Refine
Year of publication
- 2022 (2)
Document Type
- Article (2)
Language
- English (2)
Has Fulltext
- yes (2)
Is part of the Bibliography
- no (2)
Keywords
- entropy (2) (remove)
Institute
Publisher
- IOP Publishing (1)
- MDPI (1)
Detecting changes in plasmas is compulsory for control and the detection of novelties.
Moreover, automated novelty detection allows one to investigate large data sets to substantially
enhance the efficiency of data mining approaches. To this end we introduce permutation entropy
(PE) for the detection of changes in plasmas. PE is an information-theoretic complexity measure
based in fluctuation analysis that quantifies the degree of randomness (resp. disorder,
unpredictability) of the ordering of time series data. This method is computationally fast and
robust against noise, which allows the evaluation of large data sets in an automated procedure.
PE is applied on electron cyclotron emission and soft x-ray measurements in different
Wendelstein 7-X low-iota configuration plasmas. A spontaneous transition to high core-electron
temperature (Te) was detected, as well as a localized low-coherent intermittent oscillation which
ceased when Te increased in the transition. The results are validated with spectrogram analysis
and provide evidence that a complexity measure such as PE is a method to support in-situ
monitoring of plasma parameters and for novelty detection in plasma data. Moreover, the
acceleration in processing time offers implementations of plasma-state-detection that provides
results fast enough to induce control actions even during the experiment.
Metrological methods for word learning list tests can be developed with an information theoretical approach extending earlier simple syntax studies. A classic Brillouin entropy expression is applied to the analysis of the Rey’s Auditory Verbal Learning Test RAVLT (immediate recall), where more ordered tasks—with less entropy—are easier to perform. The findings from three case studies are described, including 225 assessments of the NeuroMET2 cohort of persons spanning a cognitive spectrum from healthy older adults to patients with dementia. In the first study, ordinality in the raw scores is compensated for, and item and person attributes are separated with the Rasch model. In the second, the RAVLT IR task difficulty, including serial position effects (SPE), particularly Primacy and Recency, is adequately explained (Pearson’s correlation R=0.80) with construct specification equations (CSE). The third study suggests multidimensionality is introduced by SPE, as revealed through goodness-of-fit statistics of the Rasch analyses. Loading factors common to two kinds of principal component analyses (PCA) for CSE formulation and goodness-of-fit logistic regressions are identified. More consistent ways of defining and analysing memory task difficulties, including SPE, can maintain the unique metrological properties of the Rasch model and improve the estimates and understanding of a person’s memory abilities on the path towards better-targeted and more fit-for-purpose diagnostics.