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Model-Fitting Weighted Least Squares as an Alternative to Principal Component Analysis for Analyzing Energy-Dispersive X-ray Spectroscopy Spectrum Images.
Microsc Microanal
November 2024
Centre for Analysis and Synthesis, and NanoLund, Lund University, Box 124, 22100 Lund, Sweden.
Spectrum imaging with energy-dispersive X-ray spectroscopy (EDS) has become ubiquitous in material characterization using electron microscopy. Multivariate statistical methods, commonly principal component analysis (PCA), are often used to aid analysis of the resulting multidimensional datasets; PCA can provide denoising prior to further analysis or grouping of pixels into distinct phases with similar signals. However, it is well known that PCA can introduce artifacts at low signal-to-noise ratios.
View Article and Find Full Text PDFDocumenting research in simulation science to enhance understanding for reusability.
R Soc Open Sci
October 2024
Institute of Engineering and Computational Mechanics, University of Stuttgart, Stuttgart 70569, Germany.
One goal of Open Science is to promote reusability, which requires understanding and documentation. Reusability spans a spectrum from the straightforward reuse of existing materials to the extraction and adaptation of specific elements, depending on the maturity of the reused research and the research context. Beyond knowledge, understanding is crucial for enabling reusability.
View Article and Find Full Text PDFA Cost-Aware Utility-Maximizing Bidding Strategy for Auction-Based Federated Learning.
IEEE Trans Neural Netw Learn Syst
November 2024
Auction-based federated learning (AFL) has emerged as an efficient and fair approach to incentivize data owners (DOs) to contribute to federated model training, garnering extensive interest. However, the important problem of helping data consumers (DCs) bid for DOs in competitive AFL settings remains open. Existing work simply treats that the actual cost paid by a winning DC (i.
View Article and Find Full Text PDFEffect of observer's cultural background and masking condition of target face on facial expression recognition for machine-learning dataset.
PLoS One
October 2024
Faculty of Environment and Information Sciences, Yokohama National University, Yokohama, Kanagawa, Japan.
Facial expression recognition (FER) is significantly influenced by the cultural background (CB) of observers and the masking conditions of the target face. This study aimed to clarify these factors' impact on FER, particularly in machine-learning datasets, increasingly used in human-computer interaction and automated systems. We conducted an FER experiment with East Asian participants and compared the results with the FERPlus dataset, evaluated by Western raters.
View Article and Find Full Text PDFAmong-species variation in six decades of changing migration timings explained through ecology, life-history and local migratory abundance.
Glob Chang Biol
July 2024
School of Biological Sciences, Zoology Building, University of Aberdeen, Aberdeen, UK.
Species exploiting seasonal environments must alter timings of key life-history events in response to large-scale climatic changes in order to maintain trophic synchrony with required resources. Yet, substantial among-species variation in long-term phenological changes has been observed. Advancing from simply describing such variation towards predicting future phenological responses requires studies that rigorously quantify and explain variation in the direction and magnitude of changing timings across diverse species in relation to key ecological and life-history variables.
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