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 unique text helps make sense of big data in engineering applications using tools and techniques from signal processing. It presents fundamental signal processing theories and software implementations, reviews current research trends and challenges, and describes the techniques used for analysis, design and optimization. Readers will learn about key theoretical issues such as data modelling and representation, scalable and low-complexity information processing and optimization, tensor and sublinear algorithms, and deep learning and software architecture, and their application to a wide range of engineering scenarios. Applications discussed in detail include wireless networking, smart grid systems, and sensor networks and cloud computing. This is the ideal text for researchers and practising engineers wanting to solve practical problems involving large amounts of data, and for students looking to grasp the fundamentals of big data analytics.

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.

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.

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.

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.

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 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.

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.

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.

Connecting theory with practice, this systematic and rigorous introduction covers the fundamental principles, algorithms and applications of key mathematical models for high-dimensional data analysis. Comprehensive in its approach, it provides unified coverage of many different low-dimensional models and analytical techniques, including sparse and low-rank models, and both convex and non-convex formulations. Readers will learn how to develop efficient and scalable algorithms for solving real-world problems, supported by numerous examples and exercises throughout, and how to use the computational tools learnt in several application contexts. Applications presented include scientific imaging, communication, face recognition, 3D vision, and deep networks for classification. With code available online, this is an ideal textbook for senior and graduate students in computer science, data science, and electrical engineering, as well as for those taking courses on sparsity, low-dimensional structures, and high-dimensional data. Foreword by Emmanuel Candes.

Written by leading authorities in database and Web technologies, this book is essential reading for students and practitioners alike. The popularity of the Web and Internet commerce provides many extremely large datasets from which information can be gleaned by data mining. This book focuses on practical algorithms that have been used to solve key problems in data mining and can be applied successfully to even the largest datasets. It begins with a discussion of the MapReduce framework, an important tool for parallelizing algorithms automatically. The authors explain the tricks of locality-sensitive hashing and stream-processing algorithms for mining data that arrives too fast for exhaustive processing. Other chapters cover the PageRank idea and related tricks for organizing the Web, the problems of finding frequent itemsets, and clustering. This third edition includes new and extended coverage on decision trees, deep learning, and mining social-network graphs.

Networks are everywhere: networks of friends, transportation networks and the Web. Neurons in our brains and proteins within our bodies form networks that determine our intelligence and survival. This modern, accessible textbook introduces the basics of network science for a wide range of job sectors from management to marketing, from biology to engineering, and from neuroscience to the social sciences. Students will develop important, practical skills and learn to write code for using networks in their areas of interest - even as they are just learning to program with Python. Extensive sets of tutorials and homework problems provide plenty of hands-on practice and longer programming tutorials online further enhance students' programming skills. This intuitive and direct approach makes the book ideal for a first course, aimed at a wide audience without a strong background in mathematics or computing but with a desire to learn the fundamentals and applications of network science.

The future of the field of communication lies in the ability to produce a socially relevant scholarship, without which the field is unlikely to attract the best students, command significant societal resources, or make its greatest contributions to the world's store of knowledge. This volume presents a report of the first discipline-wide, nationally sponsored communication research conference in 20 years--the Tampa Conference on Applied Communication. As the next millennium approaches, the communication field will be challenged to take its place among the disciplines whose research makes a substantial contribution to the well-being of society. How the communication field should respond to that challenge was the focus of the conference and this volume. Crossing all disciplinary boundaries, "Applied Communication in the 21st Century" addresses issues of concern to all scholars in the communication field, regardless of their various subareas, and includes the recommendation of the conferees concerning issues and responsibilities of the field, research priorities, and graduate education.

Whilst a great deal of progress has been made in recent decades, concerns persist about the course of the social sciences. Progress in these disciplines is hard to assess and core scientific goals such as discovery, transparency, reproducibility, and cumulation remain frustratingly out of reach. Despite having technical acumen and an array tools at their disposal, today's social scientists may be only slightly better equipped to vanquish error and construct an edifice of truth than their forbears - who conducted analyses with slide rules and wrote up results with typewriters. This volume considers the challenges facing the social sciences, as well as possible solutions. In doing so, we adopt a systemic view of the subject matter. What are the rules and norms governing behavior in the social sciences? What kinds of research, and which sorts of researcher, succeed and fail under the current system? In what ways does this incentive structure serve, or subvert, the goal of scientific progress?

This unique introduction to the foundational concepts of cyber-physical systems (CPS) describes key design principles and emerging research trends in detail. Several interdisciplinary applications are covered, with a focus on the wide-area management of infrastructures including electric power systems, air transportation networks, and health care systems. Design, control and optimization of cyber-physical infrastructures are discussed, addressing security and privacy issues of networked CPS, presenting graph-theoretic and numerical approaches to CPS evaluation and monitoring, and providing readers with the knowledge needed to operate CPS in a reliable, efficient, and secure manner. Exercises are included. This is an ideal resource for researchers and graduate students in electrical engineering and computer science, as well as for practitioners using cyber-physical systems in aerospace and automotive engineering, medical technology, and large-scale infrastructure operations.

Understand the fundamentals of wireless and MIMO communication with this accessible and comprehensive text. Viewing the subject through an information theory lens, but also drawing on other perspectives, it provides a sound treatment of the key concepts underpinning contemporary wireless communication and MIMO, all the way to massive MIMO. Authoritative and insightful, it includes over 330 worked examples and 450 homework problems, with solutions and MATLAB code and data available online. Altogether, this is an excellent resource for instructors and graduate students, as well as an outstanding reference for researchers and practicing engineers.

Recent changes in information science have emerged as a result of challenges faced by the business, social, and scientific worlds, as well as continued progress in information and communication technologies. Organizations have begun to seek collaborative and joint efforts that allow them to better participate in challenging and competitive opportunities. This is illustrated by the creation of highly integrated supply chains, virtual libraries and organizations, and virtual laboratories. Systems Science and Collaborative Information Systems: Theories, Practices and New Research examines the impact of new information services on day-to-day activities from a range of contemporary technical and socio-cultural perspectives. This collection also creates a sound theoretical basis for information systems and new research opportunities in the field.

Management Information Systems (MIS) play a crucial role in an organization's operations, accounting, decision-making, project management, and competitive advantage. The Oxford Handbook of Management Information Systems takes a critical and interdisciplinary view of the increasing complexity of these systems within organizations, and the strategic, managerial, and ethical issues associated with the effective use of these technologies.
The book is organized into four parts:
- Part I: Background
- Part II: Theoretical and Methodological Perspectives in MIS
- Part III: Rethinking Theory in MIS Practice
- Part IV: Rethinking MIS Practice in a Broader Context
The Handbook provides an introductory background to the discipline and a methodological and philosophical framework for discussion of key topics, before exploring the issues associated with MIS in practice and considering the broader context and future agenda of research in light of such concerns as sustainability, ethics, and globalization.
Bringing together international scholars to focus on the theory and practice of MIS, this handbook provides a comprehensive resource for academics and research students in the fields of MIS, IS, Organizational Behaviour, and Management in general.

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.

Unifying information theory and digital communication through the language of lattice codes, this book provides a detailed overview for students, researchers and industry practitioners. It covers classical work by leading researchers in the field of lattice codes and complementary work on dithered quantization and infinite constellations, and then introduces the more recent results on 'algebraic binning' for side-information problems, and linear/lattice codes for networks. It shows how high dimensional lattice codes can close the gap to the optimal information theoretic solution, including the characterisation of error exponents. The solutions presented are based on lattice codes, and are therefore close to practical implementations, with many advanced setups and techniques, such as shaping, entropy-coding, side-information and multi-terminal systems. Moreover, some of the network setups shown demonstrate how lattice codes are potentially more efficient than traditional random-coding solutions, for instance when generalising the framework to Gaussian networks.

This book presents a unified approach to a rich and rapidly evolving research domain at the interface between statistical physics, theoretical computer science/discrete mathematics, and coding/information theory. It is accessible to graduate students and researchers without a specific training in any of these fields. The selected topics include spin glasses, error correcting codes, satisfiability, and are central to each field. The approach focuses on large random instances and adopts a common probabilistic formulation in terms of graphical models. It presents message passing algorithms like belief propagation and survey propagation, and their use in decoding and constraint satisfaction solving. It also explains analysis techniques like density evolution and the cavity method, and uses them to study phase transitions.

The latest edition of this classic is updated with new problem sets and material
The Second Edition of this fundamental textbook maintains the book's tradition of clear, thought-provoking instruction. Readers are provided once again with an instructive mix of mathematics, physics, statistics, and information theory.
All the essential topics in information theory are covered in detail, including entropy, data compression, channel capacity, rate distortion, network information theory, and hypothesis testing. The authors provide readers with a solid understanding of the underlying theory and applications. Problem sets and a telegraphic summary at the end of each chapter further assist readers. The historical notes that follow each chapter recap the main points.
The Second Edition features:
* Chapters reorganized to improve teaching
* 200 new problems
* New material on source coding, portfolio theory, and feedback capacity
* Updated references
Now current and enhanced, the Second Edition of Elements of Information Theory remains the ideal textbook for upper-level undergraduate and graduate courses in electrical engineering, statistics, and telecommunications.

An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.