Results 131 to 140 of about 2,318,151 (292)

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

An Adaptive Human Pilot Model With Reaction Time Delay for Enhanced Adaptive Control in Piloted Systems

International Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces an adaptive human pilot model that captures pilot time‐delay effects in adaptive control systems. The model enables the prediction of pilot–controller interactions, facilitating safer integration and improved design of adaptive controllers for piloted applications.
Abdullah Habboush, Yildiray Yildiz
wiley   +1 more source

Artificial Intelligence Models and Tools for the Assessment of Drug–Herb Interactions

Pharmaceuticals
Artificial intelligence (AI) has emerged as a powerful tool in medical sciences that is revolutionizing various fields of drug research. AI algorithms can analyze large-scale biological data and identify molecular targets and pathways advancing ...
Marios Spanakis, Eleftheria Tzamali, Georgios Tzedakis, Chryssalenia Koumpouzi, Matthew Pediaditis, Aristides Tsatsakis, Vangelis Sakkalis   +6 more
doaj   +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

Semi-supervised meta-learning elucidates understudied molecular interactions

Communications Biology
Many biological problems are understudied due to experimental limitations and human biases. Although deep learning is promising in accelerating scientific discovery, its power compromises when applied to problems with scarcely labeled data and data ...
You Wu, Li Xie, Yang Liu, Lei Xie
doaj   +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

Collective relational inference for learning heterogeneous interactions

Nature Communications
Interacting systems are ubiquitous in nature and engineering, ranging from particle dynamics in physics to functionally connected brain regions. Revealing interaction laws is of fundamental importance but also particularly challenging due to underlying ...
Zhichao Han, Olga Fink, David S. Kammer
doaj   +1 more source

Advancing Research on Biomaterials and Biological Materials with Scanning Electron Microscopy under Environmental and Low Vacuum Conditions

Advanced Engineering Materials, EarlyView.
Herein, environmental scanning electron microscopy (ESEM) is discussed as a powerful extension of conventional SEM for life sciences. By combining high‐resolution imaging with variable pressure and humidity, ESEM allows the analysis of untreated biological materials, supports in situ monitoring of hydration‐driven changes, and advances the functional ...
Jendrian Riedel, Lea Dierker, Antoine Eyram Kwame, Kim Nora Wagner, Jonas J. Unterholzner, Jan‐Henning Dirks, Dorothea Brüggemann   +6 more
wiley   +1 more source

Photoswitchable Conductive Metal–Organic Frameworks

Advanced Functional Materials, EarlyView.
A conductive material where the conductivity can be modulated remotely by irradiation with light is presented. It is based on films of conductive metal–organic framework type Cu3(HHTP)2 with embedded photochromic molecules such as azobenzene, diarylethene, spiropyran, and hexaarylbiimidazole in the pores.
Yidong Liu, Mersad Mostaghimi, Abhinav Chandresh, Saibal Jana, Wolfgang Wenzel, Lars Heinke   +5 more
wiley   +1 more source