Results 81 to 90 of about 2,123,010 (259)
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 +4 more
wiley +1 more source
Hypothesis Testing of Edge Organizations: Laboratory Experimentation using the ELICIT Multiplayer Intelligence Game [PDF]
12th International Command and Control Research and Technology Symposium (ICCRTS), June 19-21, 2007 at the Naval War College, Newport, RI.The Edge is a relative newcomer to organizational design--one that appears especially appropriate for contemporary ...
Leweling, Tara A., Nissen, Mark E.
core +4 more sources
Edge intelligence:state-of-the-art and expectations
Edge intelligence (EI,which merges artificial intelligence (AI) into edge computing and deploys AI methods on edge devices) is regarded as a very efficient measure to provide faster and better intelligent services,having been successfully applied to ...
Kenli LI, Chubo LIU
doaj
Since the publication of the “Review of Embedded Artificial Intelligence Research” in 2023, driven by innovations in hardware architectures, advances in lightweight algorithms, and the maturation of edge–cloud collaboration technologies, embedded ...
Zhaoyun Zhang
doaj +1 more source
Enabling distributed intelligence assisted Future Internet of Things Controller (FITC)
The unprecedented prevalence of ubiquitous sensing will revolutionise the Future Internet where state-of-the-art Internet-of-Things (IoT) is believed to play the pivotal role.
Hasibur Rahman, Rahim Rahmani
doaj +1 more source
New AI‐Assisted Approach for Expanding the Solution Space: Application to Lattice Structure Design
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 +5 more
wiley +1 more source
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 +19 more
wiley +1 more source
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 +15 more
wiley +1 more source
Sustainability assessment requires methodologies that appropriately distinguish between additive and non‐additive material properties. A toxicity‐weighted scoring system is developed and applied that accounts for the disproportionate influence of highly toxic constituents through nonlinear weighting functions, providing more realistic estimates than ...
Seth Mehalic +2 more
wiley +1 more source
HEA interlayers offer a versatile route for joining high‐performance structural materials. Their compositional and structural design regulates interfacial reactions, suppresses brittle IMCs, and improves metallurgical bonding. Sandwich interlayers further integrate defect healing with precipitation strengthening, enabling improved strength–ductility ...
Lin Yuan +4 more
wiley +1 more source

