Results 141 to 150 of about 9,740,987 (348)
Advanced Intelligent Discovery, EarlyView.Chat computational fluid dynamics (CFD) introduces an large language model (LLM)‐driven agent that automates OpenFOAM simulations end‐to‐end, attaining 82.1% execution success and 68.12% physical fidelity across 315 benchmarks—far surpassing prior systems.
E Fan +8 more
wiley +1 more source
Large Language Model‐Based Chatbots in Higher Education
Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.The use of large language models (LLMs) in higher education can facilitate personalized learning experiences, advance asynchronized learning, and support instructors, students, and researchers across diverse fields. The development of regulations and guidelines that address ethical and legal issues is essential to ensure safe and responsible adaptation
Defne Yigci +4 more
wiley +1 more source
Not just keywords but MeSH keywords: Do mention for better visibility of your publication
Indian Journal of Anaesthesia, 2023 Manisha D Katikar +2 more
doaj +1 more source
SMART CLOUD FILE RETRIEVAL USING SEARCHABLE CIPHERTEXT KEYWORDS & ACCESS CONTROL ON INDEX. [PDF]
, 2017 SadeerDheyaa. Abdulameer.
openalex +1 more source
Table 40. DCs Keyword Themes frequency Hits and connectivity counts [Qual. articles]
, 2021 Yinka Moses, Trevor Hopper
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Review of Memristors for In‐Memory Computing and Spiking Neural Networks
Advanced Intelligent Systems, EarlyView.Memristors uniquely enable energy‐efficient, brain‐inspired computing by acting as both memory and synaptic elements. This review highlights their physical mechanisms, integration in crossbar arrays, and role in spiking neural networks. Key challenges, including variability, relaxation, and stochastic switching, are discussed, alongside emerging ...
Mostafa Shooshtari +2 more
wiley +1 more source
Advanced Intelligent Systems, EarlyView.Illustration of text data mining of rare earth mineral thermodynamic parameters with the large language model‐powered LMExt. A dataset is built with mined thermodynamic properties. Subsequently, a machine learning model is trained to predict formation enthalpy from the dataset.
Juejing Liu +6 more
wiley +1 more source