Although highly valuable for a variety of applications, urban mobility data are rarely made
openly available, as it contains sensitive personal information. Synthetic data aims to solve …

A metacognitive radar switches between two modes of cognition—one mode to achieve a
high-quality estimate of targets, and the other mode to hide its utility function (plan). To …

The generation and prediction of daily human mobility patterns have raised significant
interest in many scientific disciplines. Using various data sources, previous studies have …

Nowadays, urban and suburban areas face increasing environmental pressures, and
encouraging sustainable transportation behaviors at the household level has become …

This study is focused on hardware-based anonymization of location data for addressing
privacy concerns while maintaining data utility in applications such as traffic-congestion …

The global positioning system (GPS) data are commonly used for location‐based services
such as traffic flow prediction. However, such data contain considerable sensitive …

The proposed method deals with the problem of data privacy and sharing when processing
personal mobility tracking data. Previous methods concentrate on producing highly detailed …

The general theme of this thesis is inverse reinforcement learning (IRL) for cognitive
systems. By observing the end decisions generated from a cognitive system in multiple …