Results 111 to 120 of about 30,520,612 (308)

Current Status and Challenges in Data Collection for Aerospace Coatings Deposited by Plasma Spraying

Advanced Engineering Materials, EarlyView.
An innovative approach has been integrated into the GRENAT project to optimize plasma spraying and coating performance. Raw materials are accelerated and melted in the plasma generated by torches, creating coatings. Monitoring sensors collect process data which are combined with ex situ characterization data.
Lila Randriamananjara, Vincent Rat, Quentin Dubreuil, Patrice Valorge, Simon Goutier, Alain Denoirjean, Olivier Messe, Céline Ruelle, Jean‐Philippe Poli   +8 more
wiley   +1 more source

UCOPhyRehab++: A multi-modal and multi-view dataset for human rehabilitation analysis

Scientific Data
The rehabilitation of patients with musculoskeletal disorders is usually associated with the performance of prescribed exercises at home. Performing these exercises without medical supervision may lead to incorrect execution, resulting in secondary ...
Rafael Aguilar-Ortega, Jorge Zafra-Palma, Rafael Muñoz-Salinas, Manuel J. Marin-Jimenez   +3 more
doaj   +1 more source

Artificial Intelligence and Computational Science

, 2022
Repin, Sergey, Neittaanmäki, Pekka
openaire   +1 more source

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

Injection Molding at the MIT Artificial Intelligence Lab [PDF]

, 1995
This paper describes the injection molding equipment at the MIT Artificial Intelligence Lab and how to use it. Topic covered include mold design, insert molding, safety, and material properties.MIT Artificial Intelligence ...
Binnard, Michael
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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

Symbol acquisition for probabilistic high-level planning [PDF]

, 2015
We introduce a framework that enables an agent to autonomously learn its own symbolic representation of a low-level, continuous environment. Propositional symbols are formalized as names for probability distributions, providing a natural means of dealing
Lozano-Perez, Tomas, Konidaris, George, Kaelbling, Leslie P   +2 more
core  

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

CC-AFL: Contrastive Clustering–Based Asynchronous Federated Learning With Dynamic Client Scheduling for Industrial Defect Detection

Applied Computational Intelligence and Soft Computing
The non-independent and identically distributed (non-IID) nature of data across different sites and the dynamic participation of client nodes represent two critical challenges faced by distributed industrial visual defect detection systems.
Jinhai Wang, Junwei Xue, Jinshuan Wang, Jielin Wen, Chang Niu, Lufeng Luo   +5 more
doaj   +1 more source

Introduction to Artificial Intelligence

, 2010
This zip file contains the entire material for the Introduction to Artificial Intelligence module.
ukoer, Open Educational Repository in Support of Computer Science, Dr Jim Smith   +2 more
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