Browse Results

Showing 22,926 through 22,950 of 27,720 results

Saxon Math Student Edition (Intermediate #5)

by Stephen Hake

NIMAC-sourced textbook

Saxon Math Student Edition (Intermediate #3)

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.

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

Say It With Symbols, Making Sense of Symbols

by Glenda Lappan James T. Fey William M. Fitzgerald

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 Zdeněk Dostál Tomáš Kozubek 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 Zdeněk Dostál Tomáš Kozubek 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 Gabriella Pasi Barbara Vantaggi

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

by Sébastien Destercke Maria Vanina Martinez 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.

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.

Scalar and Vector Risk in the General Framework of Portfolio Theory: A Convex Analysis Approach (CMS/CAIMS Books in Mathematics #9)

by Stanislaus Maier-Paape Pedro Júdice Andreas Platen Qiji Jim Zhu

This book is the culmination of the authors’ industry-academic collaboration in the past several years. The investigation is largely motivated by bank balance sheet management problems. The main difference between a bank balance sheet management problem and a typical portfolio optimization problem is that the former involves multiple risks. The related theoretical investigation leads to a significant extension of the scope of portfolio theories. The book combines practitioners’ perspectives and mathematical rigor. For example, to guide the bank managers to trade off different Pareto efficient points, the topological structure of the Pareto efficient set is carefully analyzed. Moreover, on top of computing solutions, the authors focus the investigation on the qualitative properties of those solutions and their financial meanings. These relations, such as the role of duality, are most useful in helping bank managers to communicate their decisions to the different stakeholders. Finally, bank balance sheet management problems of varying levels of complexity are discussed to illustrate how to apply the central mathematical results. Although the primary motivation and application examples in this book are focused in the area of bank balance sheet management problems, the range of applications of the general portfolio theory is much wider. As a matter of fact, most financial problems involve multiple types of risks. Thus, the book is a good reference for financial practitioners in general and students who are interested in financial applications. This book can also serve as a nice example of a case study for applied mathematicians who are interested in engaging in industry-academic collaboration.

Scalar Boson Decays to Tau Leptons: in the Standard Model and Beyond (Springer Theses)

by Cécile Caillol

This thesis presents a study of the scalar sector in the standard model (SM), as well as various searches for an extended scalar sector in theories beyond the SM (BSM). The first part of the thesis details the search for an SM Higgs boson decaying to taus, and produced by gluon fusion, vector boson fusion, or associated production with a vector boson, leading to evidence for decays of the Higgs boson to taus. In turn, the second part highlights several searches for an extended scalar sector, with scalar boson decays to taus. In all of the analyses presented, at least one scalar boson decays to a pair of taus. The results draw on data collected by the Compact Muon Solenoid (CMS) detector during proton–proton collisions with a center-of-mass energy of 7 or 8 TeV.

Scalar Conservation Laws (SpringerBriefs in Mathematics)

by Giuseppe Maria Coclite

This book are notes prepared for the PhD courses that the author has been teaching during the last 10 years. The material available in the already existing literature (papers and essays) has been collected in this unique text, presenting the results with all the details for the reader’s convenience, fixing a unified notation, and providing a consistent framework for the subject. These notes cover many of the arguments that usually can be found in high level essays, where the proofs are simply sketched, and in papers, which are not easily available and not always self-contained.This book is intended for1. PhD students in Mathematics, Physics and Mechanical Engineering in order to learn the basic features of nonlinear scalar equations,2. researchers interested in nonlinear hyperbolic PDEs in order to learn the details behind some known and deep results on nonlinear scalar equations,3. teachers of courses on nonlinear PDEs.The readers are expected to know the basic measure theory and Sobolev spaces.

Scalar Fields in Numerical General Relativity: Inhomogeneous Inflation and Asymmetric Bubble Collapse (Springer Theses)

by Katy Clough

This book explores the use of numerical relativity (NR) methods to solve cosmological problems, and describes one of the first uses of NR to study inflationary physics. NR consists in the solution of Einstein’s Equation of general relativity, which governs the evolution of matter and energy on cosmological scales, and in systems where there are strong gravitational effects, such as around black holes. To date, NR has mainly been used for simulating binary black hole and neutron star mergers like those detected recently by LIGO. Its use as a tool in fundamental problems of gravity and cosmology is novel, but rapidly gaining interest. In this thesis, the author investigates the initial condition problem in early universe cosmology – whether an inflationary expansion period could have “got going” from initially inhomogeneous conditions – and identifies criteria for predicting the robustness of particular models. State-of-the-art numerical relativity tools are developed in order to address this question, which are now publicly available.

Scalarization and Separation by Translation Invariant Functions: with Applications in Optimization, Nonlinear Functional Analysis, and Mathematical Economics (Vector Optimization)

by Christiane Tammer Petra Weidner

Like norms, translation invariant functions are a natural and powerful tool for the separation of sets and scalarization. This book provides an extensive foundation for their application. It presents in a unified way new results as well as results which are scattered throughout the literature. The functions are defined on linear spaces and can be applied to nonconvex problems. Fundamental theorems for the function class are proved, with implications for arbitrary extended real-valued functions. The scope of applications is illustrated by chapters related to vector optimization, set-valued optimization, and optimization under uncertainty, by fundamental statements in nonlinear functional analysis and by examples from mathematical finance as well as from consumer and production theory. The book is written for students and researchers in mathematics and mathematical economics. Engineers and researchers from other disciplines can benefit from the applications, for example from scalarization methods for multiobjective optimization and optimal control problems.

Scale: Understanding the Environment

by Cristian Suteanu

This book provides up-to-date, in-depth and accessible information on the concept of scale, and focuses on its applications in geography, Earth science, environmental science, and other fields in which the environment plays a significant role. Although the book presents methods and applications as a response to practical challenges, it is primarily concept-centered: it identifies a set of distinct, yet related notions of “scale”, analyzing and elucidating their evolving meanings in a systematic way. Concepts are defined with a focus on their practical operational applicability, and the introduction of methods is supported by concrete examples. The book links theoretical insights to illustrating applications, involving a broad range of themes, from maps, fractals, and chaos theory to fine art and literature. It approaches the subject in a spatial, temporal, and spatio-temporal context, including a wide diversity of spatial features from Earth and other planets, as well as time series and space-time patterns. This monograph is expected to be useful especially because in practice the various scale-focused concepts are not neatly separated and immiscible. It is therefore helpful for scholars in physical and human geography, Earth and environmental sciences, and other fields, to benefit from a clear conceptual framework that distinguishes and illuminates the various scale-related concepts and their interconnections. Selected chapters can also support a deeper understanding of the concept of scale for graduate and undergraduate students in geography, the natural sciences, and the humanities. Information on recommended additional literature and comments about specific sources offer a guide to further reading on the topics addressed in the book.

Scale Development: Theory and Applications (Applied Social Research Methods)

by Robert F. DeVellis Carolyn T. Thorpe

Scale Development: Theory and Applications, by Robert F. DeVellis and new co-author Carolyn T. Thorpe, demystifies measurement by emphasizing a logical rather than strictly mathematical understanding of concepts. The Fifth Edition includes a new chapter that lays out the key concepts that distinguish indices from scales, contrasts various types of indices, suggests approaches for developing them, reviews validity and reliability issues, and discusses in broad terms some analytic approaches. All chapters have been updated, and the book strikes a balance between including relevant topics and highlighting recent developments in measurement while retaining an accessible, user-friendly approach to the material covered.

Scale Development: Theory and Applications (Applied Social Research Methods)

by Robert F. DeVellis Carolyn T. Thorpe

Scale Development: Theory and Applications, by Robert F. DeVellis and new co-author Carolyn T. Thorpe, demystifies measurement by emphasizing a logical rather than strictly mathematical understanding of concepts. The Fifth Edition includes a new chapter that lays out the key concepts that distinguish indices from scales, contrasts various types of indices, suggests approaches for developing them, reviews validity and reliability issues, and discusses in broad terms some analytic approaches. All chapters have been updated, and the book strikes a balance between including relevant topics and highlighting recent developments in measurement while retaining an accessible, user-friendly approach to the material covered.

Scale in Spatial Information and Analysis

by Michael F. Goodchild Jingxiong Zhang Peter Atkinson

Now ubiquitous in modern life, spatial data present great opportunities to transform many of the processes on which we base our everyday lives. However, not only do these data depend on the scale of measurement, but also handling these data (e.g., to make suitable maps) requires that we account for the scale of measurement explicitly. Scale in Spat

Scaling

by Grigory Isaakovich Barenblatt

Many phenomena in nature, engineering or society when seen at an intermediate distance, in space or time, exhibit the remarkable property of self-similarity: they reproduce themselves as scales change, subject to so-called scaling laws. It's crucial to know the details of these laws, so that mathematical models can be properly formulated and analysed, and the phenomena in question can be more deeply understood. In this 2003 book, the author describes and teaches the art of discovering scaling laws, starting from dimensional analysis and physical similarity, which are here given a modern treatment. He demonstrates the concepts of intermediate asymptotics and the renormalisation group as natural attributes of self-similarity and shows how and when these notions and tools can be used to tackle the task at hand, and when they cannot. Based on courses taught to undergraduate and graduate students, the book can also be used for self-study by biologists, chemists, astronomers, engineers and geoscientists.

Scaling: A Sourcebook for Behavioral Scientists (Neural Information Processing Ser.)

by Peter Jordan Caroline Lloyd

Despite the obvious importance of measurement in any scientific endeavor, few students of the social sciences receive adequate training in the principles and problems of assigning numerical values to the subjects, objects, events, groups and operations they study, and still less in the process of translating theoretical ideas and concepts into variables. This kind of casualness with respect to measurement is often in marked contrast to their methodically designed research, which has grown out of subtle and sophisticated theoretical consideration.Scaling is intended to remedy this deficiency by providing a broad and detailed description of the major processes for developing measurement scales. The chapters, which include both classics in the field and the best of modern work, require no great mathematical sophistication, and go well beyond the conventional study of attitudes to the more general uses of scaling. They enable the student and researcher to examine the development of measures of scalability and the problems and weaknesses they present, to become familiar with the development of tests of significance for reproducibility and scalability and the need for them, and to examine the lively history of the subject and experience the excitement that can be secured from sharing with a creative author the first report of his insight.Part One presents a series of general articles that deal in philosophic terms with the problem of measurement, with what is meant by measurement and scaling as well as the notions underlying the process of measuring. Part Two deals with the scaling methods developed by L. L. Thurstone, including paired comparison scaling, equal-appearing interval scaling, and successive interval scaling. The third part focuses upon scalogram analysis, presenting the background, rationale and procedures for Guttman scaling. The fourth part is concerned with summated rating, or Likert scaling. Part Five is a consideration of unfold

Scaling, Fractals and Wavelets (Wiley-iste Ser.)

by Patrice Abry Paulo Gonçalves Jacques Lévy Véhel

Scaling is a mathematical transformation that enlarges or diminishes objects. The technique is used in a variety of areas, including finance and image processing. This book is organized around the notions of scaling phenomena and scale invariance. The various stochastic models commonly used to describe scaling ? self-similarity, long-range dependence and multi-fractals ? are introduced. These models are compared and related to one another. Next, fractional integration, a mathematical tool closely related to the notion of scale invariance, is discussed, and stochastic processes with prescribed scaling properties (self-similar processes, locally self-similar processes, fractionally filtered processes, iterated function systems) are defined. A number of applications where the scaling paradigm proved fruitful are detailed: image processing, financial and stock market fluctuations, geophysics, scale relativity, and fractal time-space.

Scaling Laws in Dynamical Systems (Nonlinear Physical Science)

by Edson Denis Leonel

This book discusses many of the common scaling properties observed in some nonlinear dynamical systems mostly described by mappings. The unpredictability of the time evolution of two nearby initial conditions in the phase space together with the exponential divergence from each other as time goes by lead to the concept of chaos. Some of the observables in nonlinear systems exhibit characteristics of scaling invariance being then described via scaling laws. From the variation of control parameters, physical observables in the phase space may be characterized by using power laws that many times yield into universal behavior. The application of such a formalism has been well accepted in the scientific community of nonlinear dynamics. Therefore I had in mind when writing this book was to bring together few of the research results in nonlinear systems using scaling formalism that could treated either in under-graduation as well as in the post graduation in the several exact programs but no earlier requirements were needed from the students unless the basic physics and mathematics. At the same time, the book must be original enough to contribute to the existing literature but with no excessive superposition of the topics already dealt with in other text books. The majority of the Chapters present a list of exercises. Some of them are analytic and others are numeric with few presenting some degree of computational complexity.

Refine Search

Showing 22,926 through 22,950 of 27,720 results