Results 131 to 140 of about 17,367 (284)

Structure and Spectroscopic Characterisation of Phenanthroline‐Based Iodobismuthate(III) Complexes Utilised for Raw Acoustic Signal Classification

open access: yesAdvanced Intelligent Discovery, EarlyView.
Memristors based on trimethylsulfonium (phenanthroline)tetraiodobismuthate have been utilised as a nonlinear node in a delayed feedback reservoir. This system allowed an efficient classification of acoustic signals, namely differentiation of vocalisation of the brushtail possum (Trichosurus vulpecula).
Ewelina Cechosz   +4 more
wiley   +1 more source

Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook

open access: yesAdvanced 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
wiley   +1 more source

Integrating Terminological and Deductive Reasoning

open access: yes, 1994
this paper - are (1) to support both terminological and deductive reasoning, where the terminological component is based on the frame representation model FRM [Reimer 85], [Reimer 89] and (2) to provide the complete array of functionality associated with
Ulrich Reimer   +2 more
core  

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

open access: yesAdvanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia   +1 more
wiley   +1 more source

Automating AI Discovery for Biomedicine Through Knowledge Graphs and Large Language Models Agents

open access: yesAdvanced Intelligent Discovery, EarlyView.
This work proposes a novel framework that automates biomedical discovery by integrating knowledge graphs with multiagent large language models. A biologically aligned graph exploration strategy identifies hidden pathways between biomedical entities, and specialized agents use this pathway to iteratively design AI predictors and wet‐lab validation ...
Naafey Aamer   +3 more
wiley   +1 more source

Mathematics, Reason & Religion

open access: yesPensamiento. Revista de Investigación e Información Filosófica, 2015
This paper will study the relationship between mathematics and religion from the perspective of reason and the role played by reason in human knowledge. Firstly, I will study the relationship between reason, logic and mathematics.
Javier Leach
doaj  

Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning

open access: yesAdvanced Intelligent Discovery, EarlyView.
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley   +1 more source

Motion 6: Quantitative, Inductive, and Deductive Reasoning

open access: yes, 2003
The Curriculum Subcommittee moves that the current requirement for Quantitative Reasoning be renamed Quantitative, Inductive, and Deductive ...
Provost\u27s Office,
core  

AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective

open access: yesAdvanced Intelligent Discovery, EarlyView.
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley   +1 more source

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