Results 51 to 60 of about 2,830,844 (261)

What Do Large Language Models Know About Materials?

Advanced Engineering Materials, EarlyView.
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, Thomas Wallmersperger, Gianaurelio Cuniberti   +2 more
wiley   +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, Moritz Blum, Luana Caron, Alisa Chirkova, Philipp Cimiano, Basil Ell, Inga Ennen, Michael Feige, Maik Gaerner, Thomas Hilbig, Andreas Hütten, Günter Reiss, Tapas Samanta, Sonja Schöning, Christian Schröder, Lennart Schwan, Chris Taake, Martin Wortmann   +17 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

Leverage manipulation and strategic disclosure: evidence from non-financial information in annual reports based on multimodal machine learning

China Journal of Accounting Studies
This study adopts multi-modal machine learning to deeply interpret corporate non-financial information and explore the influence of corporate leverage manipulation on non-financial information disclosure.
Jianhua Tan, Yipu Li, Tiancheng Gao, Jun Pan   +3 more
doaj   +1 more source

Pengaruh Perputaran Modal Kerja, Operating Leverage dan Financial Leverage terhadap Profitabilitas Perusahaan Sektor Retail di Bursa Efek Indonesia

JKBM (Jurnal Konsep Bisnis dan Manajemen), 2019
This study aims to analyze the influence of working capital turnover, operating leverage and financial leverage on profitability. The research object is thirteen retail sector companies listed on the Indonesia Stock Exchange (IDX) which are selected ...
Muhammad Fuad, Oyami Sara, Muhammad Nur Daud   +2 more
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

Leverage Constraints and the International Transmission of Shocks [PDF]

Recent macroeconomic experience has drawn attention to the importance of interdependence among countries through financial markets and institutions, independently of traditional trade linkages.
Michael B. Devereux, James Yetman
core   +2 more sources

The Effect of Leverage, Sales Growth, Cash Flow on Financial Distress with Corporate Governance as a Moderating Variable

Accounting Analysis Journal, 2020
The aim of this study is to detect the effect of leverage, sales growth, and cash flow on financial distress with corporate governance as moderating variable.
Rizka Vidya Dwi Giarto, Fachrurrozie Fachrurrozie   +1 more
doaj   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source

Investment Patterns and Financial Leverage [PDF]

This study Investigates the influence of the type of investment opportunities facing a firm on its choice of capital structure. It is shown that the more discretionary investment opportunities a firm faces,the lower its financial leverage.
Michael S. Long, Ileen B. Malitz
core