Results 121 to 130 of about 22,603 (282)

Domain‐Aware Implicit Network for Arbitrary‐Scale Remote Sensing Image Super‐Resolution

open access: yesAdvanced Intelligent Discovery, EarlyView.
Although existing arbitrary‐scale image super‐resolution methods are flexible to reconstruct images with arbitrary scales, the characteristic of training distribution is neglected that there exists domain shift between samples of various scales. In this work, a Domain‐Aware Implicit Network (DAIN) is proposed to handle it from the perspective of domain
Xiaoxuan Ren   +6 more
wiley   +1 more source

A Survey of Efficient Lightweight Cryptography for Power-Constrained Microcontrollers

open access: yesTechnologies
Protecting sensitive data, such as data collected from sensors, is crucial for ensuring the accurate assessment of sensing devices and preventing unauthorized access.
Jesús Soto-Cruz   +5 more
doaj   +1 more source

In Situ Graph Reasoning and Knowledge Expansion Using Graph‐PRefLexOR

open access: yesAdvanced Intelligent Discovery, EarlyView.
Graph‐PRefLexOR is a novel framework that enhances language models with in situ graph reasoning, symbolic abstraction, and recursive refinement. By integrating graph‐based representations into generative tasks, the approach enables interpretable, multistep reasoning.
Markus J. Buehler
wiley   +1 more source

Inverse Engineering of Mg Alloys Using Guided Oversampling and Semi‐Supervised Learning

open access: yesAdvanced Intelligent Discovery, EarlyView.
End‐to‐end design of engineering materials such as Mg alloys must include the properties, structure, and post‐synthesis processing methods. However, this is challenging when destructive mechanical testing is needed to annotate unseen data, and the processing methods for hypothetical alloys are unknown.
Amanda S. Barnard
wiley   +1 more source

A NEW LIGHTWEIGHT CRYPTOGRAPHIC ALGORITHM

open access: diamond, 2019
S. Leelavathy   +4 more
openalex   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

open access: yesAdvanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Power and Energy Issues on Lightweight Cryptography

open access: green, 2017
Antonio J. Acosta   +3 more
openalex   +2 more sources

The Necessity of Dynamic Workflow Managers for Advancing Self‐Driving Labs and Optimizers

open access: yesAdvanced Intelligent Discovery, EarlyView.
We assess the maturity and integration readiness of key methodologies for Materials Acceleration Platforms, highlighting the need for dynamic workflow managers. Demonstrating this, we integrate PerQueue into a color‐mixing robot, showing how flexible orchestration improves coordination and optimization.
Simon K. Steensen   +6 more
wiley   +1 more source

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