Results 111 to 120 of about 73,361 (258)

Mapping the Memory Structure of High-Knowledge Students: A Longitudinal Semantic Network Analysis

Journal of Intelligence
Standard learning assessments like multiple-choice questions measure what students know but not how their knowledge is organized. Recent advances in cognitive network science provide quantitative tools for modeling the structure of semantic memory ...
Simone A. Luchini, Shuyao Wang, Yoed N. Kenett, Roger E. Beaty   +3 more
doaj   +1 more source

Creating Shared Value as an Antecedent of Value Co‐Creation: B2B Relationships in the Agri‐Food Sector

Agribusiness, EarlyView.
ABSTRACT This study analyzes the effects of value co‐creation and creation of shared value in agricultural input marketing. This study used a sample of 178 agricultural companies in Costa Rica. The data were analyzed using partial least squares structural equation modeling (PLS‐SEM) with SMART PLS software. Our findings reveal the significant influence
Luis Ricardo Solís‐Rivera, Marcelo Royo‐Vela   +1 more
wiley   +1 more source

GAGNN: a geography-aware graph neural network for citywide commuting flows prediction

International Journal of Applied Earth Observations and Geoinformation
Urban commuting flow prediction is crucial for optimizing public transportation and improving efficiency, yet traditional models often focus on geographic adjacency, overlooking the complex cross-regional interactions within transportation networks.
Youjun Tu, Peixiao Wang, Julie N.Y. Zhu, Zhiyuan Zhao, Junli Li, Sheng Wu   +5 more
doaj   +1 more source

Open semantic service networks

, 2012
Online service marketplaces will soon be part of the economy to scale the provision of specialized multi-party services through automation and standardization. Current research, such as the *-USDL service description language family, is already defining the basic building blocks to model the next generation of business services.
Cardoso, J., Pedrinaci, C., Leidig, T., Rupino, P., De Leenheer, P.G.M.   +4 more
openaire   +1 more source

AI in chemical engineering: From promise to practice

AIChE Journal, EarlyView.
Abstract Artificial intelligence (AI) in chemical engineering has moved from promise to practice: physics‐aware (gray‐box) models are gaining traction, reinforcement learning complements model predictive control (MPC), and generative AI powers documentation, digitization, and safety workflows.
Jia Wei Chew, Ronnie Andersson, Thomas Bierweiler, Patrik Ryttestal, Torsten Wik   +4 more
wiley   +1 more source

Meinongian Semantics and Artificial Intelligence

Humana.Mente: Journal of Philosophical Studies, 2013
This essay describes computational semantic networks for a philosophical audience and surveys several approaches to semantic-network semantics. In particular, propositional semantic networks (exemplified by SNePS) are discussed; it is argued that only a ...
William J. Rapaport
doaj  

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

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
wiley   +1 more source

Harnessing Large Language Models to Advance Microbiome Research: From Sequence Analysis to Clinical Applications

Advanced Intelligent Discovery, EarlyView.
Large language models are transforming microbiome research by enabling advanced sequence profiling, functional prediction, and association mining across complex datasets. They automate microbial classification and disease‐state recognition, improving cross‐study integration and clinical diagnostics.
Jieqi Xing, He Wang, Yangyang Sun, Xiaoquan Su, Shunyao Wu   +4 more
wiley   +1 more source

Age-Specific Effects of Lexical-Semantic Networks on Word Production. [PDF]

Cogn Sci, 2020
Krethlow G, Fargier R, Laganaro M.
europepmc   +1 more source

CrossMatAgent: AI‐Assisted Design of Manufacturable Metamaterial Patterns via Multi‐Agent Generative Framework

Advanced Intelligent Discovery, EarlyView.
CrossMatAgent is a multi‐agent framework that combines large language models and diffusion‐based generative AI to automate metamaterial design. By coordinating task‐specific agents—such as describer, architect, and builder—it transforms user‐provided image prompts into high‐fidelity, printable lattice patterns.
Jie Tian, Martin Taylor Sobczak, Dhanush Patil, Jixin Hou, Lin Pang, Arunachalam Ramanathan, Libin Yang, Xianyan Chen, Yuval Golan, Xiaoming Zhai, Hongyue Sun, Kenan Song, Xianqiao Wang   +12 more
wiley   +1 more source