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Recent years have seen an exponential increase in the amount of data available in all sciences and application domains. Macroecology is part of this "Big Data" trend, with a strong rise in the volume of data that we are using for our research. Here, we sum ...
There are dedicated computational models and platforms to facilitate the design and planning of multi-energy-systems. However, the widespread adoption of new technological solutions largely depends on the right business models. Whilst there exists a list o ...
Using multilayered individual massive data and geo-localization tracking, Computational Social Science and Social Physics attest the importance of face-to-face and place-to-place interactions in shaping human agency. The research suggests that collective a ...
Heterogeneous materials are used in a wide range of applications involving high heat flux environments such as concentrated solar reactors, high-temperature furnaces, or thermal protection systems of space vehicles. The thermal response of heterogeneous ma ...
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 ...
Purpose of ReviewData science is an exploding trans-disciplinary field that aims to harness the power of data to gain information or insights on researcher-defined topics of interest. In this paper, we review how data science can help advance environmental ...
In proximity mask aligner photolithography, diffraction of light at the mask pattern is the predominant source for image shape distortions such as line end shortening and corner rounding. One established method to mitigate the impact of diffraction is opti ...
In modern-data analysis applications, the abundance of data makes extracting meaningful information from it challenging, in terms of computation, storage, and interpretability. In this setting, exploiting sparsity in data has been essential to the developm ...
Advances in renewable and sustainable energy technologies critically depend on our ability to design and realize materials with optimal properties. Materials discovery and design efforts ideally involve close coupling between materials prediction, synthesi ...
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 ...
