Results 101 to 110 of about 6,303,129 (314)

In Materia Shaping of Randomness with a Standard Complementary Metal‐Oxide‐Semiconductor Transistor for Task‐Adaptive Entropy Generation

Advanced Functional Materials, EarlyView.
This study establishes a materials‐driven framework for entropy generation within standard CMOS technology. By electrically rebalancing gate‐oxide traps and Si‐channel defects in foundry‐fabricated FDSOI transistors, the work realizes in‐materia control of temporal correlation – achieving task adaptive entropy optimization for reinforcement learning ...
Been Kwak, Ryun‐Han Koo, Youngchan Cho, Changhyeon Han, Dongbin Kim, Soi Jeong, Yunho Shin, Joonhyeok Choi, Jiseong Im, Jonghyun Ko, Jong‐Ho Lee, Jangsaeng Kim, Youngho Kang, Wonjun Shin, Daewoong Kwon   +14 more
wiley   +1 more source

Prediction and Analysis of Rice Production and Yields Using Ensemble Learning Techniques

Ilkom Jurnal Ilmiah
This research focuses on predicting and analyzing rice production and yield throughout the world using ensemble learning techniques. The study applies and compares three methods: linear regression, ARIMA, and ensemble learning, to predict rice harvest ...
Yudha Islami Sulistya, Aina Musdholifah, Chrissandy Sapuletea, Elsi Titasari Br Bangun, Hizbullah Hamda, Sarah Anjani, Abednego Dwi Septiadi   +6 more
doaj   +1 more source

Toward Scalable Solutions for Silver‐Based Gas Diffusion Electrode Fabrication for the Electrochemical Conversion of CO2 – A Perspective

Advanced Functional Materials, EarlyView.
In this study, the preparation techniques for silver‐based gas diffusion electrodes used for the electrochemical reduction of carbon dioxide (eCO2R) are systematically reviewed and compared with respect to their scalability. In addition, physics‐based and data‐driven modeling approaches are discussed, and a perspective is given on how modeling can aid ...
Simon Emken, K. Ashoke Raman, Alexander Bauer, Violeta Karyofylli, Eva Jodat, André Karl, Rüdiger‐A. Eichel   +6 more
wiley   +1 more source

Does a Morphotropic Phase Boundary Exist in ZrxHf1‐xO2‐Based Thin Films?

Advanced Functional Materials, EarlyView.
This study investigates 6 nm zirconium‐rich hafnium‐zirconium oxide thin–film metal–insulator–metal capacitors using a combination of experimental methods and machine learning–based molecular dynamics simulations to provide insight into the physical mechanisms that enhance the dielectric constant near 0 V and attribute it to the field‐induced ...
Pramoda Vishnumurthy, Richard Ganser, Dong‐Gyu Kim, Intak Jeon, Chang Hwa Jung, Hanjin Lim, Thomas Mikolajick, Susan Trolier‐McKinstry, Alfred Kersch, Uwe Schroeder   +9 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

Predicting Atomic Charges in MOFs by Topological Charge Equilibration

Advanced Functional Materials, EarlyView.
An atomic charge prediction method is presented that is able to accurately reproduce ab‐initio‐derived reference charges for a large number of metal–organic frameworks. Based on a topological charge equilibration scheme, static charges that fulfill overall neutrality are quickly generated.
Babak Farhadi Jahromi, Sumukh Shankar Sharadaprasad, Rochus Schmid   +2 more
wiley   +1 more source

Rational Design of Printable Carbon Nanotube Transparent Conductive Films via Data‐Driven and Mechanistic Insights

Advanced Functional Materials, EarlyView.
A machine learning and simulation‐guided strategy is demonstrated for gentle, non‐sonication dispersion of carbon nanotubes, preserving structural integrity and performance. This approach enables transparent conductive films with low sheet resistance, high transmittance, and sub‐20 µm printability.
Ying Zhou, Ken‐ichi Nomura, Shun Muroga, Makoto Yoneya, Don N. Futaba, Takeo Yamada, Reiko Azumi, Kenji Hata   +7 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

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

Universal Electronic‐Structure Relationship Governing Intrinsic Magnetic Properties in Permanent Magnets

Advanced Functional Materials, EarlyView.
Permanent magnets derive their extraordinary strength from deep, universal electronic‐structure principles that control magnetization, anisotropy, and intrinsic performance. This work uncovers those governing rules, examines modern modeling and AI‐driven discovery methods, identifies critical bottlenecks, and reveals electronic fingerprints shared ...
Prashant Singh
wiley   +1 more source