Under the guidance of the material genome initiative (MGI), the use of data‐driven methods
to discover new materials has become an innovation of materials science. The polymer …

Safe and stable operation plays an important role in the chemical industry. Fault detection
and diagnosis (FDD) make it possible to identify abnormal process deviations early and …

Classification and regression trees, as well as their variants, are off-the-shelf methods in
Machine Learning. In this paper, we review recent contributions within the Continuous …

In this research, we develop three statistical based control charts: the Hotelling's T 2,
MEWMA (multivariate exponentially weighted moving average), and LRT (likelihood ratio …

Recent studies have shown the satisfactory results of the matrix factorization technique in
Multi-view Clustering (MVC). Compared with the single-layer formed clustering models, the …

Artificial Intelligence (AI) has advanced material research that were previously intractable,
for example, the machine learning (ML) has been able to predict some unprecedented …

Over the past decades, control charts, one of the essential tools in Statistical Process Control
(SPC), have been widely implemented in manufacturing industries as an effective approach …

Various applications of control charts in the field of health-care monitoring and surveillance
can be found in the literature. As one of the major categories, monitoring binary outcomes of …

Big Data will revolutionize modern industry by improving process optimization, facilitating
insight discovery, and improving decision-making. This big data revolution presents a …

Remote sensing technology allows to provide information about biochemical and
biophysical crop traits and monitor their spatiotemporal dynamics of agriculture ecosystems …