Search Results for author: Mark Hansen

Found 7 papers, 1 papers with code

Using Item Response Theory to Measure Gender and Racial Bias of a BERT-based Automated English Speech Assessment System

no code implementations NAACL (BEA) 2022 Alexander Kwako, Yixin Wan, Jieyu Zhao, Kai-Wei Chang, Li Cai, Mark Hansen

This study addresses the need to examine potential biases of transformer-based models in the context of automated English speech assessment.

Real-Time Go-Around Prediction: A case study of JFK airport

no code implementations18 May 2024 Ke Liu, Kaijing Ding, Lu Dai, Mark Hansen, Kennis Chan, John Schade

In this paper, we employ the long-short-term memory model (LSTM) to predict the real-time go-around probability as an arrival flight is approaching JFK airport and within 10 nm of the landing runway threshold.

Excess Delay from GDP: Measurement and Causal Analysis

no code implementations18 May 2024 Ke Liu, Mark Hansen

Ground Delay Programs (GDPs) have been widely used to resolve excessive demand-capacity imbalances at arrival airports by shifting foreseen airborne delay to pre-departure ground delay.

regression

A Simulation-Optimization Framework for Developing Wind-Resilient AAM Networks

no code implementations17 May 2024 Emin Burak Onat, Shangqing Cao, Raiyan Rizwan, Xuan Jiang, Mark Hansen, Raja Sengupta, Anjan Chakrabarty

Environmental factors pose a significant challenge to the operational efficiency and safety of advanced air mobility (AAM) networks.

Management Scheduling

Connecting Surrogate Safety Measures to Crash Probablity via Causal Probabilistic Time Series Prediction

no code implementations4 Oct 2022 Jiajian Lu, Offer Grembek, Mark Hansen

The autoregressive structure mimicked the causal relationship between condition, action and crash outcome and the probability density functions are used to calculate the conditional action probability, crash probability and conditional crash probability.

counterfactual Open-Ended Question Answering +2

Predicting Aircraft Trajectories: A Deep Generative Convolutional Recurrent Neural Networks Approach

2 code implementations31 Dec 2018 Yulin Liu, Mark Hansen

Reliable 4D aircraft trajectory prediction, whether in a real-time setting or for analysis of counterfactuals, is important to the efficiency of the aviation system.

Decoder Trajectory Prediction

Cannot find the paper you are looking for? You can Submit a new open access paper.