Results 151 to 160 of about 115,093 (312)

Hopfield Neural Networks for Online Constrained Parameter Estimation With Time‐Varying Dynamics and Disturbances

International Journal of Adaptive Control and Signal Processing, EarlyView.
This paper proposes two projector‐based Hopfield neural network (HNN) estimators for online, constrained parameter estimation under time‐varying data, additive disturbances, and slowly drifting physical parameters. The first is a constraint‐aware HNN that enforces linear equalities and inequalities (via slack neurons) and continuously tracks the ...
Miguel Pedro Silva
wiley   +1 more source

Contrastive Transfer Learning for Prediction of Adverse Events in Hospitalized Patients

IEEE Journal of Translational Engineering in Health and Medicine
Objective: Deterioration index (DI) is a computer-generated score at a specific frequency that represents the overall condition of hospitalized patients using a variety of clinical, laboratory and physiologic data.
Hojjat Salehinejad, Anne M. Meehan, Pedro J. Caraballo, Bijan J. Borah   +3 more
doaj   +1 more source

Classification of C2C12 cells at differentiation by convolutional neural network of deep learning using phase contrast images [PDF]

, 2017
Hirohiko Niioka, Satoshi Asatani, Aina Yoshimura, Hironori Ohigashi, Seiichi Tagawa, Jun Miyake   +5 more
openalex   +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

Learning With Partial-Label and Unlabeled Data: Contrastive With Negative Example Separation

IEEE Access
Semi-Supervised Partial Label Learning (SSPLL) is an important branch of weakly supervised learning, where the data consists of both partial label examples and unlabeled ones.
Bangfa Jiang, Chengkun Liu, Jing Chai
doaj   +1 more source

A generalized AI system for human embryo selection covering the entire IVF cycle via multi-modal contrastive learning [PDF]

Guangyu Wang, Kai Wang, Yuanxu Gao, Longbin Chen, Tianrun Gao, Yuanlin Ma, Zeyu Jiang, Guoxing Yang, Fajin Feng, Shuoping Zhang, Yifan Gu, Guangdong Liu, Lei Chen, Lishuang Ma, Ye Sang, Yanwen Xu, Ge Lin, Xiaohong Liu   +17 more
openalex   +1 more source

A Concept of a Digital and Traceable Manufacturing Documentation Based on Formalized Process Description Applied on Composite Aircraft Moveable

Advanced Engineering Materials, EarlyView.
The documentation of component manufacture has become an essential part of today's production processes, especially for the analysis and optimization of production or component design with regard to structural performance, economic efficiency, and sustainability.
Björn Denker, Dominik Delisle, Christian Krombholz, Martin Rädel, Frank Dressel   +4 more
wiley   +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

A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions

Advanced 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, Krzysztof S. Stopka, Michael D. Sangid   +2 more
wiley   +1 more source

EG-ConMix: An Intrusion Detection Method based on Graph Contrastive Learning [PDF]

Lijin Wu, Shanshan Lei, Feilong Liao, Yuanjun Zheng, Yuxin Liu, Wentao Fu, Hao Song, Jiajun Zhou   +7 more
openalex   +1 more source