defense
SBC: MAYACHITRA, INC. Topic: N20AT007
We propose a suite of video processing algorithms utilizing the machine learning (ML) techniques of artificial intelligence (AI) reinforcement learning, deep learning, and transfer learning to process submarine imagery obtained by means of periscope cameras. Machine learning (ML) can help in addressing the challenge of human failure of assessing the data of periscope imagery. Though pre-tuned blac ...STTR Phase I 2020 Department of DefenseNavy
SBC: Arete Associates Topic: N20AT007
Areté and the Machine Learning for Artificial Intelligence (MLAI) Lab at the University of Arizona (UofA) will develop and demonstrate new approaches that improve the performance of in situ machine learning (ML) algorithms as they evolve over time, adapt to new environments, and are capable of transferring their learned experiences across platforms. Technological advances that will be brought t ...STTR Phase I 2020 Department of DefenseNavy
SBC: Arete Associates Topic: N20AT014
Areté and the Machine Learning for Artificial Intelligence (MLAI) Lab at the University of Arizona (UofA) will develop an interactive scenario building tool capable of generating realistic synthetic 360° videos in real-time for use in training simulators for periscope operators . We refer to this solution as RealSynth360. This novel capability will be created by combining the latest advances ...STTR Phase I 2020 Department of DefenseNavy
SBC: Calabazas Creek Research, Inc. Topic: N20AT015
Magnetrons are compact, inexpensive, and highly efficient sources of RF power used in many industrial and commercial applications. For most of these applications, the requirement is for RF power without regard to precise frequency or phase control, and noise riding on the RF signal is not important. For many accelerator, defense, and communications applications, however, these characteristics prev ...STTR Phase I 2020 Department of DefenseNavy
SBC: CASCADE TECHNOLOGIES INC Topic: N19BT027
Current design tools for gas turbine engines invoke a variety of simplifying assumptions to estimate heat transfer to solid/metal engine components (e.g., isothermal boundary conditions). These approximations are often not valid, result in inaccurate predictions of heat transfer, and ultimately compromise the thermal integrity of propulsion and power systems. Wall-modeled large eddy simulation (WM ...STTR Phase II 2020 Department of DefenseNavy
SBC: ADVANCED TECHNOLOGY AND RESEARCH CORPORATION Topic: N20AT010
The overall goal of this STTR Phase I project is to develop a concept to mitigate the effects of motion/vibration for a shipboard material extrusion additive manufacturing (AM) system. NAVSEA has been installing advanced manufacturing equipment, including 3D printers, onboard ships in support of shipboard operations and to evaluate performance of the equipment in shipboard environments and in re ...STTR Phase I 2020 Department of DefenseNavy