In recent years, modern spectral analysis techniques, such as ultraviolet–visible (UV-vis)
spectroscopy, mid-infrared (MIR) spectroscopy, near-infrared (NIR) spectroscopy, Raman …

In the past 20 years, hyperspectral imaging has been widely investigated as an emerging,
promising technology for evaluating quality and safety of horticultural products. This …

With the increasing ease of measuring multiple variables per object the importance of
variable selection for data reduction and for improved interpretability is gaining importance …

Background: Humans are exposed to tens of thousands of chemical substances that need to
be assessed for their potential toxicity. Acute systemic toxicity testing serves as the basis for …

The main drivers for the development and evolution of Cyber Physical Systems (CPS) are
the reduction of development costs and time along with the enhancement of the designed …

Curse of dimensionality is known as big challenges in data mining, pattern recognition,
computer vison and machine learning in recent years. Feature selection and feature …

Background The new REACH legislation requires assessment of a large number of
chemicals in the European market for several endpoints. Developmental toxicity is one of the …

In an era of growing data complexity and volume and the advent of big data, feature
selection has a key role to play in hel** reduce high-dimensionality in machine learning …

Background: Endocrine disrupting chemicals (EDCs) are xenobiotics that mimic the
interaction of natural hormones and alter synthesis, transport, or metabolic pathways. The …

Nowadays, with a high dimensionality of dataset, it faces a great challenge in the creation of
effective methods which can select an optimal variables subset. In this study, a strategy that …