Similarity or distance measures are core components used by distance-based clustering
algorithms to cluster similar data points into the same clusters, while dissimilar or distant …

Predicting air quality in fine spatiotemporal granularity is of great importance for air pollution
control and urban sustainability. However, existing studies are either focused on predicting …

Background Air pollution exposure has been associated with an increase in mortality rates,
but few studies have focused on life expectancy, and most studies had restricted spatial …

Long-term exposure to air pollution has been associated with increased natural-cause
mortality, but the evidence on diagnoses-specific mortality outcomes is limited. Few studies …

Abstract Background The LIFE MED HISS project aims at setting up a surveillance system
on the long term effects of air pollution on health, using data from National Health Interview …

Background Epidemiological studies have documented the adverse effects of long-term
exposure to fine particulate matter (PM 2.5) on health, while there has been less research on …

We propose a novel model selection algorithm based on a penalized maximum likelihood
estimator (PMLE) for functional hidden dynamic geostatistical models (f-HDGM). These …

This study takes a data-driven approach to define urban nighttime by examining the
spatiotemporal dynamics of urban vitality. Using micro-scale spatiotemporal analysis, this …

In this paper, following a fuzzy approach and adopting an autoregressive parameterization,
we propose a robust clustering model for classifying time series. In particular, by adopting a …

According to the Air Quality Directive 2008/50/EC, air quality zoning divides a territory into
air quality zones where pollution and citizen exposure are similar and can be monitored …