Results 51 to 60 of about 7,478 (267)

Retractions in Rheumatology: Trends, Causes, and Implications for Research Integrity

Arthritis Care &Research, EarlyView.
Objective We aimed to describe the trends and main reasons for study retraction in rheumatology literature. Methods We reviewed the Retraction Watch database to identify retracted articles in rheumatology. We recorded the main study characteristics, authors’ countries, reasons for retraction, time from publication to retraction, and trends over time ...
Anna Maria Vettori, Michele Iudici
wiley   +1 more source

Artificial Intelligence–Based Online Symptom Assessment Tools for Systemic Lupus Erythematosus Diagnosis: Patient Perspectives

Arthritis Care &Research, EarlyView.
Objective The objective of this article is to identify perceptions of patients with systemic lupus erythematosus (SLE) regarding artificial intelligence (AI)–based online symptom assessment tools, and the potential of these tools to address diagnostic barriers.
Olivia A. Stein, Jennifer L. F. Lee, Evelyne Vinet, Arielle Mendel, Christian A. Pineau, Fares Kalache, Louis‐Pierre Grenier, Sasha Bernatsky   +7 more
wiley   +1 more source

Experimental investigation and deployment analysis of data-driven fault diagnosis methods for metro vehicles

Journal of Engineering and Applied Science
The revised abstract is as follows: In recent years, intelligent operation and maintenance systems, including fault diagnosis and prognosis, health management, and maintenance management systems, have been increasingly deployed in newly constructed and ...
Xichun Luo, Jianlin Mao, Tao Liu, Zifang Sun   +3 more
doaj   +1 more source

Is an Apple an Orange? A Large Language Model Benchmark for Candidate Term Extraction and Subclass Decisions Against Upper Ontologies in Engineering and Materials Science

Advanced Engineering Materials, EarlyView.
Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch, Maximilian Holland, Klaus Drechsler, Johannes Schilp   +3 more
wiley   +1 more source

A Deep Multi-Label Learning Framework for the Intelligent Fault Diagnosis of Machines

IEEE Access, 2020
Deep learning has been applied in intelligent fault diagnosis of machines since it trains deep neural networks to simultaneously learn features and recognize faults.
Jianjun Shen, Shihao Li, Feng Jia, Hao Zuo, Junxing Ma   +4 more
doaj   +1 more source

Computational Intelligence in Fault Diagnosis

, 2006
This book presents the most recent concerns and research results in industrial fault diagnosis using intelligent techniques. It focuses on computational intelligence applications to fault diagnosis with real-world applications used in different chapters to validate the different diagnosis methods.
openaire   +2 more sources

Current Status and Challenges in Data Collection for Aerospace Coatings Deposited by Plasma Spraying

Advanced Engineering Materials, EarlyView.
An innovative approach has been integrated into the GRENAT project to optimize plasma spraying and coating performance. Raw materials are accelerated and melted in the plasma generated by torches, creating coatings. Monitoring sensors collect process data which are combined with ex situ characterization data.
Lila Randriamananjara, Vincent Rat, Quentin Dubreuil, Patrice Valorge, Simon Goutier, Alain Denoirjean, Olivier Messe, Céline Ruelle, Jean‐Philippe Poli   +8 more
wiley   +1 more source

Imbalanced data fault diagnosis method for nuclear power plants based on convolutional variational autoencoding Wasserstein generative adversarial network and random forest

Nuclear Engineering and Technology
Data-driven fault diagnosis techniques are significant for the stable operation of nuclear power plants (NPPs). However, in practical applications, the fault diagnosis of NPPs usually faces imbalance data problems with small fault samples and much ...
Jun Guo, Yulong Wang, Xiang Sun, Shiqiao Liu, Baigang Du   +4 more
doaj   +1 more source

Deep Decoupling Convolutional Neural Network for Intelligent Compound Fault Diagnosis

IEEE Access, 2019
Intelligent compound fault diagnosis of rotating machinery plays a crucial role for the security, high-efficiency, and reliability of modern manufacture machines, but identifying and decoupling the compound fault are still a great challenge.
Ruyi Huang, Yixiao Liao, Shaohui Zhang, Weihua Li   +3 more
doaj   +1 more source

A Bioinspired Sensory‐CAPode With Dual Functionality: Logic Gate and Real‐Time Biosensing

Advanced Functional Materials, EarlyView.
An electrochemical capacitor diode (CAPode) redefines the frontier of iontronics by seamlessly unifying logic computing and biosensing within a single biocompatible platform. Inspired by nature's own ion‐channel circuitry, this elegant ionic system transforms complex chemical signals into precise electrical responses, paving the way for next‐generation
Hanfeng Zhou, Tianle Zheng, Haolin Jin, Xiongjun Zhou, Jiang Qu, Bilal Riaz, Ahmed Bahrawy, Jiajie Chen, Przemyslaw Galek, Julia Grothe, Stefan Kaskel   +10 more
wiley   +1 more source