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SBC: CATTO PROPELLERS Topic: N20AT006
In the proposed STTR study, Catto Propellers, Inc. (Catto) and the University of North Dakota (UND) will create an efficient new propeller design utilizing advanced composite materials for use on small unmanned x systems. During Phase I, a comprehensive study will be conducted to develop a new propeller design in order to increase propeller efficiency, reduce aerodynamic noise and utilize innova ...STTR Phase I 2020 Department of DefenseNavy
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: 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
SBC: INTELLIGENT FUSION TECHNOLOGY, INC. Topic: N20AT011
Modern US Navy ships and submarines are configured with an ever-increasing level of automation, including state-of-the-art embedded wireless sensors that monitor vital system functions. However, sensor nodes have the potential to serve as targets for cybersecurity attacks or be susceptible to corruption through accidental or malicious events. To address these shortfalls and minimize vulnerabilitie ...STTR Phase I 2020 Department of DefenseNavy
SBC: Objectsecurity LLC Topic: N20AT011
Condition-based maintenance plus (CBM+), and cyber-physical systems (CPS) in general, depend on correct sensor data for analysis, decision making and control loops. If the sensor data that arrives at the point of processing is not correct, or more accurate, is outside its accepted error range, then any further processing will be incorrect as well. This could result in, in the case of CBM+, not det ...STTR Phase I 2020 Department of DefenseNavy
SBC: Intelligent Automation, Inc. Topic: N20AT011
Navy is developing the concepts and methods to leverage Machine Learning (ML) techniques for the maintenance decision-making on condition-based maintenance plus (CBM+) platform. Effective health monitoring for condition-based and predictive maintenance requires intelligent sensor selection and placement, and context-aware interpretation of sensor data to detect the many possible fault modes. Moreo ...STTR Phase I 2020 Department of DefenseNavy
SBC: FREEDOM PHOTONICS LLC Topic: N20AT012
In this program, Freedom Photonics and its research partner institution will demonstrate an analog optical link using novel record performance laser, modulator and photodiode technology. Preliminary designs for a miniature, deployable implementation will be conducted as well in Phase I.STTR Phase I 2020 Department of DefenseNavy
SBC: DYMENSO LLC Topic: N20AT013
High power generation at millimeter wave (mm-wave) frequencies is expensive and the concurrent need for wide bandwidths at these frequencies creates an extremely challenging problem. Currently the most stringent requirements for mm-wave power and bandwidth can only be practically met by vacuum electronics (VE) technology. At present, vacuum amplifiers with the required performance are prohibitivel ...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