Results 111 to 120 of about 197,948 (294)

Characterization of Droplet Formation in Ultrasonic Spray Coating: Influence of Ink Formulation Using Phase Doppler Anemometry and Machine Learning

Advanced Materials Technologies, EarlyView.
This study explores how machine learning models, trained on small experimental datasets obtained via Phase Doppler Anemometry (PDA), can accurately predict droplet size (D32) in ultrasonic spray coating (USSC). By capturing the influence of ink complexity (solvent, polymer, nanoparticles), power, and flow rate, the model enables precise droplet control
Pieter Verding, Danny E. P. Vanpoucke, Yunus T. Aksoy, Tobias Corthouts, Maria R. Vetrano, Wim Deferme   +5 more
wiley   +1 more source

Univariate and Bivariate Empirical Mode Decomposition for Postural Stability Analysis

EURASIP Journal on Advances in Signal Processing, 2008
The aim of this paper was to compare empirical mode decomposition (EMD) and two new extended methods of  EMD named complex empirical mode decomposition (complex-EMD) and bivariate empirical mode decomposition (bivariate-EMD).
Jacques Duchêne, David Hewson, Hichem Snoussi, Hassan Amoud   +3 more
doaj   +1 more source

PERFORMANCE EVALUATION OF ENSEMBLE EMPIRICAL MODE DECOMPOSITION

Advances in Adaptive Data Analysis, 2009
Empirical mode decomposition (EMD) is an adaptive, data-driven algorithm that decomposes any time series into its intrinsic modes of oscillation, which can then be used in the calculation of the instantaneous phase and frequency. Ensemble EMD (EEMD), where the final EMD is estimated by averaging numerous EMD runs with the addition of noise, was an ...
Rami K. Niazy, Christian F. Beckmann, J. Michael Brady, Stephen M. Smith 0001   +3 more
openaire   +2 more sources

Bidirectional Process Prediction in the Laser‐Induced‐Graphene Production Using Blackbox Deep Learning

Advanced Materials Technologies, EarlyView.
This study shows that a lightweight blackbox neural network provides a practical, cost‐effective solution for bidirectional process prediction in laser‐induced graphene (LIG) fabrication. Achieving high predictive performance with minimal overhead, the approach democratizes machine learning (ML) for resource‐limited environments.
Maxim Polomoshnov, Nitheesh M. Nair, Gerardo Hernández‐Sosa, Markus Reischl   +3 more
wiley   +1 more source

Tumbling Magnetic Microrobots for Targeted In Vivo Drug Delivery in the GI Tract

Advanced Robotics Research, EarlyView.
We introduce a microrobot design and integrated system for on‐demand targeted drug release in the gastrointestinal tract. The microrobot has an embedded magnet for actuation with external magnetic fields and is visualized in real time using ultrasound. It has two drug release ports sealed with a thermally sensitive wax. Local heating of the wax using a
Aaron C. Davis, Luis Carlos Sanjuan Acosta, Shubh P. Mehta, Baiyan Qi, Yang Yang, Luis Solorio, Craig J. Goergen, David J. Cappelleri   +7 more
wiley   +1 more source

A State‐Adaptive Koopman Control Framework for Real‐Time Deformable Tool Manipulation in Robotic Environmental Swabbing

Advanced Robotics Research, EarlyView.
This work presents a state‐adaptive Koopman linear quadratic regulator framework for real‐time manipulation of a deformable swab tool in robotic environmental sampling. By combining Koopman linearization, tactile sensing, and centroid‐based force regulation, the system maintains stable contact forces and high coverage across flat and inclined surfaces.
Siavash Mahmoudi, Amirreza Davar, Dongyi Wang   +2 more
wiley   +1 more source

Backpropagation Through Soft Body: Investigating Information Processing in Brain–Body Coupling Systems

Advanced Robotics Research, EarlyView.
This study explores how information processing is distributed between brains and bodies through a codesign approach. Using the “backpropagation through soft body” framework, brain–body coupling agents are developed and analyzed across several tasks in which output is generated through the agents’ physical dynamics.
Hiroki Tomioka, Katsuma Inoue, Yasuo Kuniyoshi, Kohei Nakajima   +3 more
wiley   +1 more source

A 3D In Vitro Model of the Human Hepatobiliary Junction

Advanced Science, EarlyView.
A 3D human organoid platform reconstructs the hepatobiliary junction between primary adult hepatocytes and intrahepatic cholangiocytes. These adult hepatobiliary organoids (aHBOs) support directional bile transport from canaliculi to ductule‐like structures, enable quantitative imaging of junction dynamics, and reveal cell‐type‐specific vulnerabilities
Ashley D. Westerfield, Katarzyna A. Grzelak, Katie Katsuyama, Vardhman Kumar, Bess M. Miller, Joa Yun, Jesse Kirkpatrick, David Mankus, Margaret E. Bisher, Abigail K.R. Lytton‐Jean, Z. Gordon Jiang, David D. Lee, Christopher S. Chen, Sangeeta N. Bhatia   +13 more
wiley   +1 more source

How do you make a time series sing like a choir? Using the Hilbert-Huang transform to extract embedded frequencies from economic or financial time series [PDF]

The Hilbert-Huang transform (HHT) was developed late last century but has still to be introduced to the vast majority of economists. The HHT transform is a way of extracting the frequency mode features of cycles embedded in any time series using an ...
Crowley, Patrick M
core  

Stabilization of Single Metal Atoms on Graphitic Carbon Nitride: Synthetic Strategies and Emerging Applications

Advanced Science, EarlyView.
This review highlights recent advancements in stabilizing single metal atoms on graphitic carbon nitride emphasizing innovative synthesis strategies and emerging applications in electrocatalysis, photocatalysis and organic transformations, along with key challenges and future perspective. Abstract Emerging as a new frontier in catalysis science, single‐
Wenyao Zhang, Junjie Cui, Zhenjie Yao, Boyuan Zhu, Nithinraj Panangattu Dharmarajan, Ajayan Vinu, Junwu Zhu   +6 more
wiley   +1 more source