Impact of a content-based image retrieval system on the interpretation of chest CTs of patients with diffuse parenchymal lung disease. [PDF]
Röhrich S +17 more
europepmc +1 more source
Retractions in Rheumatology: Trends, Causes, and Implications for Research Integrity
Objective We aimed to describe the trends and main reasons for study retraction in rheumatology literature. Methods We reviewed the Retraction Watch database to identify retracted articles in rheumatology. We recorded the main study characteristics, authors’ countries, reasons for retraction, time from publication to retraction, and trends over time ...
Anna Maria Vettori, Michele Iudici
wiley +1 more source
Deep features optimization based on a transfer learning, genetic algorithm, and extreme learning machine for robust content-based image retrieval. [PDF]
Bibi R +4 more
europepmc +1 more source
Innovating Aircraft Repair Processes: The Role of Digitalization in Sustainability
This research explores how digitalization—by storing detailed non‐destructive testing data in structured DICONDE databases and creating a standard data model of the component—innovates aviation maintenance and repair processes. Coupled with a developed state‐based simulation model, it enables data‐driven, sustainable repair strategies that reduce waste,
Johanna Aigner +3 more
wiley +1 more source
Evaluation of a Novel Content-Based Image Retrieval System for the Differentiation of Interstitial Lung Diseases in CT Examinations. [PDF]
Pogarell T +7 more
europepmc +1 more source
The documentation of component manufacture has become an essential part of today's production processes, especially for the analysis and optimization of production or component design with regard to structural performance, economic efficiency, and sustainability.
Björn Denker +4 more
wiley +1 more source
Content-Based Image Retrieval Using Colour, Gray, Advanced Texture, Shape Features, and Random Forest Classifier with Optimized Particle Swarm Optimization. [PDF]
Subramanian M +3 more
europepmc +1 more source
What Do Large Language Models Know About Materials?
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer +2 more
wiley +1 more source
This article presents the NFDI‐MatWerk Ontology (MWO), a Basic Formal Ontology‐based framework for interoperable research data management in materials science and engineering (MSE). Covering consortium structures, research data management resources, services, and instruments, MWO enables semantic integration, Findable, Accessible, Interoperable, and ...
Hossein Beygi Nasrabadi +4 more
wiley +1 more source

