Fuzzy-TLX: using fuzzy integrals for evaluating human mental workload with NASA-Task Load indeX in laboratory and field studies

In order to investigate such phenomena, we have striven to build up a model relying on the minimal necessary ingredi- ents: Two populations of independent diffusing Ising parti-

Quantifications of the validity and the sensitivity of developed models suggest that rule-based expert systems can be successfully built for mental workload modelling and

The following noise filtration methods were analyzed: arithme- tic averaging filter, geometric averaging filter, median filtering, adaptive medi- an filtration, Gaussian filtration

It is demonstrated how these knowledge-bases, built by an expert upon the features extracted from the original NASA-TLX mental workload assessment technique (as per section 2.3), can

To granulate a signal TS (x,y) of length n, corresponding to the (x,y) pixel, successions of equal equivalence classes [i] Ck are considered (upper approximation). A granule

In this case, the test results are not measured in terms of clear logic (if the reference answer matches student’s answer, then the student knows the material, and vice versa), but

Because imprecision in data is better modeled by some functions rather that crisp values, i.e., nonsingleton fuzzy sets, we will consider that situation in the context of

Abstract—Most already existing indices used to compare two strict partitions with different number of clusters are based on coincidence matrices.. To extend such indices to