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Full-Text Articles in Engineering
Development Of A National-Scale Big Data Analytics Pipeline To Study The Potential Impacts Of Flooding On Critical Infrastructures And Communities, Nattapon Donratanapat
Development Of A National-Scale Big Data Analytics Pipeline To Study The Potential Impacts Of Flooding On Critical Infrastructures And Communities, Nattapon Donratanapat
Theses and Dissertations
With the rapid development of the Internet of Things (IoT) and Big data infrastructure, crowdsourcing techniques have emerged to facilitate data processing and problem solving particularly for flood emergences purposes. A Flood Analytics Information System (FAIS) has been developed as a Python Web application to gather Big data from multiple servers and analyze flooding impacts during historical and real-time events. The application is smartly designed to integrate crowd intelligence, machine learning (ML), and natural language processing of tweets to provide flood warning with the aim to improve situational awareness for flood risk management and decision making. FAIS allows the user …
Machine Learning Models Of C-17 Specific Range Using Flight Recorder Data, Marcus Catchpole
Machine Learning Models Of C-17 Specific Range Using Flight Recorder Data, Marcus Catchpole
Theses and Dissertations
Fuel is a significant expense for the Air Force. The C-17 Globemaster eet accounts for a significant portion. Estimating the range of an aircraft based on its fuel consumption is nearly as old as flight itself. Consideration of operational energy and the related consideration of fuel efficiency is increasing. Meanwhile machine learning and data-mining techniques are on the rise. The old question, "How far can my aircraft y with a given load cargo and fuel?" has given way to "How little fuel can I load into an aircraft and safely arrive at the destination?" Specific range is a measure of …
Confidence Inference In Defensive Cyber Operator Decision Making, Graig S. Ganitano
Confidence Inference In Defensive Cyber Operator Decision Making, Graig S. Ganitano
Theses and Dissertations
Cyber defense analysts face the challenge of validating machine generated alerts regarding network-based security threats. Operations tempo and systematic manpower issues have increased the importance of these individual analyst decisions, since they typically are not reviewed or changed. Analysts may not always be confident in their decisions. If confidence can be accurately assessed, then analyst decisions made under low confidence can be independently reviewed and analysts can be offered decision assistance or additional training. This work investigates the utility of using neurophysiological and behavioral correlates of decision confidence to train machine learning models to infer confidence in analyst decisions. Electroencephalography …