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Peer-to-Peer Learning Dynamics of Wide Neural Networks

ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Peer-to-peer learning is an increasingly popular framework that enables beyond-5G distributed edge devices to collaboratively train deep neural networks in a privacy-preserving manner without the aid of a central server. Neural network training algorithms for emerging environments, e.g., smart cities, have many design considerations that are difficult ...
Shreyas Chaudhari +3 more
openaire +4 more sources

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 +6 more
wiley +1 more source

Trio-ethnographic Reflection on Using Digital Storytelling to Enhance Learners’ Engagement

Vietnam Journal of Education
The teaching and learning process in the digital landscape is evolving beyond traditional one-way knowledge delivery. Using trio-ethnography, a combination of duoethnography and photography (Le et al., 2021), we sought to explore how to integrate ...
Lien Phuong Thi Le +4 more
doaj +1 more source

A Simplified Laminar Flow Model for the Pultrusion of Glass Fiber/Polyethylene Terephthalate Commingled Yarns

Advanced Engineering Materials, EarlyView.
A simplified thermoplastic pultrusion model is developed to predict thermal fields in glass fiber/polyethylene terephthalate (GF/PET) composites with reduced computational cost. By combining effective material homogenization, validation against literature data, and Gaussian‐process‐based optimization, the study reveals how heating limits, pulling speed,
Elder Soares +3 more
wiley +1 more source

Peer-Assisted Learning in Undergraduate Midwifery Clinical Education: A Qualitative Study on Experiences of Nursing Students From Three Namibian Training Institutions

SAGE Open Nursing
Introduction Peer-assisted learning is widely used in nursing education and is reported to have a positive impact on the students’ learning process. However, students’ experiences of peer-assisted learning from midwifery clinical education in resource ...
Kristine S Kandingu MSc, Vistolina Nuuyoma PhD +1 more
doaj +1 more source

Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization

Advanced Engineering Materials, EarlyView.
Magnetocaloric cooling (MCE) is an environmentally friendly refrigeration method with great potential. Optimizing MCE materials involves the preparation and screening of large quantities of samples, which in turn generates a large amount of data. A digitalization approach is presented that uses ontologies, knowledge graphs, and digital workflows to ...
Simon Bekemeier +17 more
wiley +1 more source

Decentralized federated learning using validation loss for model sharing in crop disease classification

Ecological Informatics
Agriculture plays an essential role in the economies of many countries, as it provides numerous livelihoods. However, managing crop diseases is one of the major challenges in modern agriculture.
Denis Mamba Kabala +3 more
doaj +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 +3 more
wiley +1 more source

A new approach to the peer-learning: Artificial intelligence-assisted peer-learning [PDF]

Research and Development in Medical Education, 2023
Sajedeh Kermani +3 more
doaj +1 more source

Multimodal Data‐Driven Microstructure Characterization

Advanced Engineering Materials, EarlyView.
A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang +4 more
wiley +1 more source

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