Publicaties

Automating the task of assessing an assetU+2019s status based on sensor data would not only relieve trained engineers from this time intensive task, it would also allow a continuous follow-up of assets, potentially resulting in a fine-grained view on the assetU+2019s status. In this work three unsupervised machine learning approaches that define a Health Indicator (HI) based on acoustic and vibration signals were empirically assessed. Such a HI ...

Adaptive learning systems aim to provide learning items tailored to the behavior and needs of individual learners. However, one of the outstanding challenges in adaptive item selection is that often the corresponding systems do not have information on initial ability levels of new learners entering a learning environment. Thus, the proficiency of those new learners is very difficult to be predicted. This heavily impairs the quality of ...

We propose a general framework for designing machine learning models that deal with constructing complex structures in the output space. The goal is to provide an abstraction layer to easily represent and design constructive learning models. The learning approach is based on generalized linear training techniques, and exploits techniques from combinatorial optimization to deal with the complexity of the underlying inference required in this type ...

© 2019 The Authors Risk assessment has a primary role in safety-critical industries. However, it faces a series of overall challenges, partially related to technology advancements and increasing needs. There is currently a call for continuous risk assessment, improvement in learning past lessons and definition of techniques to process relevant data, which are to be coupled with adequate capability to deal with unexpected events and provide the ...

Accurate forecasts of local and regional agricultural production are essential for agricultural market contractors and operators to assist prize agreements as early as possible in the crop growing season. These forecasts are also helpful for societies to anticipate to limited food availability. Satellite remote sensing is a fairly recent but already established technology for large-scale agricultural production forecasting thanks to its ability ...

In today's digital world, cyber security is essential for a fair and well-functioning society. People, as well as companies and governments must be able to trust their computers, mobile devices and the services they use from companies and governments.An important element of cyber security is the fight against cyber crime. This fight has surpassed the deployment of 'passive infrastructure' such as firewalls and access control systems into an arms ...

Code smells represent poor implementation choices performed by developers when enhancing source code. Their negative impact on source code maintainability and comprehen-sibility has been widely shown in the past and several techniques to automatically detect them have been devised. Most of these techniques are based on heuristics, namely they compute a set of code metrics and combine them by creating detection rules; while they have a reasonable ...

© 2018, The Author(s). How well can machine learning predict the outcome of a soccer game, given the most commonly and freely available match data? To help answer this question and to facilitate machine learning research in soccer, we have developed the Open International Soccer Database. Version v1.0 of the Database contains essential information from 216,743 league soccer matches from 52 leagues in 35 countries. The earliest entries in the ...