Results 201 to 210 of about 49,138 (261)

Experimental and smoothed particle hydrodynamics‐finite element method simulation investigation of synergistic erosion mechanism of gangue‐based abrasive water jets

Deep Underground Science and Engineering, EarlyView.
This study proposes an eco‐friendly coal permeability enhancement technique by utilizing mine waste gangue as an abrasive in high‐pressure water jets. Integrating erosion experiments with smoothed particle hydrodynamics‐finite element method coupled simulations, the research study elucidates the flow field dynamics and a nonlinear solid–liquid ...
Qingxiang Wang, Jiaxu Tang, Qiheng Ren, Ding Wang, Tong Wang   +4 more
wiley   +1 more source

SGA-DT: An adaptive fusion framework for missing data imputation and interpretable healthcare classification. [PDF]

PLoS One
Jena M, Dehuri S, Cho SB.
europepmc   +1 more source

Exponentially‐constrained Gaussian mixture model for quantifying vertical development of water‐conducting fracture zones in lithologically stratified mining roofs

Deep Underground Science and Engineering, EarlyView.
This study proposes an exponentially‐constrained Gaussian mixture model (EcGMM) to quantify vertical fracture heterogeneity in stratified roof strata. The model integrates a piecewise exponential decay term capturing global stress dissipation with Gaussian components representing localized fracture intensification at lithological interfaces.
Huiqing Yuan, Zhimin Xu, Weixiao Chen, Chenghang Zhang, Shijie Xiong, Yajun Sun   +5 more
wiley   +1 more source

A Novel Method for Motion Blur Detection and Quantification Using Signal Analysis on a Controlled Empirical Image Dataset. [PDF]

Sensors (Basel)
Nonsakhoo W, Saiyod S.
europepmc   +1 more source

Extrapolation strategy matters when transferring ecological niche models: new visualization tools for informed decisions

Ecography, EarlyView.
Abstract Ecological niche models (ENMs) are commonly used to predict species' potential distributions across space and time, allowing researchers and practitioners to assess invasion risk, estimate the impacts of future climate change, and reconstruct past distributions.
Gonzalo E. Pinilla‐Buitrago, Jamie M. Kass, Robert P. Anderson   +2 more
wiley   +1 more source

A user centric group authentication scheme for secure communication. [PDF]

Sci Rep
Gerenli O, Karabulut-Kurt G, Ozdemir E.
europepmc   +1 more source

Can we predict surgical outcomes: A systematic review and critical appraisal of clinical prediction models in epilepsy surgery

Epilepsia, EarlyView.
Abstract Objective Prediction models are increasingly being sought in epilepsy surgery to predict postoperative outcomes and support clinical decision‐making. Studies summarizing the evidence in this area can provide insight into the type of surgical prediction models, their methodology, and their performance and inform areas for future research.
Alyssa A. Federico, Mandavi Kashyap, Chantelle Q. Y. Lin, Karl M. Klein, Olayinka I. Arimoro, Samuel Wiebe   +5 more
wiley   +1 more source

Machine Learning and the Use of Spectroscopy for Adulteration Detection in Turmeric Powder. [PDF]

Molecules
Kisalaei A, Sharabiani VR, Banakar A, Taghinezhad E, Szymanek M, Dziwulska-Hunek A.   +5 more
europepmc   +1 more source

Fully automated three‐dimensional deep learning‐based magnetic resonance imaging segmentation of brain cavities in epilepsy surgery

Epilepsia, EarlyView.
Abstract Objective There are several clinical and research applications for determining the amount of brain tissue resected after epilepsy surgery; however, manual segmentation of postoperative magnetic resonance imaging (MRI) is imprecise and time‐consuming.
Raphael Fernandes Casseb, Brunno Machado de Campos, Wallace Souza Loos, Marcelo Eduardo Ramos Barbosa, Marina Koutsodontis Machado Alvim, Gabriel Chagas Lutfala Paulino, Enrico Ghizoni, Francesco Pucci, Samuel Worrell, Clarissa Lin Yassuda, Roberto Medeiros de Souza, Lara Jehi, Fernando Cendes   +12 more
wiley   +1 more source

A robust multi-location evaluation of a machine learning framework for wind power forecasting. [PDF]

PLoS One
Ali U, Sufyan M, Ali S, Ahmad M, Rehman Khan SU, Raza N, Sultana J, Habib MA.   +7 more
europepmc   +1 more source