Results 61 to 70 of about 2,043,515 (147)

Refined multiscale entropy using fuzzy metrics : validation and application to nociception assessment [PDF]

, 2019
The refined multiscale entropy (RMSE) approach is commonly applied to assess complexity as a function of the time scale. RMSE is normally based on the computation of sample entropy (SampEn) estimating complexity as conditional entropy. However, SampEn is
P. L. Gambus, Jensen, Erik Weber, Porta, Alberto, Pedro L. Gambús, J. D. Bolaños, Montserrat Vallverdú, E. W. Jensen, Erik W. Jensen, A. Porta, Bolaños, José D, Gambus, Pedro L., Vallverdú Ferrer, Montserrat, M. Vallverdú, Valencia Murillo, José Fernando, Alberto Porta, J. F. Valencia, José F. Valencia, Jose D. Bolaños   +17 more
core   +1 more source

Detecting Plateau Zokor (Eospalax baileyi) Mounds in UAV Imagery of Alpine Meadows Using Deep Learning Algorithms

Remote Sensing in Ecology and Conservation, EarlyView.
We developed PZM‐YOLO to automatically detect plateau zokor mounds in UAV imagery of alpine meadows. The model achieved reliable detection of small and densely distributed mounds under complex backgrounds, outperforming the baseline YOLOv5s. This framework supports mound counting, mound position, rodent impact assessment, and grassland restoration ...
Yang Yang, Limin Hua, Lianguo Wang, Jiazhen Li, Rui Dong, Siwei Yang   +5 more
wiley   +1 more source

Entropy and Multifractal-Multiscale Indices of Heart Rate Time Series to Evaluate Intricate Cognitive-Autonomic Interactions

, 2021
International audienceRecent research has clarified the existence of a networked system involving a cortical and subcortical circuitry regulating both cognition and cardiac autonomic control, which is dynamically organized as a function of cognitive ...
Bouny, Pierre, Arsac, Laurent, Touré Cuq, Emma, Deschodt-Arsac, Veronique, Laurent M. Arsac, Emma Touré Cuq, Pierre Bouny, Veronique Deschodt-Arsac   +7 more
core   +1 more source

Analyzing watershed system state through runoff complexity and driver interactions using multiscale entropy and deep learning

Ecological Indicators
Quantifying watershed state is crucial for ecological management and sustainable development. Traditional methods, often based on multiple indicators and subjective weighting, struggle to objectively and comprehensively capture the inherent complexity of
Xintong Liu, Hongrui Zhao
doaj   +1 more source

FEWT: Frequency‐Enhanced Wavelet‐Based Transformer for Multimodal Wheeled Bimanual Manipulation

SmartBot, EarlyView.
An embodied mobile bimanual robot learns dexterous manipulation skills through imitation learning with multimodal perception. The integration of vision, proprioception, and tactile sensing establishes a comprehensive perception–action loop, enabling the robot to continuously understand, interact with, and adapt to complex physical environments.
Jiaxin Huang, Hanyu Liu, Yunsheng Ma, Jian Shen, Yilin Zheng, Jiayi Wen, Zhigong Song   +6 more
wiley   +1 more source

Planetary Gearbox Fault Diagnosis Using RCMFE and P-t-SNE

Applied Sciences
Aiming at the difficulty of extracting fault features from nonlinear and non-stationary vibration signals of planetary gearboxes, a planetary gearbox fault diagnosis method based on Refined Composite Multiscale Fuzzy Entropy (RCMFE), Parametric-t ...
Lingyun Zhu, Huyan Zhang, Kang Huang, Chuangchuang Cui   +3 more
doaj   +1 more source

A Wildlife Multi‐Modal Recognition Method Based on Infrared Camera Images Using MWAC

Integrative Zoology, EarlyView.
A multimodal wild wildlife classification model MWAC consists of two parts:(1) Wavelet KAN module (WDS‐KAN) for image feature extraction, and (2) Label Correlated Text Extraction module (LC‐BERT) for text feature extraction. ABSTRACT Nowadays, infrared camera technology has become an important tool for large‐scale monitoring and assessment of wildlife ...
Siming Deng, Guoxiong Zhou, Genhua Liu, Zhishu Xiao, Xiaoqun Huang, Yang Hu, Ling Gui   +6 more
wiley   +1 more source

Integration of Refined Composite Multiscale Cross-Sample Entropy and Backpropagation Neural Networks for Structural Health Monitoring

, 2020
This study developed a structural health monitoring (SHM) system based on refined composite multiscale cross-sample entropy (RCMCSE) and an artificial neural network for monitoring structures under ambient vibrations.
Yu-Ching Chen, Tzu-Kang Lin
core   +1 more source

Controllable Intrinsic Surface Pattern Generation Using Slime Mold Simulations

Computer Graphics Forum, EarlyView.
Abstract Surface‐based pattern simulations have proven valuable for texture design and scientific visualization, but existing methods face several limitations. Most simulations either target a narrow range of pattern types (e.g. spots, branching) or support a broad range of patterns at the cost of time‐consuming parameter tuning.
Jeffrey Layton, Faramarz Samavati, Adam Runions   +2 more
wiley   +1 more source

The Refined Composite Downsampling Permutation Entropy Is a Relevant Tool in the Muscle Fatigue Study Using sEMG Signals

, 2021
Surface electromyography (sEMG) is a valuable technique that helps provide functional and structural information about the electric activity of muscles. As sEMG measures output of complex living systems characterized by multiscale and nonlinear behaviors,
Antonio Dávalos, Jabloun, Meryem, Meryem Jabloun, Dávalos, Antonio, Philippe Ravier, Ravier, Philippe, Olivier Buttelli, Buttelli, Olivier   +7 more
core   +1 more source