There is a need for general theoretical principles describing/explaining effective design -- those which demonstrate "unity" and enhance comprehension and usability. Theories of cohesion from linguistics and of comprehension in psychology are likely sources of such general principles. Unfortunately, linguistic approaches to discourse unity have focused exclusively on semantic elements such as synonymy or anaphora, and have ignored other linguistic elements such as syntactic parallelism and phonological alliteration. They have also overlooked the non-linguistic elements -- visual factors such as typography or color, and auditory components such as pitch or duration. In addition, linguistic approaches have met with criticism because they have failed to explain the relationship between semantic cohesive elements and coherence. On the other hand, psychological approaches to discourse comprehension have considered the impact of a wider range of discourse elements -- typographical cuing of key terms to enhance comprehension -- but have failed to provide general theoretical explanations for such observations.
This volume uses Gestalt theory to provide general principles for predicting one aspect of coherence -- that of continuity -- across the entire range of discourse elements, and also to outline the relationship between cohesion and coherence. The theoretical core of this book argues that the cognitive principles that explain why humans "sense" unity in a succession of sounds (a whole musical piece) or in a configuration of visual shapes (a complete object) are the basis of principles which explain why we "sense" unity in oral, written, and electronically produced documents.

Winner of the Neumann Prize for the History of Mathematics.

In their second collaboration, biographers Jimmy Soni and Rob Goodman present the story of Claude Shannon—one of the foremost intellects of the twentieth century and the architect of the Information Age, whose insights stand behind every computer built, email sent, video streamed, and webpage loaded. Claude Shannon was a groundbreaking polymath, a brilliant tinkerer, and a digital pioneer. He constructed the first wearable computer, outfoxed Vegas casinos, and built juggling robots. He also wrote the seminal text of the digital revolution, which has been called “the Magna Carta of the Information Age.”

In this elegantly written, exhaustively researched biography, Soni and Goodman reveal Claude Shannon’s full story for the first time. With unique access to Shannon’s family and friends, A Mind at Play brings this singular innovator and always playful genius to life.

This book is written in honour of Professor Lars H. Zetterberg, who is the pioneer of information and coding theory in Sweden, and his direct and indirect influence on the evaluation in Sweden of these topics is quite considerable. The various contributions give overviews of different topics within the area of coding theory. Each covers a speciality where - in most cases - good overviews are not easily available. The five papers together provide a good and representative sample of Swedish research activities within the field of coding theory.

The challenges to humanity posed by the digital future, the first detailed examination of the unprecedented form of power called "surveillance capitalism," and the quest by powerful corporations to predict and control our behavior. In this masterwork of original thinking and research, Shoshana Zuboff provides startling insights into the phenomenon that she has named surveillance capitalism. The stakes could not be higher: a global architecture of behavior modification threatens human nature in the twenty-first century just as industrial capitalism disfigured the natural world in the twentieth. Zuboff vividly brings to life the consequences as surveillance capitalism advances from Silicon Valley into every economic sector. Vast wealth and power are accumulated in ominous new "behavioral futures markets," where predictions about our behavior are bought and sold, and the production of goods and services is subordinated to a new "means of behavioral modification." The threat has shifted from a totalitarian Big Brother state to a ubiquitous digital architecture: a "Big Other" operating in the interests of surveillance capital. Here is the crucible of an unprecedented form of power marked by extreme concentrations of knowledge and free from democratic oversight. Zuboff's comprehensive and moving analysis lays bare the threats to twenty-first century society: a controlled "hive" of total connection that seduces with promises of total certainty for maximum profit -- at the expense of democracy, freedom, and our human future. With little resistance from law or society, surveillance capitalism is on the verge of dominating the social order and shaping the digital future -- if we let it.

Networks surround us, from social networks to protein - protein interaction networks within the cells of our bodies. The theory of random graphs provides a necessary framework for understanding their structure and development. This text provides an accessible introduction to this rapidly expanding subject. It covers all the basic features of random graphs - component structure, matchings and Hamilton cycles, connectivity and chromatic number - before discussing models of real-world networks, including intersection graphs, preferential attachment graphs and small-world models. Based on the authors' own teaching experience, it can be used as a textbook for a one-semester course on random graphs and networks at advanced undergraduate or graduate level. The text includes numerous exercises, with a particular focus on developing students' skills in asymptotic analysis. More challenging problems are accompanied by hints or suggestions for further reading.

This largely self-contained book on the theory of quantum information focuses on precise mathematical formulations and proofs of fundamental facts that form the foundation of the subject. It is intended for graduate students and researchers in mathematics, computer science, and theoretical physics seeking to develop a thorough understanding of key results, proof techniques, and methodologies that are relevant to a wide range of research topics within the theory of quantum information and computation. The book is accessible to readers with an understanding of basic mathematics, including linear algebra, mathematical analysis, and probability theory. An introductory chapter summarizes these necessary mathematical prerequisites, and starting from this foundation, the book includes clear and complete proofs of all results it presents. Each subsequent chapter includes challenging exercises intended to help readers to develop their own skills for discovering proofs concerning the theory of quantum information.

Erst die elektronische Signatur wird dem E-Commerce zum Durchbruch verhelfen. Dieses Werk setzt sich mit den Akzeptanzproblemen auseinander, die beim Einsatz moderner Technologien fur die vertrauenswurdige elektronische Kommunikation entstehen. Rechtliche Fragen spielen hier eine wichtige Rolle, aber auch Moral und Kultur. Die Situation in diesen Bereichen wird im Buch diskutiert und daraus Handlungsempfehlungen fur den Verbraucher- und Datenschutz, die technische Ausgestaltung sowie den Umgang mit Risiken gegeben. Dies fuhrt zu einem visionaren Modell der Informationsgesellschaft.

Wahrend die Kryptologie Konzepte und Methoden aus der Komplexitatstheorie verwendet, ist die Forschung in der Komplexitatstheorie wiederum oft durch Fragen aus der Kryptologie motiviert. Der Band hebt die enge Verflechtung dieser beiden Gebiete hervor und fuhrt auf verstandlicher Weise in das faszinierende Gebiet der Kryptokomplexitat" ein. Das Buch enthalt zahlreiche Abbildungen und Ubungsaufgaben sowie ein ausfuhrliches Stichwort- und Literaturverzeichnis. Es eignet sich fur Studierende der Informatik, Mathematik oder Ingenieurswissenschaften."

This extraordinary three-volume work, written in an engaging and rigorous style by a world authority in the field, provides an accessible, comprehensive introduction to the full spectrum of mathematical and statistical techniques underpinning contemporary methods in data-driven learning and inference. This first volume, Foundations, introduces core topics in inference and learning, such as matrix theory, linear algebra, random variables, convex optimization and stochastic optimization, and prepares students for studying their practical application in later volumes. A consistent structure and pedagogy is employed throughout this volume to reinforce student understanding, with over 600 end-of-chapter problems (including solutions for instructors), 100 figures, 180 solved examples, datasets and downloadable Matlab code. Supported by sister volumes Inference and Learning, and unique in its scale and depth, this textbook sequence is ideal for early-career researchers and graduate students across many courses in signal processing, machine learning, statistical analysis, data science and inference.

"Beautiful Data" is both a history of big data and interactivity, and a sophisticated meditation on ideas about vision and cognition in the second half of the twentieth century. Contending that our forms of attention, observation, and truth are contingent and contested, Orit Halpern historicizes the ways that we are trained, and train ourselves, to observe and analyze the world. Tracing the postwar impact of cybernetics and the communication sciences on the social and human sciences, design, arts, and urban planning, she finds a radical shift in attitudes toward recording and displaying information. These changed attitudes produced what she calls communicative objectivity: new forms of observation, rationality, and economy based on the management and analysis of data. Halpern complicates assumptions about the value of data and visualization, arguing that changes in how we manage and train perception, and define reason and intelligence, are also transformations in governmentality. She also challenges the paradoxical belief that we are experiencing a crisis of attention caused by digital media, a crisis that can be resolved only through intensified media consumption.

Proofs play a central role in advanced mathematics and theoretical computer science, yet many students struggle the first time they take a course in which proofs play a significant role. This bestselling text's third edition helps students transition from solving problems to proving theorems by teaching them the techniques needed to read and write proofs. Featuring over 150 new exercises and a new chapter on number theory, this new edition introduces students to the world of advanced mathematics through the mastery of proofs. The book begins with the basic concepts of logic and set theory to familiarize students with the language of mathematics and how it is interpreted. These concepts are used as the basis for an analysis of techniques that can be used to build up complex proofs step by step, using detailed 'scratch work' sections to expose the machinery of proofs about numbers, sets, relations, and functions. Assuming no background beyond standard high school mathematics, this book will be useful to anyone interested in logic and proofs: computer scientists, philosophers, linguists, and, of course, mathematicians.

This is the first full-length book on the major theme of symmetry in graphs. Forming part of algebraic graph theory, this fast-growing field is concerned with the study of highly symmetric graphs, particularly vertex-transitive graphs, and other combinatorial structures, primarily by group-theoretic techniques. In practice the street goes both ways and these investigations shed new light on permutation groups and related algebraic structures. The book assumes a first course in graph theory and group theory but no specialized knowledge of the theory of permutation groups or vertex-transitive graphs. It begins with the basic material before introducing the field's major problems and most active research themes in order to motivate the detailed discussion of individual topics that follows. Featuring many examples and over 450 exercises, it is an essential introduction to the field for graduate students and a valuable addition to any algebraic graph theorist's bookshelf.

With its intuitive yet rigorous approach to machine learning, this text provides students with the fundamental knowledge and practical tools needed to conduct research and build data-driven products. The authors prioritize geometric intuition and algorithmic thinking, and include detail on all the essential mathematical prerequisites, to offer a fresh and accessible way to learn. Practical applications are emphasized, with examples from disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology. Over 300 color illustrations are included and have been meticulously designed to enable an intuitive grasp of technical concepts, and over 100 in-depth coding exercises (in Python) provide a real understanding of crucial machine learning algorithms. A suite of online resources including sample code, data sets, interactive lecture slides, and a solutions manual are provided online, making this an ideal text both for graduate courses on machine learning and for individual reference and self-study.

Algorithms play a central role both in the theory and in the practice of computing. The goal of the authors was to write a textbook that would not trivialize the subject but would still be readable by most students on their own. The book contains over 120 exercises. Some of them are drills; others make important points about the material covered in the text or introduce new algorithms not covered there. The book also provides programming projects. From the Table of Contents: Chapter 1: Basic knowledge of Mathematics, Relations, Recurrence relation and Solution techniques, Function and Growth of functions. Chapter 2: Different Sorting Techniques and their analysis. Chapter 3: Greedy approach, Dynamic Programming, Branch and Bound techniques, Backtracking and Problems, Amortized analysis, and Order Statics. Chapter 4: Graph algorithms, BFS, DFS, Spanning Tree, Flow Maximization Algorithms. Shortest Path Algorithms. Chapter 5: Binary search tree, Red black Tree, Binomial heap, B-Tree and Fibonacci Heap. Chapter 6: Approximation Algorithms, Sorting Networks, Matrix operations, Fast Fourier Transformation, Number theoretic Algorithm, Computational geometry Randomized Algorithms, String matching, NP-Hard, NP-Completeness, Cooks theorem.

Information is central to the evolution of biological complexity, a physical system relying on a continuous supply of energy. Biology provides superb examples of the consequent Darwinian selection of mechanisms for efficient energy utilisation. Genetic information, underpinned by the Watson-Crick base-pairing rules is largely encoded by DNA, a molecule uniquely adapted to its roles in information storage and utilisation.This volume addresses two fundamental questions. Firstly, what properties of the molecule have enabled it to become the predominant genetic material in the biological world today and secondly, to what extent have the informational properties of the molecule contributed to the expansion of biological diversity and the stability of ecosystems. The author argues that bringing these two seemingly unrelated topics together enables Schroedinger's What is Life?, published before the structure of DNA was known, to be revisited and his ideas examined in the context of our current biological understanding.

This book is a history of the future. It shows how our contemporary understanding of the Internet is shaped by visions of the future that were put together in the 1950s and 1960s. At the height of the Cold War, the Americans invented the only working model of communism in human history: the Internet. Yet, for all of its libertarian potential, the goal of this hi-tech project was geopolitical dominance: the ownership of time was control over the destiny of humanity. The potentially subversive theory of cybernetics was transformed into the military-friendly project of 'artificial intelligence'. Capitalist growth became the fastest route to the 'information society'. The rest of the world was expected to follow America's path into the networked future. Today, we're still being told that the Internet is creating the information society - and that America today is everywhere else tomorrow. Thankfully, at the beginning of the twenty-first century, the DIY ethic of the Internet shows that people can resist these authoritarian prophecies by shaping information technologies in their own interest. Ultimately, if we don't want the future to be what it used to be, we must invent our own, improved and truly revolutionary future.

This book provides readers the idea of systemically synthesizing various kind of knowledge, which needs to combine analytical thinking and synthetic thinking. Systems science is expected to help in solving contemporary complex problems, utilizing interdisciplinary knowledge effectively and combining analytical thinking and synthetic thinking efficiently. However, traditional systems science has been divided into two schools: one seeks a systematic procedure to give a correct objective answer; the other develops an emergent, systemic process so that the user can continue exploratory learning. It is not an exaggeration to say that analytical thinking and synthetic thinking have been developed independently, in different schools. This book integrates approaches developed in these two schools, using ideas in knowledge science that have been emerging recently under the influence of Eastern thinking. It emphasizes the importance of utilizing intuition in systems approaches, whereas other books usually try to solve problems rationally and objectively, rejecting subjectivity. This book never denies rationality and objectivity; however, complex problems of today do not always yield to complete analysis. The novelty of this present volume is that it takes in the ideas of synthetic thinking in knowledge science to develop systems science further. The chapter contributors, who are experienced systems scientists with a profound understanding of knowledge management, discuss knowledge synthesis from the Western and Eastern cultural perspectives. The book introduces a theory on systemic knowledge synthesis in an odd chapter and then presents an application of the theory in the next chapter in order to contribute to developing translational systems science.

Recommended by Bill Gates A thought-provoking and wide-ranging exploration of machine learning and the race to build computer intelligences as flexible as our own In the world's top research labs and universities, the race is on to invent the ultimate learning algorithm: one capable of discovering any knowledge from data, and doing anything we want, before we even ask. In The Master Algorithm, Pedro Domingos lifts the veil to give us a peek inside the learning machines that power Google, Amazon, and your smartphone. He assembles a blueprint for the future universal learner--the Master Algorithm--and discusses what it will mean for business, science, and society. If data-ism is today's philosophy, this book is its bible.

How is cultural identity accomplished interactively? What happens when different cultural identities contact one another? This book presents a series of papers, from classic essays to original expositions, which respond to these questions. The view of communication offered here -- rather than ignoring culture, or making it a variable in an equation -- is based on cultural patterns and situated communication practices, unveiling the multiplicity of factors involved in particular times and places.
The contributors to this unusual volume represent a wide range of fields. Their equally diverse offerings will serve to clarify cultural distinctiveness in some communication phenomena, and lay groundwork for the identification of cross-cultural generalities in others.

This book is a comprehensive introduction to the methods and algorithms of modern data analytics. It provides a sound mathematical basis, discusses advantages and drawbacks of different approaches, and enables the reader to design and implement data analytics solutions for real-world applications. This book has been used for more than ten years in the Data Mining course at the Technical University of Munich. Much of the content is based on the results of industrial research and development projects at Siemens.

Successfully communicating with people from another culture requires learning more than just their language. While fumbling a word or phrase may cause embarrassment, breaking the unspoken cultural rules that govern personal interactions can spell disaster for businesspeople, travelers, and indeed anyone who communicates across cultural boundaries. To help you avoid such damaging gaffes, Tracy Novinger has compiled this authoritative, practical guide for deciphering and following "the rules" that govern cultures, demonstrating how these rules apply to the communication issues that exist between the United States and Mexico.

Novinger begins by explaining how a major proportion of communication within a culture occurs nonverbally through behavior and manners, shared attitudes, common expectations, and so on. Then, using real-life examples and anecdotes, she pinpoints the commonly occurring obstacles to communication that can arise when cultures differ in their communication techniques. She shows how these obstacles come into play in contacts between the U.S. and Mexico and demonstrates that mastering the unspoken rules of Mexican culture is a key to cementing business and social relationships. Novinger concludes with nine effective, reliable principles for successfully communicating across cultures.

A real estate investment professional currently residing in Austin, Texas, Tracy Novinger writes from extensive research and her personal experiences of living and working in cultures as diverse as Aruba and Tahiti. She was born in the Caribbean, studied in Brazilian schools, speaks several languages, has traveled extensively, and has a master's degree in communications.