Results 151 to 160 of about 680 (283)

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

Complementary metal-oxide-semiconductor (CMOS) time of evaporation measurement system for binary chemical monitoring. [PDF]

Sci Rep
Ghafar-Zadeh E, Forouhi S, Osouli Tabrizi H, Panahi A, Tahernezhad Y, Amrollahi Biyouki A.   +5 more
europepmc   +1 more source

A Generalized Framework for Data‐Efficient and Extrapolative Materials Discovery for Gas Separation

Advanced Intelligent Discovery, EarlyView.
This study introduces an iterative supervised machine learning framework for metal‐organic framework (MOF) discovery. The approach identifies over 97% of the best performing candidates while using less than 10% of available data. It generalizes across diverse MOF databases and gas separation scenarios.
Varad Daoo, Jayant K. Singh
wiley   +1 more source

Conférence invitée : L’hydrométrie en Europe: des services hydrologiques à l’hydrologie des services

, 2013
Hydrometry in Europe: from services of hydrology to hydrological services. Hydrology is in a change process in order to address new climate, scientific, economic and social challenges. Appropriate answers in water issues need permanent improvements of
Berod, Dominique
core  

Multimodal Learning with Rashomon Analysis for Battery Discharge Capacity Prediction

Advanced Intelligent Discovery, EarlyView.
Multimodal fusion integrates composition, crystal‐structure, and radial‐distribution descriptors to predict battery discharge capacity. Rashomon analysis across near‐optimal models reveals that explanatory variation is structured rather than arbitrary, separating stable mechanistic signals from model‐contingent attributions and providing a more ...
Jue Gong, Lejia Wang, Tianqing Zhu, Keith Butler, Sichao Li   +4 more
wiley   +1 more source

Intermittent pneumatic compression devices for the prevention and treatment of breast cancer-related lymphedema-a systematic review and meta-analysis. [PDF]

Support Care Cancer
Su L, Huang H, Tong Y, Dong L, Gu C, Zhuang S, Bai S, Jin Y.   +7 more
europepmc   +1 more source

Predicting Crystal Structures and Ionic Conductivities in Li3YCl6−xBrx Halide Solid Electrolytes Using a Fine‐Tuned Machine Learning Interatomic Potential

Advanced Intelligent Systems, EarlyView.
This study refines the Crystal Hamiltonian Graph Network to predict energies, structures, and lithium‐ion dynamics in halide electrolytes. By generating ordered structural models and using an iterative fine‐tuning workflow, we achieve near‐ab initio accuracy for phase stability and ionic transport predictions.
Jonas Böhm, Aurélie Champagne
wiley   +1 more source

Symposium on hydrometry a contribution to the International Hydrological Decade

, 1973
International Symposium on Hydrometry 1970 Koblenz
core   +1 more source

Anthropometric Measurements and Laboratory Methods for Pregnancy: An Update Review to Evaluation of Body Composition. [PDF]

Curr Nutr Rep
Açar Y, Köksal E.
europepmc   +1 more source

Correction methods and applications of ERT in complex terrain. [PDF]

MethodsX
Zhao M, Jia M, Yang L, Suo K, Lu Y, Wei Q, Zhang Y.   +6 more
europepmc   +1 more source