Results 181 to 190 of about 6,622 (258)

Boosted unsupervised feature selection for tumor gene expression profiles

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract In an unsupervised scenario, it is challenging but essential to eliminate noise and redundant features for tumour gene expression profiles. However, the current unsupervised feature selection methods treat all samples equally, which tend to learn discriminative features from simple samples.
Yifan Shi, Kaixiang Yang, Mengzhi Wang, Zhiwen Yu, Huanqiang Zeng, Yang Hu   +5 more
wiley   +1 more source

An Accurate QRS complex and P wave Detection in ECG Signals using Complete Ensemble Empirical Mode Decomposition Approach. [PDF]

IEEE Access, 2019
Hossain B, Bashar SK, Walkey AJ, McManus DD, Chon KH.   +4 more
europepmc   +1 more source

Recognition of Spatiotemporal Feature Images of Zero‐Sequence Voltage for Single‐Phase High‐Impedance Ground Faults Under Complex Conditions

High Voltage, EarlyView.
ABSTRACT Diagnosing high‐impedance ground faults (HIGFs) in distribution networks is extremely challenging because high transition resistance significantly reduces electrical signal strength and unpredictable initial fault phase angles coupled with asymmetric voltage disturbances often lead to misclassification.
Zhengyang Li, Yijia Cao, Chun Chen, Weiyu Wang, Yansha Li, Jinglu Li   +5 more
wiley   +1 more source

Using multilabel classification neural network to detect intersectional DIF with small sample sizes

British Journal of Mathematical and Statistical Psychology, EarlyView.
Abstract This study introduces InterDIFNet, a multilabel classification neural network for detecting intersectional differential item functioning (DIF) in educational and psychological assessments, with a focus on small sample sizes. Unlike traditional marginal DIF methods, which often fail to capture the effects of intersecting identities and require ...
Yale Quan, Chun Wang
wiley   +1 more source

A Comprehensive Fault Diagnosis Method for Rolling Bearings Based on Refined Composite Multiscale Dispersion Entropy and Fast Ensemble Empirical Mode Decomposition. [PDF]

Entropy (Basel), 2019
Zhang W, Zhou J.
europepmc   +1 more source

OUGS: Active View Selection via Object‐aware Uncertainty Estimation in 3DGS

Computer Graphics Forum, EarlyView.
Abstract Recent advances in 3D Gaussian Splatting (3DGS) have achieved state‐of‐the‐art results for novel view synthesis. However, efficiently capturing high‐fidelity reconstructions of specific objects within complex scenes remains a significant challenge.
Haiyi Li, Qi Chen, Denis Kalkofen, Hsiang‐Ting Chen   +3 more
wiley   +1 more source

Survey on Visualization of Information Diffusion over Networks

Computer Graphics Forum, EarlyView.
Abstract Information Diffusion (ID) describes how a value (e.g., a pathogen, a rumor, a packet) spreads through an underlying “medium” network of elements (e.g., a social or computer network). Understanding the information diffusion process is essential to predicting trends, controlling misinformation, and enhancing decision‐making as well as ...
T. Baumgartl, M. Sondag, V. Filipov, M. Tuscher, S. Rajendran, S. Miksch, D. Archambault, A. Arleo, T. von Landesberger   +8 more
wiley   +1 more source

From Regression to Reasoning: Predicting M&A Announcement Returns With Large Language Models

European Financial Management, EarlyView.
ABSTRACT This study investigates whether large language models (LLMs) can predict short‐term market reactions to M&A announcements. We prompt OpenAI's latest reasoning models (o3, GPT‐5, and GPT‐5.1) to forecast whether the combined market value of acquirer and target will increase or decrease, drawing on deal‐, firm‐, and macroeconomic data for large ...
Maximilian Schreiter, Aldrik Struve, Maximilian Uhle   +2 more
wiley   +1 more source

Discharge‐Targeted Hydraulic Tomography to Quantify and Locate Aquifer Discharge

Groundwater, EarlyView.
Abstract Quantifying and localizing groundwater discharge is inherently difficult. It requires knowledge about hydraulic conductivity and the hydraulic gradient on the scale of interest. Conventional hydraulic testing, such as pumping tests, may fail in the presence of heterogeneity and complex structural boundaries.
Konstantin Drach, Carsten Leven, Olaf A. Cirpka   +2 more
wiley   +1 more source

Regularization Approaches for High‐Dimensional Cox Models: A Case Study in Triple‐Negative Breast Cancer

International Statistical Review, EarlyView.
Summary In high‐dimensional survival analysis, effective variable selection is crucial both for model interpretation and predictive performance. This paper investigates Cox regression with lasso and adaptive lasso penalties in genomic datasets where covariates far outnumber observations.
Pilar González‐Barquero, Rosa E. Lillo, Álvaro Méndez‐Civieta   +2 more
wiley   +1 more source