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4 produkter
4 produkter
123 kr
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The indispensable, illustrated pocket guide to New York movies, from Martin Scorsese and Woody Allen to Lena Dunham and Noah Baumbach. ALSO AVAILABLE: Close-Ups: Wes Anderson Close-Ups: Vampire Movies New York has always been one of the world’s most filmed cities, with its apartments housing tenants like Rosemary's baby and the Royal Tenenbaums, its skyscrapers scaled by the likes of King Kong and graffiti artists and its rubble-strewn streets prowled by everyone from Travis Bickle to Carrie Bradshaw.In this illustrated pocket guide to New York and its movies, Mark Asch explores the Big Apple block by block and neighbourhood by neighbourhood, jogging past the iconic bench from Manhattan, eating at Katz’s Deli from When Harry Met Sally and mooching around the Coney Island boardwalk like one of The Warriors. Retracing the steps of countless iconic actors, cinematographers and directors, he draws up a unique cinematic map of The City That Never Sleeps.
123 kr
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983 kr
Skickas inom 7-10 vardagar
Data assimilation is an approach that combines observations and model output, with the objective of improving the latter. This book places data assimilation into the broader context of inverse problems and the theory, methods, and algorithms that are used for their solution. It provides a framework for, and insight into, the inverse problem nature of data assimilation, emphasising 'why' and not just 'how'. Methods and diagnostics are emphasised, enabling readers to readily apply them to their own field of study. This comprehensive guide is accessible to non-experts and contains numerous examples and diverse applications from a broad range of domains, including geophysics, environmental acoustics, medical imaging, mechanical and biomedical engineering, economics and finance, and traffic control and urban planning. Readers will also find included the latest methods for advanced data assimilation, combining variational and statistical approaches.
1 376 kr
Skickas inom 5-8 vardagar
A Toolbox for Digital Twins: From Model-Based to Data-Driven brings together the mathematical and numerical frameworks needed for developing digital twins (DTs). Starting from the basics—probability, statistics, numerical methods, optimization, and machine learning—and moving on to data assimilation, inverse problems, and Bayesian uncertainty quantification, the book provides a comprehensive toolbox for DTs. Readers will findguidelines and decision trees to help the reader choose the right tools for the job,emphasis on the design process, denoted as the "inference cycle," whose aim is to propose a global methodology for complex problems,a comprehensive reference section with all recent methods, covering both model-based and data-driven approaches, anda vast selection of examples and all accompanying code. A Toolbox for Digital Twins: From Model-Based to Data-Driven is for researchers and engineers, engineering students, and scientists in any domain where data and models need to be coupled to produce digital twins.