Machine learning is a promising tool to reconstruct time-series phenomena, such as
variability of active galactic nuclei (AGNs), from sparsely sampled data. Here, we use three …

This study aims to investigate how alternations of the land surface temperature (LST) affects
the normalized difference vegetation index (NDVI) in Paphos forest, Cyprus, using Landsat …

Accurate measurement of meteorological parameters is crucial for weather forecasting and
climate change research. However, missing observations in rainfall data can pose a …

With rapid urbanization, awareness of environmental pollution is growing rapidly and,
accordingly, interest in environmental sensors that measure atmospheric and indoor air …

Observing phenological changes are important for evaluating the natural regeneration
process of forests, especially in Mediterranean areas where the regeneration of coniferous …

Vertebrates first emerged from water to land in the Paleozoic. Our understanding about the
process has been steadily refined through paleontological studies, although the soft-body …

Extensive monitoring of particulate matter (PM) smaller than 2.5 µ m, ie, PM 2.5, is critical for
understanding changes in local air quality due to policy measures. With the emergence of …

Abstract The Water Quality Index (WQI) is used to monitor the health and usability of a water
body. In this study, we aimed to construct time series prediction models using groundwater …

PM2. 5 has been linked to numerous pollution-mediated adverse health effects and their
monitoring is key for taking preventative and mitigative measures. Accurate measurements …

Data-driven models have been recognized as powerful tools to support Structural Health
Monitoring (SHM). This paper contributes to the literature by exploring two data-driven …