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Hidden Semi-Markov Models-Based Visual Perceptual State Recognition for Pilots [PDF]
Sensors, 2023 Pilots’ loss of situational awareness is one of the human factors affecting aviation safety. Numerous studies have shown that pilot perception errors are one of the main reasons for a lack of situational awareness without a proper system to detect these ...
Lina Gao, Changyuan Wang, Gongpu Wu
doaj +2 more sources
Semi-Markov and hidden semi-Markov models of energy systems [PDF]
E3S Web of Conferences, 2018 The problem of information control systems creation for energy systems and transition to intelligent control and engineering is one of the important problems of reliability and efficiency theory for energy systems. The solution of this problem is possible based on construction of mathematical models concerning different aspects of these systems ...
Yuriy E. Obzherin
openalex +3 more sources
biomvRhsmm: genomic segmentation with hidden semi-Markov model. [PDF]
Biomed Res Int, 2014 High-throughput technologies like tiling array and next-generation sequencing (NGS) generate continuous homogeneous segments or signal peaks in the genome that represent transcripts and transcript variants (transcript mapping and quantification), regions of deletion and amplification (copy number variation), or regions characterized by particular ...
Du Y, Murani E, Ponsuksili S, Wimmers K.
europepmc +5 more sources
Labeling self-tracked menstrual health records with hidden semi-Markov models [PDF]
IEEE Journal of Biomedical and Health Informatics, 2021 AbstractGlobally, millions of women track their menstrual cycle and fertility via smartphone-based health apps, generating multivariate time series with frequent missing data. To leverage data from self-tracking tools in epidemiological studies on fertility or the menstrual cycle’s effects on diseases and symptoms, it is critical to have methods for ...
Laura Symul, Susan Holmes
+7 more sources
Bayesian Nonparametric Hidden Semi-Markov Models [PDF]
, 2012 There is much interest in the Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM) as a natural Bayesian nonparametric extension of the ubiquitous Hidden Markov Model for learning from sequential and time-series data. However, in many settings the HDP-HMM's strict Markovian constraints are undesirable, particularly if we wish to learn or encode
Matthew Johnson, Alan S. Willsky
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Hidden Semi-Markov Models for Predictive Maintenance [PDF]
Mathematical Problems in Engineering, 2015 Realistic predictive maintenance approaches are essential for condition monitoring and predictive maintenance of industrial machines. In this work, we propose Hidden Semi-Markov Models (HSMMs) with (i) no constraints on the state duration density function and (ii) being applied to continuous or discrete observation. To deal with such a type of HSMM, we
Francesco Cartella +3 more
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Hidden semi-Markov models to segment reading phases from eye movements
Journal of Eye Movement Research, 2022 Our objective is to analyze scanpaths acquired through participants achieving a reading task aiming at answering a binary question: Is the text related or not to some given target topic? We propose a data-driven method based on hidden semi-Markov chains to segment scanpaths into phases deduced from the model states, which are shown to represent ...
Brice Olivier +2 more
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A hidden semi-Markov model for estimating burst suppression EEG. [PDF]
Annu Int Conf IEEE Eng Med Biol Soc, 2019 Burst suppression is an electroencephalogram (EEG) pattern associated with profoundly inactivated brain states characterized by cerebral metabolic depression. This pattern is distinguished by short-duration band-limited electrical activity (bursts) interspersed between relatively near-isoelectric periods (suppressions).
Chakravarty S +4 more
europepmc +6 more sources
The Hierarchical Dirichlet Process Hidden Semi-Markov Model [PDF]
, 2012 There is much interest in the Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM) as a natural Bayesian nonparametric extension of the traditional HMM. However, in many settings the HDP-HMM's strict Markovian constraints are undesirable, particularly if we wish to learn or encode non-geometric state durations.
Matthew Johnson, Alan S. Willsky
openalex +4 more sources
Hidden Semi-Markov Models for Rainfall-Related Insurance Claims
Insurance: Mathematics and Economics, 2023 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yue Shi +3 more
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