Results 71 to 80 of about 6,586,139 (300)

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

Multimodal Intercultural Information and Communication Technology - A Framework for Designing and Evaluating Multimodal Intercultural Communicators [PDF]

, 2009
Även tillgänglig i Hprints: http://hprints.org/hprints-00504104The paper presents a framework, combined with a checklist for designing and evaluating multimodal, intercultural ICT, especially when embodied artificial communicators are used as front ends
Ahlsén, Elisabeth, Elisabeth Ahlsén, Ahlsén, E., Allwood, Jens,, Allwood, Jens, Jens Allwood   +5 more
core   +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

Students' multimodal knowledge practices in a makerspace learning environment [PDF]

, 2020
In this study, we aim to widen the understanding of how students' collaborative knowledge practices are mediated multimodally in a school's makerspace learning environment.
Kumpulainen, Kristiina, Kajamaa, Anu
core   +1 more source

Ontology‐Aligned Structuring and Reuse of Multimodal Materials Data and Workflows Toward Automatic Reproduction

Advanced Engineering Materials, EarlyView.
Reproduction of stacking fault energy calculations from literature with a semi‐automated large language model‐assisted extraction procedure: extraction of simulation protocol, atomistic structures, computational parameters, and reported results, ontology alignment, knowledge graph construction and, finally, recomputation forvalidation.
Sepideh Baghaee Ravari, Abril Azocar Guzman, Sarath Menon, Stefan Sandfeld, Tilmann Hickel, Markus Stricker   +5 more
wiley   +1 more source

MINT.tools: Tools and Adaptors Supporting Acquisition, Annotation and Analysis of Multimodal Corpora [PDF]

, 2013
Kousidis S, Pfeiffer T, Schlangen D. MINT.tools: Tools and Adaptors Supporting Acquisition, Annotation and Analysis of Multimodal Corpora. In: Proceedings of Interspeech 2013.
Kousidis, Spyridon, Schlangen, David ; https://orcid.org/, Pfeiffer, Thies ; https://orcid.org/   +2 more
core  

DRFusion: Enhancing balanced and sufficient multimodal learning for human emotion recognition

Alexandria Engineering Journal
Inspired by human multisensory synergy, multimodal emotion recognition (MER) has advanced human–computer interaction by integrating complementary information from multiple sources.
Haipeng Yu, Hengzhou Xu, Jian Wang, Hua Li   +3 more
doaj   +1 more source

Multimodal texts in the process of learning foreign languages [PDF]

Baština
Due to the global spread of new technologies and communication channels, today's students are increasingly engaged in multimodal content and are significantly exposed to digital information on a daily basis.
Vidosavljević Milena M.
doaj   +1 more source

Microstructure Reconstruction in Battery Electrodes Using Machine Learning Based on Low‐Voltage Focused Ion Beam–Scanning Electron Microscopy Tomography Images

Advanced Engineering Materials, EarlyView.
Low‐voltage FIB‐SEM tomography combined with a image preprocessing pipeline improves phase contrast and enables reliable machine‐learning segmentation of conductive networks in lithium‐ion battery electrodes. Structural descriptors are extracted from segmented images, done semimanually and automated, and compared.
Lisa Beran, Vincent Nebel, Dominik Perius, Kshitij Kumar, Yannis Heim, Laura Bies, Tobias Kraus   +6 more
wiley   +1 more source

Unsupervised Segmentation of Object Manipulation Operations from Multimodal Input [PDF]

, 2011
Barchunova A, Moringen J, Großekathöfer U, et al. Unsupervised Segmentation of Object Manipulation Operations from Multimodal Input. In: Hammer B, Villmann T, eds. Machine Learning Reports. New Challenges in Neural Computation.
Großekathöfer, Ulf, Barchunova, Alexandra ; https://orcid.org/, Moringen, Jan, Janssen, Herbert, Ritter, Helge ; https://orcid.org/, Haschke, Robert ; https://orcid.org/, Villmann, Thomas, Wachsmuth, Sven ; https://orcid.org/, Hammer, Barbara   +8 more
core