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Titlebook: Nanoinformatics; Isao Tanaka Book‘‘‘‘‘‘‘‘ 2018 The Editor(s) (if applicable) and The Author(s) 2018 Machine learning.Big data.Atomic resol

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Ryoji Kanno,Genki Kobayashi,Kota Suzuki,Masaaki Hirayama,Daisuke Mori,Kazuhisa Tamura
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Topological Data Analysis for the Characterization of Atomic Scale Morphology from Atom Probe Tomogroms at or near interfaces. Hence, unlike scattering techniques such as electron microscopy, interfaces appear diffused, not sharp. This, in turn, makes it challenging to visualize and quantitatively interpret the microstructure at the “meso” scale, where one is interested in the shape and form of th
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High Spatial Resolution Hyperspectral Imaging with Machine-Learning Techniquessets, methods based on matrix factorization such as principal component analysis (PCA), multivariate curve resolution (MCR), and nonnegative matrix factorization (NMF) are useful to find an essential low-dimensional data subspace hidden in the HSI dataset. This chapter describes our developed NMF me
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Grain Boundary Engineering of Alumina Ceramicsreduced the diffusivity of oxygen and aluminum, respectively. Thus, the mesoscopic arrangements of segregating dopants, which were selected by taking into consideration the behavior of the diffusion species and the role of dopants, enabled the alumina film to have enhanced oxygen shielding capabilit
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Ichigaku Takigawa,Ken-ichi Shimizu,Koji Tsuda,Satoru Takakusagien in the same way as it did in America. On the other side of the globe, however, there does exist a country capable of serving as a suitable mirror. We speak, of course, of Russia. That country also came relatively late onto the cultural horizon, and was not privy to the Renaissance tradition. Furt
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