Time series classification and clustering are important for data mining research, which is
conducive to recognizing movement patterns, finding customary routes, and detecting …

In recent years, water quality monitoring has been crucial to improve water resource
protection and management. Under the relevant laws and regulations, environmental …

Abstract Treatment and prevention of cardiovascular diseases often rely on
Electrocardiogram (ECG) interpretation. Dependent on the physician's variability, ECG …

To meet the recent demands for automated security systems, this study proposes a novel
single-template strategy that uses mean templates and local stability-weighted dynamic time …

Subsequence search and distance measures are crucial tools in time series data mining.
This paper presents our Python package entitled TSSEARCH, which provides a …

Recent comparative studies on mobility patterns are emerging to describe the changes in
mobility patterns due to the COVID-19 pandemic. Most of the current studies utilize travel …

Passwords are still used on a daily basis for all kind of applications. However, they are not
secure enough by themselves in many cases. This work enhances password scenarios …

Compounded weather events such as sequential heatwaves are likely to increasingly
impact freshwater ecosystems in the future. Satellite-derived chlorophyll-a concentration …

This paper develops a multi-dimensional Dynamic Time Warping (DTW) algorithm to identify
varying lead-lag relationships between two different time series. Specifically, this manuscript …

Modern smartphones and wearables often contain multiple embedded sensors which
generate significant amounts of data. This information can be used for body monitoring …