Results 131 to 140 of about 132,491 (300)
On the implicit learnability of knowledge [PDF]
The deployment of knowledge-based systems in the real world requires addressing the challenge of knowledge acquisition. While knowledge engineering by hand is a daunting task, machine learning has been proposed as an alternative.
Mocanu, Ionela Georgiana
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Causal‐Guided Ultra‐Long‐Term Time Series Forecasting Via Anticipated Covariates
Advanced Science, EarlyView.Often treated as unknown, information from the future remains underutilized.We demonstrate that in a coupled dynamical system, providing the future state of the effect enables accurate forecasting of the cause for a long timesteps. A time series forecasting paradigm that introduces anticipated covariates to represent such known future states is ...
Jintong Zhao +4 more
wiley +1 more source
Updatable Closed‐Form Evaluation of Arbitrarily Complex Multiport Network Connections
Advanced Electronic Materials, EarlyView.The inverse design of electrically large wave devices often uses reduced‐order multiport models with discrete optimization, requiring many evaluations of complex interconnections between subsystems that differ only in a few blocks. This paper introduces a closed‐form framework enabling efficient Woodbury low‐rank updates of related, previous ...
Hugo Prod'homme, Philipp del Hougne
wiley +1 more source
Physics‐Based Compact Modeling of Advanced 3D Nanoscale Vertical NAND Flash Memory
Advanced Electronic Materials, EarlyView.For advanced 3D NAND flash memory, a unified compact model for SPICE is proposed that spans from the intrinsic unit cell to the full string and captures the electrostatic coupling with adjacent inhibit strings. It can successfully predict read behavior, program/erase dynamics, and interactions between neighboring cells, reflecting array‐level behavior ...
Ilho Myeong, Seonho Shin, Ickhyun Song
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Advancing Energy Materials by In Situ Atomic Scale Methods
Advanced Energy Materials, Volume 15, Issue 11, March 18, 2025.Progress in in situ atomic scale methods leads to an improved understanding of new and advanced energy materials, where a local understanding of complex, inhomogeneous systems or interfaces down to the atomic scale and quantum level is required. Topics from photovoltaics, dissipation losses, phase transitions, and chemical energy conversion are ...
Christian Jooss +21 more
wiley +1 more source
A classroom quasi-experimental study to explore Processing Instruction [PDF]
, 2010 Processing Instruction (VanPatten, 1996, 2002a, 2004) contains two types of input activity: Referential activities, which force learners to focus on a form and its meaning, and affective activities, which contain multiple exemplars of the target form but
Chen, Hsin-Ying
core
Deciphering Intricacies in Directional CO2 Conversion From Electrolysis to CO2 Batteries
Advanced Energy Materials, EarlyView.This review will delve into the inherent connections and distinctions of CO2‐directed conversion in ECO2RR and CO2 batteries, in terms of product types, catalyst selection, catalytic mechanisms, and electrochemical performances, while proposing a benchmarking framework for the evaluation of CO2 batteries and innovative CO2 battery configurations for ...
Changfan Xu +5 more
wiley +1 more source
Asymmetric Multi‐Site Ion Exchange in Porous Carbon Electrodes
Advanced Energy Materials, EarlyView.A lognormal‐distribution 2D EXSY NMR framework uncovers the full spectrum of ion dynamics in hierarchical porous carbons, bridging fast surface exchange and confined in‐pore transport—establishing structure–transport relationships for next‐generation energy storage, gas storage, and ion removal materials.
Henry R. N. B. Enninful +5 more
wiley +1 more source
Explicit Versus Implicit Grammar Knowledge
, 2018 This entry defines explicit and implicit grammar instruction. It also introduces the related concepts of explicit versus implicit learning and knowledge. These are discussed in relation to important theoretical and practical questions concerning the role
Basturkmen, Helen, Helen Basturkmen
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Advanced Energy Materials, EarlyView.Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park +19 more
wiley +1 more source