Results 81 to 90 of about 4,106 (250)

A new drag and lift correlation for spherocylinders from fully resolved Immersed Boundary Method

AIChE Journal, EarlyView.
Abstract Many industrial processes deal with non‐spherical particles, e.g., mineral mining and biomass conversion. It is crucial to understand the particles' hydrodynamics to control and optimize these processes. To extend the current state‐of‐the‐art from arrays of spherical particles to spherocylindrical particles, we performed extensive particle ...
A. H. Huijgen, Y. Sterkenburgh, Y. Tang, N. G. Deen, M. W. Baltussen   +4 more
wiley   +1 more source

GenForge: An LMM Agent Framework for Intelligent Knowledge Extraction from Nuclear Fuel Reprocessing Literature

Information
Nuclear Fuel Reprocessing literature contains critical experimental parameters, safety information, theoretical relations, and process data that are highly heterogeneous and subject to strict logical constraints.
Hengfei Wang, Ting Yu, Yuanzheng Xin, Zonghui Lu, Shuangjian Li, Yingting Luo, Guoan Ye, Helin Gong, Tao Zhu   +8 more
doaj   +1 more source

Architecture Design of Healthcare Software-as-a-Service Platform for Cloud-Based Clinical Decision Support Service [PDF]

Healthcare Informatics Research, 2015
ObjectivesTo design a cloud computing-based Healthcare Software-as-a-Service (SaaS) Platform (HSP) for delivering healthcare information services with low cost, high clinical value, and high usability.MethodsWe analyzed the architecture requirements of ...
Sungyoung Oh, Jieun Cha, Myungkyu Ji, Hyekyung Kang, Seok Kim, Eunyoung Heo, Jong Soo Han, Hyunggoo Kang, Hoseok Chae, Hee Hwang, Sooyoung Yoo   +10 more
doaj   +1 more source

bowtie-json-schema/bowtie: v2023.05.1

, 2023
Full Changelog: https://github.com/bowtie-json-schema/bowtie/compare/v0.86.1...v2023.05.
Julian Berman, Greg Dennis, Anish Kshirsagar, Noman Dhoni, Agnivesh Chaubey, Akanksha Kushwaha, Santhosh Kumar Tekuri, Jason Desrosiers   +7 more
core   +1 more source

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

Advanced 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, Xinyi Chen, Xu Ye, Yulin Yang, Bin Ai   +4 more
wiley   +1 more source

The Interoperability Challenge in DFT Workflows Across Implementations

Advanced Intelligent Discovery, EarlyView.
Interoperability and cross‐validation remain major challenges in the computational materials science. In this work, we introduce a common input/output standard that enables internal translation across multiple workflow managers—AiiDA, PerQueue, Pipeline Pilot, and SimStack—while producing results in a unified schema.
Simon K. Steensen, Tushar Singh Thakur, Manuel Dillenz, Johan M. Carlsson, Celso R. C. Rêgo, Eibar Flores, Hamidreza Hajiyani, Felix Hanke, Juan María García Lastra, Wolfgang Wenzel, Nicola Marzari, Tejs Vegge, Giovanni Pizzi, Ivano E. Castelli   +13 more
wiley   +1 more source

bowtie-json-schema/bowtie: v0.53.0

, 2022
What's Changed <ul> <li>Fix hyperjump skipped tests implementation by @jdesrosiers in <a href="https://github.com/bowtie-json-schema/bowtie/pull/90">https://github.com/bowtie-json-schema/bowtie/pull/90</a></li> </ul> ...
Julian Berman, Greg Dennis, Jason Desrosiers, Santhosh Kumar Tekuri   +3 more
core   +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, Gabriel Villarrubia Gonzalez, Ademir Nied, Laio Oriel Seman, Anne Carolina Rodrigues Klaar, Stefano Frizzo Stefenon   +5 more
wiley   +1 more source

nZEB beyond prediction in smart built environments: formalising engineering knowledge through modular explainable machine learning

Energy Informatics
This paper demonstrates how explainable machine learning (XAI) can be operationalised as a methodological pathway for formalising engineering knowledge from high-frequency building operational data.
Nuno Soares Domingues
doaj   +1 more source

The molecular entities in linked data dataset

Data in Brief, 2020
The Molecular Entities in Linked Data (MEiLD) dataset comprises data of distinct atoms, molecules, ions, ion pairs, radicals, radical ions, and others that can be identifiable as separately distinguishable chemical entities.
Dominik Tomaszuk, Łukasz Szeremeta
doaj   +1 more source