Publications
Enhanced parallel simulation for ACAS X development
Summary
Summary
ACAS X is the next generation airborne collision avoidance system intended to meet the demands of the rapidly evolving U.S. National Airspace System (NAS). The collision avoidance safety and operational suitability of the system are optimized and continuously evaluated by simulating billions of characteristic aircraft encounters in a fast-time Monte...
Processing of crowdsourced observations of aircraft in a high performance computing environment
Summary
Summary
As unmanned aircraft systems (UASs) continue to integrate into the U.S. National Airspace System (NAS), there is a need to quantify the risk of airborne collisions between unmanned and manned aircraft to support regulation and standards development. Both regulators and standards developing organizations have made extensive use of Monte Carlo...
Fast training of deep neural networks robust to adversarial perturbations
Summary
Summary
Deep neural networks are capable of training fast and generalizing well within many domains. Despite their promising performance, deep networks have shown sensitivities to perturbations of their inputs (e.g., adversarial examples) and their learned feature representations are often difficult to interpret, raising concerns about their true capability and trustworthiness. Recent...
Human balance models optimized using a large-scale, parallel architecture with applications to mild traumatic brain injury
Summary
Summary
Static and dynamic balance are frequently disrupted through brain injuries. The impairment can be complex and for mild traumatic brain injury (mTBI) can be undetectable by standard clinical tests. Therefore, neurologically relevant modeling approaches are needed for detection and inference of mechanisms of injury. The current work presents models of...
Attacking Embeddings to Counter Community Detection
Summary
Summary
Community detection can be an extremely useful data triage tool, enabling a data analyst to split a largenetwork into smaller portions for a deeper analysis. If, however, a particular node wanted to avoid scrutiny, it could strategically create new connections that make it seem uninteresting. In this work, we investigate...
Sensorimotor conflict tests in an immersive virtual environment reveal subclinical impairments in mild traumatic brain injury
Summary
Summary
Current clinical tests lack the sensitivity needed for detecting subtle balance impairments associated with mild traumatic brain injury (mTBI). Patient-reported symptoms can be significant and have a huge impact on daily life, but impairments may remain undetected or poorly quantified using clinical measures. Our central hypothesis was that provocative sensorimotor...
Seasonal Inhomogeneous Nonconsecutive Arrival Process Search and Evaluation
Summary
Summary
Seasonal data may display different distributions throughout the period of seasonality. We fit this type of model by determiningthe appropriate change points of the distribution and fitting parameters to each interval. This offers the added benefit of searching for disjoint regimes, which may denote the samedistribution occurring nonconsecutively. Our algorithm...
Complex Network Effects on the Robustness of Graph Convolutional Networks
Summary
Summary
Vertex classification—the problem of identifying the class labels of nodes in a graph—has applicability in a wide variety of domains. Examples include classifying subject areas of papers in citation net-works or roles of machines in a computer network. Recent work has demonstrated that vertex classification using graph convolutional networks is...
Data trust methodology: a blockchain-based approach to instrumenting complex systems
Summary
Summary
Increased data sharing and interoperability has created challenges in maintaining a level of trust and confidence in Department of Defense (DoD) systems. As tightly-coupled, unique, static, and rigorously validated mission processing solutions have been supplemented with newer, more dynamic, and complex counterparts, mission effectiveness has been impacted. On the one...
Antennas and RF components designed with graded index composite materials
Summary
Summary
Antennas and RF components in general, can greatly benefit with the recent development of low-loss 3D print graded index materials. The additional degrees of freedom provided by graded index materials can result in the design of antennas and other RF components with superior performance than currently available designs based on...