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Novel computational methods such as artificial neural networks, adaptive neuro-fuzzy inference systems and genetic programming are used in this chapter for the modeling of the nonlinear behavior of composite laminates subjected to constant amplitude loadin ...
Machine learning encompasses tools and algorithms that are now becoming popular in almost all scientific and technological fields. This is true for molecular dynamics as well, where machine learning offers promises of extracting valuable information from t ...
Historical newspapers are of interest to many humanities scholars as sources of information and language closely tied to a particular time, social context and place. Digitised newspapers are also of interest to many data-driven researchers who seek large b ...
Recent advances in material science and digital fabrication provide promising opportunities for product design, mechanical and biomedical engineering, robotics, architecture, art, and science. Engineered materials and personalized fabrication are revolutio ...
Machine learning encompasses tools and algorithms that are now becoming popular in almost all scientific and technological fields. This is true for molecular dynamics as well, where machine learning offers promises of extracting valuable information from t ...
Computational methods are crucial for the analysis of diffusion magnetic resonance imaging (MRI) of the brain. Computational diffusion MRI can provide rich information at many size scales, including local microstructure measures such as diffusion anisotrop ...
We present a novel algorithm based on the ensemble Kalman filter to solve inverse problems involving multiscale elliptic partial differential equations. Our method is based on numerical homogenization and finite element discretization and allows to recover ...
This thesis aims to further investigate rare natural disasters and studies adaptation decisions under uncertainty by solving several computational economic models. The modeling of rare natural disasters depends on the treatment of catastrophic outcomes wit ...
Computational nanophotonics has already made a disruptive impact on the photonic and optoelectronic industries and has dramatically influenced the ways today's optical engineers create, optimize, and use innovative materials and computer-aided services. Th ...
The rapid rise of organic-inorganic lead halide perovskites has amazed the photovoltaic community. As the efficiency race continues for this revolutionary class of light-harvesting materials, many questions on the structural, electronic and optical propert ...
