Results 81 to 90 of about 89,992 (292)
Advanced 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
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Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook
Advanced Intelligent Discovery, EarlyView.Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang +4 more
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IET Computer Vision, 2013 Under local illumination assumption, phenomenological appearance models capture surface appearance through the mathematical modelling of the reflection process.
Shireen Y. Elhabian, Aly A. Farag
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Advanced Intelligent Discovery, EarlyView.This article investigates how persistent homology, persistent Laplacians, and persistent commutative algebra reveal complementary geometric, topological, and algebraic invariants or signatures of real‐world data. By analyzing shapes, synthetic complexes, fullerenes, and biomolecules, the article shows how these mathematical frameworks enhance ...
Yiming Ren, Guo‐Wei Wei
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Bundle-based pruning in the max-plus curse of dimensionality free method
, 2014 Recently a new class of techniques termed the max-plus curse of dimensionality-free methods have been developed to solve nonlinear optimal control problems. In these methods the discretization in state space is avoided by using a max-plus basis expansion
Gaubert, Stephane +2 more
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Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.A laser pointer‐guided robotic grasping method for arbitrary objects based on promptable segment anything model and force‐closure analysis is presented. Grasp generation methods based on force‐closure analysis can calculate the optimal grasps for objects through their appearances. However, the limited visual perception ability makes robots difficult to
Yan Liu +5 more
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GraphNeuralCloth: A Graph‐Neural‐Network‐Based Framework for Non‐Skinning Cloth Simulation
Advanced Intelligent Systems, EarlyView.This study presents a cloth motion capture system and a point‐cloud‐to‐mesh processing method to support the prediction of real‐world fabric deformation. GraphNeuralCloth, a graph neural‐network (GNN)‐based framework is also proposed to estimate the cloth morphology change in real time.
Yingqi Li +9 more
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Advanced Intelligent Systems, EarlyView.Electrical impedance tomography (EIT) tactile skins enable multiplexed measurements that trade sensing speed against information richness. This work introduces an economy‐of‐touch framework that treats tactile sensing as an information‐budgeting problem.
Xiaoxian Xu, David Hardman, Fumiya Iida
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Selective Sequestration of Toxic NOx Gases by P‐Doped Graphene: A Density Functional Theory Study
Advanced Physics Research, EarlyView.P‐doped graphene (P‐grap) is explored as an NOx sensor through DFT simulations. The analysis of its geometry, binding energies, electronic properties, and atom‐in‐molecule characteristics demonstrates that P‐grap is a selective sensor for NOx among a mixture of various gases.
Anwar Ali +3 more
wiley +1 more source
On Some Characterization of GS-exponential kind of Convex Functions [PDF]
, 2023 Ehtesham Akhter, Musavvir Ali
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