Results 41 to 50 of about 25,587 (261)

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

Approximate CNN Hardware Accelerators for Resource Constrained Devices

IEEE Access
Implementation of Convolutional Neural Networks (CNNs) on edge devices require reduction in computational complexity. Leveraging optimization techniques or approximate computing techniques can reduce the overhead associated with hardware implementation ...
P Thejaswini, Gautham Suresh, V. Chiraag, Sukumar Nandi   +3 more
doaj   +1 more source

Hardware Acceleration Design for Edge Intelligence of Transmission Lines [PDF]

Jisuanji gongcheng
In recent years, with the development of the Internet of Things (IoT) for power transmission, the online monitoring of transmission lines has become a key construction focus. However, the computational capacity and power consumption of embedded platforms
ZHANG Shuhua, WANG Jiye, ZHAO Chuanqi, CHEN Hongming, GUO Yongwen
doaj   +1 more source

Hardware Acceleration

, 2023
AbstractWith Moore’s law and Dennard’s scaling no longer fueling the improvement in computing performance, new avenues for increasing performance are needed. Hardware acceleration is one avenue where many researchers and industrial parties are working and investing.
openaire   +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

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

A Practical Noise2Noise Denoising Pipeline for High‐Throughput Raman Spectroscopy

Advanced Engineering Materials, EarlyView.
A lightweight and reproducible denoising pipeline for high‐throughput Raman spectroscopy is introduced, based on a 1D convolutional autoencoder trained with a Noise2Noise strategy. Using only repeated short‐exposure acquisitions, the method suppresses stochastic noise without reference spectra, enabling reliable spectral reconstruction while preserving
David Martin‐Calle, Cesar Alvarez‐Llamas, Vincent Motto‐Ros, Christophe Dujardin, Jérémie Margueritat, David Rodney   +5 more
wiley   +1 more source

Inheritance and Innovation Development of Sports Based on Deep Learning and Artificial Intelligence

IEEE Access, 2023
This work aims to speed up the intelligent construction of Sports and Leisure Characteristic Towns (SLCT) in the new era. AI and robot technologies have become the pillar of scientific research.
Rui Zhou, Fan Wu
doaj   +1 more source

Resistive Neural Hardware Accelerators

Proceedings of the IEEE, 2023
Deep Neural Networks (DNNs), as a subset of Machine Learning (ML) techniques, entail that real-world data can be learned and that decisions can be made in real-time. However, their wide adoption is hindered by a number of software and hardware limitations. The existing general-purpose hardware platforms used to accelerate DNNs are facing new challenges
Kamilya Smagulova, Mohammed E. Fouda, Fadi J. Kurdahi, Khaled N. Salama, Ahmed M. Eltawil   +4 more
openaire   +3 more sources

Semantic Modeling in Materials Science and Engineering With Platform MaterialDigital Core Ontology 3.0

Advanced Engineering Materials, EarlyView.
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, Philipp von Hartrott, Jörg Waitelonis, Thomas Hanke, Henk Birkholz, Hossein Beygi Nasrabadi, Khashayar Razghandi, Kamilla Zaripova, Felix Thonagel, Fabian Neuhaus, Martin Glauer, Lars Vogt, Harald Sack, Lutz Mädler, Bernd Bayerlein, Chris Eberl   +15 more
wiley   +1 more source