Results 51 to 60 of about 37,626 (249)
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
Intelligent Personalized Searching [PDF]
, 2013 Search engine is a very useful tool for almost everyone nowadays. People use search engine for the purpose of searching about their personal finance, restaurants, electronic products, and travel information, to name a few.
Lau, Wing
core +1 more source
, 2015 Specific to Math Information Retrieval is combining text with mathematical formulae both in documents and in queries. Rigorous evaluation of query expansion and merging strategies combining math and standard textual keyword terms in a query are given. It
Aizawa A. +4 more
core +1 more source
Enhanced Security for Dynamic Multi Keyword Ranked Search Using Greedy Best First Search
International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2019 Today, due to the enormous growth of data technology in cloud computing, the data owners are stimulated to outsource their data in data management to reduce cost and for the convenient. Data confidentiality, in general, can be obtained by encrypting the data before it is outsourced.
Bibin Baby, Sharmila Banu
openaire +1 more source
Automating AI Discovery for Biomedicine Through Knowledge Graphs and Large Language Models Agents
Advanced 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
Recent Trends in Metabolomics by NMR Spectroscopy
Angewandte Chemie, EarlyView.AI tools were applied to analyze more than 5 000 publications indexed in Scopus (2018–2025), identifying key trends and research directions in NMR‐based metabolomics. The artificial intelligence‐assisted workflow classified papers into six main fields of application, human health, food and nutrition, veterinary science, plants, environment, and ...
Giorgio Di Paco +6 more
wiley +2 more sources
Bridging the Semantic Gap with SQL Query Logs in Natural Language Interfaces to Databases
, 2019 A critical challenge in constructing a natural language interface to database (NLIDB) is bridging the semantic gap between a natural language query (NLQ) and the underlying data. Two specific ways this challenge exhibits itself is through keyword mapping
Baik, Christopher +2 more
core +1 more source
Cell Segmentation Beyond 2D—A Review of the State‐of‐the‐Art
Advanced Intelligent Discovery, EarlyView.Cell segmentation underpins many biological image analysis tasks, yet most deep learning methods remain limited to 2D despite the inherently 3D nature of cellular processes. This review surveys segmentation approaches beyond 2D, comparing 2.5D and fully 3D methods, analyzing 31 models and 32 volumetric datasets, and introducing a unified reference ...
Fabian Schmeisser +6 more
wiley +1 more source
An Autonomous Large Language Model‐Agent Framework for Transparent and Local Time Series Forecasting
Advanced Intelligent Discovery, EarlyView.Architecture of the proposed large language model (LLM)‐based agent framework for autonomous time series forecasting in thermal power generation systems. The framework operates through a vertical pipeline initiated by natural language queries from users, which are processed by the LLM Agent Core powered by Llama.cpp and a ReAct loop with persistent ...
William Gouvêa Buratto +5 more
wiley +1 more source
AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective
Advanced 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