Results 11 to 20 of about 1,286,114 (315)
Gaussian mixture model for time series-based structural damage detection
Computer Assisted Methods in Engineering and Science, 2017 In this paper, a time series-based damage detection algorithm is proposed using Gaussian mixture model (GMM) and expectation maximization (EM) framework. The vibration time series from the structure are modelled as the autoregressive (AR) processes. The
Marek Słoński
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Research on flow characteristics of aerostatic circular thrust bearing
The Journal of Engineering, 2018 In order to improve the pressure distribution, the aerostatic circular thrust bearing with single supply hole was studied. In the computational fluid dynamics (CFD) simulation, the laminar model, the turbulent model, the mixture model of laminar and ...
Hechun Yu +4 more
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Long Time Sequential Task Learning From Unstructured Demonstrations
IEEE Access, 2019 Learning from demonstration (LfD), which provides a natural way to transfer skills to robots, has been extensively researched for decades, and an army of methods and applications have been developed and investigated for learning an individual or low ...
Huiwen Zhang, Yuwang Liu, Weijia Zhou
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Sample- and segment-size specific Model Selection in Mixture Regression Analysis [PDF]
, 2006 As mixture regression models increasingly receive attention from both theory and practice, the question of selecting the correct number of segments gains urgency.
Sarstedt, Marko
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Granular Temperature and Segregation in Dense Sheared Particulate Mixtures
KONA Powder and Particle Journal, 2016 In gravity-driven flows of different-sized (same density) particles, it is well known that larger particles tend to segregate upward (toward the free surface), and the smaller particles downward in the direction of gravity.
Kimberly M. Hill, Yi Fan
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Global Heart, 2020 Background: Although increased age is associated with higher systolic blood pressure (SBP) in general, there may be variation across individuals in how SBP changes over time.
Haiqun Lin +11 more
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Energies, 2021 The present study deals with the numerical simulation of mixed convective heat transfer from an unconfined heated square cylinder using nanofluids (Al2O3-water) for Reynolds number (Re) 10–150, Richardson number (Ri) 0–1, and nanoparticles volume ...
Rajendra S. Rajpoot +2 more
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IgnasiPuigUPC/Mixture-Model-Application-Article-Code: Release 1
, 2021 First release of the code, data and html companions to the article "A mixture model application in monitoring error message rates for a distributed industrial ...
IgnasiPuigUPC
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Modeling Learner Heterogeneity: A Mixture Learning Model With Responses and Response Times
Frontiers in Psychology, 2018 The increased popularity of computer-based testing has enabled researchers to collect various types of process data, including test takers' reaction time to assessment items, also known as response times. In recent studies, the relationship between speed
Susu Zhang, Shiyu Wang
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Deep Gaussian mixture models [PDF]
Statistics and Computing, 2017 Deep learning is a hierarchical inference method formed by subsequent multiple layers of learning able to more efficiently describe complex relationships. In this work, Deep Gaussian Mixture Models are introduced and discussed. A Deep Gaussian Mixture model (DGMM) is a network of multiple layers of latent variables, where, at each layer, the variables ...
Cinzia Viroli, Geoffrey J. McLachlan
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