Metrics for Evaluating Explainable Recommender Systems

Recommender systems aim to support their users by reducing information overload so that they can make better decisions. Recommender systems must be transparent, so users can form mental models about the system’s goals, internal state, and capabilities, that are in line with their actual design. Explanations and transparent behaviour of the...

A fast characterization method for semi-invasive fault injection attacks

Semi-invasive fault injection attacks are powerful techniques well-known by attackers and secure embedded system designers. When performing such attacks, the selection of the fault injection parameters is of utmost importance and usually based on the experience of the attacker. Surprisingly, there exists no formal and general approach to...

Testing the predictive power of visual discomfort from glare metrics in the near-window and near-wall zones of the daylit classroom environment

The objective of the present study was to find how well a group of selected luminance-based metrics predict reported visual discomfort from daylight glare in spatial conditions that differ from the conditions where metrics tend to developed and validated for. An empirical study involving the assessment of visual discomfort from glare by n=50...

Chamulteon: Coordinated Auto-Scaling of Micro-Services

Nowadays, in order to keep track of the fast-changing requirements of Internet applications, auto-scaling is used as an essential mechanism for adapting the number of provisioned resources to the resource demand. The straightforward approach is to deploy a set of common and opensource single-service auto-scalers for each service independently....