EDD Online is a sophisticated interface to access the rich contents of the most comprehensive English dialect dictionary ever published, the English Dialect Dictionary by Joseph Wright (1898-1905). It covers the main English-speaking countries worldwide from 1700 to 1903. Owing to the implementation of diverse software, it allows for combined, nested, quantified and mappable query results on linguistic and cultural issues.
Austrian building regulations require sufficient ventilation to control indoor air quality and humidity levels, but fail to provide specific guidelines on how this should be accomplished. We have developed a Monte-Carlo-based calculation method that estimates the ventilation requirements to be implemented in an easy-to-use tool that requires as little input as possible.
We want to show how historic information can be represented and displayed in different formats to convey the information contained in archival resources. An online representation and transcription of two medieval documents containing mining awards are related to a knowledge graph and maps that permit the exploration of the relations between mining areas, mines and people.
Will we have a white Christmas in Innsbruck in 2022? As of nine days before Christmas, the answer has become quite clear. A machine-learning model that combines atmospheric science, meteorological observations and statistical expertise gave the answer how high (or low) the probability of waking up in a white landscape on December 24, 2022, is.
We designed and implemented an online service that allows investigating how the meaning of any word has developed historically. It uses Google Books n-gram data – a dataset of several terabytes of text data compiled from around 5% of all books ever published.
We take a fresh look at approximation paradigms for dynamical systems, by fitting differential equations to cardiac data using artificial neural networks (ANNs). As an example, the equations of the monodomain system model the electric activity inside cardiac tissues, and we trained a neural network approximating the expressions of their nonlinear terms.
We performed a meta-analysis and clustered neuroimaging data from 4207 participants. Results provide a roadmap for dissecting human social cognition into more elementary and neurobiologically grounded processes.