Results 111 to 120 of about 380,780 (306)

Reliable and Efficient Inference of Bayesian Networks from Sparse Data by Statistical Learning Theory [PDF]

, 2003
Dominik Janzing, Daniel Herrmann
openalex   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

Developing Medical Students as Educators: A Course Applying Teaching and Learning Theory to Question Writing. [PDF]

Med Sci Educ, 2023
Hubner BA, Walker J.
europepmc   +1 more source

Complex Cryptographic and User‐Centric Physically Unclonable Functions Enabled by Strain‐Sensitive Nanocrystals via Selective Ligand Exchange

Advanced Functional Materials, EarlyView.
This study investigates electromechanical PUFs that improve on traditional electric PUFs. The electron transport materials are coated randomly through selective ligand exchange. It produces multiple keys and a key with motion dependent on percolation and strain, and approaches almost ideal inter‐ and intra‐hamming distances.
Seungshin Lim, Hanseok Seo, Taesung Park, Byung Ku Jung, Junhyeok Park, Young Kyun Choi, Dae Yang Oh, Soong Ju Oh   +7 more
wiley   +1 more source

Can the learning of a topic in craft theory be improved for carpentry and joinery apprentices by using a tool of digital media as a learning resource?

, 2009
David J. Loftus
openalex   +1 more source

Ice Lithography: Recent Progress Opens a New Frontier of Opportunities

Advanced Functional Materials, EarlyView.
This review focuses on recent advancements in ice lithography, including breakthroughs in compatible precursors and substrates, processes and applications, hardware, and digital methods. Moreover, it offers a roadmap to uncover innovation opportunities for ice lithography in fields such as biological, nanoengineering and microsystems, biophysics and ...
Bingdong Chang, Gwendoline A. E. Anand, Rubaiyet Haque, Dylan A. Chiaro, Mona Sharma, Andrew R. Williams, Frank Niklaus, Daryl W. Yee, Gavin M. King, Anpan Han   +9 more
wiley   +1 more source

Metasurface-empowered snapshot hyperspectral imaging with convex/deep (CODE) small-data learning theory. [PDF]

Nat Commun, 2023
Lin CH, Huang SH, Lin TH, Wu PC.
europepmc   +1 more source

Learning domain theories

, 2004
Pulman, S, Liakata, M
openaire   +4 more sources

Reinforcement Learning: Theory and Application [PDF]

openalex   +1 more source

Ultrahigh‐Yield, Multifunctional, and High‐Performance Organic Memory for Seamless In‐Sensor Computing Operation

Advanced Functional Materials, EarlyView.
Molecular engineering of a nonconjugated radical polymer enables a significant enhancement of the glass transition temperature. The amorphous nature and tunability of the polymer, arising from its nonconjugated backbone, facilitates the fabrication of organic memristive devices with an exceptionally high yield (>95%), as well as substantial ...
Daeun Kim, Jaehyoung Ko, Namju Kim, Quynh H. Nguyen, Hoyeon Lee, Joohwan Eo, Seongeon Jin, Ji Eon Kwon, Seung‐Yeol Jeon, Youngdo Jeong, Dongseok Kwon, Sung Gap Im, Sanghan Lee, Byung Chul Jang, Yongho Joo   +14 more
wiley   +1 more source