Results 71 to 80 of about 8,368,743 (296)

Machine learning (ML) in science and STEM education: a systematic review

open access: yesFrontiers in Education
Especially in Machine Learning (ML), the quick development of Artificial Intelligence (AI) has heightened interest in its ability to aid science and STEM education. Still, ML has frequently been used as a technical tool for assessment and analysis inside
Malek Jdaitawi   +7 more
doaj   +1 more source

Clinical Validation of Artificial Intelligence (AI)‐based Cartilage Segmentation Predicting Knee Replacement

open access: yesArthritis Care &Research, Accepted Article.
Objective For cartilage morphology to serve as a scalable endpoint in clinical trials, analyses should be performed automatically without human interaction. To clinically validate artificial intelligence (AI)‐based analysis, we studied cartilage loss from MRI prior to knee replacement.
Felix Eckstein   +3 more
wiley   +1 more source

Extending Service Beyond Active Duty: Generalizability of Rheumatoid Arthritis Research Conducted Among U.S. Veterans

open access: yesArthritis Care &Research, Accepted Article.
Biomedical research involving United States Veterans continues to advance healthcare beyond the Veterans Health Administration. This is particularly true in rheumatoid arthritis (RA), where Veteran‐centric research has uncovered novel insights into pathogenesis, risk factors, and disease manifestations, informing clinical care and research across both ...
Austin M. Wheeler   +20 more
wiley   +1 more source

Learning curves for decision making in supervised machine learning: a survey

open access: yes
Learning curves are a concept from social sciences that has been adopted in the context of machine learning to assess the performance of a learning algorithm with respect to a certain resource, e.g., the number of training examples or the number of ...
van Rijn J.N., Mohr F.
core   +1 more source

Learning Tree Models in Noise: Exact Asymptotics and Robust Algorithms

open access: yes, 2021
Presented online on February 10, 2021 at 12:15 p.m.Vincent Y. F. Tan is an Assistant Professor in the Department of Electrical and Computer Engineering (ECE) and the Department of Mathematics at the National University of Singapore (NUS).
Tan, Vincent Y. F.
core  

A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems

open access: yesInternational Journal of Adaptive Control and Signal Processing, Volume 39, Issue 3, Page 566-581, March 2025.
A Q‐learning algorithm to solve the two‐player zero‐sum game problem for nonlinear systems. ABSTRACT This paper deals with the two‐player zero‐sum game problem, which is a bounded L2$$ {L}_2 $$‐gain robust control problem. Finding an analytical solution to the complex Hamilton‐Jacobi‐Issacs (HJI) equation is a challenging task.
Afreen Islam   +2 more
wiley   +1 more source

Practical Applications of Signal Processing and Machine Learning in a Dynamic Retail Environment

open access: yes, 2018
Presented on October 31, 2018 at 12:15 p.m. in the Marcus Nanotechnology Building, Room 1116.Graham Poliner is the SVP of Strategy and Analytics at Macy’s, Inc.
Poliner, Graham
core   +1 more source

A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions

open access: yesAdvanced Engineering Materials, EarlyView.
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice   +2 more
wiley   +1 more source

Field Report from Collaborative Research Center 1625: Heterogeneous Research Data Management Using Ontology Representations

open access: yesAdvanced Engineering Materials, EarlyView.
A unified research data management framework for heterogeneous materials data is presented. The system integrates multimodal datasets using ontologies and knowledge graphs, enabling interoperability and FAIR (findable, accessible, interoperable, reusable) data principles. By linking data across scales and workflows, it supports reproducible, Artifitial
Doaa Mohamed   +6 more
wiley   +1 more source

Prediction of remaining useful life and downtime of induction motors with supervised machine learning

open access: yesApplied Computer Science
This research aims to use a vibration monitoring system along with machine learning techniques to predict the downtime and Remaining Useful Life (RUL) of three-phase induction motors in the manufacturing sector.
Muhammad Dzulfiqar ANINDHITO, SUHARJITO
doaj   +1 more source

Home - About - Disclaimer - Privacy