Results 91 to 100 of about 3,126,616 (266)

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

An empirical study of enterprise investment relationship networks in China

Humanities & Social Sciences Communications
Enterprise investment relationships serve as a microcosm reflecting macroeconomic vitality, which is restricted and affected by geographic locations of these enterprises.
Lai Jiang, Jiale Wang, Chunxiao Li, Yaohui Jin, Yanyan Xu   +4 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

TRANSFORMER VS. MAMBA AS SKIN CANCER CLASSIFIER: PRELIMINARY RESULTS

KPI Science News
Background: Skin cancer is a deadly disease that takes dozens of thousands of lives yearly. The key element of successful treatment of it is early detection. However, invasive detection methods are not always feasible.
Владислав Нікітін, Валерій Данілов   +1 more
doaj   +1 more source

Predicting wet age-related macular degeneration (AMD) using DARC (detecting apoptosing retinal cells) AI (artificial intelligence) technology. [PDF]

Expert Rev Mol Diagn, 2021
Corazza P, Maddison J, Bonetti P, Guo L, Luong V, Garfinkel A, Younis S, Cordeiro MF.   +7 more
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

Co-design with affect stories and applied ethics for health technologies

Frontiers in Communication
The integration of digital health technologies in clinical practices and everyday lives of patients raises several issues. Some of them are related to applied ethics.
Ambre Davat, Ambre Davat, Fabienne Martin-Juchat, Fabienne Martin-Juchat, Thierry Ménissier, Thierry Ménissier   +5 more
doaj   +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

Dataset for visitations of public green spaces in Shanghai, China

Scientific Data
Research on urban green spaces remains active, with a shift towards data-driven methodologies. Leveraging mobile phone data from 10 million anonymized users in Shanghai, we identify park visitations over four months and construct a real population-level ...
Yuting Feng, Shaoyu Huang, Shengze Chen, Chenghe Guan, Ying Li, Qiaoyu Tan, Yaohui Jin, Xiaokang Yang, Yanyan Xu   +8 more
doaj   +1 more source

Inpainting Semantic and Depth Features to Improve Visual Place Recognition in the Wild

IEEE Access
Visual place recognition is one of the core modern computer vision tasks concerned with identifying location based on the image taken there. Modern state-of-the-art approaches heavily rely on RGB images which are largely affected by changes in the same ...
Ilia Semenkov, Aleksei Karpov, Andrey V. Savchenko, Ilya Makarov   +3 more
doaj   +1 more source