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Geometric and topological inference deals with the retrieval of information about a geometric object using only a finite set of possibly noisy sample points. It has connections to manifold learning and provides the mathematical and algorithmic foundations of the rapidly evolving field of topological data analysis. Building on a rigorous treatment of simplicial complexes and distance functions, this self-contained book covers key aspects of the field, from data representation and combinatorial questions to manifold reconstruction and persistent homology. It can serve as a textbook for graduate students or researchers in mathematics, computer science and engineering interested in a geometric approach to data science.

Shapes --- Geometric analysis. --- Pattern perception. --- Topology. --- Mathematical models.

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Flutter analysis. --- NASTRAN. --- Propellers. --- Disks (shapes) --- Aerodynamic loads.

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There are a variety of models which can be used to study nuclear structure and dynamics. This book gives a comprehensive overview of these various models, concentrating in particular on a description of deformed and rotating nuclei. Following a treatment of the semi-empirical mass formula and nuclear stability, the liquid-drop and simple shell models are introduced and described. The spherical nuclear one-particle potential is introduced and developed to cover the case of deformed nuclei. The latter chapters of the book are devoted to discussions of barrier penetration, fast nuclear rotation, nucleon-nucleon interactions and the pairing interaction. Many problems and solutions are included, which help to illustrate key concepts. The book will be invaluable to graduate students of nuclear physics, and to anyone engaged in research in this field.

Nuclear structure. --- Nuclear shell theory. --- Nuclear shapes. --- Nuclear spin.

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Light alloy sheets forming --- Aluminium sheets forming --- Aluminium shapes forming

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Art and science --- Art. --- Shapes --- Art et sciences --- Art --- Formes