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Advances in data acquisition technologies and supercomputing for large-scale simulations have led to an exponential growth in the volume of spatial data. This growth is accompanied by an increase in data complexity, such as spatial density, but also by mor ...
In the past two decades, the use of ontologies has been proven to be an effective tool for enriching existing information systems in the digital data modelling domain and exploiting those assets for semantic interoperability. With the rise of Industry 4.0, ...
Federated learning has emerged as an umbrella term for centralized coordination strategies in multi-agent environments. While many federated learning architectures process data in an online manner, and are hence adaptive by nature, most performance analyse ...
The study of how people schedule their daily activities is of interest in the context of transport demand forecasting using activity based-models, where activity schedules are generated in order to estimate the trip demand they produce. Machine learning ha ...
We study user interaction with touchscreens based on swipe gestures for personal authentication. This approach has been analyzed only recently in the last few years in a series of disconnected and limited works. We summarize those recent efforts and then c ...
Context. The Gaia Data Release 2 (DR2) contains more than half a million sources that are identified as variable stars. Aims. We summarise the processing and results of the identification of variable source candidates of RR Lyrae stars, Cepheids, long-peri ...
Motivation: Unbiased clustering methods are needed to analyze growing numbers of complex data sets. Currently available clustering methods often depend on parameters that are set by the user, they lack stability, and are not applicable to small data sets. ...
In this paper we lay the groundwork for a robust cross-device comparison of data-driven disruption prediction algorithms on DIII-D and JET tokamaks. In order to consistently carry on a comparative analysis, we define physics-based indicators of disruption ...
The federated learning setting is prone to suffering from non-identically distributed data across participating agents. This gives rise to the task of model personalization, where agents collaborate to train several different machine learning models instea ...
Advanced technologies based on Internet of Things (IOT) are blazing a trail to effective and efficient management of an overall plant. In this context, manufacturing companies require an innovative strategy to survive in a competitive business environment, ...