Browsing by Author "Ayensa Jiménez, Jacobo"
Now showing items 1-7 of 7
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Article
A multiscale data-driven approach for bone tissue biomechanics
(Elsevier, 2020-08)The data-driven methodology with application to continuum mechanics relies upon two main pillars: (i) experimental ...
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Article
A new reliability-based data-driven approach for noisy experimental data with physical constraints
(Elsevier, 2018-01)Data Science has burst into simulation-based engineering sciences with an impressive impulse. However, data are never ...
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Article
An unsupervised data completion method for physically-based data-driven models
(Elsevier, 2019-02)Data-driven methods are an innovative model-free approach for engineering and sciences, still in process of maturation. ...
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Article
Analysis of the parametric correlation in mathematical modeling of In vitro glioblastoma evolution using copulas
(MDPI, 2021)Modeling and simulation are essential tools for better understanding complex biological processes, such as cancer evolution. ...
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Article
Mathematical formulation and parametric analysis of in vitro cell models in microfuidic devices: application to diferent stages of glioblastoma evolution
(Nature Research, 2020)In silico models and computer simulation are invaluable tools to better understand complex biological processes such as ...
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Master's Final Project
Un modelo probabilístico para el cálculo estructural de sistemas mecánicos y la aplicación a la optimización de sistemas
(2016)La necesidad imperiosa por situar la ingeniería en un contexto de escasez obliga indirectamente cada vez más al ingeniero ...
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Article
Understanding glioblastoma invasion using physically-guided neural networks with internal variables
(Public Library Science, 2022-04)Microfluidic capacities for both recreating and monitoring cell cultures have opened the door to the use of Data Science ...