Results 281 to 290 of about 12,455,841 (338)

Multi-criteria dynamic weighting for batch mode active learning in aero-engine remaining useful life prediction

Ying Chen, Lubing Wang, Xufeng Zhao
openalex   +1 more source

Enhancing Synaptic Plasticity and Multistate Retention of Organic Neuromorphic Devices Using Anion‐Excessive Gel Electrolyte

Advanced Functional Materials, EarlyView.
Anion‐excessive gel‐based organic synaptic transistors (AEG‐OSTs) that can maintain electrical neutrality are developed to enhance synaptic plasticity and multistate retention. Key improvement is attributed to the maintenance of electrical neutrality in the electrolyte even after electrochemical doping, which reduces the Coulombic force acting on ...
Yousang Won, Jeongwoo Lee, Hyunwook Kim, Joon Hak Oh   +3 more
wiley   +1 more source

Targeted probiotic tabletting: A hybrid active learning and finite element modelling approach for process optimisation. [PDF]

Int J Pharm X
Wang B, Wang X, Klymenko OV, Hu J, Gibson R, Middleton A, Wu CY.   +6 more
europepmc   +1 more source

Development and Practice of Experimental Classwork on Ester Synthesis, Including Active and Inquiry-Based Learning for Science Programs

Yutaka Maeda, Daiki UCHIDA, Tatsuya Samejima, Michio Yamada   +3 more
openalex   +2 more sources

Spectrally Tuned Floating‐Gate Synapse Based on Blue‐ and Red‐Absorbing Organic Molecules for Wavelength‐Selective Neural Networks and Fashion Image Classifications

Advanced Functional Materials, EarlyView.
The characteristics of a vertical floating gate heterostructure transistor device that exhibits neuromorphic potentiation under visible light illumination are investigated. Due to spectrally‐tuned absorbance properties of each thin film layer and introduction of tunneling dielectric, the device enables wavelength‐selective tuning of synaptic plasticity
Seungme Kang, Jisoo Park, Jinwoong Hong, Jinmin Park, Jeongbo Lee, Hyeonjung Kim, Wonjun Shin, Eva Bestelink, Radu A. Sporea, Seyong Oh, Chung Whan Lee, Yun‐Hi Kim, Hocheon Yoo   +12 more
wiley   +1 more source

Knowledge graph-aided Bayesian active learning for top-K genetic interaction discovery. [PDF]

Sci Rep
Soper B, Lisicki M, Silva M, Cadena J, Zhu H, Sundaram S, Ray P, Drocco J.   +7 more
europepmc   +1 more source

THE USE OF ACTIVE LEARNING METHODS IN THE TRAINING OF FUTURE TEACHERS

Ozodova, Muqaddas
openalex   +1 more source

PRELIVE: A Framework for Predicting Lipid Nanoparticles In Vivo Efficacy and Reducing Reliance on Animal Testing

Advanced Functional Materials, EarlyView.
PREdicting LNP In Vivo Efficacy (PRELIVE) framework enables the prediction of lipid nanoparticle (LNPs) organ‐specific delivery through dual modeling approaches. Composition‐based models using formulation parameters and protein corona‐based models using biological fingerprints both achieve high predictive accuracy across multiple organs.
Belal I. Hanafy, Chuan‐En Lu, Kai Liu, Audrey Gallud   +3 more
wiley   +1 more source

Active learning meets metadynamics: automated workflow for reactive machine learning interatomic potentials.

Digit Discov
Vitartas V, Zhang H, Juraskova V, Johnston-Wood T, Duarte F.   +4 more
europepmc   +1 more source

Challenges and perceptions of dental undergraduate students regarding active learning in clinical practice: A qualitative study. [PDF]

PLoS One
Rodrigues MLA, Silva BNCD, Anjos MAD, Menegazzo EB, Herval ÁM, Guerra LM, Bulgareli JV.   +6 more
europepmc   +1 more source