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Digital Afterlife Death Matters in a Digital Age

Digital Afterlife Death Matters in a Digital Age

Despite the range of studies into grief and mourning in relation to the digital research to date largely focuses on the cultural practices and meanings that are played out in and through digital environments. Digital Afterlife brings together experts from diverse fields who share an interest in Digital Afterlife and the wide-ranging issues that relate to this. The book covers a variety of matters that have been neglected in other research texts for example: The legal ethical and philosophical conundrums of Digital Afterlife The ways digital media are currently being used to expand the possibilities of commemorating the dead and managing the grief of those left behind Our lives are shaped by and shape the creation of our Digital Afterlife as the digital has become a taken for granted aspect of human experience. This book will be of interest to undergraduates from computing theology business studies philosophy psychology sociology and education from all types of institutions. Secondary audiences include researchers and postgraduate researchers with an interest in the digital. At a practical level the cost of data storage and changing data storage systems mitigate the likelihood of our digital presence existing in perpetuity. Whether we create accidental or intentional digital memories this has psychological consequences for ourselves and for society. Essentially the foreverness of forever is in question. Maggi Savin-Baden is Professor of Higher Education Research at the University of Worcester. She has a strong publication record of over 50 research publications and 17 books. Victoria Mason-Robbie is a Chartered Psychologist and an experienced lecturer having worked in the Higher Education sector for over 15 years. Her current research focuses on evaluating web-based avatars pedagogical agents and virtual humans. | Digital Afterlife Death Matters in a Digital Age

GBP 44.99
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Evaluating What Works An Intuitive Guide to Intervention Research for Practitioners

Evaluating What Works An Intuitive Guide to Intervention Research for Practitioners

Those who work in allied health professions and education aim to make people’s lives better. Often however it is hard to know how effective this work has been: would change have occurred if there was no intervention? Is it possible we are doing more harm than good? To answer these questions and develop a body of knowledge about what works we need to evaluate interventions. Objective intervention research is vital to improve outcomes but this is a complex area where it is all too easy to misinterpret evidence. This book uses practical examples to increase awareness of the numerous sources of bias that can lead to mistaken conclusions when evaluating interventions. The focus is on quantitative research methods and exploration of the reasons why those both receiving and implementing intervention behave in the ways they do. Evaluating What Works: Intuitive Guide to Intervention Research for Practitioners illustrates how different research designs can overcome these issues and points the reader to sources with more in-depth information. This book is intended for those with little or no background in statistics to give them the confidence to approach statistics in published literature with a more critical eye recognise when more specialist advice is needed and give them the ability to communicate more effectively with statisticians. Key Features: Strong focus on quantitative research methods Complements more technical introductions to statistics Provides a good explanation of how quantitative studies are designed and what biases and pitfalls they can involve | Evaluating What Works An Intuitive Guide to Intervention Research for Practitioners

GBP 44.99
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Foundations of Quantitative Finance Book I: Measure Spaces and Measurable Functions

Foundations of Quantitative Finance Book I: Measure Spaces and Measurable Functions

This is the first in a set of 10 books written for professionals in quantitative finance. These books fill the gap between informal mathematical developments found in introductory materials and more advanced treatments that summarize without formally developing the important foundational results professionals need. Book I in the Foundations in Quantitative Finance Series develops topics in measure spaces and measurable functions and lays the foundation for subsequent volumes. Lebesgue and then Borel measure theory are developed on ℝ motivating the general extension theory of measure spaces that follows. This general theory is applied to finite product measure spaces Borel measures on ℝn and infinite dimensional product probability spaces. The overriding goal of these books is a complete and detailed development of the many mathematical theories and results one finds in popular resources in finance and quantitative finance. Each book is dedicated to a specific area of mathematics or probability theory with applications to finance that are relevant to the needs of professionals. Practitioners academic researchers and students will find these books valuable to their career development. All ten volumes are extensively self-referenced. The reader can enter the collection at any point or topic of interest and then work backward to identify and fill in needed details. This approach also works for a course or self-study on a given volume with earlier books used for reference. Advanced quantitative finance books typically develop materials with an eye to comprehensiveness in the given subject matter yet not with an eye toward efficiently curating and developing the theories needed for applications in quantitative finance. This book and series of volumes fill this need. | Foundations of Quantitative Finance Book I: Measure Spaces and Measurable Functions

GBP 68.99
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The Geometry of Musical Rhythm What Makes a Good Rhythm Good? Second Edition

Introduction to Self-Driving Vehicle Technology

Introduction to Self-Driving Vehicle Technology

This book aims to teach the core concepts that make Self-driving vehicles (SDVs) possible. It is aimed at people who want to get their teeth into self-driving vehicle technology by providing genuine technical insights where other books just skim the surface. The book tackles everything from sensors and perception to functional safety and cybersecurity. It also passes on some practical know-how and discusses concrete SDV applications along with a discussion of where this technology is heading. It will serve as a good starting point for software developers or professional engineers who are eager to pursue a career in this exciting field and want to learn more about the basics of SDV algorithms. Likewise academic researchers technology enthusiasts and journalists will also find the book useful. Key Features: Offers a comprehensive technological walk-through of what really matters in SDV development: from hardware software to functional safety and cybersecurity Written by an active practitioner with extensive experience in series development and research in the fields of Advanced Driver Assistance Systems (ADAS) and Autonomous Driving Covers theoretical fundamentals of state-of-the-art SLAM multi-sensor data fusion and other SDV algorithms. Includes practical information and hands-on material with Robot Operating System (ROS) and Open Source Car Control (OSCC). Provides an overview of the strategies trends and applications which companies are pursuing in this field at present as well as other technical insights from the industry. | Introduction to Self-Driving Vehicle Technology

GBP 48.99
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Understanding Artificial Intelligence

Mathematics and Statistics for the Quantitative Sciences

Mathematics and Statistics for the Quantitative Sciences

Mathematics and Statistics for the Quantitative Sciences was born from a radical reimagining of first-year mathematics. While calculus is often seen as the foundational mathematics required for any scientist this often leads to mathematics being seen as some ultimately useless hoop that needs to be jumped through in order to do what someone really wants to do. This sentiment is everywhere at every level of education. It even shows up in how people stereotype mathematics courses. What this book aims to do therefore is serve as a foundational text in everyday mathematics in a way that is both engaging and practically useful. The book seeks to teach the mathematics needed to start to answer fundamental questions like ‘why’ or ‘how’. Why do we only need to take census data once every few years? How do we determine the optimal dosing of a new pharmaceutical without killing people in the process? Or more generally what does it even mean to be average? Or what does it mean for two things to actually be different? These questions require a different way of thinking — a quantitative intuition that goes beyond rote memorization and equips readers to meet the quantitative challenges inherent in any applied discipline. Features Draws from a diverse range of fields to make the applications as inclusive as possible Would be ideal as a foundational mathematical and statistical textbook for any applied quantitative science course

GBP 74.99
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Mathematics in Cyber Research

Mathematics in Cyber Research

In the last decade both scholars and practitioners have sought novel ways to address the problem of cybersecurity. Innovative outcomes have included applications such as blockchain as well as creative methods for cyber forensics software development and intrusion prevention. Accompanying these technological advancements discussion on cyber matters at national and international levels has focused primarily on the topics of law policy and strategy. The objective of these efforts is typically to promote security by establishing agreements among stakeholders on regulatory activities. Varying levels of investment in cyberspace however comes with varying levels of risk; in some ways this can translate directly to the degree of emphasis for pushing substantial change. At the very foundation or root of cyberspace systems and processes are tenets and rules governed by principles in mathematics. Topics such as encrypting or decrypting file transmissions modeling networks performing data analysis quantifying uncertainty measuring risk and weighing decisions or adversarial courses of action represent a very small subset of activities highlighted by mathematics. To facilitate education and a greater awareness of the role of mathematics in cyber systems and processes a description of research in this area is needed. Mathematics in Cyber Research aims to familiarize educators and young researchers with the breadth of mathematics in cyber-related research. Each chapter introduces a mathematical sub-field describes relevant work in this field associated with the cyber domain provides methods and tools as well as details cyber research examples or case studies. Features One of the only books to bring together such a diverse and comprehensive range of topics within mathematics and apply them to cyber research. Suitable for college undergraduate students or educators that are either interested in learning about cyber-related mathematics or intend to perform research within the cyber domain. The book may also appeal to practitioners within the commercial or government industry sectors. Most national and international venues for collaboration and discussion on cyber matters have focused primarily on the topics of law policy strategy and technology. This book is among the first to address the underpinning mathematics.

GBP 160.00
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Text Analytics An Introduction to the Science and Applications of Unstructured Information Analysis

Engineering Production-Grade Shiny Apps

Engineering Production-Grade Shiny Apps

From the Reviews [This book] contains an excellent blend of both Shiny-specific topics … and practical advice from software development that fits in nicely with Shiny apps. You will find many nuggets of wisdom sprinkled throughout these chapters…. Eric Nantz Host of the R-Podcast and the Shiny Developer Series (from the Foreword) [This] book is a gradual and pleasant invitation to the production-ready shiny apps world. It …exposes a comprehensive and robust workflow powered by the {golem} package. [It] fills the not yet covered gap between shiny app development and deployment in such a thrilling way that it may be read in one sitting…. In the industry world where processes robustness is a key toward productivity this book will indubitably have a tremendous impact. David Granjon Sr. Expert Data Science Novartis Presented in full color Engineering Production-Grade Shiny Apps helps people build production-grade shiny applications by providing advice tools and a methodology to work on web applications with R. This book starts with an overview of the challenges which arise from any big web application project: organizing work thinking about the user interface the challenges of teamwork and the production environment. Then it moves to a step-by-step methodology that goes from the idea to the end application. Each part of this process will cover in detail a series of tools and methods to use while building production-ready shiny applications. Finally the book will end with a series of approaches and advice about optimizations for production. Features Focused on practical matters: This book does not cover Shiny concepts but practical tools and methodologies to use for production. Based on experience: This book is a formalization of several years of experience building Shiny applications. Original content: This book presents new methodologies and tooling not just a review of what already exists. Engineering Production-Grade Shiny Apps covers medium to advanced content about Shiny so it will help people that are already familiar with building apps with Shiny and who want to go one step further.

GBP 48.99
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Choreomata Performance and Performativity after AI

The Future of Work and Technology Global Trends Challenges and Policies with an Australian Perspective

The Effect An Introduction to Research Design and Causality

A First Course in Functional Analysis

Programming for Hybrid Multi/Manycore MPP Systems

Programming for Hybrid Multi/Manycore MPP Systems

Ask not what your compiler can do for you ask what you can do for your compiler. John Levesque Director of Cray’s Supercomputing Centers of ExcellenceThe next decade of computationally intense computing lies with more powerful multi/manycore nodes where processors share a large memory space. These nodes will be the building block for systems that range from a single node workstation up to systems approaching the exaflop regime. The node itself will consist of 10’s to 100’s of MIMD (multiple instruction multiple data) processing units with SIMD (single instruction multiple data) parallel instructions. Since a standard affordable memory architecture will not be able to supply the bandwidth required by these cores new memory organizations will be introduced. These new node architectures will represent a significant challenge to application developers. Programming for Hybrid Multi/Manycore MPP Systems attempts to briefly describe the current state-of-the-art in programming these systems and proposes an approach for developing a performance-portable application that can effectively utilize all of these systems from a single application. The book starts with a strategy for optimizing an application for multi/manycore architectures. It then looks at the three typical architectures covering their advantages and disadvantages. The next section of the book explores the other important component of the target—the compiler. The compiler will ultimately convert the input language to executable code on the target and the book explores how to make the compiler do what we want. The book then talks about gathering runtime statistics from running the application on the important problem sets previously discussed. How best to utilize available memory bandwidth and virtualization is covered next along with hybridization of a program. The last part of the book includes several major applications and examines future hardware advancements and how the application developer may prepare for those advancements.

GBP 44.99
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A First Course in Ergodic Theory

Abstract Algebra A First Course

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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Introduction to Real Analysis

Introduction to Real Analysis

This classic textbook has been used successfully by instructors and students for nearly three decades. This timely new edition offers minimal yet notable changes while retaining all the elements presentation and accessible exposition of previous editions. A list of updates is found in the Preface to this edition. This text is based on the author’s experience in teaching graduate courses and the minimal requirements for successful graduate study. The text is understandable to the typical student enrolled in the course taking into consideration the variations in abilities background and motivation. Chapters one through six have been written to be accessible to the average student w hile at the same time challenging the more talented student through the exercises. Chapters seven through ten assume the students have achieved some level of expertise in the subject. In these chapters the theorems examples and exercises require greater sophistication and mathematical maturity for full understanding. In addition to the standard topics the text includes topics that are not always included in comparable texts. Chapter 6 contains a section on the Riemann-Stieltjes integral and a proof of Lebesgue’s t heorem providing necessary and sufficient conditions for Riemann integrability. Chapter 7 also includes a section on square summable sequences and a brief introduction to normed linear spaces. C hapter 8 contains a proof of the Weierstrass approximation theorem using the method of aapproximate identities. The inclusion of Fourier series in the text allows the student to gain some exposure to this important subject. The final chapter includes a detailed treatment of Lebesgue measure and the Lebesgue integral using inner and outer measure. The exercises at the end of each section reinforce the concepts. Notes provide historical comments or discuss additional topics. | Introduction to Real Analysis

GBP 46.99
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Fundamentals of Causal Inference With R

Fundamentals of Causal Inference With R

Overall this textbook is a perfect guide for interested researchers and students who wish to understand the rationale and methods of causal inference. Each chapter provides an R implementation of the introduced causal concepts and models and concludes with appropriate exercises. An-Shun Tai & Sheng-Hsuan Lin in BiometricsOne of the primary motivations for clinical trials and observational studies of humans is to infer cause and effect. Disentangling causation from confounding is of utmost importance. Fundamentals of Causal Inference explains and relates different methods of confounding adjustment in terms of potential outcomes and graphical models including standardization difference-in-differences estimation the front-door method instrumental variables estimation and propensity score methods. It also covers effect-measure modification precision variables mediation analyses and time-dependent confounding. Several real data examples simulation studies and analyses using R motivate the methods throughout. The book assumes familiarity with basic statistics and probability regression and R and is suitable for seniors or graduate students in statistics biostatistics and data science as well as PhD students in a wide variety of other disciplines including epidemiology pharmacy the health sciences education and the social economic and behavioral sciences. Beginning with a brief history and a review of essential elements of probability and statistics a unique feature of the book is its focus on real and simulated datasets with all binary variables to reduce complex methods down to their fundamentals. Calculus is not required but a willingness to tackle mathematical notation difficult concepts and intricate logical arguments is essential. While many real data examples are included the book also features the Double What-If Study based on simulated data with known causal mechanisms in the belief that the methods are best understood in circumstances where they are known to either succeed or fail. Datasets R code and solutions to odd-numbered exercises are available on the book's website at www. routledge. com/9780367705053. Instructors can also find slides based on the book and a full solutions manual under 'Instructor Resources'. | Fundamentals of Causal Inference With R

GBP 56.99
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Risk Monetization Converting Threats and Opportunities into Impact on Project Value

Risk Monetization Converting Threats and Opportunities into Impact on Project Value

Risk Monetization: Converting Threats and Opportunities into Impact on Project Value addresses the organizational political cultural and technical issues related to implementing a successful risk assessment management and monetization process. Suitable for readers in any organization or area of expertise the book assumes no prior background in risk assessment management or monetization. With more than three decades of experience in risk-process implementation the author first explains the benefits of the risk-monetization process and how risk matters are generally not handled properly in contemporary organizations. He then introduces the terms and definitions essential to making risk monetization successful in a project. The text goes on to give examples of risk-monetization techniques applied in a variety of settings before discussing the typical risk situation for most projects and the shortcomings of conventional processes. It also describes how risk identification assessment management and monetization processes are set up in an ideal environment as well as in imperfect situations. The final chapter focuses on how investment decisions are made based on the monetization and ranking of risks. Enhancing your project’s value this book offers step-by-step practical guidance on identifying assessing managing and monetizing both threats and opportunities so that risk impedes the bottom line as little as possible. It shows you how to convert probable risks into positive impacts on the chance of success and/or profitability of any project. | Risk Monetization Converting Threats and Opportunities into Impact on Project Value

GBP 69.99
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Algorithms for Next-Generation Sequencing

Learn R As a Language

Learn R As a Language

Learning a computer language like R can be either frustrating fun or boring. Having fun requires challenges that wake up the learner’s curiosity but also provide an emotional reward on overcoming them. This book is designed so that it includes smaller and bigger challenges in what I call playgrounds in the hope that all readers will enjoy their path to R fluency. Fluency in the use of a language is a skill that is acquired through practice and exploration. Although rarely mentioned separately fluency in a computer programming language involves both writing and reading. The parallels between natural and computer languages are many but differences are also important. For students and professionals in the biological sciences humanities and many applied fields recognizing the parallels between R and natural languages should help them feel at home with R. The approach I use is similar to that of a travel guide encouraging exploration and describing the available alternatives and how to reach them. The intention is to guide the reader through the R landscape of 2020 and beyond. Features R as it is currently used Few prescriptive rules—mostly the author’s preferences together with alternatives Explanation of the R grammar emphasizing the R way of doing things Tutoring for programming in the small using scripts The grammar of graphics and the grammar of data described as grammars Examples of data exchange between R and the foreign world using common file formats Coaching for becoming an independent R user capable of both writing original code and solving future challenges What makes this book different from others: Tries to break the ice and help readers from all disciplines feel at home with R Does not make assumptions about what the reader will use R for Attempts to do only one thing well: guide readers into becoming fluent in the R language Pedro J. Aphalo is a PhD graduate from the University of Edinburgh and is currently a lecturer at the University of Helsinki. A plant biologist and agriculture scientist with a passion for data electronics computers and photography in addition to plants Dr. Aphalo has been a user of R for 25 years. He first organized an R course for MSc students 18 years ago and is the author of 13 R packages currently in CRAN. | Learn R As a Language

GBP 56.99
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