{"product_id":"statistical-methods-for-materials-science-the-data-science-of-microstructure-characterization","title":"Statistical Methods for Materials Science: The Data Science of Microstructure Characterization","description":"\u003cp\u003e\u003cstrong\u003eBook Details\u003c\/strong\u003e\u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor\u003c\/strong\u003e: Jeffrey P. Simmons\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003ePublisher\u003c\/strong\u003e: CRC Press\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eEdition\u003c\/strong\u003e: 1st Edition\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eBinding\u003c\/strong\u003e: Hardcover\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eFormat\u003c\/strong\u003e: Import\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eNumber of Pages\u003c\/strong\u003e: 536\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eISBN\u003c\/strong\u003e: 9781498738200\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eLanguages\u003c\/strong\u003e: English\u003c\/p\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003cp\u003e\u003cstrong\u003eDimensions\u003c\/strong\u003e: 10.5 x 8.0 x 1.3 inches\u003c\/p\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003chr\u003e\n\u003cp\u003e\u003cstrong\u003eAbout The Book\u003c\/strong\u003e\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003e\"Data Analytics for Materials Science\"\u003c\/strong\u003e by \u003cstrong\u003eJeffrey P. Simmons\u003c\/strong\u003e introduces the crucial intersection of \u003cstrong\u003edata analytics\u003c\/strong\u003e and \u003cstrong\u003ematerials science\u003c\/strong\u003e. As data analytics becomes increasingly important in materials research, this book provides the practical tools and statistical methods needed to analyze large datasets, specifically in the context of \u003cstrong\u003emicrostructure characterization\u003c\/strong\u003e. The text explores advanced techniques, including \u003cstrong\u003einverse methods\u003c\/strong\u003e, \u003cstrong\u003edenoising\u003c\/strong\u003e, and \u003cstrong\u003edata modeling\u003c\/strong\u003e, essential for modern materials science research.\u003c\/p\u003e\n\u003cp\u003eThe book features an in-depth discussion of several key topics, including \u003cstrong\u003ecompressed sensing methods\u003c\/strong\u003e, \u003cstrong\u003estochastic models\u003c\/strong\u003e, \u003cstrong\u003eextreme estimation\u003c\/strong\u003e, and various approaches to \u003cstrong\u003epattern detection\u003c\/strong\u003e. These methodologies are particularly useful for researchers who are tasked with analyzing complex materials data and seeking to improve the accuracy and efficiency of their analyses.\u003c\/p\u003e\n\u003cp\u003eWith contributions from experts such as \u003cstrong\u003eCharles A. Bouman\u003c\/strong\u003e, \u003cstrong\u003eMarc De Graef\u003c\/strong\u003e, and \u003cstrong\u003eLawrence F. Drummy Jr.\u003c\/strong\u003e, this book stands out for its ability to bridge the gap between computational methods and materials science. It serves as a comprehensive resource for \u003cstrong\u003eresearchers\u003c\/strong\u003e and \u003cstrong\u003estudents\u003c\/strong\u003e in \u003cstrong\u003ematerials science\u003c\/strong\u003e, as well as professionals working in fields requiring the analysis of large-scale image datasets and microstructural data.\u003c\/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbout the Author\u003c\/strong\u003e:\u003cbr\u003e\u003cstrong\u003eJeffrey P. Simmons\u003c\/strong\u003e is a Scientist at the \u003cstrong\u003eAir Force Research Laboratory (AFRL)\u003c\/strong\u003e with extensive experience in \u003cstrong\u003ecomputational imaging\u003c\/strong\u003e and \u003cstrong\u003ematerials science\u003c\/strong\u003e. His research focuses on \u003cstrong\u003emicroscopy data analysis\u003c\/strong\u003e and \u003cstrong\u003ephase-field modeling\u003c\/strong\u003e. \u003cstrong\u003eCharles A. Bouman\u003c\/strong\u003e, a \u003cstrong\u003eShowalter Professor\u003c\/strong\u003e at \u003cstrong\u003ePurdue University\u003c\/strong\u003e, is a leading expert in \u003cstrong\u003estatistical signal and image processing\u003c\/strong\u003e. \u003cstrong\u003eMarc De Graef\u003c\/strong\u003e, a professor at \u003cstrong\u003eCarnegie Mellon University\u003c\/strong\u003e, specializes in \u003cstrong\u003emicrostructural characterization\u003c\/strong\u003e of materials. \u003cstrong\u003eLawrence F. Drummy Jr.\u003c\/strong\u003e, a senior materials engineer at \u003cstrong\u003eAFRL\u003c\/strong\u003e, contributes his expertise in \u003cstrong\u003efunctional materials\u003c\/strong\u003e and \u003cstrong\u003ematerials engineering\u003c\/strong\u003e.\u003c\/p\u003e","brand":"Taylor \u0026 Francis","offers":[{"title":"Default Title","offer_id":49951519703344,"sku":"Sarat_9781498738200","price":14029.0,"currency_code":"INR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0690\/9968\/4144\/files\/taylor-francis-book-default-title-statistical-methods-for-materials-science-the-data-science-of-microstructure-characterization-41325299401008.jpg?v=1775949990","url":"https:\/\/www.retailmaharaj.com\/bn\/products\/statistical-methods-for-materials-science-the-data-science-of-microstructure-characterization","provider":"Retail Maharaj","version":"1.0","type":"link"}