Results 241 to 250 of about 14,908,682 (295)

Exploring Collaborative Patterns in Neurodiverse Teams: A Hidden Markov Model Approach Using Physiological Signals. [PDF]

Proc Hum Factors Ergon Soc Annu Meet
Kim S, Wang M, Fok M, Hornburg CB, Jeon M, Scarpa A.   +5 more
europepmc   +1 more source

Hidden Markov Model for Parkinson's Disease Patients Using Balance Control Data. [PDF]

Bioengineering (Basel)
Safi K, Aly WHF, Kanj H, Khalifa T, Ghedira M, Hutin E.   +5 more
europepmc   +1 more source

The Geographic Moran Effect: Theory, Methods, and Interpretation

Geographical Analysis, Volume 59, Issue 1, January 2027.
ABSTRACT The Moran effect traditionally refers to the synchronization of population dynamics driven by shared environmental forcing rather than direct interactions among populations. Although extensively studied in population ecology, the Moran effect has received limited attention in geography, and its applicability remains insufficiently explored. In
Zhenzhi Jiao, X. Angela Yao, Jean‐Claude Thill   +2 more
wiley   +1 more source

Hidden Markov model-based similarity measure (HMM-SM) for gait quality assessment of lower-limb prosthetic users using inertial sensor signals. [PDF]

J Neuroeng Rehabil
Ng G, Andrysek J.
europepmc   +1 more source

Map‐Matching With Recursive Bayes Filter and Context‐Dependent Transition Dynamics for Scene Modeling in Automated Driving

Proceedings in Applied Mathematics and Mechanics, Volume 26, Issue 4, December 2026.
ABSTRACT We present an efficient multi‐object map‐matching approach for scene modeling in the context of automated driving. The mapping of traffic participants to the road topology is a key component of the scene modeling step in the processing pipeline for situation‐aware automated driving.
Maximilian Gerwien, Klaus Röbenack
wiley   +1 more source

An imputation method for single‐cell RNA sequencing data based on a parallel gated recurrent unit neural network

Quantitative Biology, Volume 14, Issue 4, December 2026.
Abstract Single‐cell RNA sequencing (scRNA‐seq) generates high‐dimensional transcriptomic data but is severely affected by dropout events, which obscure true gene–gene relationships. These missing values introduce bias into downstream analyses, complicate data processing, and reduce analytical efficiency.
Shuang Xu, Xiangtao Li, Jingsong Li, Yu Jiang   +3 more
wiley   +1 more source

Genomic characterization of a MAGIC population containing introgressions from four tetraploid Gossypium species

The Plant Genome, Volume 19, Issue 4, December 2026.
Abstract One strategy for increasing the genetic diversity of upland cotton (Gossypium hirsutum) involves the introgression of beneficial alleles from related and wild tetraploid species. Progress in this area has been limited due to undesirable outcomes associated with whole genome interspecific hybridization. To minimize genetic influences from other
Ganesh Pinnika, Ping Li, Jack C. McCarty, Johnie N. Jenkins, David D. Fang   +4 more
wiley   +1 more source

Speech Synthesis Based on Hidden Markov Models [PDF]

Proceedings of the IEEE, 2013
This paper gives a general overview of hidden Markov model (HMM)-based speech synthesis, which has recently been demonstrated to be very effective in synthesizing speech.
Keiichi Tokuda, Junichi Yamagishi, Tomoki Toda   +2 more
exaly   +2 more sources

Hidden Semi-Markov Models

Artificial Intelligence, 2010
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Shunzheng Yu
exaly   +3 more sources

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Markov models — hidden Markov models

Nature Methods, 2019
“Everything we see hides another thing, we always want to see what is hidden by what we see” — Rene ...
Jasleen K. Grewal, Martin Krzywinski, Naomi Altman   +2 more
openaire   +1 more source