With the gradual development of and improvement in earthquake early warning systems
(EEWS), more accurate real-time seismic intensity measurements (IMs) methods are needed …

This paper proposes a deep learning-based generalized ground motion model (GGMM) for
interface and intraslab subduction earthquakes recorded in Chile. A total of∼ 7000 ground …

Rapid and accurate prediction of peak ground acceleration (PGA) is an important basis for
determining seismic damage through on-site earthquake early warning (EEW). The current …

Rapidly and accurately predicting on-site peak ground velocity (PGV) is important for
earthquake hazard mitigation. Traditional methods used to predict PGV involve a single …

This comprehensive survey addresses the notable yet relatively uncharted territory of
machine learning (ML) applications within the realm of earthquake engineering. While …

The onsite early warning techniques that issue earthquake alerts based on the seismic
response of single stations have proven to be quite successful in detecting damage. The …

On-site earthquake early warning techniques, which issue alerts based on seismic waves
measured at a single station, are promising, and have performed quite successfully during …

This study explored men's experience of miscarriage. Semi-structured interviews were
conducted with ten men with personal experience of miscarriage, analysed using …

Time series data associated with seismic activities pose significant challenges in disaster
preparedness. These challenges underscore the need for reliable and timely damage …

Earthquakes have long pose a vast danger to human existence and infrastructure. Over
time, sizeable studies have been performed in the field of earthquake prediction, mainly on …