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The Practice of Reproducible Research
The Practice of Reproducible Research presents concrete examples of how researchers in the data-intensive sciences are working to improve the reproducibility of their research projects. In each of the thirty-one case studies in this volume, the author or team describes the workflow that they used to complete a real-world research project. Authors highlight how they utilized particular tools, ideas, and practices to support reproducibility, emphasizing the very practical how, rather than the why or what, of conducting reproducible research. Part 1 provides an accessible introduction to reproducible research, a basic reproducible research project template, and a synthesis of lessons learned from across the thirty-one case studies. Parts 2 and 3 focus on the case studies themselves. The Practice of Reproducible Research is an invaluable resource for students and researchers who wish to better understand the practice of data-intensive sciences and learn how to make their own research more reproducible.
The Light and Smith Manual
The Fourth Edition of The Light and Smith Manual continues a sixty-five-year tradition of providing to both students and professionals an indispensable, comprehensive, and authoritative guide to Pacific coast marine invertebrates of coastal waters, rocky shores, sandy beaches, tidal mud flats, salt marshes, and floats and docks. This classic and unparalleled reference has been newly expanded to include all common and many rare species from Point Conception, California, to the Columbia River, one of the most studied areas in the world for marine invertebrates. In addition, although focused on the central and northern California and Oregon coasts, this encyclopedic source is useful for anyone ...
Compressed Sensing & Sparse Filtering
This book is aimed at presenting concepts, methods and algorithms ableto cope with undersampled and limited data. One such trend that recently gained popularity and to some extent revolutionised signal processing is compressed sensing. Compressed sensing builds upon the observation that many signals in nature are nearly sparse (or compressible, as they are normally referred to) in some domain, and consequently they can be reconstructed to within high accuracy from far fewer observations than traditionally held to be necessary. Apart from compressed sensing this book contains other related approaches. Each methodology has its own formalities for dealing with such problems. As an example, in t...
Archbold
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