Results 251 to 260 of about 855,098 (342)

AI driven web crawling for semantic extraction of news content from newspapers. [PDF]

Sci Rep
S S, A K AA.
europepmc   +1 more source

Assessing the Performance of Biopolymers as Substrates for Flexible Printed Supercapacitors Containing Liquid Electrolytes

Advanced Energy and Sustainability Research, EarlyView.
The fossil‐based substrates of a printed supercapacitor containing liquid electrolytes can only be replaced with biopolymers if they have adequate permeabilities. This article studies three biopolymers based on their processability, printability, and barrier properties to find a more sustainable substrate option.
Iida Kangashaka, Timo Punkari, Aapo Kattainen, Chirag Mevada, Jari Keskinen, Matti Mäntysalo, Essi Sarlin   +6 more
wiley   +1 more source

Transparent Reporting of AI in Systematic Literature Reviews: Development of the PRISMA-trAIce Checklist. [PDF]

JMIR AI
Holst D, Moenck K, Koch J, Schmedemann O, Schüppstuhl T.   +4 more
europepmc   +1 more source

Internet of Things‐Based Framework Application at a University Campus Scale: Linking Smart Monitoring Systems and Stormwater Management

Advanced Intelligent Discovery, EarlyView.
This study presents an Internet of Things‐based stormwater monitoring framework piloted at the University of Maryland campus to support Municipal Separate Stormwater Sewer System compliance and adaptive planning. Developed with key campus stakeholders, the framework integrates real‐time sensor deployment, data‐informed insights on runoff and water ...
Qianyao Si, Priscila B. R. Alves, Mitchell A. Pavao‐Zuckerman, Allen P. Davis, Tara Burke, Bryan S. Quinn, Elizabeth M. Bonsignore, Jennifer A. Cotting, Jason Baer, Kaitlyn Peterson, Pierre Gaunaurd, Tamara L. Clegg, David Loshin, Andrew M. Fellows, Taylor Keen, Gerrit J. Knaap, Marccus D. Hendricks   +16 more
wiley   +1 more source

USING ARTIFICIAL INTELLIGENCE TO OPTIMISE THE WEB-BASED SOFTWARE DEVELOPMENT PROCESS

Artem Beliakov
openalex   +1 more source

Exploring Quantum Support Vector Regression for Predicting Hydrogen Storage Capacity of Nanoporous Materials

Advanced Intelligent Discovery, EarlyView.
In this study we employed support vector regressor and quantum support vector regressor to predict the hydrogen storage capacity of metal–organic frameworks using structural and physicochemical descriptors. This study presents a comparative analysis of classical support vector regression (SVR) and quantum support vector regression (QSVR) in predicting ...
Chandra Chowdhury
wiley   +1 more source

Blockchain integration for rare disease clinical trials. [PDF]

Ann Med Surg (Lond)
Riaz U, Talha M, Ali U, Hassan M, Mahato RK.   +4 more
europepmc   +1 more source

Decoding Tattoo and Permanent Makeup Pigments: Linking Physicochemical Properties to Absorption, Distribution, Metabolism, and Elimination Profiles Using Quantitative Structure–Activity Relationship (QSAR)‐Based New Approach Methodologies (NAMs)

Advanced Intelligent Discovery, EarlyView.
This study applies QSAR‐based new approach methodologies to 90 synthetic tattoo and permanent makeup pigments, revealing systemic links between their physicochemical properties and absorption, distribution, metabolism, and elimination profiles. The correlation‐driven analysis using SwissADME, ChemBCPP, and principal component analysis uncovers insights
Girija Bansod, Ajay Vikram Singh, Preeti Bhardwaj, Tulika Rai, Sweta Vijay Nakhale, Amruta Shelar, Rajendra Patil, Peter Laux, Andreas Luch, Christopher J. Osgood, Michael W. Stacey   +10 more
wiley   +1 more source

2015 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology: WI-IAT 2015: December 6-9, Singapore: Proceedings

, 2016
Ee‐Peng Lim, Ah‐Hwee Tan, Yuefeng Li, Einoshin Suzuki, Bryan Kian Hsiang Low, Jason Watson   +5 more
openalex   +1 more source

Named Entity Recognition Models for Machine Learning Interatomic Potentials: A User‐Centric Approach to Knowledge Extraction from Scientific Literature

Advanced Intelligent Discovery, EarlyView.
Named entity recognition pipeline for knowledge extraction from scientific literature. Machine learning interatomic potential (MLIP) is an emerging technique that has helped achieve molecular dynamics simulations with unprecedented balance between efficiency and accuracy. Recently, the body of MLIP literature has been growing rapidly, which propels the
Bowen Zheng, Grace X. Gu
wiley   +1 more source