Results 151 to 160 of about 80,948 (300)
Automatic Determination of Quasicrystalline Patterns from Microscopy Images
This work introduces a user‐friendly machine learning tool to automatically extract and visualize quasicrystalline tiling patterns from atomically resolved microscopy images. It uses feature clustering, nearest‐neighbor analysis, and support vector machines. The method is broadly applicable to various quasicrystalline systems and is released as part of
Tano Kim Kender +2 more
wiley +1 more source
Memristors based on trimethylsulfonium (phenanthroline)tetraiodobismuthate have been utilised as a nonlinear node in a delayed feedback reservoir. This system allowed an efficient classification of acoustic signals, namely differentiation of vocalisation of the brushtail possum (Trichosurus vulpecula).
Ewelina Cechosz +4 more
wiley +1 more source
This article describes a multimodal fusion data acquisition and processing system about electromyography for dynamic movement recognition and bioelectrical impedance for key posture recognition. In addition, a new dynamic–static fusion algorithm strategy is designed.
Chenhao Cao +5 more
wiley +1 more source
The circular dichroism (CD) and circularly polarised (CPL) of a bis‐perylene diimide macrocycle are measured in single crystals. These chiroptical properties are tuned by the macrocycle's π–π stacking interactions in the solid‐state. Abstract Chiral materials that manipulate circularly polarised light have burgeoning applications across optoelectronics,
Denis Hartmann +6 more
wiley +2 more sources
This article develops a soft magnetic sensor array to extract 3D and distributional muscle deformations, which has highly consistent measurements in amphibious environments, robustness to hydraulic pressure, and about 200 ms faster response than an inertial measurement unit, achieving over 98% classification accuracy and below 3% phase estimation ...
Yuchao Liu +8 more
wiley +1 more source
This work presents a deep learning model to autonomously recognize and classify the secretion retention into three levels for patients receiving invasive mechanical ventilation, achieving 89.08% accuracy. This model can be implemented to ventilators by edge computing, whose feasibility is approved.
Shuai Wang +6 more
wiley +1 more source
Impact of Biomimetic Pinna Shape Variation on Clutter Echoes: A Machine Learning Approach
Bats with dynamic ear structures navigate dense, echo‐rich environments, yet the echoes they receive are highly random. This study shows that machine learning can reliably detect structural signatures in these seemingly chaotic biosonar signals. The results open new directions for biologically inspired sensing, where time‐varying receiver shapes ...
Ibrahim Eshera +2 more
wiley +1 more source
Mode Coupling and Nonlinear Resonances of MEMS Arch Resonators for Bandpass Filters. [PDF]
Hajjaj AZ, Hafiz MA, Younis MI.
europepmc +1 more source
Intravascular electroencephalography (ivEEG) using micro‐intravascular electrodes was developed. Cortical‐vein ivEEG showed a higher signal‐to‐noise ratio and finer spatial resolution of somatosensory evoked potentials (SEPs) than superior sagittal sinus ivEEG, and deep‐vein ivEEG captured clear visual evoked potentials.
Takamitsu Iwata +15 more
wiley +1 more source
Deep Learning Methods for Assessing Time‐Variant Nonlinear Signatures in Clutter Echoes
Motion classification from biosonar echoes in clutter presents a fundamental challenge: extracting structured information from stochastic interference. Deep learning successfully discriminates object speed and direction from bat‐inspired signals, achieving 97% accuracy with frequency‐modulated calls but only 48% with constant‐frequency tones. This work
Ibrahim Eshera +2 more
wiley +1 more source

