Basic Methods of Linear Functional Analysis

As the world becomes increasingly connected, it is also more exposed to a myriad of cyber threats. We need to use multiple types of tools and techniques to learn and understand the evolving threat landscape. Data is a common thread linking various types of devices and end users. Analyzing data across different segments of cybersecurity domains, particularly data generated during cyber-attacks, can help us understand threats better, prevent future cyber-attacks, and provide insights into the evolving cyber threat landscape. This book takes a data oriented approach to studying cyber threats, showing in depth how traditional methods such as anomaly detection can be extended using data analytics and also applies data analytics to non-traditional views of cybersecurity, such as multi domain analysis, time series and spatial data analysis, and human-centered cybersecurity.

In this commentary, Ruth Anne Reese offers a multi-disciplinary study of 1 Peter that builds on contemporary scholarship and research methods. She explores the relationship of the letter to the Old Testament, as reflected in the themes of exodus, exile, suffering, and glory. Integrating sociological analysis, she offers insights into the social situation of the letter's audience that have grown out of post-colonial and empire criticism. Reese also explores the themes of majority-minority relationships, non-retaliation, and ethical living. Her study reveals a more subversive character to 1 Peter than is often posited. Written in an accessible style, Reese's commentary provides overviews of important scholarly questions and points readers to a range of potential answers to those questions. It also features a 'Closer Look' section on a significant topic in each passage, as well as 'Bridging the Horizon' sections that connect the ancient context of 1 Peter with the contemporary world.

In this commentary, Ruth Anne Reese offers a multi-disciplinary study of 1 Peter that builds on contemporary scholarship and research methods. She explores the relationship of the letter to the Old Testament, as reflected in the themes of exodus, exile, suffering, and glory. Integrating sociological analysis, she offers insights into the social situation of the letter's audience that have grown out of post-colonial and empire criticism. Reese also explores the themes of majority-minority relationships, non-retaliation, and ethical living. Her study reveals a more subversive character to 1 Peter than is often posited. Written in an accessible style, Reese's commentary provides overviews of important scholarly questions and points readers to a range of potential answers to those questions. It also features a 'Closer Look' section on a significant topic in each passage, as well as 'Bridging the Horizon' sections that connect the ancient context of 1 Peter with the contemporary world.

This compact course is written for the mathematically literate reader who wants to learn to analyze data in a principled fashion. The language of mathematics enables clear exposition that can go quite deep, quite quickly, and naturally supports an axiomatic and inductive approach to data analysis. Starting with a good grounding in probability, the reader moves to statistical inference via topics of great practical importance – simulation and sampling, as well as experimental design and data collection – that are typically displaced from introductory accounts. The core of the book then covers both standard methods and such advanced topics as multiple testing, meta-analysis, and causal inference.

Fay and Brittain present statistical hypothesis testing and compatible confidence intervals, focusing on application and proper interpretation. The emphasis is on equipping applied statisticians with enough tools - and advice on choosing among them - to find reasonable methods for almost any problem and enough theory to tackle new problems by modifying existing methods. After covering the basic mathematical theory and scientific principles, tests and confidence intervals are developed for specific types of data. Essential methods for applications are covered, such as general procedures for creating tests (e.g., likelihood ratio, bootstrap, permutation, testing from models), adjustments for multiple testing, clustering, stratification, causality, censoring, missing data, group sequential tests, and non-inferiority tests. New methods developed by the authors are included throughout, such as melded confidence intervals for comparing two samples and confidence intervals associated with Wil

This compact course is written for the mathematically literate reader who wants to learn to analyze data in a principled fashion. The language of mathematics enables clear exposition that can go quite deep, quite quickly, and naturally supports an axiomatic and inductive approach to data analysis. Starting with a good grounding in probability, the reader moves to statistical inference via topics of great practical importance – simulation and sampling, as well as experimental design and data collection – that are typically displaced from introductory accounts. The core of the book then covers both standard methods and such advanced topics as multiple testing, meta-analysis, and causal inference.

Quasi-interpolation is one of the most useful and often applied methods for the approximation of functions and data in mathematics and applications. Its advantages are manifold: quasi-interpolants are able to approximate in any number of dimensions, they are efficient and relatively easy to formulate for scattered and meshed nodes and for any number of data. This book provides an introduction into the field for graduate students and researchers, outlining all the mathematical background and methods of implementation. The mathematical analysis of quasi-interpolation is given in three directions, namely on the basis (spline spaces, radial basis functions) from which the approximation is taken, on the form and computation of the quasi-interpolants (point evaluations, averages, least squares), and on the mathematical properties (existence, locality, convergence questions, precision). Learn which type of quasi-interpolation to use in different contexts and how to optimise its features to su

Tracing almost 200 years of history, Explaining Tort and Crime explains the development of tort law and criminal law in England compared with other legal systems. Referencing legal systems from around the globe, it uses innovative comparative and historical methods to identify patterns of legal development, to investigate the English law of fault doctrine across tort and crime, and to chart and explain three procedural interfaces: criminal powers to compensate, timing rules to control parallel actions, and convictions as evidence in later civil cases. Matthew Dyson draws on decades of research to offer an analysis of the field, examining patterns of legal development, visible as motifs in the law of many legal systems.

An updated edition of a widely used textbook, offering a clear and comprehensive presentation of mathematics for undergraduate economics students.This text offers a clear and comprehensive presentation of the mathematics required to tackle problems in economic analyses, providing not only straightforward exposition of mathematical methods for economics students at the intermediate and advanced undergraduate levels but also a large collection of problem sets. This updated and expanded fourth edition contains numerous worked examples drawn from a range of important areas, including economic theory, environmental economics, financial economics, public economics, industrial organization, and the history of economic thought. These help students develop modeling skills by showing how the same basic mathematical methods can be applied to a variety of interesting and important issues. The five parts of the text cover fundamentals, calculus, linear algebra, optimization, and dynamics. The onl

Differential Equations with Mathematica, Fifth Edition uses the fundamental concepts of the popular platform to solve (analytically, numerically, and/or graphically) differential equations of interest to students, instructors, and scientists. Mathematica's diversity makes it particularly well suited to performing calculations encountered when solving many ordinary and partial differential equations. In some cases, Mathematica's built-in functions can immediately solve a differential equation by providing an explicit, implicit, or numerical solution. In other cases, Mathematica can be used to perform the calculations encountered when solving a differential equation. Because one goal of elementary differential equations courses is to introduce students to basic methods and algorithms so that they gain proficiency in them, nearly every topic covered this book introduces basic commands, also including typical examples of their application. A study of differential equations relies on concep

Michelson's analysis of almost 150,000 divorce trials reveals routine and egregious violations of China's own laws upholding the freedom of divorce, gender equality, and the protection of women's physical security. Using 'big data' computational techniques to scrutinize cases covering 2009–2016 from all 252 basic-level courts in two Chinese provinces, Henan and Zhejiang, Michelson reveals that women have borne the brunt of a dramatic intensification since the mid-2000s of a decades-long practice of denying divorce requests. This book takes the reader upstream to the institutional sources of China's clampdown on divorce and downstream to its devastating and highly gendered human toll, showing how judges in an overburdened court system clear their oppressive dockets at the expense of women's lawful rights and interests. This book is a must-read for anyone interested in Chinese courts, judicial decision-making, family law, gender violence, and the limits and possibilities of the globaliza

An introduction to computational modeling for cognitive neuroscientists, covering both foundational work and recent developments. Cognitive neuroscientists need sophisticated conceptual tools to make sense of their field’s proliferation of novel theories, methods, and data. Computational modeling is such a tool, enabling researchers to turn theories into precise formulations. This book offers a mathematically gentle and theoretically unified introduction to modeling cognitive processes. Theoretical exercises of varying degrees of difficulty throughout help readers develop their modeling skills. After a general introduction to cognitive modeling and optimization, the book covers models of decision making; supervised learning algorithms, including Hebbian learning, delta rule, and backpropagation; the statistical model analysis methods of model parameter estimation and model evaluation; the three recent cognitive modeling approaches of reinforcement learning, unsupervised learning, and

Best practices for addressing the bias and inequality that may result from the automated collection, analysis, and distribution of large datasets.Human-centered data science is a new interdisciplinary field that draws from human-computer interaction, social science, statistics, and computational techniques. This book, written by founders of the field, introduces best practices for addressing the bias and inequality that may result from the automated collection, analysis, and distribution of very large datasets. It offers a brief and accessible overview of many common statistical and algorithmic data science techniques, explains human-centered approaches to data science problems, and presents practical guidelines and real-world case studies to help readers apply these methods. The authors explain how data scientists’ choices are involved at every stage of the data science workflow―and show how a human-centered approach can enhance each one, by making the process more transparent, aski

A detailed and up-to-date introduction to machine learning, presented through the unifying lens of probabilistic modeling and Bayesian decision theory.This book offers a detailed and up-to-date introduction to machine learning (including deep learning) through the unifying lens of probabilistic modeling and Bayesian decision theory. The book covers mathematical background (including linear algebra and optimization), basic supervised learning (including linear and logistic regression and deep neural networks), as well as more advanced topics (including transfer learning and unsupervised learning). End-of-chapter exercises allow students to apply what they have learned, and an appendix covers notation. Probabilistic Machine Learning grew out of the author’s 2012 book, Machine Learning: A Probabilistic Perspective. More than just a simple update, this is a completely new book that reflects the dramatic developments in the field since 2012, most notably deep learning. In addition, the ne

Bone and Soft Tissue Augmentation in Implantology addresses useful methods of bone grafting procedures in implant treatment based on current biologic principles and constitutes a unique reference in this field. The book describes, in over 760 pages and 2837 mostly color illustrations, the different possibilities available to augment the bone volume in width and height. The information presented includes not only the underlying scientific concepts of the different augmentation techniques with autogenous bone, but also the associated soft tissue management, from safe approaches to different possibilities for soft tissue augmentation and papilla reconstruction techniques. The book provides surgeons with a basic understanding of the biologic response to bone grafting procedures. Experienced implantologists will benefit from the in-depth background information, details of high-level surgical techniques, and scientific results, which will enable them to optimize their surgical procedures. Ea

This book analyses all relevant questions of State responsibility and attribution arising from the conduct of rebels and governments in the context of civil wars and rebellions aiming at the establishment of a new government or the creation of a new State. Based on a comprehensive analysis of both old and recent State practice, and case law, including investment awards, as well as the works of scholars and the International Law Commission, the book identifies ten basic rules which can be used by States and international tribunals. It explains the history, content and scope of application of the specific solutions adopted in Article 10 of the International Law Commission Articles on State responsibility to address particular problems. The book also critically revisits some of the solutions that have been put forward by tribunals and scholars, and examines a number of questions which have never been addressed by them before.

David Sandwell developed this advanced textbook over a period of nearly 30 years for his graduate course at Scripps Institution of Oceanography. The book augments the classic textbook Geodynamics by Don Turcotte and Jerry Schubert, presenting more complex and foundational mathematical methods and approaches to geodynamics. The main new tool developed in the book is the multi-dimensional Fourier transform for solving linear partial differential equations. The book comprises nineteen chapters, including: the latest global data sets; quantitative plate tectonics; plate driving forces associated with lithospheric heat transfer and subduction; the physics of the earthquake cycle; postglacial rebound; and six chapters on gravity field development and interpretation. Each chapter has a set of student exercises that make use of the higher-level mathematical and numerical methods developed in the book. Solutions to the exercises are available online for course instructors, on request.

This introductory overview explores the methods, models and interdisciplinary links of artificial economics, a new way of doing economics in which the interactions of artificial economic agents are computationally simulated to study their individual and group behavior patterns. Conceptually and intuitively, and with simple examples, Mercado addresses the differences between the basic assumptions and methods of artificial economics and those of mainstream economics. He goes on to explore various disciplines from which the concepts and methods of artificial economics originate; for example cognitive science, neuroscience, artificial intelligence, evolutionary science and complexity science. Introductory discussions on several controversial issues are offered, such as the application of the concepts of evolution and complexity in economics and the relationship between artificial intelligence and the philosophies of mind. This is one of the first books to fully address artificial economics

Foreign military intervention has had a profound impact on post-colonial African history and politics. Interventions have destabilized borderlands, overthrown governments, and taken a devastating toll on populations. Emizet F. Kisangani and Jeffrey Pickering advance a new theoretical framework and combine quantitative, qualitative, and historical methods to shed fresh light on these important but understudied events. Their detailed analysis brings understanding to supportive and hostile interventions and to interventions by former colonial states, non-colonial foreign actors, and African countries. Kisangani and Pickering also analyse military incursions into ungoverned territories and lands engulfed in civil war. Showcasing a variety of examples from the Second Congo War to the Ethiopian-Eritrean conflict, the book offers a rich and accessible examination of military intervention on the continent.

Foreign military intervention has had a profound impact on post-colonial African history and politics. Interventions have destabilized borderlands, overthrown governments, and taken a devastating toll on populations. Emizet F. Kisangani and Jeffrey Pickering advance a new theoretical framework and combine quantitative, qualitative, and historical methods to shed fresh light on these important but understudied events. Their detailed analysis brings understanding to supportive and hostile interventions and to interventions by former colonial states, non-colonial foreign actors, and African countries. Kisangani and Pickering also analyse military incursions into ungoverned territories and lands engulfed in civil war. Showcasing a variety of examples from the Second Congo War to the Ethiopian-Eritrean conflict, the book offers a rich and accessible examination of military intervention on the continent.

The Cambridge Companion to Literature and Psychoanalysis explains the link between literature and psychoanalysis for students, critics and teachers. It offers a twenty-first century resource for defining and analyzing the psychoanalytic dimensions of human creativity in contemporary society. Essays provide critical perspectives on selected canonical authors, such as William Shakespeare, Jane Austen, Virginia Woolf, Toni Morrison, and James Baldwin It also offers analysis of contemporary literature of social, sexual and political turmoil, as well as newer forms such as film, graphic narrative, and autofiction. Divided into five sections, each offering the reader different subject areas to explore, this volume shows how psychoanalytic approaches to literature can provide valuable methods of interpretation. It will be a key resource for students, teachers and researchers in the field of literature and psychoanalysis as well as literary theory.

The Cambridge Companion to Literature and Psychoanalysis explains the link between literature and psychoanalysis for students, critics and teachers. It offers a twenty-first century resource for defining and analyzing the psychoanalytic dimensions of human creativity in contemporary society. Essays provide critical perspectives on selected canonical authors, such as William Shakespeare, Jane Austen, Virginia Woolf, Toni Morrison, and James Baldwin It also offers analysis of contemporary literature of social, sexual and political turmoil, as well as newer forms such as film, graphic narrative, and autofiction. Divided into five sections, each offering the reader different subject areas to explore, this volume shows how psychoanalytic approaches to literature can provide valuable methods of interpretation. It will be a key resource for students, teachers and researchers in the field of literature and psychoanalysis as well as literary theory.

This monograph is the first to present the theory of global attractors of Hamiltonian partial differential equations. A particular focus is placed on the results obtained in the last three decades, with chapters on the global attraction to stationary states, to solitons, and to stationary orbits. The text includes many physically relevant examples and will be of interest to graduate students and researchers in both mathematics and physics. The proofs involve novel applications of methods of harmonic analysis, including Tauberian theorems, Titchmarsh's convolution theorem, and the theory of quasimeasures. As well as the underlying theory, the authors discuss the results of numerical simulations and formulate open problems to prompt further research.

The desire for humanity and the desire for security have co-existed as long as humans have been alive. As science has become increasingly sophisticated, so have the methods of self-defence by States. Nanotechnology is already changing warfare by increasing capabilities upon which armed forces are heavily reliant: more efficient energy storage, advanced photovoltaics, and improved military protective equipment to name a few of these developments. Some applications of nanomaterials by the military are both powerful and subtle, and have neurological and biological applications: 'devices that can infiltrate electronics and seize control at crucial moments, artificial “disease” agents that can rest harmlessly in victims' bodies until activated by an external signal'. The advance of the use or contemplation of use of these types of nanoscale applications by the military requires urgent analysis in light of existing international law, particularly in light of their potential effects on humans

A concise introduction to geophysical data processing - many of the techniques associated with the general field of time series analysis - for advanced students, researchers, and professionals. The textbook begins with calculus before transitioning to discrete time series via the sampling theorem, aliasing, use of complex sinusoids, development of the discrete Fourier transform from the Fourier series, and an overview of linear digital filter types and descriptions. Aimed at senior undergraduate and graduate students in geophysics, environmental science, and engineering with no previous background in linear algebra, probability, or statistics, this textbook draws scenarios and datasets from across the world of geophysics, and shows how data processing techniques can be applied to real-world problems using detailed examples, illustrations, and exercises (using MATLAB or similar computing environment). Online supplementary resources include datasets for students, and a solutions manual a

As digital convergence marks the transition from print to screen culture, translation plays an increasingly important role of in the production and dissemination of the news. The translation of information in the news media is a pervasive set of practices that affects the daily consumption of the news and a topic of relevance to scholars in several areas of the humanities and the social sciences. This book provides a wide-ranging and accessible introduction to research in news media translation practices, products and processes, illustrating and discussing historical, theoretical and descriptive perspectives. Inter- and multi-disciplinary research spans fields such as Translation Studies, Linguistics, Journalism and Media Studies, and includes approaches from Critical Discourse Analysis and narrative theory to Systemic Functional Linguistics and Corpus Linguistics. The book also offers first-hand analyses of news texts in English and Italian, approaching news translation from an ethnom

As digital convergence marks the transition from print to screen culture, translation plays an increasingly important role of in the production and dissemination of the news. The translation of information in the news media is a pervasive set of practices that affects the daily consumption of the news and a topic of relevance to scholars in several areas of the humanities and the social sciences. This book provides a wide-ranging and accessible introduction to research in news media translation practices, products and processes, illustrating and discussing historical, theoretical and descriptive perspectives. Inter- and multi-disciplinary research spans fields such as Translation Studies, Linguistics, Journalism and Media Studies, and includes approaches from Critical Discourse Analysis and narrative theory to Systemic Functional Linguistics and Corpus Linguistics. The book also offers first-hand analyses of news texts in English and Italian, approaching news translation from an ethnom

Designed as a textbook for a one or two-term introduction to mathematical statistics for students training to become data scientists, Foundations of Statistics for Data Scientists: With R and Python is an in-depth presentation of the topics in statistical science with which any data scientist should be familiar, including probability distributions, descriptive and inferential statistical methods, and linear modelling. The book assumes knowledge of basic calculus, so the presentation can focus on 'why it works' as well as 'how to do it.' Compared to traditional "mathematical statistics" textbooks, however, the book has less emphasis on probability theory and more emphasis on using software to implement statistical methods and to conduct simulations to illustrate key concepts. All statistical analyses in the book use R software, with an appendix showing the same analyses with Python.The book also introduces modern topics that do not normally appear in mathematical statistics texts but ar

Korean has proven to be an invaluable language to theoretical linguists, providing abundant examples of, and counterexamples to, key theoretical issues at the forefront of modern linguistic theories. Exploring the Korean language from both a syntactic and semantic perspective, this book provides an up-to-date linguistic analysis of its structure, combining Minimalist Syntax with accompanying compositional formal semantics. EunHee Lee's detailed chapters cover the core architecture and phenomena of Korean, looking at the lexical layer, the functional layer, nominal structure, movements and complex clauses. A broad range of empirically and theoretically important phenomena are discussed, enabling students and professional linguists alike to understand the workings of the language in current theoretical frameworks. The book also includes discussion questions, exercises and a list of further reading to solidify the theoretical concepts, stimulate thinking and develop the ability to analyze

This lucid, accessible introduction to supervised machine learning presents core concepts in a focused and logical way that is easy for beginners to follow. The author assumes basic calculus, linear algebra, probability and statistics but no prior exposure to machine learning. Coverage includes widely used traditional methods such as SVMs, boosted trees, HMMs, and LDAs, plus popular deep learning methods such as convolution neural nets, attention, transformers, and GANs. Organized in a coherent presentation framework that emphasizes the big picture, the text introduces each method clearly and concisely “from scratch” based on the fundamentals. All methods and algorithms are described by a clean and consistent style, with a minimum of unnecessary detail. Numerous case studies and concrete examples demonstrate how the methods can be applied in a variety of contexts.

This lucid, accessible introduction to supervised machine learning presents core concepts in a focused and logical way that is easy for beginners to follow. The author assumes basic calculus, linear algebra, probability and statistics but no prior exposure to machine learning. Coverage includes widely used traditional methods such as SVMs, boosted trees, HMMs, and LDAs, plus popular deep learning methods such as convolution neural nets, attention, transformers, and GANs. Organized in a coherent presentation framework that emphasizes the big picture, the text introduces each method clearly and concisely “from scratch” based on the fundamentals. All methods and algorithms are described by a clean and consistent style, with a minimum of unnecessary detail. Numerous case studies and concrete examples demonstrate how the methods can be applied in a variety of contexts.

Practical Techniques in Molecular Biotechnology intends to familiarise students with the basics of the well-known experiments of molecular biotechnology and related courses like chemical biotechnology and cell biology. The content of the book will be useful in strengthening the basic skills and help students to apply the concepts to real-world problems. This book emphasises important concepts like bioanalytical techniques, biochemical analysis of proteins, recombinant DNA, and protein technology etc. The text will help students to understand the theoretical aspects of the techniques and provide experience with hands-on techniques to demonstrate practical troubleshooting and data analysis. The text is supported with diagrams, data, summaries for the quick recap and appendices with useful protocols and calculation methods.

Second Language Research: Methodology and Design is a clear, comprehensive overview of cure issues in L2 research. Authored by well-known scholars in SLA and supported by a wealth of examples from actual studies and extensive pedagogical resources, this book first introduces students to the key topics and debates in L2 research. It then guides readers step-by step through the research process - from basic principles and collection methods through study design, and reporting - to the point of being able to conduct their own research from beginning to end.This book is an essential text for students and novice researchers of SLA, applied linguistics, and second and foreign language teaching. Key FeaturesA wealth of graphics, visuals and exercises in each chapter. "Time to think" and "Time to do" boxes within chaptersHelpful glossary and extensive author and subject indicesNew to This EditionSubstantially reorganized chaptersSignificantly expanded chapters on qualitative and mixed methodsS

Young, Munson and Okiishi's A Brief Introduction to Fluid Mechanics is designed to cover the standard topics in a basic fluid mechanics course in a streamlined manner that meets the learning needs of students better than the encyclopedic style of traditional texts. The text lucidly presents basic analysis techniques and addresses practical concerns and applications with a strong visual approach. This approach helps students connect the math and theory to the physical world and practical applications and apply these connections to solving problems. This adapted edition of the book comes with updates that clarify, enhance, and expand certain ideas and concepts. It includes new sections on Finite Control Volume Analysis, Compressible Flow, Equilibrium of Moving Fluids, Most Efficient Channel Section. The new examples and problems build upon the understanding of engineering applications of fluid mechanics and the edition has been completely updated to use SI units.

The book aids planners in answering the following crucial questions： “Who are they?”, “What do they do?”, “Where do these activities occur?”, "How human activities are connected?”, "What are the economic effects?". In addition to detailed explanations of the selected methods, the book provides a context (scenario analysis) for applying them in performance assessment and impact analysis.