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Civil Engineering Materials - From Theory to Practice (Paperback): Qiang Yuan, Zanqun Liu, Keren Zheng, Cong Ma Civil Engineering Materials - From Theory to Practice (Paperback)
Qiang Yuan, Zanqun Liu, Keren Zheng, Cong Ma
R3,709 Discovery Miles 37 090 Ships in 12 - 19 working days

Civil Engineering Materials: From Theory to Practice presents the state-of-the-art in civil engineering materials, including the fundamental theory of materials needed for civil engineering projects and unique insights from decades of large-scale construction in China. The title includes the latest advances in new materials and techniques for civil engineering, showing the relationship between composition, structure and properties, and covering ultra-high-performance concrete and self-compacting concrete developed in China. This book provides comprehensive coverage of the most commonly used, most advanced materials for use in civil engineering. This volume consists of eight chapters covering the fundamentals of materials, inorganic cementing materials, Portland cement concrete, bricks, blocks and building mortar, metal, wood, asphalt and polymers.

Spectral Methods for Data Science - A Statistical Perspective (Paperback): Yuxin Chen, Yuejie Chi, Jianqing Fan, Cong Ma Spectral Methods for Data Science - A Statistical Perspective (Paperback)
Yuxin Chen, Yuejie Chi, Jianqing Fan, Cong Ma
R2,315 Discovery Miles 23 150 Ships in 10 - 15 working days

In contemporary science and engineering applications, the volume of available data is growing at an enormous rate. Spectral methods have emerged as a simple yet surprisingly effective approach for extracting information from massive, noisy and incomplete data. A diverse array of applications have been found in machine learning, imaging science, financial and econometric modeling, and signal processing.This monograph presents a systematic, yet accessible introduction to spectral methods from a modern statistical perspective, highlighting their algorithmic implications in diverse large-scale applications. The authors provide a unified and comprehensive treatment that establishes the theoretical underpinnings for spectral methods, particularly through a statistical lens.Building on years of research experience in the field, the authors present a powerful framework, called leave-one-out analysis, that proves effective and versatile for delivering fine-grained performance guarantees for a variety of problems. This book is essential reading for all students, researchers and practitioners working in Data Science.

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