In accordance with the rapid proliferation of machine learning (ML) and data management,
ML applications have evolved to encompass all engineering disciplines. Owing to the …

Precise long-term streamflow prediction has always been important in the hydrology field,
and has provided essential information for efficient water-resource management and …

Abstract Functional End-of-Line Testing is a powerful but expensive approach for industrial
quality assurance. A major cost driver of End-of-Line Testing is the often overlong and …

We devise in this paper a Multilevel Adaptive Reduction Technique (MART) for time series
data. MART extracts the main features of a time series and encodes them in a reduced data …

Time series forecasting plays a crucial role in diverse fields, necessitating the development
of robust models that can effectively handle complex temporal patterns. In this article, we …

Solar physicists frequently use solar magnetic field parameters for analyzing and predicting
solar events. Temporal observation of magnetic field parameters, ie, multivariate time series …

Edge devices, with their widely varying capabilities, support a diverse range of edge AI
models. This raises the question: how does an edge model differ from a high-accuracy …

In the medtech industry models of the cardiiovascular systems and simulations are valuable
tools for the development of new products ad therapies. The simulator Aplysia has been …

Human Activity Recognition (HAR) is a vast and complex research domain that has multiple
applications, such as healthcare, surveillance or human-computer interaction. Several …

Abstract Human Activity Recognition (HAR) is a vast and complex research domain that has
multiple applications, such as healthcare, surveillance or human-computer interaction …