Results 91 to 100 of about 64,158 (253)
Advanced Functional Materials, EarlyView.A reconfigurable RRAM platform utilizing thermally pre‐formed filaments (TPFs) is developed to realize robust hardware security. By exploiting the thermodynamic stochasticity of TPFs, exceptionally reliable physically unclonable functions (PUFs) are achieved.
Seongbin Kwon +4 more
wiley +1 more source
Parsimonious ultrametric Gaussian mixture models
Statistics and ComputingAbstractGaussian mixture models represent a conceptually and mathematically elegant class of models for casting the density of a heterogeneous population where the observed data is collected from a population composed of a finite set of G homogeneous subpopulations with a Gaussian distribution.
Cavicchia, C, Vichi, M, Zaccaria, G
openaire +3 more sources
Advanced Functional Materials, EarlyView.Sulfur‐doped graphitized carbon nanofibers act as adaptive catalyst–support platforms, enabling dynamic sulfur‐mediated reconstruction and strong metal–support interactions. This unique behavior enhances catalyst stability and controls reaction pathways, achieving highly selective urea oxidation (∼92% N2) coupled with efficient hydrogen evolution ...
Melanie Guillén‐Soler +4 more
wiley +1 more source
Advanced Healthcare Materials, EarlyView.Metabolic labeling of nascent proteins in 3D microtissue spheroids provides a powerful analytical approach for large‐scale tissue engineering. Incorporation of non‐canonical amino acids with fluorescent tagging enables spatiotemporal investigation of extracellular matrix deposition and its evolution during multicellular tissue development and fusion ...
Theresa Koenig +3 more
wiley +1 more source
Urban Mobility Modeling: Application to Seoul Bike-Sharing Data
Engineering ProceedingsThis study applies a model from the normal variance–mean mixture family to capture daily demand in urban bike sharing. We fit both a mixture-based model and a standard Gaussian model to the logarithmic returns of total daily rental counts from the Seoul ...
Farouk Mselmi +2 more
doaj +1 more source
Gaussian Mixture Model with Rare Events
J. Mach. Learn. Res.We study here a Gaussian Mixture Model (GMM) with rare events data. In this case, the commonly used Expectation-Maximization (EM) algorithm exhibits extremely slow numerical convergence rate. To theoretically understand this phenomenon, we formulate the numerical convergence problem of the EM algorithm with rare events data as a problem about a ...
Xuetong Li +2 more
openaire +3 more sources
A Discriminative Gaussian Mixture Model with Sparsity
, 2019 In probabilistic classification, a discriminative model based on the softmax function has a potential limitation in that it assumes unimodality for each class in the feature space. The mixture model can address this issue, although it leads to an increase in the number of parameters.
Hideaki Hayashi, Seiichi Uchida
openaire +3 more sources
Advanced Healthcare Materials, EarlyView.Microfluidic coaxial extrusion generates size‐controlled 3D lymphatic tubes from primary human dermal lymphatic endothelial cells in a defined four‐component matrix. These engineered vessels self‐organize into stable lymphatic endothelium, maintain selective macromolecular permeability for 30 days, and enable direct comparison with blood endothelial ...
Elsa Mazari‐Arrighi +8 more
wiley +1 more source
A Probabilistic Multimedia Retrieval Model and Its Evaluation
EURASIP Journal on Advances in Signal Processing, 2003 We present a probabilistic model for the retrieval of multimodal documents. The model is based on Bayesian decision theory and combines models for text-based search with models for visual search.
de Jong Franciska +4 more
doaj +1 more source
Determining classes of food items for health requirements and nutrition guidelines using Gaussian mixture models. [PDF]
Front Nutr, 2023 Balakrishna Y +3 more
europepmc +1 more source