Bryan Matthews

发表

Comparative study of metroplex airspace and procedures using machine learning to discover flight track anomalies

David Nielsen, John Schade, Bryan Matthews, 2015, 2015 IEEE/AIAA 34th Digital Avionics Systems Conference (DASC).

Aircraft Exceedances Vary According to Time of Day and Workload

Erin E. Flynn-Evans, Nikunj C. Oza, Michael Feary, 2018 .

New Sensors and Techniques for the Structural Health Monitoring of Propulsion Systems

Mark R. Woike, Ali Abdul-Aziz, Bryan Matthews, 2013, TheScientificWorldJournal.

Using ADOPT Algorithm and Operational Data to Discover Precursors to Aviation Adverse Events

Nikunj C. Oza, Vijay Manikandan Janakiraman, Bryan Matthews, 2018 .

Adaptive Fault Detection on Liquid Propulsion Systems with Virtual Sensors: Algorithms and Architectures

Ashok N. Srivastava, Bryan Matthews, 2010 .

Ares I-X Ground Diagnostic Prototype

Mark Schwabacher, Rodney Martin, Robert D. Waterman, 2010 .

Unsupervised Anomaly Detection for Liquid-Fueled Rocket Propulsion Health Monitoring

Mark Schwabacher, Nikunj C. Oza, Bryan Matthews, 2007, Journal of Aerospace Computing Information and Communication.

Automated discovery of flight track anomalies

David Nielsen, John Schade, Bryan Matthews, 2014, 2014 IEEE/AIAA 33rd Digital Avionics Systems Conference (DASC).

RNAV STAR Procedural Adherence

Bryan Matthews, Michael Stewart, 2017 .

Measures and models for predicting cognitive fatigue

Leonard J. Trejo, Roman Rosipal, Bryan Matthews, 2005, SPIE Defense + Commercial Sensing.

Integrating Parallel and Distributed Data Mining Algorithms into the NASA Earth Exchange (NEX)

Ramakrishna R. Nemani, Kamalika Das, Ankush Khandelwal, 2014 .

Algorithms for Spectral Decomposition with Applications to Optical Plume Anomaly Detection

Santanu Das, Bryan Matthews, Askok N. Srivastava, 2008 .

Data Mining for ISHM of Liquid Rocket Propulsion Status Update

Mark Schwabacher, Richard Watson, Ashok N. Srivastava, 2006 .

Unsupervised Anomaly Detection in Flight Data Using Convolutional Variational Auto-Encoder

Milad Memarzadeh, Ilya Avrekh, Bryan Matthews, 2020, Aerospace.

Rotor health monitoring combining spin tests and data-driven anomaly detection methods

Mark R. Woike, Ali Abdul-Aziz, Nikunj C. Oza, 2012 .

Propulsion health monitoring of a turbine engine disk using spin test data

Mark R. Woike, Ali Abdul-Aziz, George Y. Baakilini, 2010, Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring.

RNAV Adherence Data Integration System Using Aviation and Environmental Sources

Ilya Avrekh, Bryan Matthews, Michael Stewart, 2018 .

Discovery of Abnormal Flight Patterns in Flight Track Data

David Schleicher, John Schade, Kennis Chan, 2013 .

DiscoveringAnomalousAviationSafetyEventsUsingScalableData Mining Algorithms

Kanishka Bhaduri, Kamalika Das, Santanu Das, 2014 .

Multi-Class Multiple Instance Learning for Predicting Precursors to Aviation Safety Events pdf

Dimitri N. Mavris, Tejas G. Puranik, Marc-Henri Bleu-Laine, 2021, Journal of Aerospace Information Systems.

Multi-Class Anomaly Detection in Flight Data Using Semi-Supervised Explainable Deep Learning Model

Milad Memarzadeh, Bryan Matthews, Thomas Templin, 2021 .

Predicting Adverse Events and their Precursors in Aviation Using Multi-Class Multiple-Instance Learning

Dimitri N. Mavris, Tejas G. Puranik, Marc-Henri Bleu-Laine, 2021 .

Multiclass Anomaly Detection in Flight Data Using Semi-Supervised Explainable Deep Learning Model

Milad Memarzadeh, Bryan Matthews, Thomas Templin, 2021, Journal of Aerospace Information Systems.

Identifying Precursors to Anomalies Using Inverse Reinforcement Learning ∗

Vijay Manikandan Janakiraman, Bryan Matthews, Nikunj Oza, 2014 .

Data-Driven Anomaly Detection Performance for the Ares I-X Ground Diagnostic Prototype

Mark Schwabacher, Rodney Martin, Bryan Matthews, 2010 .