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Summability Theory and Its Applications

Summability Theory and Its Applications explains various aspects of summability and demonstrates its applications in a rigorous and coherent manner. The content can readily serve as a reference or as a useful series of lecture notes on the subject. This substantially revised new edition includes brand new material across several chapters as well as several corrections including: the addition of the domain of Cesaro matrix C(m) of order m in the classical sequence spaces to Chapter 4; and introducing the domain of four-dimensional binomial matrix in the spaces of bounded convergent in the Pringsheim's sense both convergent in the Pringsheim's sense and bounded and regularly convergent double sequences in Chapter 7. Features Investigates different types of summable spaces and computes their dual Suitable for graduate students and researchers with a (special) interest in spaces of single and double sequences matrix transformations and domains of triangle matrices Can serve as a reference or as supplementary reading in a computational physics course or as a key text for special Analysis seminars.

GBP 130.00

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Anyone Can Code The Art and Science of Logical Creativity

Anyone Can Code: The Art and Science of Logical Creativity introduces computer programming as a way of problem-solving through logical thinking. It uses the notion of modularization as a central lens through which we can make sense of many software concepts. This book takes the reader through fundamental concepts in programming by illustrating them in three different and distinct languages: C/C++ Python and Javascript. Key features: Focuses on problem-solving and algorithmic thinking instead of programming functions syntax and libraries; Includes engaging examples including video games and visual effects; Provides exercises and reflective questions. This book gives beginner and intermediate learners a strong understanding of what they are doing so that they can do it better and with any other tool or language that they may end up using later. | Anyone Can Code The Art and Science of Logical Creativity

GBP 56.99

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Data Driven Science for Clinically Actionable Knowledge in Diseases

Data-driven science has become a major decision-making aid for the diagnosis and treatment of disease. Computational and visual analytics enables effective exploration and sense making of large and complex data through the deployment of appropriate data science methods meaningful visualisation and human-information interaction. This edited volume covers state-of-the-art theory method models design evaluation and applications in computational and visual analytics in desktop mobile and immersive environments for analysing biomedical and health data. The book is focused on data-driven integral analysis including computational methods and visual analytics practices and solutions for discovering actionable knowledge in support of clinical actions in real environments. By studying how data and visual analytics have been implemented into the healthcare domain the book demonstrates how analytics influences the domain through improving decision making specifying diagnostics selecting the best treatments and generating clinical certainty. | Data Driven Science for Clinically Actionable Knowledge in Diseases

GBP 44.99

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Clean Numerical Simulation

This book describes the basic principles of Clean Numerical Simulation (CNS) proposed by the author in 2009 as well as several of its applications. Unlike conventional algorithms CNS gives in a sufficiently long interval of time a convergent chaotic trajectory whose numerical noise is much lower than the true physical solution so that one can gain accurately. Thus CNS provides for the first time an ability to check statistics stability of chaos leading to a completely new concept of ultra-chaos which has both trajectory instability and statistics instability and thus is of a higher disorder. Notably it is impossible to repeat experimental results of ultra-chaos even in the statistical sense. However the reproducibility of physical experiments forms a cornerstone for modern science. Thus ultra-chaos reveals an incompleteness of the modern science paradigm. In addition it also reveals statistics stability as a precondition for use of conventional algorithms including direct numerical simulation (DNS). In Clean Numerical Simulation several conjectures and open problems are proposed including a modified fourth Clay millennium problem. Indeed CNS opens the door for us to enter the clean numerical world of chaos and turbulence.

GBP 74.99

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Principles of Scientific Methods

Principles of Scientific Methods focuses on the fundamental principles behind scientific methods. The book refers to science in a broad sense including natural science physics mathematics statistics social science political science and engineering science. A principle is often abstract and has broad applicability while a method is usually concrete and specific. The author uses many concrete examples to explain principles and presents analogies to connect different methods or problems to arrive at a general principle or a common notion. He mainly discusses a particular method to address the great idea behind the method not the method itself. The book shows how the principles are not only applicable to scientific research but also to our daily lives. The author explains how scientific methods are used for understanding how and why things happen making predictions and learning how to prevent mistakes and solve problems. Studying the principles of scientific methods is to think about thinking and to enlighten our understanding of scientific research. Scientific principles are the foundation of scientific methods. In this book you‘ll see how the principles reveal the big ideas behind our scientific discoveries and reflect the fundamental beliefs and wisdoms of scientists. The principles make the scientific methods coherent and constitute the source of creativity.

GBP 175.00

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Entropy Randomization in Machine Learning

Entropy Randomization in Machine Learning presents a new approach to machine learning—entropy randomization—to obtain optimal solutions under uncertainty (uncertain data and models of the objects under study). Randomized machine-learning procedures involve models with random parameters and maximum entropy estimates of the probability density functions of the model parameters under balance conditions with measured data. Optimality conditions are derived in the form of nonlinear equations with integral components. A new numerical random search method is developed for solving these equations in a probabilistic sense. Along with the theoretical foundations of randomized machine learning Entropy Randomization in Machine Learning considers several applications to binary classification modelling the dynamics of the Earth’s population predicting seasonal electric load fluctuations of power supply systems and forecasting the thermokarst lakes area in Western Siberia. Features • A systematic presentation of the randomized machine-learning problem: from data processing through structuring randomized models and algorithmic procedure to the solution of applications-relevant problems in different fields • Provides new numerical methods for random global optimization and computation of multidimensional integrals • A universal algorithm for randomized machine learning This book will appeal to undergraduates and postgraduates specializing in artificial intelligence and machine learning researchers and engineers involved in the development of applied machine learning systems and researchers of forecasting problems in various fields.

GBP 82.99

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Applications of Regression for Categorical Outcomes Using R

This book covers the main models within the GLM (i. e. logistic Poisson negative binomial ordinal and multinomial). For each model estimations interpretations model fit diagnostics and how to convey results graphically are provided. There is a focus on graphic displays of results as these are a core strength of using R for statistical analysis. Many in the social sciences are transitioning away from using Stata SPSS and SAS to using R and this book uses statistical models which are relevant to the social sciences. Social Science Applications of Regression for Categorical Outcomes Using R will be useful for graduate students in the social sciences who are looking to expand their statistical knowledge and for Quantitative social scientists due to it’s ability to act as a practitioners guide. Key Features: Applied- in the sense that we will provide code that others can easily adapt Flexible- R is basically just a fancy calculator. Our programs will enable users to derive quantities that they can use in their work Timely- many in the social sciences are currently transitioning to R or are learning it now. Our book will be a useful resource Versatile- we will write functions into an R package that can be applied to all of the regression models we will cover in the book Aesthetically pleasing- one advantage of R relative to other software packages is that graphs are fully customizable. We will leverage this feature to yield high-end graphical displays of results Affordability- R is free. R packages are free. There is no need to purchase site licenses or updates.

GBP 59.99

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Banach Limit and Applications

Banach Limit and Applications provides all the results in the area of Banach Limit its extensions generalizations and applications to various fields in one go (as far as possible). All the results in this field after Banach introduced this concept in 1932 were scattered till now. Sublinear functionals generating and dominating Banach Limit unique Banach Limit (almost convergence) invariant means and invariant limits absolute and strong almost convergence applications to ergodicity law of large numbers Fourier series uniform distribution of sequences uniform density core theorems and functional Banach limits are discussed in this book. The discovery of functional analysis such as the Hahn-Banach Theorem and the Banach-Steinhaus Theorem helped the researchers to develop a modern rich and unified theory of sequence spaces by encompassing classical summability theory via matrix transformations and the topics related to sequence spaces which arose from the concept of Banach limits all of which are presented in this book. The unique features of this book are as follows: All the results in this area which were scattered till now are in one place. The book is the first of its kind in the sense that there is no other competitive book. The contents of this monograph did not appear in any book form before. The audience of this book are the researchers in this area and Ph. D. and advanced master’s students. The book is suitable for one- or two-semester course work for Ph. D. students M. S. students in North America and Europe and M. Phil. and master’s students in India.

GBP 130.00

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Artificial Intelligence on Dark Matter and Dark Energy Reverse Engineering of the Big Bang

As we prod the cosmos at very large scales basic tenets of physics seem to crumble under the weight of contradicting evidence. This book helps mitigate the crisis. It resorts to artificial intelligence (AI) for answers and describes the outcome of this quest in terms of an ur-universe a quintessential compact multiply connected space that incorporates a fifth dimension to encode space-time as a latent manifold. In some ways AI is bolder than humans because the huge corpus of knowledge starting with the prodigious Standard Model (SM) of particle physics poses almost no burden to its conjecture-framing processes. Why not feed AI with the SM enriched by the troubling cosmological phenomenology on dark matter and dark energy and see where AI takes us vis-à-vis reconciling the conflicting data with the laws of physics? This is precisely the intellectual adventure described in this book and – to the best of our knowledge – in no other book on the shelf. As the reader will discover many AI conjectures and validations ultimately make a lot of sense even if their boldness does not feel altogether human yet. This book is written for a broad readership. Prerequisites are minimal but a background in college math/physics/computer science is desirable. This book does not merely describe what is known about dark matter and dark energy but also provides readers with intellectual tools to engage in a quest for the deepest cosmological mystery. | Artificial Intelligence on Dark Matter and Dark Energy Reverse Engineering of the Big Bang

GBP 89.99

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Grothendieck Construction of Bipermutative-Indexed Categories

The Grothendieck construction provides an explicit link between indexed categories and opfibrations. It is a fundamental concept in category theory and related fields with far-reaching applications. Bipermutative categories are categorifications of rings. They play a central role in algebraic K-theory and infinite loop space theory. This monograph is a detailed study of the Grothendieck construction over a bipermutative category in the context of categorically enriched multicategories with new and important applications to inverse K-theory and pseudo symmetric E∞-algebras. After carefully recalling preliminaries in enriched categories bipermutative categories and enriched multicategories we show that the Grothendieck construction over a small tight bipermutative category is a pseudo symmetric Cat-multifunctor and generally not a Cat-multifunctor in the symmetric sense. Pseudo symmetry of Cat-multifunctors is a new concept we introduce in this work. The following features make it accessible as a graduate text or reference for experts: Complete definitions and proofs Self-contained background. Parts of Chapters 1–3 7 9 and 10 contain background material from the research literature Extensive cross-references Connections between chapters. Each chapter has its own introduction discussing not only the topics of that chapter but also its connection with other chapters Open questions. Appendix A contains open questions that arise from the material in the text and are suitable for graduate students This book is suitable for graduate students and researchers with an interest in category theory algebraic K-theory homotopy theory and related fields. The presentation is thorough and self-contained with complete details and background material for non-expert readers. | Grothendieck Construction of Bipermutative-Indexed Categories

GBP 110.00

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Tidy Finance with R

This textbook shows how to bring theoretical concepts from finance and econometrics to the data. Focusing on coding and data analysis with R we show how to conduct research in empirical finance from scratch. We start by introducing the concepts of tidy data and coding principles using the tidyverse family of R packages. Code is provided to prepare common open-source and proprietary financial data sources (CRSP Compustat Mergent FISD TRACE) and organize them in a database. We reuse these data in all the subsequent chapters which we keep as self-contained as possible. The empirical applications range from key concepts of empirical asset pricing (beta estimation portfolio sorts performance analysis Fama-French factors) to modeling and machine learning applications (fixed effects estimation clustering standard errors difference-in-difference estimators ridge regression Lasso Elastic net random forests neural networks) and portfolio optimization techniques. Highlights 1. Self-contained chapters on the most important applications and methodologies in finance which can easily be used for the reader’s research or as a reference for courses on empirical finance. 2. Each chapter is reproducible in the sense that the reader can replicate every single figure table or number by simply copying and pasting the code we provide. 3. A full-fledged introduction to machine learning with tidymodels based on tidy principles to show how factor selection and option pricing can benefit from Machine Learning methods. 4. Chapter 2 on accessing and managing financial data shows how to retrieve and prepare the most important datasets financial economics: CRSP and Compustat. The chapter also contains detailed explanations of the most relevant data characteristics. 5. Each chapter provides exercises based on established lectures and classes which are designed to help students to dig deeper. The exercises can be used for self-studying or as a source of inspiration for teaching exercises. | Tidy Finance with R

GBP 59.99

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Abstract Algebra A First Course

When a student of mathematics studies abstract algebra he or she inevitably faces questions in the vein of What is abstract algebra or What makes it abstract? Algebra in its broadest sense describes a way of thinking about classes of sets equipped with binary operations. In high school algebra a student explores properties of operations (+ − × and ÷) on real numbers. Abstract algebra studies properties of operations without specifying what types of number or object we work with. Any theorem established in the abstract context holds not only for real numbers but for every possible algebraic structure that has operations with the stated properties. This textbook intends to serve as a first course in abstract algebra. The selection of topics serves both of the common trends in such a course: a balanced introduction to groups rings and fields; or a course that primarily emphasizes group theory. The writing style is student-centered conscientiously motivating definitions and offering many illustrative examples. Various sections or sometimes just examples or exercises introduce applications to geometry number theory cryptography and many other areas. This book offers a unique feature in the lists of projects at the end of each section. the author does not view projects as just something extra or cute but rather an opportunity for a student to work on and demonstrate their potential for open-ended investigation. The projects ideas come in two flavors: investigative or expository. The investigative projects briefly present a topic and posed open-ended questions that invite the student to explore the topic asking and to trying to answer their own questions. Expository projects invite the student to explore a topic with algebraic content or pertain to a particular mathematician’s work through responsible research. The exercises challenge the student to prove new results using the theorems presented in the text. The student then becomes an active participant in the development of the field. | Abstract Algebra A First Course

GBP 99.99

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