الصفحة 73
الصفحة 73
Bioelectricity : A Quantitative Approach
"The authors’ goal in producing this book was to provide an introductory text to electrophysiology, based on a quantitative approach. In attempting to achieve this goal, therefore, the authors have opened the book with a useful, and digestible, introduction to various aspects of the mathematics relevant to this field, including vectors, introduction to Laplace, Gauss’s theorem, and Green’s theorem. This book will be useful for students in medical physics and biomedical engineering wishing to enter the field of electrophysiological investigation. It will also be helpful for biologists and physiologists who wish to understand the mathematical treatment of the processes and signals at the center of the interesting interdisciplinary field.
Binomial models in finance
This book deals with many topics in modern financial mathematics in a way that does not use advanced mathematical tools and shows how these models can be numerically implemented in a practical way. The book is aimed at undergraduate students, MBA students, and executives who wish to understand and apply financial models in the spreadsheet computing environment.The basic building block is the one-step binomial model where a known price today can take one of two possible values at the next time. In this simple situation, risk neutral pricing can be defined and the model can be applied to price forward contracts, exchange rate contracts, and interest rate derivatives.
Binary Quadratic Forms: An Algorithmic Approach
This book deals with algorithmic problems concerning binary quadratic forms 2 2 f(X,Y)= aX +bXY +cY with integer coe?cients a, b, c, the mathem- ical theories that permit the solution of these problems, and applications to cryptography.
Big Data Science in Finance
Explains the mathematics, theory, and methods of Big Data as applied to finance and investing Examines the mathematics, theory, and practical use of the revolutionary techniques that are transforming the industry. Designed for mathematically-advanced students and discerning financial practitioners alike, this energizing book presents new, cutting-edge content based on world-class research taught in the leading Financial Mathematics and Engineering programs in the world. Marco Avellaneda, a leader in quantitative finance, and quantitative methodology author Irene Aldridge help readers harness the power of Big Data. Provides a complete account of Big Data that includes proofs, step-by-step applications, and code samples Explains the difference between Principal Component Analysis (PCA) and Singular Value Decomposition (SVD) Covers vital topics in the field in a clear, straightforward manner Compares, contrasts, and discusses Big Data and Small Data Includes Cornell University-tested educational materials such as lesson plans, end-of-chapter questions, and downloadable lecture slides
Big Data – BigData 2020; 9th International Conference, Held as Part of the Services Conference Federation, SCF 2020, Honolulu, HI, USA, September 18-20, 2020, Proceedings
Constitutes the proceedings of the 9th International Conference on Big Data, BigData 2020, held as part of SCF 2020, during September 18-20, 2020. The conference was planned to take place in Honolulu, HI, USA and was changed to a virtual format due to the COVID-19 pandemic. The 16 full and 3 short papers presented were carefully reviewed and selected from 52 submissions. The topics covered are Big Data Architecture, Big Data Modeling, Big Data As A Service, Big Data for Vertical Industries (Government, Healthcare, etc.), Big Data Analytics, Big Data Toolkits, Big Data Open Platforms, Economic Analysis, Big Data for Enterprise Transformation, Big Data in Business Performance Management, Big Data for Business Model Innovations and Analytics, Big Data in Enterprise Management Models and Practices, Big Data in Government Management Models and Practices, and Big Data in Smart Planet Solutions.
Beyond the apparent Banality of the mathematics classroom
New research in mathematics education deals with the complexity of the mathematics’ classroom. The classroom teaching situation constitutes a pertinent unit of analysis for research into the ternary didactic relationship which binds teachers, students and mathematical knowledge. The classroom is considered as a complex didactic system, which offers the researcher an opportunity to gauge the boundaries of the freedom that is left with regard to choices about the knowledge to be taught and the ways of organizing the students’ learning, while giveing rise to the study of interrelations between three main elements of the teaching process the: mathematical content to be taught and learned, management of the various time dimensions, and activity of the teacher who prepares and manages the class, to the benefit of the students' knowledge and the teachers' own experience.
Beyond partial differential equations : On linear and Quasi-Linear abstract hyperbolic evolution equations
The present volume is self-contained and introduces to the treatment of linear and nonlinear (quasi-linear) abstract evolution equations by methods from the theory of strongly continuous semigroups.
Benefit/Cost-Driven Software Development : With Benefit Points and Size Points
This book presents a set of basic techniques for estimating the benefit of IT development projects and portfolios. It also offers methods for monitoring how much of that estimated benefit is being achieved during projects. Readers can then use these benefit estimates together with cost estimates to create a benefit/cost index to help them decide which functionalities to send into construction and in what order. This allows them to focus on constructing the functionality that offers the best value for money at an early stage.
Benchmarking, Temporal Distribution, and Reconciliation Methods for Time Series
This book discusses the statistical methods most often applied for such adjustments, ranging from ad hoc procedures to regression-based models. The latter are emphasized, because of their clarity, ease of application, and superior results. Each topic is illustrated with many real case examples. In order to facilitate understanding of their properties and limitations of the methods discussed, a real data example, the Canada Total Retail Trade Series, is followed throughout the book.This book brings together the scattered literature on these topics and presents them using a consistent notation and a unifying view.
Beginning Excel What-If Data Analysis tools : Getting started with goal seek, data tables, scenarios, and solver
Excels what-if data analysis tools let you experiment with your data to project future results. In turn, these predictions will lead to better decision making and unlock the mystery of many business analysis scenarios. For example, what-if data analysis tools will enable you to forecast how lowering the price per unitwhile increasing projected unit salesmight affect your profit margins. Beginning Excel What-If Data Analysis Tools explores the use of Goal Seek, Data Tables, Scenarios, and Solver to help you get insight on your data. This book is focused and to the point, and it provides tutorial treatment of what-if tools in a practical, hands-on manner.
Becoming an urban physics and math teacher : Infinite potential
What happens as beginning urban teachers transition through their first few years in the classroom? This book captures one teacher's journey through the first three years of teaching science and mathematics in a large urban district in the US. The authors focus on Ian's agency as a beginning teacher and explore his success in working with diverse students. Using critical ethnography combined with first-person narrative, they investigate Ian's teaching practices in four contexts: his student teaching experience, his work with students on a summer curriculum development project, his first year of teaching in a small, urban high school, and his second year of teaching in a large, comprehensive high school. In each field, the authors describe the structural changes Ian encounters and the ways in which he re-utilizes the practices he used successfully in previous fields.
Bayesian reliability
Bayesian Reliability presents modern methods and techniques for analyzing reliability data from a Bayesian perspective. The adoption and application of Bayesian methods in virtually all branches of science and engineering have significantly increased over the past few decades. This increase is largely due to advances in simulation-based computational tools for implementing Bayesian methods. The authors extensively use such tools throughout this book, focusing on assessing the reliability of components and systems with particular attention to hierarchical models and models incorporating explanatory variables. Such models include failure time regression models, accelerated testing models, and degradation models. The authors pay special attention to Bayesian goodness-of-fit testing, model validation, reliability test design, and assurance test planning. Throughout the book, the authors use Markov chain Monte Carlo (MCMC) algorithms for implementing Bayesian analyses--algorithms that make the Bayesian approach to reliability computationally feasible and conceptually straightforward.
Bayesian networks and Influence diagrams : A guide to construction and analysis
Probabilistic networks, also known as Bayesian networks and influence diagrams, have become one of the most promising technologies in the area of applied artificial intelligence, offering intuitive, efficient, and reliable methods for diagnosis, prediction, decision making, classification, troubleshooting, and data mining under uncertainty. Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. Intended primarily for practitioners, this book does not require sophisticated mathematical skills or deep understanding of the underlying theory and methods nor does it discuss alternative technologies for reasoning under uncertainty.
Bayesian core : A practical approach to computational Bayesian statistics
This Bayesian modeling book provides an operational methodology for conducting Bayesian inference, rather than focusing on its theoretical justifications. Special attention is paid to the derivation of prior distributions in each case and specific reference solutions are given for each of the models.
Bayesian computation with R : Introduces Bayesian modeling by use of computation using the R language
R's open source nature, free availability, and large number of contributor packages have made R the software of choice for many statisticians in education and industry. Bayesian Computation with R introduces Bayesian modeling by the use of computation using the R language.
Battery management systems : Accurate state-of-charge indication for battery-powered applications
Builds further on the contents of the first volume in the Philips Research Book Series, Battery Management Systems - Design by Modelling. Since the subject of battery SoC indication requires a number of disciplines, this book covers all important disciplines starting from (electro)chemistry to understand battery behaviour, via mathematics to enable modelling of the observed battery behaviour and measurement science to enable accurate measurement of battery variables and assessment of the overall accuracy, to electrical engineering to enable an efficient implementation of the developed SoC indication system. It will therefore serve as an important source of information for any person working in engineering and involved in battery management.
Basics of fluid mechanics and introduction to computational fluid dynamics
Brings together the theoretical basics of fluid dynamics with a systemaic overview of the appropriate numerical and computational methods for solving the problems presented in the book. Also, effective codes for a majority of the examples are included.
Basic Real Analysis
Basic Real Analysis and Advanced Real Analysis (available separately or together as a Set) systematically develop those concepts and tools in real analysis that are vital to every mathematician, whether pure or applied, aspiring or established. These works present a comprehensive treatment with a global view of the subject, emphasizing the connections between real analysis and other branches of mathematics.
Basic Probability Theory with Applications
This book presents elementary probability theory with interesting and well-chosen applications that illustrate the theory. An introductory chapter reviews the basic elements of differential calculus which are used in the material to follow. The theory is presented systematically, beginning with the main results in elementary probability theory. This is followed by material on random variables. Random vectors, including the all important central limit theorem, are treated next. The last three chapters concentrate on applications of this theory in the areas of reliability theory, basic queuing models, and time series. Examples are elegantly woven into the text and over 400 exercises reinforce the material and provide students with ample practice.
Basic principles and applications of probability theory
This introductory chapter discusses such notions as determinism, chaos and randomness, p- dictibility and unpredictibility, some initial approaches to formalizing r- domness and it surveys certain problems that can be solved by probability theory. This will perhaps give one an idea to what extent the theory can - swer questions arising in speci?c random occurrences and the character of the answers provided by the theory. 1. 1 The Nature of Randomness The phrase “by chance” has no single meaning in ordinary language. For instance, it may mean unpremeditated, nonobligatory, unexpected, and so on. Its opposite sense is simpler: “not by chance” signi?es obliged to or bound to (happen). In philosophy, necessity counteracts randomness. Necessity signi?es conforming to law – it can be expressed by an exact law. The basic laws of mechanics, physics and astronomy can be formulated in terms of precise quantitativerelationswhichmustholdwithironcladnecessity.
