Search results for "probabilistic models"
showing 4 items of 4 documents
Development of a Taekwondo Combat Model Based on Markov Analysis
2019
The purpose of the present study was to examine male and female Olympic taekwondo competitors' movement patterns according to their tactical actions by applying a Markov processes analysis. To perform this study, 11,474 actions by male competitors and 12,980 actions by female competitors were compiled and analyzed. The results yielded 32 significant sequences among male competitors and 30 among female competitors. Male competitors demonstrated 11 sequences initiated by an attack, 11 initiated by a counterattack, and 10 initiated by a defensive action. Female competitors demonstrated nine sequences initiated by an attack, 11 initiated by a counterattack, and 10 initiated by a defensive move.…
Inverted Repeats in Viral Genomes
2004
We investigate 738 complete genomes of viruses to detect the presence of short inverted repeats. The number of inverted repeats found is compared with the prediction obtained for a Bernoullian and for a Markovian control model. We find as a statistical regularity that the number of observed inverted repeats is often greater than the one expected in terms of a Bernoullian or Markovian model in several of the viruses and in almost all those with a genome longer than 30,000 bp.
Discovering human mobility from mobile data : probabilistic models and learning algorithms
2020
Smartphone usage data can be used to study human indoor and outdoor mobility. In our work, we investigate both aspects in proposing machine learning-based algorithms adapted to the different information sources that can be collected.In terms of outdoor mobility, we use the collected GPS coordinate data to discover the daily mobility patterns of the users. To this end, we propose an automatic clustering algorithm using the Dirichlet process Gaussian mixture model (DPGMM) so as to cluster the daily GPS trajectories. This clustering method is based on estimating probability densities of the trajectories, which alleviate the problems caused by the data noise.By contrast, we utilize the collecte…
Whatever next? Predictive brains, situated agents, and the future of cognitive science
2012
In the target article, Andy Clark addresses the question of how a probabilistic predictive coding model of the mind relates to our personal level mental lives. This question, he suggests, is “potentially the most important” (MS46). The question is important indeed, but Clark’s answer fails to capitalize on another possible advantage of this approach. Clark suggests that there is a disconnect between the way the world appears to us, on one hand, and the way that it is represented in the brain, on the other. He deals with this disconnect by limiting the scope of the theory, by pointing out that he is discussing a theory of how brains encode and process information, not a theory about how thin…