Results 81 to 90 of about 28,871 (249)
A flexure‐based variable stiffness structure is developed by integrating phase‐change modulation and adhesive interfacial locking of gallium. The design enables a wide stiffness variability, transitioning from soft, flexible behavior to rigid, load‐supporting performance.
Sungjin Kim +2 more
wiley +1 more source
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
A comparative study of ensemble learning algorithms for high-frequency trading
High-Frequency Trading utilizes powerful mathematical algorithms to execute transactions at an extremely rapid pace, which makes the use of machine learning techniques for prediction necessary.
El Mehdi Ferrouhi, Ibrahim Bouabdallaoui
doaj +1 more source
Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization
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
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
Multimodal Data‐Driven Microstructure Characterization
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
High frequency trading, often known as HFT, is a subset of algorithmic trading, which is one of the most significant improvements to the trading environment in recent years.
Visalakshi Palaniappan +4 more
doaj +1 more source
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 +2 more
wiley +1 more source
PASTA‐ELN: Simplifying Research Data Management for Experimental Materials Science
Research data management faces ongoing hurdles as many ELNs remain complex and restrictive. PASTA‐ELN offers an open‐source, cross‐platform solution that prioritizes simplicity, offline access, and user control. Its in tuitive folder structure, modular Python add‐ons, and open formats enable seamless documentation, FAIR data practices, and easy ...
S. Brinckmann, G. Winkens, R. Schwaiger
wiley +1 more source
Testing of Dependencies between Stock Returns and Trading Volume by High Frequency Data [PDF]
This paper is concerned with a dependence analysis of returns, return volatility and trading volume for five companies listed on the Vienna Stock Exchange and five from theWarsaw Stock Exchange. Taking into account high frequency data for these companies,
Piotr Gurgul, Robert Syrek
doaj

