Publications
Classifier performance estimation with unbalanced, partially labeled data
Summary
Summary
Class imbalance and lack of ground truth are two significant problems in modern machine learning research. These problems are especially pressing in operational contexts where the total number of data points is extremely large and the cost of obtaining labels is very high. In the face of these issues, accurate...
Improving security at the system-call boundary in a type-safe operating system
Summary
Summary
Historically, most approaches to operating sytems security aim to either protect the kernel (e.g., the MMU) or protect user applications (e.g., W exclusive or X). However, little study has been done into protecting the boundary between these layers. We describe a vulnerability in Tock, a type-safe operating system, at the...
Key Challenges and Prospects for Optical Standoff Trace Detection of Explosives
Summary
Summary
Sophisticated improvised explosive devices (IEDs) challenge the capabilities of current sensors, particularly in areas away from static checkpoints. This security gap could be filled by standoff chemical sensors that detect IEDs based on external trace explosive residues. Unfortunately, previous efforts have not led to widely deployed capabilities. Crucially, the physical...
Potential impacts of climate warming and increased summer heat stress on the electric grid: a case study for a large power transformer (LPT) in the Northeast United States
Summary
Summary
Large power transformers (LPTs) are critical yet vulnerable components of the power grid. More frequent and intense heat waves or high temperatures can degrade their operational lifetime and increase the risk of premature failure. Without adequate preparedness, a widespread situation could ultimately lead to prolonged grid disruption and incur excessive...
Detecting pathogen exposure during the non-symptomatic incubation period using physiological data
Summary
Summary
Early pathogen exposure detection allows better patient care and faster implementation of public health measures (patient isolation, contact tracing). Existing exposure detection most frequently relies on overt clinical symptoms, namely fever, during the infectious prodromal period. We have developed a robust machine learning based method to better detect asymptomatic states...
Peregrine: 3-D network localization and navigation
Summary
Summary
Location-aware devices will create new services and applications in emerging fields such as autonomous driving, smart cities, and the Internet of Things. Many existing localization systems rely on anchors such as satellites at known positions which broadcast radio signals. However, such signals may be blocked by obstacles, corrupted by multipath...
Preliminary UAS Weather Research Roadmap(1.51 MB)
Summary
Summary
A companion Lincoln Laboratory report (ATC-437, “Preliminary Weather Information Gaps for UAS Operations”) identified initial gaps in the ability of current weather products to meet the needs of UAS operations. Building off of that work, this report summarizes the development of a proposed initial roadmap for research to fill the...
Preliminary Weather Information Gap Analysis for UAS Operations(4.88 MB)
Summary
Summary
Unmanned Aircraft System (UAS) operations in the National Airspace System (NAS) are rapidly increasing. For example, 2017 has seen dramatically increased low altitude UAS usage for disaster relief and by first responders. The ability to carry out these operations, however, can be strongly impacted by adverse weather conditions. This report...
Preliminary weather information gap analysis for UAS operations, revision 1
Summary
Summary
Unmanned Aircraft System (UAS) operations in the National Airspace System (NAS) are rapidly increasing. For example, 2017 has seen dramatically increased low altitude UAS usage for disaster relief and by first responders. The ability to carry out these operations, however, can be strongly impacted by adverse weather conditions. This report...
MOVPE growth of LWIR AlInAs/GaInAs/InP quantum cascade lasers: impact of growth and material quality on laser performance
Summary
Summary
The quality of epitaxial layers in quantum cascade lasers (QCLs) has a primary impact on QCL performance, and establishing correlations between epitaxial growth and materials properties is of critical importance for continuing improvements. We present an overview of the growth challenges of these complex QCL structures; describe the metalorganic vapor...