Results 71 to 80 of about 781,500 (170)
Inherent Fuzzy Entropy for the Improvement of EEG Complexity Evaluation [PDF]
, 2018 © 2017 IEEE. In recent years, the concept of entropy has been widely used to measure the dynamic complexity of signals. Since the state of complexity of human beings is significantly affected by their health state, developing accurate complexity ...
Zehong Cao +3 more
core +1 more source
Advanced Science, EarlyView.Polymer‐based hydrogels have emerged as promising materials for atmospheric water harvesting (AWH) due to their high water affinity, tunable network structure, and excellent moisture adsorption‐desorption performance. Functional hydrogel systems enable efficient water capture and controlled release under low‐energy conditions, offering a sustainable ...
Swagata Datta +6 more
wiley +1 more source
, 2016 Multiscale entropy (MSE) is an appealing tool to characterize the complexity of time series over multiple temporal scales. Recent developments in the field have tried to extend the MSE technique in different ways. Building on these trends, we propose the
Azami, Hamed, Escudero, Javier
core +1 more source
Prioritised fuzzy constraint satisfaction problems: axioms, instantiation and validation [PDF]
, 2003 This paper identifies a generic axiom framework for prioritised fuzzy constraint satisfaction problems (PFCSPs), and proposes methods to instantiate it (i.e., to construct specific schemes which obey the generic axiom framework).
Luo, X. +14 more
core +1 more source
BioengineeringAlzheimer’s disease (AD) is a neurodegenerative brain disorder that affects cognitive functioning and memory. Current diagnostic tools, including neuroimaging techniques and cognitive questionnaires, present limitations such as invasiveness, high costs ...
Andrea Cataldo +5 more
semanticscholar +1 more source
Research on Feature Extraction of Ship-Radiated Noise Based on Multiscale Fuzzy Dispersion Entropy
Journal of Marine Science and Engineering, 2023 In recent years, fuzzy dispersion entropy (FDE) has been proposed and used in the feature extraction of various types of signals. However, FDE can only analyze a signal from a single time scale during practical application and ignores some important information.
Yuxing Li +3 more
openaire +2 more sources
Evolution of Physical Intelligence Across Scales
Advanced Intelligent Discovery, EarlyView.By following the evolution of physical intelligence across scales, this article shows how intelligence arises from materials, structures, physical interactions, and collectives. It establishes physical intelligence as the evolutionary foundation upon which embodied intelligence is built.
Ke Liu +7 more
wiley +1 more source
Jixie chuandong, 2021 When the gearbox fails， its vibration signal is unstable and nonlinear. The commonly applied gearbox fault diagnosis methods are almost all based on the single-channel vibration signal analysis，which is easy to cause the loss of fault information，so the ...
Fuming Zhou +4 more
doaj
Cell Segmentation Beyond 2D—A Review of the State‐of‐the‐Art
Advanced Intelligent Discovery, EarlyView.Cell segmentation underpins many biological image analysis tasks, yet most deep learning methods remain limited to 2D despite the inherently 3D nature of cellular processes. This review surveys segmentation approaches beyond 2D, comparing 2.5D and fully 3D methods, analyzing 31 models and 32 volumetric datasets, and introducing a unified reference ...
Fabian Schmeisser +6 more
wiley +1 more source
Multiscale Fluctuation-Based Dispersion Entropy and Its Applications to Neurological Diseases
IEEE Access, 2019 Fluctuation-based dispersion entropy (FDispEn) is a new approach to estimate the dynamical variability of the fluctuations of signals. It is based on Shannon entropy and fluctuation-based dispersion patterns.
Hamed Azami +6 more
doaj +1 more source