The GC–MS dataset was integrated with the sensory data using a series of exploratory and predictive multivariate statistical ...

Professor Klaus Nordhausen develops modern multivariate statistical methods to analyze high-dimensional and large datasets in different fields.

Jane Marsh, Editor-In-Chief at Environment.co, explores how advanced data analytics and digital technologies can revitalise ...

Discover how multivariate models use multiple variables for investment forecasting, risk analysis, and decision-making in finance. Ideal for portfolio management.

TSD 20: Multivariate meta-analysis of summary data for combining treatment effects on correlated outcomes and evaluating surrogate endpoints (PDF, 1.2MB) – October 2019 – Updated December 2022: ...

UHPLC-QTOF metabolomics and the Global Natural Products Social Molecular Networking (GNPS) platform revealed 185 secondary metabolites in Egyptian blue lily, which link flavonoid-rich flowers to ...

Immunological techniques include both experimental methods to study the immune system and methods to generate or use immunological reagents as experimental tools. The most common immunological methods ...

Techniques and instrumentation refers to the development of methods and tools to be used in applied physics, materials science or nanotechnology for design, synthesis, manufacturing, imaging or ...

Based Detection, Linguistic Biomarkers, Machine Learning, Explainable AI, Cognitive Decline Monitoring Share and Cite: de Filippis, R. and Al Foysal, A. (2025) Early Alzheimer’s Disease Detection from ...

A reversible instance normalization layer to normalize individual series. A linear embedding layer that projects individual series into the embedding space. Mamba blocks that capture the correlations ...

Abstract: In the real world, a large number of multivariate time series data are generated by Internet of Things systems, which are composed of many connected sensing devices. Therefore, it is ...