Results 71 to 80 of about 29,305 (254)

GraphRAG for engineering diagrams: ChatP&ID enables LLM interaction with P&IDs

AIChE Journal, EarlyView.
Abstract Piping and Instrumentation Diagrams (P&IDs) are central to process engineering workflows, yet extracting information from them remains a tedious and time‐consuming task. This work introduces ChatP&ID, a framework enabling natural‐language interaction with smart P&IDs through Graph Retrieval‐Augmented Generation (GraphRAG), to our knowledge ...
Achmad Anggawirya Alimin, Artur M. Schweidtmann   +1 more
wiley   +1 more source

The effects of heavy pruning and root pruning on the contents of dimethylsulfide in green tea. [PDF]

Agricultural and Biological Chemistry, 1981
AOKI, Satoshi, NAKAYAMA, Aogu
openaire   +2 more sources

Toward Knowledge‐Guided AI for Inverse Design in Manufacturing: A Perspective on Domain, Physics, and Human–AI Synergy

Advanced Intelligent Discovery, EarlyView.
This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee, Hyeonbin Moon, Junhyeong Lee, Seunghwa Ryu   +3 more
wiley   +1 more source

Uso de poda verde, plásticos refletivos, antitranspirante e potássio na produção de pêssegos Using green pruning, reflective plastics, antitranspirant and potassium in peach production

Pesquisa Agropecuária Brasileira, 2006
O objetivo deste trabalho foi avaliar técnicas que viabilizem a produção de pêssegos de melhor qualidade, ao potencializar características externas como a coloração vermelha na epiderme e o tamanho, bem como características químicas relativas ao sabor ...
Renato Trevisan, Flávio Gilberto Herter, Enilton Fick Coutinho, Emerson Dias Gonçalves, Carlos Augusto Posser Silveira, Cláudio José da Silva Freire   +5 more
doaj   +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, Muhammad Nabeel Asim, Shan Munir, Andreas Dengel   +3 more
wiley   +1 more source

Less is more: Towards green code large language models via unified structural pruning

Information Processing & Management
The extensive application of Large Language Models (LLMs) in generative coding tasks has raised concerns due to their high computational demands and energy consumption. Unlike previous structural pruning methods designed for classification models that deal with lowdimensional classification logits, generative Code LLMs produce high-dimensional token ...
Guang Yang, Yu Zhou, Xiangyu Zhang, Wei Cheng, Ke Liu, Xiang Chen, Terry Yue Zhuo, Taolue Chen   +7 more
openaire   +2 more sources

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

Advanced 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

A Robust Deep Temporal Causal Discovery Platform for Single‐Cell Gene Regulatory Network Reconstruction

Advanced Intelligent Discovery, EarlyView.
scTIGER2.0 is a deep‐learning framework that infers gene regulatory networks from single‐cell RNA sequencing data. By integrating correlation, pseudotime ordering, deep learning and bootstrap‐based significance testing, it reduces false positives and reveals directional gene interactions.
Nishi Gupta, Madison Dautle, Shaoqiang Zhang, Yong Chen   +3 more
wiley   +1 more source

ESTIMATION OF BIOMASS COMMERCIAL SPROUTS OF Ilex paraguariensis A.ST.-HIL

Ciência Florestal, 2009
This study aimed at developing some models that allow estimating the biomass of commercial green shoots of Ilex paraguariensis after pruning, at 10 years-old. In September 2007, 40 Ilex paraguariensis were pruned.
Elisabete Vuaden, Frederico Dimas Fleig, Gerson Luiz Selle, Mayara Dalla Lana, Gustavo Fernandes da Silva, Jonas Flores Vargas   +5 more
doaj   +1 more source

Overcoming the Phase Discontinuity Problem in RIS Optimization: A Robust and Scalable Phase‐Aware Deep Regression Framework via Hybrid CNN–LSTM Architecture

Advanced Intelligent Systems, EarlyView.
The phase discontinuity problem—where the cyclic nature of phase angles causes catastrophic errors near the ±π boundary—is a fundamental obstacle in learning‐based reconfigurable intelligent surface (RIS) optimization. A phase‐aware hybrid CNN–LSTM framework resolves this by decomposing phase predictions into sine–cosine components, mapping circular ...
Seda Savaşçı Şen, Ali Çalhan, Murtaza Cicioğlu, Oğuzhan Demiryürek   +3 more
wiley   +1 more source