Results 241 to 250 of about 619,668 (328)

“Visiting scientist effect”? Exploring the impact of time‐lags in the digitization of 2D landmark data

open access: yesThe Anatomical Record, EarlyView.
Abstract Measurement error (ME) in geometric morphometrics has been the subject of countless articles, but none specific to the effect of time lags on landmark digitization error. Yet, especially for visiting scientists working on museum collections, it is not uncommon to collect data in multiple rounds, with interruptions of weeks or years. To explore
Andrea Cardini
wiley   +1 more source

A Methodological Approach to Prioritize Digital Twin Development in Manufacturing

open access: yesApplied Stochastic Models in Business and Industry, EarlyView.
ABSTRACT The digital age has brought about a need for organizations to utilize Digital Twins to improve operational efficiency and decision‐making. However, it is difficult for companies to identify and prioritize Digital Twin initiatives that meet the needs of their stakeholders and align with the capabilities of the company and its strategic plans ...
Sara Blasco Román, Till Böttjer
wiley   +1 more source

The Slow‐Rotating Nucleus of Comet C/2013 R1 (Lovejoy)

open access: yesAstronomische Nachrichten, EarlyView.
ABSTRACT The close approach of comet C/2013 R1 (Lovejoy) allowed us to conduct an in‐depth study of the morphology of the inner coma. From the measurement of the dust emission structures expanding near the cometary nucleus in November–December 2013, we derived a slow rotation period of 47.8±1.2$$ 47.8\pm 1.2 $$ h.
Federico Manzini   +12 more
wiley   +1 more source

Learning high-accuracy error decoding for quantum processors. [PDF]

open access: yesNature
Bausch J   +17 more
europepmc   +1 more source

Redshift‐Agnostic Machine Learning Classification: Unveiling Peak Performance in Galaxy, Star, and Quasar Classification (Using SDSS DR17)

open access: yesAstronomische Nachrichten, EarlyView.
ABSTRACT Classification of galaxies, stars, and quasars using spectral data is fundamental to astronomy, but often relies heavily on redshift. This study evaluates the performance of 10 machine learning algorithms on SDSS data to classify these objects, with a particular focus on scenarios where redshift information is unavailable.
Debashis Chatterjee, Prithwish Ghosh
wiley   +1 more source

Optimizing fountain codes for DNA data storage. [PDF]

open access: yesComput Struct Biotechnol J
Schwarz PM, Freisleben B.
europepmc   +1 more source

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