Physical Sciences and Mathematics Commons^™

Using Natural Language Processing To Identify Mental Health Indicators In Aviation Voluntary Safety Reports, Michael Sawyer, Katherine Berry, Amelia Kinsella, R Jordan Hinson, Edward Bynum

National Training Aircraft Symposium (NTAS)

Voluntary Safety Reporting Programs (VSRPs) are a critical tool in the aviation industry for monitoring safety issues observed by the frontline workforce. While VSRPs primarily focus on operational safety, report narratives often describe factors such as fatigue, workload, culture, staffing, and health, directly or indirectly impacting mental health. These reports can provide individual and organizational insights into aviation personnel's physical and psychological well-being. This poster introduces the AVIation Analytic Neural network for Safety events (AVIAN-S) model as a potential tool to extract and monitor these insights. AVIAN-S is a novel machine-learning model that leverages natural language processing (NLP) to analyze …

Workforce Of The Future Begins With Aviation Stem, Lyndsay Digneo

National Training Aircraft Symposium (NTAS)

The United States has always been a world leader in aviation. This leadership position relies on the strength of the American STEM workforce and the quality of the nation’s educational, industrial, and government institutions. Therefore, it is imperative to nurture today’s students to become a well-trained STEM workforce in the future.

The Federal Aviation Administration (FAA) William J. Hughes Technical Center (WJHTC) recognizes that in pursuing its mission of aviation research, engineering, development, and test and evaluation, it is in a unique position to support aviation STEM activities for schools (K-12), post-secondary institutions, and community organizations. In 2016, the Technical …

A Bidirectional Deep Lstm Machine Learning Method For Flight Delay Modelling And Analysis, Desmond B. Bisandu, Irene Moulitsas

National Training Aircraft Symposium (NTAS)

Flight delays can be prevented by providing a reference point from an accurate prediction model because predicting flight delays is a problem with a specific space. Only a few algorithms consider predicted classes' mutual correlation during flight delay classification or prediction modelling tasks. None of these existing methods works for all scenarios. Therefore, the need to investigate the performance of more models in solving the problem of flight delay is vast and rapidly increasing. This paper presents the development and evaluation of LSTM and BiLSTM models by comparing them for a flight delay prediction. The LSTM does the feature extraction …

Integrated Organizational Machine Learning For Aviation Flight Data, Michael J. Pritchard, Paul Thomas, Eric Webb, Jon Martin, Austin Walden

National Training Aircraft Symposium (NTAS)

An increased availability of data and computing power has allowed organizations to apply machine learning techniques to various fleet monitoring activities. Additionally, our ability to acquire aircraft data has increased due to the miniaturization of small form factor computing machines. Aircraft data collection processes contain many data features in the form of multivariate time-series (continuous, discrete, categorical, etc.) which can be used to train machine learning models. Yet, three major challenges still face many flight organizations 1) integration and automation of data collection frameworks, 2) data cleanup and preparation, and 3) embedded machine learning framework. Data cleanup and preparation has …

Suas: Cybersecurity Threats, Vulnerabilities, And Exploits, Philip Craiger, Gary Kessler, William Rose

National Training Aircraft Symposium (NTAS)

The FAA predicts that purchases of hobbyist small unmanned aerial systems (sUAS) will grow from 1.9 million in 2016 to 4.3 million by 2020, and commercial sUAS to increase from 600,000 in 2016 to 2.7 million by 2020. sUAS, often referred to as 'drones,' are comprised of aeronautical hardware, a CPU, RAM, onboard storage, radio frequency communications, sensors, a camera, and a controller used by the pilot-in-command (PIC). Some have argued that a sUAS is essentially a flying computer. As such, sUAS are sometimes susceptible to many of the types of attacks that are often used on PC-based computers attached …

Effects Of Graphical Weather Information Versus Textual Weather Information On Situation Awareness In Meteorology, Stefan Melendez M.S.A., Andrew Dattel Ph.D., Christopher Herbster Ph.D., Debbie Schaum M.A., Andrey Babin

National Training Aircraft Symposium (NTAS)

Prior to a flight, pilots gather meteorological information in order to assess the weather conditions pertaining to their flight and to make decisions based on it. This information can come in various formats, such as text and graphical weather information. Research has shown that people have varying learning preferences and that most people prefer visual learning to verbal learning (i.e., graphical over text). It is hypothesized that this difference in learning preference can affect the way pilots interpret and apply the information they obtain prior to their flight. The researcher hypothesizes that graphical weather information has a greater, more positive …