Results 81 to 90 of about 411 (174)

Data‐Driven Modeling of Forces Exerted by Pneumatic Actuators for a Pediatric Exosuit

open access: yesAdvanced Intelligent Systems, EarlyView.
This work presents the experimental analysis and data‐driven modeling of the interaction forces between soft pneumatic actuators designed to assist upper‐extremity motion in a pediatric exosuit and an engineered test rig, across different experimental conditions: (A) force profiling of shoulder actuators, with varying actuator anchoring points and ...
Mehrnoosh Ayazi   +4 more
wiley   +1 more source

Artificial Intelligence for Multiscale Modeling in Solid‐State Physics and Chemistry: A Comprehensive Review

open access: yesAdvanced Intelligent Systems, EarlyView.
This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy   +2 more
wiley   +1 more source

Optimizing 3D Bin Packing of Heterogeneous Objects Using Continuous Transformations in SE(3)

open access: yesAdvanced Intelligent Systems, EarlyView.
This article presents a method for solving the three‐dimensional bin packing problem for heterogeneous objects using continuous rigid‐body transformations in SE(3). A heuristic optimization framework combines signed‐distance functions, neural network approximations, point‐cloud bin modeling, and physics simulation to ensure feasibility and stability ...
Michele Angelini, Marco Carricato
wiley   +1 more source

MusicSwarm: Biologically Inspired Intelligence for Music Composition

open access: yesAdvanced Intelligent Systems, EarlyView.
Biologically inspired swarms of frozen foundation models self‐organize to compose complex music without fine‐tuning. By coordinating through stigmergic signals, decentralized agents dynamically evolve specialized roles and adapt to solve complex tasks.
Markus J. Buehler
wiley   +1 more source

Resurgence of Chern-Simons Theory at the Trivial Flat Connection. [PDF]

open access: yesCommun Math Phys
Garoufalidis S   +3 more
europepmc   +1 more source

Comparing the Latent Features of Universal Machine‐Learning Interatomic Potentials

open access: yesAdvanced Intelligent Systems, EarlyView.
This study quantitatively assesses how universal machine‐learning interatomic potentials encode the chemical space into latent features, showing unique model‐specific representations with high cross‐model reconstruction errors. It explores how training datasets, protocols, and targets affect these encodings.
Sofiia Chorna   +5 more
wiley   +1 more source

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