The.Hottest

David Muir Wood ... 488 pages - Publisher: Cambridge Univ. Press; 1st edition (April, 1991) ... Language: English - ISBN-10: 0521337828 - ISBN-13: 978-0521337823 ...

Soils can rarely be described as ideally elastic or perfectly plastic and yet simple elastic and plastic models form the basis for the most traditional geotechnical engineering calculations. With the advent of cheap powerful computers the possibility of performing analyses based on more realistic models has become widely available. One of the aims of this book is to describe the basic ingredients of a family of simple elastic-plastic models of soil behavior and to demonstrate how such models can be used in numerical analyses. Such numerical analyses are often regarded as mysterious black boxes but a proper appreciation of their worth requires an understanding of the numerical models on which they are based. Though the models on which this book concentrates are simple, understanding of these will indicate the ways in which more sophisticated models will perform.

A. S. Beletich, P. J. Uno ... 344 pages - Publisher: NewSouth Publishing; 2nd edition (April, 2003)  ... Language: English - ISBN-10: 086840621X - ISBN-13: 978-0868406213 ...

This book is the essential and easy-to-use guide for all students and practicing engineers who need to understand and design concrete structures. This second edition of the book is updated to include the revised Concrete Structures and Loading Codes. It develops: simple theory to help the student understand fundamental principles ; design formulas from first principles ; and design charts for all aspects of reinforced concrete design. It incorporates: many design samples to help the user understand the design processes ; the current 2001 AS3600 Concrete Structures Code requirements for deflection and crack control in beams and slabs ; high strength concrete column design charts with concrete strengths of 65, 80, 100 and 120MPa used in modern design and expected to be included in the next main revision of the code.

Andrew Gelman, Jennifer Hill ... 648 pages - Publisher: Cambridge Univ. Press; (December, 2006) ... Language: English - ISBN-10: 052168689X - ISBN-13: 978-0521686891 ...

Data Analysis Using Regression and Multilevel/Hierarchical Models is a comprehensive manual for the applied researcher who wants to perform data analysis using linear and nonlinear regression and multilevel models. The book introduces a wide variety of models, whilst at the same time instructing the reader in how to fit these models using available software packages. The book illustrates the concepts by working through scores of real data examples that have arisen from the authors' own applied research, with programming codes provided for each one. Topics covered include causal inference, including regression, poststratification, matching, regression discontinuity, and instrumental variables, as well as multilevel logistic regression and missing-data imputation. Practical tips regarding building, fitting, and understanding are provided throughout.

Rex B. Kline ... 534 pages - Publisher: The Guilford Press; 4th edition (November, 2015) ... Language: English - ISBN-10: 146252334X - ISBN-13: 978-1462523344 ...

Emphasizing concepts and rationale over mathematical minutiae, this is the most widely used, complete, and accessible structural equation modeling (SEM) text. Continuing the tradition of using real data examples from a variety of disciplines, the significantly revised fourth edition incorporates recent developments such as Pearl's graphing theory and the structural causal model (SCM), measurement invariance, and more. Readers gain a comprehensive understanding of all phases of SEM, from data collection and screening to the interpretation and reporting of the results. Learning is enhanced by exercises with answers, rules to remember, and topic boxes. The companion website supplies data, syntax, and output for the book's examples--now including files for Amos, EQS, LISREL, Mplus, Stata, and R (lavaan). New to This Edition: Extensively revised to cover important new topics: Pearl's graphing theory and the SCM, causal inference frameworks, conditional process modeling, path models for longitudinal data, item response theory, and more. + Chapters on best practices in all stages of SEM, measurement invariance in confirmatory factor analysis, and significance testing issues and bootstrapping. + Expanded coverage of psychometrics. + Additional computer tools: online files for all detailed examples, previously provided in EQS, LISREL, and Mplus, are now also given in Amos, Stata, and R (lavaan). + Reorganized to cover the specification, identification, and analysis of observed variable models separately from latent variable models.

Johan A. K. Suykens, Marco Signoretto ... 525 pages - Publisher: Chapman and Hall/CRC; (October, 2014) ... Language: English - ISBN-10: 1482241390 - ISBN-13: 978-1482241396 ...

Regularization, Optimization, Kernels, and Support Vector Machines offers a snapshot of the current state of the art of large-scale machine learning, providing a single multidisciplinary source for the latest research and advances in regularization, sparsity, compressed sensing, convex and large-scale optimization, kernel methods, and support vector machines. Consisting of 21 chapters authored by leading researchers in machine learning, this comprehensive reference: Covers the relationship between support vector machines (SVMs) and the Lasso * Discusses multi-layer SVMs * Explores nonparametric feature selection, basis pursuit methods, and robust compressive sensing * Describes graph-based regularization methods for single- and multi-task learning * Considers regularized methods for dictionary learning and portfolio selection * Addresses non-negative matrix factorization * Examines low-rank matrix and tensor-based models * Presents advanced kernel methods for batch and online machine learning, system identification, domain adaptation, and image processing * Tackles large-scale algorithms including conditional gradient methods, (non-convex) proximal techniques, and stochastic gradient descent. Regularization, Optimization, Kernels, and Support Vector Machines is ideal for researchers in machine learning, pattern recognition, data mining, signal processing, statistical learning, and related areas.

Boominathan Adimoolam, Subhadeep Banerjee ... 274 pages - Publisher: Springer; (June, 2018) ... Language: English - ASIN: B07DMTL38L by Amazon

This book gathers selected proceedings of the annual conference of the Indian Geotechnical Society, and covers various aspects of soil dynamics and earthquake geotechnical engineering. The book includes a wide range of studies on seismic response of dams, foundation-soil systems, natural and man-made slopes, reinforced-earth walls, base isolation systems and so on, especially focusing on the soil dynamics and case studies from the Indian subcontinent. The book also includes chapters addressing related issues such as landslide risk assessments, liquefaction mitigation, dynamic analysis of mechanized tunneling, and advanced seismic soil-structure-interaction analysis. Given its breadth of coverage, the book offers a useful guide for researchers and practicing civil engineers alike.

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