Results 81 to 90 of about 11,244 (210)

Prognosis of Bearing Acoustic Emission Signals Using Supervised Machine Learning [PDF]

, 2018
© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new ...
Elforjani, Mohamed, Shanbr, Suliman
core   +2 more sources

Evaluation of the reliability of markerless tumor tracking with single‐energy and dual‐energy imaging using machine learning

Journal of Applied Clinical Medical Physics, Volume 27, Issue 5, May 2026.
Abstract Background Markerless tumor tracking (MTT) using single‐energy (SE) kilovoltage (kV) imaging has been proposed as a technique for lung tumor motion management. However, bony structures can obscure the tumor and make tracking challenging.
Ha Nguyen, Jason Luce, Liangjia Zhu, Mathias Lehmann, Hyejoo Kang, Matthew M. Harkenrider, John C. Roeske   +6 more
wiley   +1 more source

Predicting Remaining Useful Life using Time Series Embeddings based on Recurrent Neural Networks [PDF]

, 2017
We consider the problem of estimating the remaining useful life (RUL) of a system or a machine from sensor data. Many approaches for RUL estimation based on sensor data make assumptions about how machines degrade.
Agarwal, Puneet, Gugulothu, Narendhar, Malhotra, Pankaj, Shroff, Gautam, TV, Vishnu, Vig, Lovekesh   +5 more
core   +3 more sources

Health Prognostics in Multi‐Sensor Systems Based on Multivariate Functional Data Analysis

Applied Stochastic Models in Business and Industry, Volume 42, Issue 3, May/June 2026.
ABSTRACT Recent developments in big data analysis, machine learning, Industry 4.0, and IoT applications have enabled the monitoring and processing of multi‐sensor data collected from systems, allowing for the prediction of the “Remaining Useful Life” (RUL) of system components.
Cevahir Yildirim, Alba M. Franco‐Pereira, Rosa E. Lillo   +2 more
wiley   +1 more source

A New Strategy: Remaining Useful Life Prediction of Wind Power Bearings Based on Deep Learning under Data Missing Conditions

Mathematics
With its formidable nonlinear mapping capabilities, deep learning has been widely applied in bearing remaining useful life (RUL) prediction. Given that equipment in actual work is subject to numerous disturbances, the collected data tends to exhibit ...
Xuejun Li, Xu Lei, Lingli Jiang, Tongguang Yang, Zhenyu Ge   +4 more
doaj   +1 more source

GCC2 in Small Extracellular Vesicles as a Diagnostic and Prognostic Biomarker of Early‐Stage Lung Adenocarcinoma

Journal of Extracellular Vesicles, Volume 15, Issue 5, May 2026.
Plasma sEV‐GCC2 enables early detection and prognostic stratification of lung adenocarcinoma. This multicenter study integrates biomarker validation with functional evidence, supporting sEV‐GCC2 as a clinically relevant biomarker. ABSTRACT Emerging evidence suggests that GRIP and coiled‐coil domain‐containing two enriched small extracellular vesicles ...
Byeong Hyeon Choi, Hyonggin An, Sukki Cho, Sungsoo Lee, Hyeong Ryul Kim, Jong Ho Cho, Jun Hee Lee, Ga Yoon Kim, Ok Hwa Jeon, Hyunku Shin, Yeonho Choi, Hyun Koo Kim   +11 more
wiley   +1 more source

Predicting the Remaining Useful Life of an Aircraft Engine Using a Stacked Sparse Autoencoder with Multilayer Self-Learning

Complexity, 2018
Because they are key components of aircraft, improving the safety, reliability and economy of engines is crucial. To ensure flight safety and reduce the cost of maintenance during aircraft engine operation, a prognostics and health management system that
Jian Ma, Hua Su, Wan-lin Zhao, Bin Liu
doaj   +1 more source

Serum Metabolomics Study Reveals a Diagnostic Model for Lung Cancer Brain Metastasis

The Clinical Respiratory Journal, Volume 20, Issue 5, May 2026.
The overall workflow of noninvasive and efficient early diagnostic methods and key features of metabolic dysregulation associated with lung cancer brain metastasis, providing novel molecular insights into its pathogenesis and laying a foundation for future translational applications.
Hongxia Zhu, Yinuo Jin, Xin You, Qi Wang
wiley   +1 more source

Sequential Network with Residual Neural Network for Rotatory Machine Remaining Useful Life Prediction Using Deep Transfer Learning

Shock and Vibration, 2020
Deep learning has a strong feature learning ability, which has proved its effectiveness in fault prediction and remaining useful life prediction of rotatory machine.
Hao Zhang, Qiang Zhang, Siyu Shao, Tianlin Niu, Xinyu Yang, Haibin Ding   +5 more
doaj   +1 more source

Methods of Technical Prognostics Applicable to Embedded Systems [PDF]

, 2012
Hlavní cílem dizertace je poskytnutí uceleného pohledu na problematiku technické prognostiky, která nachází uplatnění v tzv. prediktivní údržbě založené na trvalém monitorování zařízení a odhadu úrovně degradace systému či jeho zbývající životnosti a to ...
Krupa, Miroslav
core