Use of generative models and deep learning for physics-based systems is currently dominated by the task of emulation. However, the remarkable flexibility offered by data-driven architectures would suggest to extend this ...

Implementing approaches based on process mining in inter-organizational collaboration environments presents challenges related to the granularity of event logs, the privacy and autonomy of business processes, and the ...

Gravity-driven capillary viscometers (GDCVs) are used to obtain the viscosity function of non-Newtonian fluids from measurements of the instantaneous fluid height in the overhead reservoir. The reliability of this viscometry ...

In 2002, Bandt and Pompe [Phys. Rev. Lett. 88, 174102 (2002)] introduced a successfully symbolic encoding scheme based on the ordinal relation between the amplitude of neighboring values of a given data sequence, from which ...

Process monitoring is a fundamental task to support operator decisions under ab- normal situations. Most process monitoring approaches, such as Principal Components Analysis and Locality Preserving Projections, are based ...

Prokaryotic and eukaryotic Na(+)-driven transporters couple the movement of one or more Na(+) ions down their electrochemical gradient to the active transport of a variety of solutes. When more than one Na(+) is involved, ...

This project aims to bring the use of data and factual analysis to the discussion about the current educational system’s efficiency and effectiveness, aimed especially at Brazil’s public superior education. It begins by ...

Data-based decision making is a critical part of the education scenario at all levels. Decisions informed by data are likely to be more effective and relevant to the immediate indigenous context. Data-based decision making ...