In the automotive sector, vehicle data gathered through On-board Diagnostics (OBD) systems offers continuous insights into vehicle health status and performance. Leveraging this data for predictive maintenance can significantly reduce unplanned failures, enhance safety, and extend vehicle...

Metropolitan polycentricity is a topic that has been extensively studied. Traditional approaches to identifying urban centers have relied on high-resolution survey data, which is limited in many regions. More recent studies utilizing open-access point of interest (POI) data have primarily...

The K-means algorithm and its variants are well-known clustering techniques. In actuarial applications, these partitioning methods can identify clusters of policies with similar attributes. The resulting partitions provide an actuarial framework for creating maps of dominant risks and...

We examine the rise of dark shipping – oil tankers disabling AIS transceivers to evade detection – amid Western sanctions on Iran, Syria, North Korea, Venezuela, and Russia. Using a machine learning-based ship clustering model, we track dark-shipped crude oil trade flows worldwide and detect...

The management of the COVID-19 pandemic not only depends on the stringency measures established by governments but also and more importantly on the underlying capacity of territories in economic and health and sanitary infrastructure. This study aims to identify how the underlying conditions of...