Award Data

Target detection and recognition is a challenging problem because of changes in appearance, viewing direction, occlusion and other covariates. Systems that can accurately and efficiently detect and track objects can provide several benefits in surveillance, monitoring and other applications. As part of this effort, we propose to develop a robust learning-based approach to detect, track and recogni ...

Over the last decade the amount of data available from the internet, sensors and other sources has grown dramatically providing the opportunity to gain novel insights in many fields. Uncovering non-linear low dimensional structure in high-dimensional data (i.e., manifold learning), a key to summarization, remains a challenging problem which ultimately inhibits knowledge discovery. Intelligent Auto ...

For Robotic/Autonomous Systems (RAS) to be truly effective in the battlefield, they need to be integrated with intelligent decision-making capabilities. In particular, the following capabilities will help them dealing with the challenging real-world problems of off-road navigation: 1) Accurate terrain traversability assessment; 2) Optimal trajectory computation; and 3) Effective maneuver selection ...

This effort proposes to develop situational awareness methodologies for mission critical ship system based on the state-of-the-art probabilistic knowledge graph (KG) and deep learning. The proposed KG approach can incorporate various data fusion technologies for analysis of unstructured data (text, images, etc.) and structured data (signal feeds, database items, etc.) for automated decision suppor ...

Materials for thermal protection are required to protect structural components of space vehicles during the re-entry stage, missile launching systems, and solid rocket motors (SRMs). Polymer resins that have high char retention (e.g., phenolic resins) are the most common matrices in the composite materials for rigid thermal protection systems (TPSs) due to their tunable density, lower cost, and hi ...

Additive manufacturing (AM) systems, especially metal AM, bring revolutionary capabilities, but suffer from a lack of understanding of the defects that exist within the components. In this research, based on selective experimental study and numerical simulations, we will develop an empirical database of defects and their effects on mechanical properties using Laser Powder Bed Fusion (LPBF) technol ...

Oceanit proposes to research and develop chemical or non-chemical methods and processes to impart surface morphology modifications to aluminum-magnesium (Al-Mg) alloys to mitigate and increase the exfoliation corrosion resistance.

The ability to predict the ignitibility potential of a combustor at various operating conditions is not practical at this time due to the complexity of this process. Ignition within a gas turbine combustor is dependent on various parameters; including spark (or plasma) energy, flow conditions, fuel/air ratio, and fuel spray density. All these parameters must be properly predicted in order to effec ...

To address the need of auto-extracting data relevant to significant events and to archive patterns, Intelligent Automation, Inc. (IAI) team proposes to continue developing a Scalable Event Extractor for Multi-Level Event Data and Pattern Archiving: SEE. The key innovations of our proposed SEE system are (1) a large class of analytics that extract valuable and important information from raw data, a ...

There is an urgent need to bypass or cross the blood brain barrier (BBB) to deliver drugs for TBI treatment. This project aims to develop targted intranasally delivered, magnetically propulsed, and targted nanoparticles for traumatic brain injury (TBI). In Phase I, we will demonstrate the design, fabrication, and in vitro characterization of proposed drug laden magnetic nanoparticles as well as co ...