In this work, we report on a novel application of Locality Sensitive Hashing (LSH) to seismic
data at scale. Based on the high waveform similarity between reoccurring earthquakes, our …

Prediction of earthquakes has been long of interest of scientists to create a timely warning to
save lives and reduce the damage. During the last few decades, scientists could record and …

Earthquakes usually cause severe injuries and loss of life, so researchers have developed
various methods to predict them. However, the prediction accuracies of these methods are …

Spectral analysis method is commonly used in estimating moment magnitude for small to
medium size earthquake. Most moment magnitude studies have been focused on the …

The generation of synthetic data is becoming a fundamental task in the daily life of any
organization due to the new protection data laws that are emerging. Because of the rise in …

As is widely acknowledged, the transportation of goods by road can, in one way or another,
be linked to a range of macroeconomic indicators. A hybrid artificial intelligence system is …

WorNplace accident rates are always a constant source of concern in different scenarios. On
the other hand, different economic cycles modify employment indicators, thereby affecting …

Network telemetry, sensor readings, and other machine-generated data are growing
exponentially in volume. Meanwhile, the computational resources available for processing …

Predicting earthquakes has been one of the most challenging tasks as it occurs arbitrarily
and the economy is affected due to damage of the properties and lives. Detections of the …