Results 171 to 180 of about 5,102,541 (276)

Detection of Step and Pulse Components and Estimation of Displacement Waveform Based on Near-fault Seismic Ground Motion Record

Journal of Japan Association for Earthquake Engineering, 2020
openaire   +1 more source

Field Report from Collaborative Research Center 1625: Heterogeneous Research Data Management Using Ontology Representations

Advanced Engineering Materials, EarlyView.
A unified research data management framework for heterogeneous materials data is presented. The system integrates multimodal datasets using ontologies and knowledge graphs, enabling interoperability and FAIR (findable, accessible, interoperable, reusable) data principles. By linking data across scales and workflows, it supports reproducible, Artifitial
Doaa Mohamed, Samuel García Vázquez, Behnam Mardani, Victor Dudarev, Alfred Ludwig, Maribel Acosta, Markus Stricker   +6 more
wiley   +1 more source

Modeling Long-Term Postseismic Deformation Following the 2020 Mw 7.0 Samos Earthquake Using Campaign and Continuous GNSS Observations. [PDF]

Sensors (Basel)
Solak Hİ, Tiryakioğlu İ, Gezgin C, Aladoğan K, Yalvaç S, Aktuğ B, Yiğit CÖ, Dönmez E, Demirelli E, Eyübagil EE, Çakanşimşek Ünlükaya EB, Şahiner F, Yıldırım MC, Gülal VE.   +13 more
europepmc   +1 more source

Towards Defect Phase Diagrams: From Research Data Management to Automated Workflows

Advanced Engineering Materials, EarlyView.
A research data management infrastructure is presented for the systematic integration of heterogeneous experimental and simulation data required for defect phase diagrams. The approach combines openBIS with a companion application for large‐object storage, automated metadata extraction, provenance tracking and federated data access, thereby supporting ...
Khalil Rejiba, Sang‐Hyeok Lee, Christina Gasper, Martina Freund, Sandra Korte‐Kerzel, Ulrich Kerzel   +5 more
wiley   +1 more source

OD-ViTFScL: Asynchronous Few-Shot Continual Learning for Intelligent Process Monitoring and Fault Diagnosis in Petrochemical Plants. [PDF]

Sensors (Basel)
Oshidele O, Lin S.
europepmc   +1 more source

Is an Apple an Orange? A Large Language Model Benchmark for Candidate Term Extraction and Subclass Decisions Against Upper Ontologies in Engineering and Materials Science

Advanced Engineering Materials, EarlyView.
Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch, Maximilian Holland, Klaus Drechsler, Johannes Schilp   +3 more
wiley   +1 more source

Machine learning-based Bayesian optimization of tuned inerter dampers for enhanced seismic response control in high-rise base-isolated structures. [PDF]

Sci Rep
Huang S, Zhu K.
europepmc   +1 more source

Early tsunami detection with near-fault ocean-bottom pressure gauge records based on the comparison with seismic data

Early tsunami detection with near-fault ocean-bottom pressure gauge records based on the comparison with seismic data
Offshore real-time ocean bottom networks of seismometers and ocean bottom pressure (OBP) gauges have been recently established such as DONET and S-net around the Japanese islands. One of their purposes is to practice rapid and accurate tsunami forecasting.
openaire   +1 more source

Symbolic Regression and Multi‐Objective Optimization of the Flory–Huggins Interaction Parameter for Hydrogels

Advanced Engineering Materials, EarlyView.
We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang, Adrian Ehrenhofer, Thomas Wallmersperger   +2 more
wiley   +1 more source

From Modality Performance to Graceful Degradation: A PRISMA 2020 Systematic Review of Sensor Architectures for Autonomous Vehicles. [PDF]

Sensors (Basel)
Viktor P.
europepmc   +1 more source