Aircraft Tail-Specific Performance Modeling for Fuel Efficient Flight Operations in the Cruise Phase

Fuel-efficient flight operations and improved Air Traffic Management (ATM) operations are identified as one of the main pillars in achieving net-zero CO2 emissions by 2050. While considerable research has focused on airspace management and ATM operations, flight operations as managed by airlines have received little attention. <br/><br/>Accurate...

Accelerating Machine Learning Queries with Linear Algebra Query Processing

The rapid growth of large-scale machine learning (ML) models has led numerous commercial companies to utilize ML models for generating predictive results to help business decision-making. As two primary components in traditional predictive pipelines, data processing, and model predictions often operate in separate execution environments,...

A Multiclass Classification Model for Tooth Removal Procedures

Surprisingly little is known about tooth removal procedures. This might be due to the difficulty of gaining reliable data on these procedures. To improve our understanding of these procedures, machine learning techniques were used to design a multiclass classification model of tooth removal based on force, torque, and movement data recorded...

Predicting Flight Delay Distributions: A Machine Learning-Based Approach at a Regional Airport

In an effort to improve an airport operation optimization model, this research investigates the possibility of predicting probability distributions of flight delays with machine learning algorithms. The research is centered around Rotterdam The Hague...

Aircraft Disruption Management: Increasing Performance with Machine Learning Predictions

Airlines experience schedule disruptions on a daily basis. Poor weather conditions, unscheduled aircraft maintenance and congested air spaces are just a few of the causes that prevent airlines from operating their flight schedules as planned. In the third quarter of 2017 over 20% of all scheduled flights in Europe suffered from delays. Operation...

Machine Learning as Enabler of Design-to-Robotic-Operation

This essay promotes Artificial Intelligence (AI) via Machine Learning (ML) as a fundamental enabler of technically intelligent built-environments. It does this by detailing ML’s successful application within three deployment domains: (1) Human Activity Recognition, (2) Object as well as Facial-Identity and -Expression Recognition, and (3) Speech...

Efficient Multiclass ROC Approximation by Decomposition via Confusion Matrix Perturbation Analysis

Receiver operator characteristic (ROC) analysis has become a standard tool in the design and evaluation of two-class classification problems. It allows for an analysis that incorporates all possible priors, costs, and operating points, which is important in many real problems, where conditions are often nonideal. Extending this to the multiclass...