Results 121 to 130 of about 5,352,065 (277)
Arrhythmia ECG Noise Reduction by Ensemble Empirical Mode Decomposition [PDF]
, 2012 [[abstract]]A novel noise filtering algorithm based on ensemble empirical mode decomposition (EEMD) is proposed to remove artifacts in electrocardiogram (ECG) traces.
張剛鳴;Chang, Kang-Ming
core
Porous Carbon Materials for Carbon Dioxide Capture
Carbon Energy, EarlyView.This work aims to address the current status and challenges associated with the regulation of pore structures, as well as the influence of pore structures on CO2 capture. Systematic quantitative analysis of structure–property relationships, combined with machine learning approaches, can effectively evaluate the contributions of structural ...
Zhifu Liu +6 more
wiley +1 more source
Carbon Energy, EarlyView.Integrating renewable energy with electrochemical conversion and storage is crucial for sustainable energy solutions. Nitrogen‐doped biomass‐derived carbon materials have emerged as effective catalysts for key reactions such as ORR, HER, and CO2RR. This review explores their synthesis, functionalization, characterization, and catalytic applications ...
Shilong Fu +3 more
wiley +1 more source
European Journal of Personality, EarlyView., 2020 Abstract Divergent thinking (DT) is an important constituent of creativity that captures aspects of fluency and originality. The literature lacks multivariate studies that report relationships between DT and its aspects with relevant covariates, such as cognitive abilities, personality traits (e.g. openness), and insight. In two multivariate studies (N
S. Weiss +6 more
wiley +1 more source
Multidimensional and multivariate empirical mode decomposition [PDF]
, 2019 Over the last decade, Empirical Mode Decomposition (EMD) has developed into a versatile tool for adaptive, scale-based modal decomposition. EMD has proven to be capable of decomposing multivariate signals with cross-channel mode alignment.
Thirumalaisamy, Mruthun R.
core
Applied Multivariate Research, v.12 no.2 (complete version)
, 2006 The journal Applied Multivariate Research is sponsored by the Society for Applied Multivariate Research and specializes in publishing methodological and content papers that deal with the application of both classical and more modem multivariate ...
core +1 more source
The Canadian Journal of Chemical Engineering, EarlyView.Abstract Pinpointing the true roots of energy waste in large, multi‐unit industrial systems is notoriously difficult: the data are high‐dimensional, and process units are tightly interlinked. This paper presents a powerful hybrid diagnostic framework that integrates explainable AI (XAI), Granger causality (GC), and fault tree analysis (FTA).
Mohamed El Koujok +2 more
wiley +1 more source
Applied SciencesFault location technology is crucial for enhancing the efficiency of fault maintenance and ensuring the safety of the power supply in small current grounding systems.
Jiyuan Cao +4 more
doaj +1 more source
Vine copula knockoffs for variable selection in gene expression studies
Canadian Journal of Statistics, EarlyView.Abstract Identifying clinical and genetic markers is essential for stratifying cancer patients by survival outcomes and guiding personalized treatment strategies. However, gene expression studies often involve high‐dimensional predictors with mixed data types and complex dependence, which complicates reliable variable selection.
José Ulises Márquez Urbina +3 more
wiley +1 more source
Optimal subsampling for regression with mixed‐type predictors
Canadian Journal of Statistics, EarlyView.Abstract Subsampling has emerged as an appealing strategy to mitigate the computational and storage challenges imposed by large datasets. Recent subsampling techniques have shown notable computational gains for data dominated by numerical predictors. However, real‐world datasets frequently contain both numerical and categorical predictors.
Jiaqing Zhu, Lin Wang, Fasheng Sun
wiley +1 more source