Results 241 to 250 of about 131,180 (321)

An Artificial Neural Network with Bayes' Theorem (Hybrid) for Automated Bearing Faults Diagnosis

Yeo Siang Chuan, Lim Meng Hee, Hui Kar Hoou, Eng Hoe Cheng, Hui Kar Hoou, Universiti Teknologi Malaysia, Eng Hoe Cheng, Universiti Teknologi Malaysia   +7 more
openalex   +2 more sources

A Dirichlet‐Multinomial Gibbs Algorithm for Assessing the Accuracy of Binary Tests in the Absence of a Gold Standard

Statistics in Medicine, Volume 45, Issue 1-2, January 2026.
ABSTRACT Each patient is simultaneously given several binary tests for a disease. The tests are partitioned into disjoint groups, assumed to be conditionally independent between groups, but allowed to have arbitrary dependence within a group. The groups are intended to capture similar biological features of the tests.
Joseph B. Kadane
wiley   +1 more source

Bayesian Response‐Adaptive Randomization for Cluster Randomized Controlled Trials

Statistics in Medicine, Volume 45, Issue 1-2, January 2026.
ABSTRACT Cluster randomized controlled trials where groups (or clusters) of individuals, rather than single individuals, are randomized are especially useful when individual‐level randomization is not feasible or when interventions are naturally delivered at the group level.
Yunyi Liu, Maile Young Karris, Sonia Jain   +2 more
wiley   +1 more source

Quantum Shannon Information Theory-Design of Communication, Ciphers, and Sensors. [PDF]

Entropy (Basel)
Hirota O.
europepmc   +1 more source

Method for moving object detection based on adaptive filtration method and Bayes theorem application for changing estimation

, 2015
N.I. Chervyakov, A.A. Tupikin
openalex   +1 more source

Needle in a Haystack: Information Recovery in Low Signal‐to‐Noise Piezoresponse Force Microscopy Data

Small Methods, Volume 10, Issue 2, 22 January 2026.
Reconstruction of low signal‐to‐noise ratio signals enables improved information recovery in piezoresponse force microscopy data, even in data with a substantial amount of noise. Incorporating signal processing errors to detect and Bayesian matrix completion methods to reconstruct low SNR signals substantially alters the apparent PFM switching ...
Kerisha N. Williams, Henry Shaowu Yuchi, Gardy Kevin Ligonde, Mathew Repasky, Yao Xie, Nazanin Bassiri‐Gharb   +5 more
wiley   +1 more source

Flipping the Conditional: Why We Are Probably Wrong About Probabilities. [PDF]

Paediatr Anaesth
Sidebotham D, Dare T.
europepmc   +1 more source

Phishing URL Detection and Interpretability With Machine Learning: A Cross‐Dataset Approach

SECURITY AND PRIVACY, Volume 9, Issue 1, January/February 2026.
ABSTRACT Phishing attacks pose a significant security threat, particularly through deceptive emails designed to trick users into clicking on malicious links, with phishing URLs often serving as the primary indicator of such attacks. This paper presents a machine learning approach for detecting phishing email attacks by analyzing the URLs embedded ...
Liyan Yi, Adebayo Omotosho, Hamed Balogun   +2 more
wiley   +1 more source

An Integrated Machine Learning Approach for Real‐Time Prediction, Diagnostics and Optimization of Uranium‐Leaching Groundwater System

Water Resources Research, Volume 62, Issue 1, January 2026.
Abstract Reliable and efficient simulation and optimization (SO) approach are crucial for groundwater management. Traditionally, SO of groundwater system relies on process‐based numerical models, which often feature low computational efficiency, and unsatisfactory accuracy under limited amount of supportive data and time‐varying aquifer conditions ...
Zhenjiao Jiang, Jinxin Wang, Jiangjiang Zhang, Mengdi Chen, Bin Yu, Tianfu Xu   +5 more
wiley   +1 more source

Locally Relevant Streamflow by Integrating a Land Surface Model Ensemble With a Two‐Stage LSTM Post‐Processor

Water Resources Research, Volume 62, Issue 1, January 2026.
Abstract Process‐based land surface models (LSMs) are widely used for global water cycle and runoff assessments, but when integrated with hydrodynamic models, the streamflow simulations exhibit significant uncertainties in uncalibrated mode, limiting their effectiveness in local hydrology applications.
Bhanu Magotra, Manabendra Saharia
wiley   +1 more source