Results 81 to 90 of about 545,363 (263)

High‐Performance Transparent, Deformable, and Recoverable Biomimetic Stevia–PVA Hydrogel Triboelectric Nanogenerator with Machine Learning‐Assisted Motion Recognition

Advanced Materials, EarlyView.
A transparent, deformable stevia–PVA hydrogel triboelectric nanogenerator delivers significantly enhanced mechanical strength and electrical output through biomimetic hydrogen‐bonded networks. Coupled with machine learning–assisted signal recognition, the self‐powered hydrogel enables accurate human‐motion sensing for intelligent wearable and IoT ...
Thien Trung Luu, Bui Minh Quang, Toan Minh Pham, Jinsoo Kim, Kyungwho Choi, Dukhyun Choi   +5 more
wiley   +1 more source

Large‐Scale Determination of Frontier Orbital Energies of Disordered Small‐Molecule Organic Semiconductors Using Exciplex Emission Spectra

Advanced Materials, EarlyView.
ABSTRACT Accurately knowing the frontier orbital energies of the structurally disordered small‐molecule organic semiconductors that are used in optoelectronic devices such as organic light‐emitting diodes is required to rationally improve their performance. Here, we show that these energies can be deduced with a large accuracy from the peak energies of
Christian B. McDonald, Hiroki Tomita, Giacomo Cotelli, Louka L. Brüll, Nanno G. de Rooij, Lucas R.L. Norg, Milo Clément, Reinder Coehoorn   +7 more
wiley   +1 more source

Distilling Diverse Knowledge for Deep Ensemble Learning

IEEE Access
Bidirectional knowledge distillation improves network performance by sharing knowledge between networks during the training of multiple networks. Additionally, performance is further improved by using an ensemble of multiple networks during inference ...
Naoki Okamoto, Tsubasa Hirakawa, Takayoshi Yamashita, Hironobu Fujiyoshi   +3 more
doaj   +1 more source

Phase Engineering of Nanomaterials (PEN): Evolution, Current Challenges, and Future Opportunities

Advanced Materials, EarlyView.
This review summarizes the synthesis, phase transition, advanced characterization spanning ex situ to in situ and operando techniques, and diverse applications of phase engineering of nanomaterials (PEN). It further outlines key challenges and future opportunities, such as phase stability, architecture control, and artificial intelligence (AI)‐driven ...
Ye Chen, Zhanxi Fan, Jingjie Ge, Qiyuan He, Zhuangchai Lai, Jiawei Liu, Chaoliang Tan, Hua Zhang   +7 more
wiley   +1 more source

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

Deep Learning- and Word Embedding-Based Heterogeneous Classifier Ensembles for Text Classification

Complexity, 2018
The use of ensemble learning, deep learning, and effective document representation methods is currently some of the most common trends to improve the overall accuracy of a text classification/categorization system.
Zeynep H. Kilimci, Selim Akyokus
doaj   +1 more source

In Situ Copper Electroplating Turns Material Extrusion 3D Printers Into Metal–Polymer Hybrid Fabricators

Advanced Materials Technologies, EarlyView.
An in situ electroplating approach for MEX 3D printing is proposed, enabling copper deposition during the fabrication of conductive polymers. The method combines a printer‐integrated plating head, ML‐based g‐code control, and stop‐and‐go printing, achieving near‐bulk copper conductivity and enabling fully embedded, assembly‐free electronic components ...
Gianluca Percoco, Nicola Larovere, Antonio Zagaria, Antonio Pavone, Rosanna Rifino, Gianni Stano   +5 more
wiley   +1 more source

Automatic Detection of Students’ Engagement During Online Learning: A Bagging Ensemble Deep Learning Approach

IEEE Access
The COVID-19 pandemic has reshaped education and shifted learning from in-person to online. While this shift offers advantages such as liberating the learning process from time and space constraints and enabling education to occur anywhere and anytime, a
Mayanda Mega Santoni, T. Basaruddin, Kasiyah Junus, Oenardi Lawanto   +3 more
doaj   +1 more source

Direct Gravity‐Induced Modulation of Cardiac Conduction Pathways Evidenced Through Propagation Features in Electrophysiological Mapping

Advanced Materials Technologies, EarlyView.
A high‐density wearable body‐surface potential mapping array reveals how gravity reshapes cardiac conduction in real time. By resolving spatiotemporal delay patterns invisible to conventional ECG, the platform uncovers posture‐dependent electrophysiological adaptations across the thorax.
Ruben Ruiz‐Mateos Serrano, Matias L. Picchio, Daniele Mantione, David Mecerreyes, George G. Malliaras   +4 more
wiley   +1 more source

Learning enhanced ensemble filters

Journal of Computational Physics
The filtering distribution in hidden Markov models evolves according to the law of a mean-field model in state-observation space. The ensemble Kalman filter (EnKF) approximates this mean-field model with an ensemble of interacting particles, employing a Gaussian ansatz for the joint distribution of the state and observation at each observation time ...
Eviatar Bach, Ricardo Baptista, Edoardo Calvello, Bohan Chen, Andrew Stuart   +4 more
openaire   +2 more sources