Results 101 to 110 of about 85,695 (269)

Discharge estimation in compound channels with converging and diverging floodplains using an optimised Gradient Boosting Algorithm

Journal of Hydroinformatics
River discharge estimation is vital for effective flood management and infrastructure planning. River systems consist of a main channel and floodplains, collectively forming a compound channel, posing challenges in discharge calculation, particularly ...
Shashank Shekhar Sandilya, Bhabani Shankar Das, Sébastien Proust, Divyanshu Shekhar   +3 more
doaj   +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

Feature Selection for Machine Learning‐Driven Accelerated Discovery and Optimization in Emerging Photovoltaics: A Review

Advanced Intelligent Discovery, EarlyView.
Feature selection combined with machine learning and high‐throughput experimentation enables efficient handling of high‐dimensional datasets in emerging photovoltaics. This approach accelerates material discovery, improves process optimization, and strengthens stability prediction, while overcoming challenges in data quality and model scalability to ...
Jiyun Zhang, Jiayi Tan, Qizhen Song, Tian Du, Jens Hauch, Christoph J. Brabec   +5 more
wiley   +1 more source

Liquid propellant sloshing in mobile tanks of arbitrary shape [PDF]

Equations for dynamic behavior of liquid propellants sloshing in mobile tanks of arbitrary ...
Lomen, D. O.
core   +1 more source

A Solution for Exosome‐Based Analysis: Surface‐Enhanced Raman Spectroscopy and Artificial Intelligence

Advanced Intelligent Discovery, EarlyView.
Exosomes are emerging as powerful biomarkers for disease diagnosis and monitoring. This review highlights the integration of surface‐enhanced Raman spectroscopy with artificial intelligence to enhance molecular fingerprinting of exosomes. Machine learning and deep learning techniques improve spectral interpretation, enabling accurate classification of ...
Munevver Akdeniz, Zakarya Al‐Shaebi, Omer Aydin   +2 more
wiley   +1 more source

A Machine Learning Perspective on the Brønsted–Evans–Polanyi Relation in Water‐Gas Shift Catalysis on MXenes

Advanced Intelligent Discovery, EarlyView.
Machine learning predicts activation energies for key steps in the water‐gas shift reaction on 92 MXenes. Random Forest is identified as the most accurate model. Reaction energy and reactant LogP emerge as key descriptors. The approach provides a predictive framework for catalyst design, grounded in density functional theory data and validated through ...
Kais Iben Nassar, Tiago L. P. Galvão, José D. Gouveia, José R. B. Gomes   +3 more
wiley   +1 more source

Digital risk perception among middle-aged and older adults in China: a perspective from mobile phone dependence within the I-PACE model

Frontiers in Psychiatry
IntroductionThe digital inclusion of middle-aged and older adults, while socially beneficial, exposes this population with relatively lower digital literacy to increased cybersecurity risks.
Ying Lu, Ying Lu, Rou Zhang, Weihui Dai
doaj   +1 more source

Artificial Intelligence‐Driven Insights into Electrospinning: Machine Learning Models to Predict Cotton‐Wool‐Like Structure of Electrospun Fibers

Advanced Intelligent Discovery, EarlyView.
Electrospinning allows the fabrication of fibrous 3D cotton‐wool‐like scaffolds for tissue engineering. Optimizing this process traditionally relies on trial‐and‐error approaches, and artificial intelligence (AI)‐based tools can support it, with the prediction of fiber properties. This work uses machine learning to classify and predict the structure of
Paolo D’Elia, Giovanna Pappalardo, Aldo R. Boccaccini, Liliana Liverani   +3 more
wiley   +1 more source

Quantitative color fundus photography parameters as potential biomarkers of axial length progression: evidence from a machine learning cohort study

Frontiers in Cell and Developmental Biology
PurposeEarly identification of children at risk for accelerated axial elongation is essential for implementing timely myopia control strategies. Quantitative parameters derived from color fundus photography (CFP) may capture subtle structural and ...
Zixun Wang, Feifei Han, Xiaoling Zhang, Xiaoling Zhang, Jingjie Ding, Jingtao Yu, Xueshuo Xie, Zhiqing Li, Bei Du, Ruihua Wei   +9 more
doaj   +1 more source

Data-Driven Identification of Long-Term Glycemia Clusters and Their Individualized Predictors in Finnish Patients with Type 2 Diabetes

Clinical Epidemiology, 2023
Piia Lavikainen,1,* Gunjan Chandra,2,* Pekka Siirtola,2 Satu Tamminen,2 Anusha T Ihalapathirana,2 Juha Röning,2 Tiina Laatikainen,3– 5 Janne Martikainen1 1School of Pharmacy, University of Eastern Finland, Kuopio, Finland; 2Biomimetics and ...
Lavikainen P, Chandra G, Siirtola P, Tamminen S, Ihalapathirana AT, Röning J, Laatikainen T, Martikainen J   +7 more
doaj