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Today businesses are facing radical transformations through digitalization of services and products. Accordingly, their ability to innovate is increasingly linked to the capacity to innovate through information and communication technologies (ICTs). This a ...
We consider multitype branching processes evolving in a Markovian random environment. To determine whether or not the branching process becomes extinct almost surely is akin to computing the maximal Lyapunov exponent of a sequence of random matrices, which ...
The advent of the Web reshaped the way in which humans memorize information, arguably unlike any other technological advance of the last decades. Rather than remembering the information itself, people are primed to find the needed information through Web s ...
Nowadays, the complexity of the relationships information has with power and control, business and ideology has been amplified, in part because the networks information now flows over are more complex and farther reaching than prior networks (Chadwick & Ho ...
The main challenge of new information technologies is to retrieve intelligible information from the large volume of digital data gathered every day. Among the variety of existing data sources, the satellites continuously observing the surface of the Earth ...
Adaptive networks are well-suited to perform decentralized information processing and optimization tasks and to model various types of self-organized and complex behavior encountered in nature. Adaptive networks consist of a collection of agents with proce ...
Elsevier2014
Prediction in environmental systems, such as hydrological streamflow prediction, is a challenging task. Although on a small scale, many of the physical processes are well described, accurate predictions of macroscopical (e.g. catchment scale) behavior with ...
With the general technological advances of the recent years, current learning environments amass an abundance of data. Albeit such data offer the chance of better understand the learning process, stakeholders – learners, teachers and institutions – often n ...
When inferring models from hydrological data or calibrating hydrological models, we are interested in the information content of those data to quantify how much can potentially be learned from them. In this work we take a perspective from (algorithmic) inf ...
Throughout its historical development, hydrology as an earth science, but especially as a problem-centred engineering discipline has largely relied (quite successfully) on the assumption of stationarity. This includes assuming time invariance of boundary c ...
