Results 81 to 90 of about 234,412 (208)

A Review of Fault‐Tolerant Control Applications in Process Equipment: Boilers, Heat Exchangers, Pumps, Turbines, and Engines for Greater Reliability

Engineering Reports, Volume 8, Issue 9, September 2026.
The article explores ways such as ultrasonic guided wave testing, infrared thermography, acoustic emission, vibration analysis, and oil analysis to prevent faults from affecting the plant and help with fault isolation. It focuses on how FTC is combined with modern tools like Artificial Intelligence (AI), the Internet of Things (IoT), sliding mode ...
Arslan Ahmed Amin, Arslan Aslam, Ansa Mubarak, Saba Waseem, Umair Shahzad   +4 more
wiley   +1 more source

An abnormal traffic detection method for chain information management system network based on convolutional neural network

Frontiers in Physics
Chain information management system is widely used, providing convenience for the operation and management of enterprises. However, the problem of abnormal network traffic becomes increasingly prominent currently.
Chao Liu, Chunxiang Liu, Changrong Liu
doaj   +1 more source

Dual‐view scout scans with deep learning for ultra‐low dose attenuation correction in PET

Medical Physics, Volume 53, Issue 9, September 2026.
Abstract Background Accurate attenuation correction (AC) is essential for quantitative positron emission tomography (PET). Conventional CT‐based AC provides reliable attenuation (μ‐) maps but adds radiation, introduces PET/CT misalignment artifacts, and is unavailable on stand‐alone PET systems.
Florence M. Muller, Margaret E. Daube‐Witherspoon, Michael J. Parma, Amy E. Perkins, Peter B. Noël, Christian Vanhove, Stefaan Vandenberghe, Joel S. Karp   +7 more
wiley   +1 more source

A Large Language Model‐Based Approach for Fault Detection and Its Application

Safety Science and Technology, Volume 1, Issue 3, September 2026.
This work proposes an interpretable fault detection framework utilizing pre‐trained large language models to overcome small sample sizes and label scarcity in industrial datasets. A stepwise tuple‐based validation mitigates hallucinations, ensuring reliable detection.
Yihua Ye, Yin Zhu, Liming Che, Hua Zhou
wiley   +1 more source

Comparative analysis of autoencoder architectures for breast cancer detection using dynamic infrared thermography

Engineering Science and Technology, an International Journal
Breast cancer is the most diagnosed cancer among women worldwide. Early detection substantially improves treatment outcomes, especially when lesions are small and localized.
Burcu Acar Demirci, Mehmet Engin, Erkan Zeki Engin   +2 more
doaj   +1 more source

Out-of-Roundness Wheel Damage Identification in Railway Vehicles Using AutoEncoder Models

Applied Sciences
This study presents a comparative analysis of three AutoEncoder (AE) models—Variational AutoEncoder (VAE), Sparse AutoEncoder (SAE), and Convolutional AutoEncoder (CAE)—to detect and quantify structural anomalies in railway vehicle wheels, such as ...
Renato Melo, Rafaelle Finotti, António Guedes, Vítor Gonçalves, Andreia Meixedo, Diogo Ribeiro, Flávio Barbosa, Alexandre Cury   +7 more
doaj   +1 more source

An experimental investigation into the correlation between Acoustic Emission (AE) and bubble dynamics [PDF]

, 2011
Bubble and cavitation effects phenomena can be encountered in two-phase gas-liquid systems in industry. In certain industries, particularly high-risk systems such as a nuclear reactor/plant, the detection of bubble dynamics, and the monitoring and ...
Husin, Shuib
core   +3 more sources

Code and results for "AE-MoSE: an AutoEncoder Mixture of Spatial Experts for Geodemographic Classification"

This work introduces a novel approach to geodemographic classification that combines an AutoEncoder architecture with a Mixture of Experts framework, incorporating a Graph Neural Network into the gating component to create a Mixture of Spatial Experts ...
Stef De Sabbata (7358834)
core   +1 more source

Bitcoin price prediction using Autoencoder-based GRU and LSTM models [PDF]

The high volatility of Bitcoin prices presents a major challenge in forecasting, as predictive models must capture both short-term fluctuations and long-term trends.
Yamasari, Yuni, Yohannes, Ervin, Nafisah, Nurun   +2 more
core   +1 more source

A new hybrid model for improving outlier detection using combined autoencoder and variational autoencoder

Scientific Reports
In this paper, we propose a new hybrid model, called AVE, that integrates the strengths of Autoencoder (AE) and Variational Autoencoder (VAE) to enhance outlier detection for numerous high-dimensional datasets.
Ahmed M. Daoud, Osama M. Elkomy, Walid I. Khedr, Khalid M. Hosny   +3 more
doaj   +1 more source