Results 151 to 160 of about 522,455 (311)

Engagement Patterns with an AI Health Coach for Systemic Sclerosis Self‐Management: A Mixed Methods Study

Arthritis Care &Research, Accepted Article.
Objective To evaluate utility of an artificial intelligence (AI) health coach for systemic sclerosis (SSc) self‐management and identify patterns associated with participant engagement. Methods We conducted a mixed‐methods study in which an AI health coach, powered by a large language model (LLM), was used to support self‐management for SSc.
Nirali Shah, Melanie Morris, Cristina Daraban, Sophia Johnson, Susan L. Murphy   +4 more
wiley   +1 more source

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

International 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, Anthony Siming Chen, Guido Herrmann   +2 more
wiley   +1 more source

Research on Water Resource Modeling Based on Machine Learning Technologies

Water resource modeling is an important means of studying the distribution, change, utilization, and management of water resources. By establishing various models, water resources can be quantitatively described and predicted, providing a scientific ...
Ze Liu, Zechuan Zhao, Yang Lv, Jingzhao Zhou, Xiaoyang Yang   +4 more
core   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

The Potential of a CT-Based Machine Learning Radiomics Analysis to Differentiate Brucella and Pyogenic Spondylitis

, 2023
Parhat Yasin,1 Muradil Mardan,2 Dilxat Abliz,3 Tao Xu,1 Nuerbiyan Keyoumu,4 Abasi Aimaiti,4 Xiaoyu Cai,1 Weibin Sheng,1 Mardan Mamat1 1Department of Spine Surgery, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, 830054 ...
Sheng W, Abliz D, Aimaiti A, Yasin P, Xu T, Keyoumu N, Mamat M, Mardan M, Cai X   +8 more
core  

Artificial intelligence and machine learning applications for cultured meat

Frontiers in Artificial Intelligence
Cultured meat has the potential to provide a complementary meat industry with reduced environmental, ethical, and health impacts. However, major technological challenges remain which require time-and resource-intensive research and development efforts ...
Michael E. Todhunter, Sheikh Jubair, Ruchika Verma, Rikard Saqe, Kevin Shen, Breanna Duffy   +5 more
doaj   +1 more source

What Do Large Language Models Know About Materials?

Advanced Engineering Materials, EarlyView.
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer, Thomas Wallmersperger, Gianaurelio Cuniberti   +2 more
wiley   +1 more source

Transferable Machine Learning Interatomic Potential for Carbon Hydrogen Systems

In this study, we developed a machine learning interatomic potential based on artificial neural networks (ANN) to model carbon-hydrogen (C-H) systems. The ANN potential was trained on a dataset of C-H clusters obtained through density functional theory ...
Mingjie, Liu, Somayeh, Faraji
core   +1 more source

Machine learning methods for background potential estimation in 2DEGs

Physica E: Low-dimensional Systems and Nanostructures
In the realm of quantum-effect devices and materials, two-dimensional electron gases (2DEGs) stand as fundamental structures that promise transformative technologies. However, the presence of impurities and defects in 2DEGs poses substantial challenges, impacting carrier mobility, conductivity, and quantum coherence time.
Carlo da Cunha, Nobuyuki Aoki, David K. Ferry, Kevin Vora, Yu Zhang   +4 more
openaire   +2 more sources

Author Correction: Machine learning potential for interacting dislocations in the presence of free surfaces. [PDF]

Sci Rep, 2023
Lanzoni D, Rovaris F, Montalenti F.
europepmc   +1 more source