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Saxon Math Course 2, Student Edition

by Stephen Hake

NIMAC-sourced textbook

Saxon Math Intermediate (Grade #3)

by Saxon Publishers Hake

Saxon Math Intermediate 3–5 is a textbook-based comprehensive series that incorporates instructional materials, activities, and technology to support mastery of the Common Core State Standards.

Saxon Math K, Student Workbook, Part 2

by Nancy Larson Ellen Fenty-Morrison

NIMAC-sourced textbook

Saxon Math Performance Tasks (Intermediate #3)

by Stephen Hake

NIMAC-sourced textbook

Saxon Math Performance Tasks (Intermediate #4)

by Stephen Hake

NIMAC-sourced textbook

Saxon Math Performance Tasks (Intermediate #5)

by Stephen Hake

NIMAC-sourced textbook

Saxon Math Student Edition (Intermediate #3)

by Stephen Hake

NIMAC-sourced textbook

Saxon Math Student Edition (Intermediate #5)

by Stephen Hake

NIMAC-sourced textbook

Saxon Math Student Edition: Course 2 2018

by Houghton Mifflin Harcourt

*This textbook has been transcribed in UEB, formatted according to Braille textbook formats, proofread and corrected.

Saxon Math, Course 1

by Stephen Hake

NIMAC-sourced textbook

Saxon Math, Course 3

by Stephen Hake

NIMAC-sourced textbook

Saxon Math, Grade 4, Volume 1

by Stephen Hake

NIMAC-sourced textbook

Saxon Math, Grade 4, Volume 2

by Stephen Hake

NIMAC-sourced textbook

Saxon Math, Intermediate 3-5, Calculator Activities

by Stephen Hake

NIMAC-sourced textbook

Saxon Math: Student Workbook Grade 1, Volume 1

by Nancy Larson

Saxon Math, Student Workbook Grade 1, Volume 1 by Nancy Larson

Say It With Symbols, Making Sense of Symbols

by Glenda Lappan James T. Fey William M. Fitzgerald

NIMAC-sourced textbook

Say It With Symbols: Making Sense of Symbols (Texas)

by Glenda Lappan James T. Fey William M. Fitzgerald Susan N. Friel Elizabeth Difanis Phillips

NIMAC-sourced textbook

Scala: From a Functional Programming Perspective

by Vicenç Torra

This book gives an introduction to the programming language Scala. It presents it from a functional programming perspective. The book explains with detail functional programming and recursivity, and includes chapters on lazy and eager evaluation, streams, higher-order functions (including map, fold, reduce, and aggregate), and algebraic data types. The book also describes the object-oriented aspects of Scala, as they are a fundamental part of the language. In addition, the book includes a chapter on parallelism in Scala, giving an overview of the actor model.

Scalable Algorithms for Contact Problems (Advances in Mechanics and Mathematics #36)

by Tomáš Kozubek Zdeněk Dostál Marie Sadowská Vít Vondrák

This book presents a comprehensive and self-contained treatment of the authors’ newly developed scalable algorithms for the solutions of multibody contact problems of linear elasticity. The brand new feature of these algorithms is theoretically supported numerical scalability and parallel scalability demonstrated on problems discretized by billions of degrees of freedom. The theory supports solving multibody frictionless contact problems, contact problems with possibly orthotropic Tresca’s friction, and transient contact problems. It covers BEM discretization, jumping coefficients, floating bodies, mortar non-penetration conditions, etc. The exposition is divided into four parts, the first of which reviews appropriate facets of linear algebra, optimization, and analysis. The most important algorithms and optimality results are presented in the third part of the volume. The presentation is complete, including continuous formulation, discretization, decomposition, optimality results, and numerical experiments. The final part includes extensions to contact shape optimization, plasticity, and HPC implementation. Graduate students and researchers in mechanical engineering, computational engineering, and applied mathematics, will find this book of great value and interest.

Scalable Algorithms for Contact Problems (Advances in Mechanics and Mathematics #36)

by Tomáš Kozubek Zdeněk Dostál Marie Sadowská Vít Vondrák

This book presents a comprehensive treatment of recently developed scalable algorithms for solving multibody contact problems of linear elasticity. The brand-new feature of these algorithms is their theoretically supported numerical scalability (i.e., asymptotically linear complexity) and parallel scalability demonstrated in solving problems discretized by billions of degrees of freedom. The theory covers solving multibody frictionless contact problems, contact problems with possibly orthotropic Tresca’s friction, and transient contact problems. In addition, it also covers BEM discretization, treating jumping coefficients, floating bodies, mortar non-penetration conditions, etc. This second edition includes updated content, including a new chapter on hybrid domain decomposition methods for huge contact problems. Furthermore, new sections describe the latest algorithm improvements, e.g., the fast reconstruction of displacements, the adaptive reorthogonalization of dual constraints, and an updated chapter on parallel implementation. Several chapters are extended to give an independent exposition of classical bounds on the spectrum of mass and dual stiffness matrices, a benchmark for Coulomb orthotropic friction, details of discretization, etc. The exposition is divided into four parts, the first of which reviews auxiliary linear algebra, optimization, and analysis. The most important algorithms and optimality results are presented in the third chapter. The presentation includes continuous formulation, discretization, domain decomposition, optimality results, and numerical experiments. The final part contains extensions to contact shape optimization, plasticity, and HPC implementation. Graduate students and researchers in mechanical engineering, computational engineering, and applied mathematics will find this book of great value and interest.

Scalable Pattern Recognition Algorithms

by Pradipta Maji Sushmita Paul

This book addresses the need for a unified framework describing how soft computing and machine learning techniques can be judiciously formulated and used in building efficient pattern recognition models. The text reviews both established and cutting-edge research, providing a careful balance of theory, algorithms, and applications, with a particular emphasis given to applications in computational biology and bioinformatics. Features: integrates different soft computing and machine learning methodologies with pattern recognition tasks; discusses in detail the integration of different techniques for handling uncertainties in decision-making and efficiently mining large biological datasets; presents a particular emphasis on real-life applications, such as microarray expression datasets and magnetic resonance images; includes numerous examples and experimental results to support the theoretical concepts described; concludes each chapter with directions for future research and a comprehensive bibliography.

Scalable Uncertainty Management: 12th International Conference, SUM 2018, Milan, Italy, October 3-5, 2018, Proceedings (Lecture Notes in Computer Science #11142)

by Davide Ciucci Barbara Vantaggi Gabriella Pasi

This book constitutes the refereed proceedings of the 12th International Conference on Scalable Uncertainty Management, SUM 2018, which was held in Milan, Italy, in October 2018. The 23 full, 6 short papers and 2 tutorials presented in this volume were carefully reviewed and selected from 37 submissions. The conference is dedicated to the management of large amounts of complex, uncertain, incomplete, or inconsistent information. New approaches have been developed on imprecise probabilities, fuzzy set theory, rough set theory, ordinal uncertainty representations, or even purely qualitative models.

Scalable Uncertainty Management: 13th International Conference, SUM 2019, Compiègne, France, December 16–18, 2019, Proceedings (Lecture Notes in Computer Science #11940)

by Martin Theobald Nahla Ben Amor Benjamin Quost

This book constitutes the refereed proceedings of the 13th International Conference on Scalable Uncertainty Management, SUM 2019, which was held in Compiègne, France, in December 2019. The 25 full, 4 short, 4 tutorial, 2 invited keynote papers presented in this volume were carefully reviewed and selected from 44 submissions. The conference is dedicated to the management of large amounts of complex, uncertain, incomplete, or inconsistent information. New approaches have been developed on imprecise probabilities, fuzzy set theory, rough set theory, ordinal uncertainty representations, or even purely qualitative models.

Scalable Uncertainty Management: 16th International Conference, SUM 2024, Palermo, Italy, November 27–29, 2024, Proceedings (Lecture Notes in Computer Science #15350)

by Maria Vanina Martinez Sébastien Destercke Giuseppe Sanfilippo

This book constitutes the refereed proceedings of the 16th International Conference on Scalable Uncertainty Management, SUM 2024, held in Palermo, Italy, during November 27–29, 2024. The 28 full and 7 short papers presented in this volume were carefully reviewed and selected from 43 submissions. SUM 2024 solicited three types of paper submissions: Long papers reporting on original research or providing surveys that synthesize current research trends, short papers describing promising work in progress, systems, or positions on controversial issues, and extended abstracts.

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