Results 51 to 60 of about 172,456 (264)
The challenge of learning environmental knowledge in the era of industrial society 4.0 amidst the implementation of hybrid learning is low digital literacy capability.
Rahmatulloh, Napis
doaj +1 more source
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
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
Digitalizing electroplating requires both domain knowledge and interoperability. This work introduces PlatOn, a domain ontology for trivalent chromium plating and coating characterization, and a hybrid pipeline that aligns it to a mid‐level reference ontology by combining eight similarity metrics with language model reasoning. Expert‐validated mappings
Janik Harter +10 more
wiley +1 more source
Exploring Boost Efficiency in Text Analysis by Using AI Techniques in Port Companies
This study presents how integrating natural language processing (NLP) and machine learning (ML) optimizes strategic management in the port sector. Using hybrid NLP-ML models, the accuracy of classification and prediction of strategic information is ...
Claudia Durán +6 more
doaj +1 more source
This review comprehensively evaluates extrusion‐based additive manufacturing for advanced ceramics, detailing feedstock options and key process parameters. By critically addressing defect mechanisms like porosity and cracking, the work highlights optimization strategies through machine learning and advanced postprocessing.
Meisam Bakhtiari +4 more
wiley +1 more source
We apply a foundational machine‐learning interatomic potential based on the graph atomic cluster expansion (GRACE) to simulate the commercial Ni‐based single‐crystal superalloy CMSX‐4. Hybrid Monte‐Carlo/molecular dynamics sampling resolves short‐range order in the γ phase and L12 sublattice occupancies in the γ’ phase and connects them to stacking ...
Aditya Vishwakarma +4 more
wiley +1 more source
Blended Learning and Hybrid Learning
Seiring perkembangan teknologi informasi dan komunikasi, dunia pendidikan mengalami perkembangan dengan pesat. Sistem pembelajaran konvensional mulai dikombinasikan bahkan dialihkan dengan sistem pembelajaran berbasis digital atau online learning.
Nurul Indah Wahyu Ningsih, Fitri Yuliana
openaire +1 more source
Optoelectronic synaptic devices based on solution‐processed molecular telluride GST‐225 phase‐change inks are demonstrated for three‐factor learning. A global optical signal broadcast through a silicon waveguide induces non‐volatile conductance updates exclusively in locally electrically flagged memristors.
Kevin Portner +14 more
wiley +1 more source
In the ever-expanding online fashion market, businesses in the clothing sales sector are presented with substantial growth opportunities. To utilize this potential, it is crucial to implement effective methods for accurately identifying clothing items ...
Waseem Abbas +4 more
doaj +1 more source

