Results 131 to 140 of about 24,340,587 (290)
Continual Learning for Multimodal Data Fusion of a Soft Gripper
Advanced Robotics Research, EarlyView.Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley +1 more source
Advanced Robotics Research, EarlyView.This review maps the methods to monitor robots’ health by fusing vibration, sound, control signals, vision, force, and oil information with artificial intelligence. It identifies deep learning, transfer learning, digital twins, and physics‐informed models as key methodological pathways enabling earlier diagnosis, safer human–robot collaboration, and ...
Yuting Qiao +6 more
wiley +1 more source
A multivariate analysis of cardiopulmonary parameters in archery performance
Human Movement, 2018 Vijayamurugan Eswaramoorthi +9 more
doaj +1 more source
Advanced Science, EarlyView.This study reveals a copper‐driven mechanism of COPD acute exacerbations mediated by the TNF‐α/ATP7A axis. TNF‐α suppresses the copper transporter ATP7A via competitive NF‐κB/CREB1/CBP signaling, resulting in intracellular copper accumulation, mitochondrial oxidative stress, and epithelial barrier disruption.
Xinru Xiao +7 more
wiley +1 more source
Tools for Exploring Multivariate Data: The Package ICS [PDF]
Invariant coordinate selection (ICS) has recently been introduced as a method for exploring multivariate data. It includes as a special case a method for recovering the unmixing matrix in independent components analysis (ICA).
Klaus Nordhausen +2 more
core
An Integrated NLP‐ML Framework for Property Prediction and Design of Steels
Advanced Science, EarlyView.This study presents a data‐driven framework that uses language‐processing techniques to interpret steel processing descriptions and machine‐learning models to predict mechanical properties. By organising complex process histories into meaningful groups and enabling rapid property forecasts, the work supports faster, more informed steel design through ...
Kiran Devraju +5 more
wiley +1 more source
"Multivariate stochastic volatility" [PDF]
We provide a detailed summary of the large and vibrant emerging literature that deals with the multivariate modeling of conditional volatility of financial time series within the framework of stochastic volatility.
Manabu Asai +2 more
core
ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals
Advanced Science, EarlyView.The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray +3 more
wiley +1 more source
Collinearity and multivariable analysis [PDF]
Intensive Care Medicine, 2016 Pierre-Géraud, Claret +2 more
openaire +2 more sources
SAS/IML Macros for a Multivariate Analysis of Variance Based on Spatial Signs [PDF]
Recently, new nonparametric multivariate extensions of the univariate sign methods have been proposed. Randles (2000) introduced an affine invariant multivariate sign test for the multivariate location problem. Later on, Hettmansperger and Randles (2002)
Jaakko Nevalainen, Hannu Oja
core