Results 101 to 110 of about 1,578 (156)

Fine‐tuning ab initio XANES spectra calculations using the Bayesian optimization algorithm

Journal of Synchrotron Radiation, Volume 33, Issue 5, Page 1455-1466, September 2026.
A Bayesian optimization technique is used to tune the FEFF and FDMNES packages and to improve matching between theoretical and experimental spectra. The tests were performed on monometallic Ni, Fe and Pd K‐edge XANES spectra using several different spectrum similarity metrics.Theoretical modeling of X‐ray absorption near‐edge structure (XANES) spectra ...
Andrey A. Sapronov, Dmitry E. Doronkin, Jan-Dierk Grunwaldt   +2 more
wiley   +1 more source

Development and Clinical Utility of Machine Learning Models for Prediction of Same‐Day Discharge in Outpatient Hip and Knee Replacement: A Prognostic Study

Acta Anaesthesiologica Scandinavica, Volume 70, Issue 8, September 2026.
ABSTRACT Background Hip and knee replacement are common procedures with an increasing focus on same‐day surgery. However, capacity constraints limit the number of eligible patients actually being scheduled for same‐day discharge, calling for further selection of those with the highest likelihood of same‐day discharge.
Christoffer C. Jørgensen, Jakob B. Frederiksen, Henrik Kehlet, Martin Lindberg‐Larsen, Kirill Gromov, Claus Varnum, Thomas Jakobsen, Manuel Josef Bieder, Mikkel Rathsach Andersen, Søren Overgaard, Torben B. Hansen, Troels Petersen   +11 more
wiley   +1 more source

Prediction of soil conditioner dosages for shield tunneling in sandy soil based on machine learning

Case Studies in Construction Materials
Inadequate soil conditioning during Earth Pressure Balance shield (EPBS) tunneling in sandy strata frequently causes operational issues. This study developed a data-driven framework integrating 15 operational and geological parameters from Shenyang Metro
Keqi Liu, Xueyi Liang, Wen Zhao, Xiumei Cao, Hezheng Pei   +4 more
doaj   +1 more source

A SHAP‐Informed Formal Feature Attribution Framework for Drug–Drug Interaction Risk in Large‐Scale Claims Data

Clinical and Translational Science, Volume 19, Issue 9, September 2026.
ABSTRACT Pairwise drug–drug interaction databases flag co‐prescribed pairs, but they under‐weight multi‐drug combinations that drive adverse drug events in older adults. We studied that gap in Virginia All‐Payer Claims Database records (2016–2019) for adults aged 65–114 years with non‐opioid emergency department visits (n = 1182 cases; 16,105 matched ...
R. Jerome Dixon, Elvin T. Price
wiley   +1 more source

MSPCIFormer: A Multi‐Scale Patching Channel‐Independent Transformer for Cryptocurrency Price Forecasting

Expert Systems, Volume 43, Issue 9, September 2026.
ABSTRACT Forecasting cryptocurrency prices remains challenging due to extreme volatility, regime‐dependent dynamics, and unstable cross‐asset correlations. Statistical methods such as ARIMA and GARCH assume stationarity and linear dependence structures, making them inadequate for capturing non‐linear temporal patterns in high volatile cryptocurrency ...
Huali Zhao, Martin Crane, Marija Bezbradica   +2 more
wiley   +1 more source

KLASIFIKASI OBAT ANTI TUBERKULOSIS MENGGUNAKAN ALGORITMA CATEGORICAL BOOSTING DENGAN OPTIMASI OPTUNA [PDF]

Penyakit tuberkulosis merupakan salah satu penyebab utama kematian global, dengan angka kematian mencapai 1,30 juta jiwa pada tahun 2022, meningkat sebesar 3,2% dibandingkan tahun sebelumnya.
Harmoni, Yosua Satria Bara
core  

Using a large language model to automate harmful algal bloom prediction

Limnology and Oceanography Letters, Volume 11, Issue 5, September 2026.
Ming Li, Jorge Z. Verduzco, Xiaohong Wang, Pedro R. Costa, Patricia M. Glibert   +4 more
wiley   +1 more source

Application of FCEEMD-TSMFDE and adaptive CatBoost in fault diagnosis of complex variable condition bearings

Scientific Reports
The mode mixing problem and inherent mode function selection bias in Fast Ensemble Empirical Mode Decomposition (FEEMD) result in ineffective extraction of fault components during the denoising stage, the loss of coarse-grained information in Multiscale ...
Min Mao, Bingwei Xu, Yuhuan Sun, Kairong Tan, Yuran Wang, Chao Zhou, Chengjiang Zhou, Jingzong Yang   +7 more
doaj   +1 more source

Optimizing Machine Learning Models for Urban Sciences: A Comparative Analysis of Hyperparameter Tuning Methods

Urban Science
Advancing urban scholarship and addressing pressing challenges such as gentrification, housing affordability, and urban sprawl require robust predictive models.
Tris Kee, Winky K.O. Ho
doaj   +1 more source

Deep Learning Framework With Optuna-Based Hyperparameter Tuning for Predicting Dry Turning Process Performance of 42CrMo4 Steel

IEEE Access
This study presents an integrated experimental and data-driven modeling framework for predicting key machining responses such as tool wear (TW), material removal rate (MRR), and surface roughness (Ra) during dry turning of 42CrMo4 alloy steel ...
Vasanth Siva Kumar, Mogana Priya Chinnasamy, Swetha R Kumar   +2 more
doaj   +1 more source