Results 101 to 110 of about 4,529 (276)

Intelligent Monitoring System Based on Noise-Assisted Multivariate Empirical Mode Decomposition Feature Extraction and Neural Networks. [PDF]

Comput Intell Neurosci, 2022
Zhao LF, Siahpour S, Haeri Yazdi MR, Ayati M, Zhao TY.   +4 more
europepmc   +1 more source

Feature extraction from ear-worn sensor data for gait analysis [PDF]

, 2014
Gait analysis has a significant role in assessing human's walking pattern. It is generally used in sports science for understanding body mechanics, and it is also used to monitor patients' neuro-disorder related gait abnormalities.
Benny Lo, Li, Ling, Ling Li, Guang-Zhong Yang, Louis Atallah, Yang, Guang-Zhong, Atallah, Louis, Lo, Benny   +7 more
core   +1 more source

Effectiveness of Sustainability Rating Scales in Dual‐Labeling: The Role of Eco‐Label Familiarity in Consumer Responses

Business Strategy and the Environment, EarlyView.
ABSTRACT Eco‐labels and sustainability rating scales are widely used to communicate product sustainability, yet it remains unclear whether combining these signals enhances or undermines consumer responses. Drawing on signaling theory, this study examines how eco‐label familiarity and the presence of a sustainability rating scale jointly shape consumer ...
Sara Raubvogel, Mariana Moncada de la Fuente, Marilyne Chicoine, Ebenezer Miezah Kwofie   +3 more
wiley   +1 more source

Research on rotor fault diagnosis technology of three-phase asynchronous motor based on NA-MEMD mutual information and SVM

Measurement + Control
Aiming at the problem of mode aliasing in the adaptive decomposition of nonlinear and non-stationary current signals generated by three-phase asynchronous motor faults, and the fault features contained in signals collected by a single sensor can not be ...
Hui Ali, Yu Jie, Lu Weiqiang
doaj   +1 more source

Mechanistic deconvolution of BSA size variants by constrained Raman pseudo‐Voigt hard modeling during anion‐exchange chromatography

Biotechnology Progress, EarlyView.
Abstract In biopharmaceutical manufacturing, protein aggregation is a critical quality attribute, necessitating rapid and reliable analytical strategies during downstream processes like anion‐exchange chromatography (AEX). While Raman spectroscopy enables continuous monitoring of protein secondary structure, standard data‐driven regression models ...
Jakob Heyer‐Müller, Robin Schiemer, Lars Robbel, Michael Schmitt, Jürgen Hubbuch   +4 more
wiley   +1 more source

Deep LSTM Surrogates for MEMD: A Noise-Assisted Approach to EEG Intrinsic Mode Function Extraction

Information
In this paper, we propose a deep learning-based surrogate model for Multivariate Empirical Mode Decomposition (MEMD) using Long Short-Term Memory (LSTM) networks, aimed at efficiently extracting Intrinsic Mode Functions (IMFs) from ...
Pablo Andres Muñoz-Gutierrez, Diego Fernando Ramirez-Jimenez, Eduardo Giraldo   +2 more
doaj   +1 more source

Frequency-Resolved Dynamic Functional Connectivity Reveals Scale-Stable Features of Connectivity-States

Frontiers in Human Neuroscience, 2018
Investigating temporal variability of functional connectivity is an emerging field in connectomics. Entering dynamic functional connectivity by applying sliding window techniques on resting-state fMRI (rs-fMRI) time courses emerged from this topic.
Markus Goldhacker, Markus Goldhacker, Ana M. Tomé, Ana M. Tomé, Mark W. Greenlee, Elmar W. Lang, Elmar W. Lang   +6 more
doaj   +1 more source

AI inspired EEG-based spatial feature selection method using multivariate empirical mode decomposition for emotion classification. [PDF]

Multimed Syst, 2022
Asghar MA, Khan MJ, Rizwan M, Shorfuzzaman M, Mehmood RM.   +4 more
europepmc   +1 more source

Artificial Intelligence Tools for Carbon Nanotube Research: Opportunities From Synthesis to Applications

Carbon and Hydrogen, EarlyView.
Artificial intelligence tools are reshaping carbon nanotube research by connecting synthesis, characterization, and application‐oriented design. This review outlines how supervised learning, deep learning, Bayesian optimization, and large language models accelerate data extraction, experiment planning, and structure–property discovery for carbon ...
Yanlong Zhao, Fei Wang, Qixuan Cai, Aike Xi, Kangkang Wang, Khaixien Leu, Rufan Zhang   +6 more
wiley   +1 more source

Feature Extraction and Simulation of EEG Signals During Exercise-Induced Fatigue

IEEE Access, 2019
Accurate extraction of EEG signal characteristics during exercise fatigue can provide a scientific basis for sports fatigue detection and exercise fatigue injury treatment.
Zhongwan Yang, Huijie Ren
doaj   +1 more source