Results 91 to 100 of about 935,753 (293)

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source

Automation spectrum, inner / outer compatibility and other potentially useful human factors concepts for assistance and automation [PDF]

, 2008
Enabled by scientific, technological and societal progress, and pulled by human demands, more and more aspects of our life can be assisted or automated.
Kelsch, Johann, Löper, Christian, Flemisch, Frank, Schieben, Anna   +3 more
core  

AI-Enhanced Robotic Process Automation: A Review of Intelligent Automation Innovations

IEEE Access
The rapid technological growth in recent decades due to the integration of robust technologies and automation have led to the rise of digital services and the emergence of Industry 4.0.
Sadia Afrin, Shobnom Roksana, Riad Akram
doaj   +1 more source

Cerenkov Luminescence Tomography for In Vivo Radiopharmaceutical Imaging

International Journal of Biomedical Imaging, 2011
Cerenkov luminescence imaging (CLI) is a cost-effective molecular imaging tool for biomedical applications of radiotracers. The introduction of Cerenkov luminescence tomography (CLT) relative to planar CLI can be compared to the development of X-ray CT ...
Jianghong Zhong, Chenghu Qin, Xin Yang, Shuping Zhu, Xing Zhang, Jie Tian   +5 more
doaj   +1 more source

New AI‐Assisted Approach for Expanding the Solution Space: Application to Lattice Structure Design

Advanced Engineering Materials, EarlyView.
This work introduces an innovative framework for designing structured materials by ex panding the design space through reparameterization of qualitative variables into continuous structural descriptors. Combined with machine‐learning‐based prediction and multi‐objective optimization, the approach enables the discovery of novel lattice architectures ...
G. H. Gahimbare, Y. Beideler, D. Chune, R. De Guio, T. Roland, H. Chibane   +5 more
wiley   +1 more source

The impact of 5G on the evolution of intelligent automation and industry digitization. [PDF]

J Ambient Intell Humaniz Comput, 2023
Attaran M.
europepmc   +1 more source

OntOMat: Toward Ontology‐Based Product and Process Design Engineering and Optimization Solutions Fueling Circular Value Chains

Advanced Engineering Materials, EarlyView.
The OntOMat ontology establishes a structured framework for polymer matrix fiber reinforced composite materials, integrating manufacturing processes, characterization methods, and multiscale design through the VDI/VDE 3682 formalized process description standard.
Nicolas Christ, Jörg Hohe, Martin Kördel, Michael Giese, Niklas Toffert, Christian Seidel, Olaf Rehme, Patrik Schneider, Oliver Focke, Elie Abi Aoun, Claas Falldorf, Beñat Gutierrez, Alexandra Kühn, Sven Torstrick-von der Lieth, Christoph Herden, Erik Johannsen, Jan‐Uwe R. Schmidt, Felix Winkelmann, Andreas Schott, Daniel Schott   +19 more
wiley   +1 more source

Semantic Modeling in Materials Science and Engineering With Platform MaterialDigital Core Ontology 3.0

Advanced Engineering Materials, EarlyView.
The community‐driven Platform MaterialDigital Core Ontology (PMDco) 3.0 is introduced as a Basic Formal Ontology‐aligned semantic backbone for the processing–structure–properties paradigm in Materials Science and Engineering. Modular engineering, automated releases, and validation workflows are highlighted and key semantic patterns for materials ...
Markus Schilling, Philipp von Hartrott, Jörg Waitelonis, Thomas Hanke, Henk Birkholz, Hossein Beygi Nasrabadi, Khashayar Razghandi, Kamilla Zaripova, Felix Thonagel, Fabian Neuhaus, Martin Glauer, Lars Vogt, Harald Sack, Lutz Mädler, Bernd Bayerlein, Chris Eberl   +15 more
wiley   +1 more source

Validating Intelligent Automation Systems in Pharmacovigilance: Insights from Good Manufacturing Practices. [PDF]

Drug Saf, 2021
Huysentruyt K, Kjoersvik O, Dobracki P, Savage E, Mishalov E, Cherry M, Leonard E, Taylor R, Patel B, Abatemarco D.   +9 more
europepmc   +1 more source

A real-time decision-making method for USV swarm area coverage empowered by large language models

Zhongguo Jianchuan Yanjiu
ObjectiveUnmanned surface vehicle (USV) swarms are increasingly utilized for complex maritime tasks, such as continuous environmental monitoring, island patrols, and strategic surveillance.
Mingzhe YANG, Lulu PAN, Peng WANG, Yi GUO, Zehui ZHANG, Haibin SHAO   +5 more
doaj   +1 more source