Characterising microplastics based on spectroscopic measurements is one key step of many
studies that analyse the fate of microplastics in the environment. Over the years, many …

In the past decades, process engineers are facing increasingly more data analytics
challenges and having difficulties obtaining valuable information from a wealth of process …

The application of deep learning approaches to finance has received a great deal of
attention from both investors and researchers. This study presents a novel deep learning …

Data mining and analytics have played an important role in knowledge discovery and
decision making/supports in the process industry over the past several decades. As a …

Sleep scoring is used as a diagnostic technique in the diagnosis and treatment of sleep
disorders. Automated sleep scoring is crucial, since the large volume of data should be …

Application of neuroscience methods to analyze and understand human behavior related to
markets and marketing exchange has recently gained research attention. The basic aim is to …

In this study, we propose and evaluate a technique known as common average referencing
(CAR) to generate a more ideal reference electrode for microelectrode recordings. CAR is a …

Electroencephalographic (EEG) recordings are often contaminated with muscle artifacts.
This disturbing myogenic activity not only strongly affects the visual analysis of EEG, but also …

Physiological signals such as ECG signals are obtained from a patient. In accordance with
one or more embodiments, an apparatus, system and/or method is directed to at least two …

The relationship between stock market returns and economic activity is investigated using
signal decomposition techniques based on wavelet analysis. After the application of the …