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.

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.

This book provides a comprehensive explanation of forward error correction, which is a vital part of communication systems. The book is written in such a way to make the subject easy and understandable for the reader. The book starts with a review of linear algebra to provide a basis for the text. The author then goes on to cover linear block codes, syndrome error correction, cyclic codes, Galois fields, BCH codes, Reed Solomon codes, and convolutional codes. Examples are provided throughout the text.

This book constitutes the refereed post-conference proceedings of two conferences: The 8th EAI International Conference on ArtsIT, Interactivity and Game Creation (ArtsIT 2019), and the 4th EAI International Conference on Design, Learning, and Innovation (DLI 2019). Both conferences were hosed in Aalborg, Denmark, and took place November 6-8, 2019. The 61 revised full papers presented were carefully selected from 98 submissions. The papers represent a forum for the dissemination of cutting-edge research results in the area of arts, design and technology, including open related topics like interactivity and game creation.

This three volume set (CCIS 1237-1239) constitutes the proceedings of the 18th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2020, in June 2020. The conference was scheduled to take place in Lisbon, Portugal, at University of Lisbon, but due to COVID-19 pandemic it was held virtually. The 173 papers were carefully reviewed and selected from 213 submissions. The papers are organized in topical sections: homage to Enrique Ruspini; invited talks; foundations and mathematics; decision making, preferences and votes; optimization and uncertainty; games; real world applications; knowledge processing and creation; machine learning I; machine learning II; XAI; image processing; temporal data processing; text analysis and processing; fuzzy interval analysis; theoretical and applied aspects of imprecise probabilities; similarities in artificial intelligence; belief function theory and its applications; aggregation: theory and practice; aggregation: pre-aggregation functions and other generalizations of monotonicity; aggregation: aggregation of different data structures; fuzzy methods in data mining and knowledge discovery; computational intelligence for logistics and transportation problems; fuzzy implication functions; soft methods in statistics and data analysis; image understanding and explainable AI; fuzzy and generalized quantifier theory; mathematical methods towards dealing with uncertainty in applied sciences; statistical image processing and analysis, with applications in neuroimaging; interval uncertainty; discrete models and computational intelligence; current techniques to model, process and describe time series; mathematical fuzzy logic and graded reasoning models; formal concept analysis, rough sets, general operators and related topics; computational intelligence methods in information modelling, representation and processing.

This book focuses on current practices in scientific and technical communication, historical aspects, and characteristics and biblio graphic control of various forms of scientific and technical literature. It integrates the inventory approach for scientific and technical communication.

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 first half of the book provides an introduction to general topology, with ample space given to exercises and carefully selected applications. The second half of the text includes topics in asymmetric topology, a field motivated by applications in computer science. Recurring themes include the interactions of topology with order theory and mathematics designed to model loss-of-resolution situations.

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.

Situated at the intersection of current debates regarding meaning and representation, this text casts doubt on the seeming innocence of the activity of communication. Using poststructuralist literary theory and philosophy, Chang argues that modern communication theories fail to provide an adequate explanation for how communication is possible. Through a detailed examination of the basis of the idea of communication - with its semantic core of "commonality" or the transcendence of difference - Chang argues against the tendency of theorists to value understanding over misunderstanding, clarity over ambiguity, order over disorder. To this end the author revisits the thought of Derrida and considers deconstruction in general. Specifically, he uses the critique of the phenomenological tradition emerging from poststructuralism to clarify the commitments and assumptions inherent in models of communication.

This book is written for anyone who is interested in how a field of research evolves and the fundamental role of understanding uncertainties involved in different levels of analysis, ranging from macroscopic views to meso- and microscopic ones. We introduce a series of computational and visual analytic techniques, from research areas such as text mining, deep learning, information visualization and science mapping, such that readers can apply these tools to the study of a subject matter of their choice. In addition, we set the diverse set of methods in an integrative context, that draws upon insights from philosophical, sociological, and evolutionary theories of what drives the advances of science, such that the readers of the book can guide their own research with their enriched theoretical foundations. Scientific knowledge is complex. A subject matter is typically built on its own set of concepts, theories, methodologies and findings, discovered by generations of researchers and practitioners. Scientific knowledge, as known to the scientific community as a whole, experiences constant changes. Some changes are long-lasting, whereas others may be short lived. How can we keep abreast of the state of the art as science advances? How can we effectively and precisely convey the status of the current science to the general public as well as scientists across different disciplines? The study of scientific knowledge in general has been overwhelmingly focused on scientific knowledge per se. In contrast, the status of scientific knowledge at various levels of granularity has been largely overlooked. This book aims to highlight the role of uncertainties, in developing a better understanding of the status of scientific knowledge at a particular time, and how its status evolves over the course of the development of research. Furthermore, we demonstrate how the knowledge of the types of uncertainties associated with scientific claims serves as an integral and critical part of our domain expertise.

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 second volume, Inference, builds on the foundational topics established in volume I to introduce students to techniques for inferring unknown variables and quantities, including Bayesian inference, Monte Carlo Markov Chain methods, maximum-likelihood estimation, hidden Markov models, Bayesian networks, and reinforcement learning. A consistent structure and pedagogy is employed throughout this volume to reinforce student understanding, with over 350 end-of-chapter problems (including solutions for instructors), 180 solved examples, almost 200 figures, datasets and downloadable Matlab code. Supported by sister volumes Foundations 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.

"Library and Information Science Trends and Research: Europe", co-edited by Professor Amanda Spink and Dr. Jannica Heinstrom provides an understanding of the new directions in library and information science/management, education and research in Europe. The volume focuses on new research directions within the field but will also discuss curriculum changes due to the rapidly developing information world. Europe has developed substantially both socially and economically in the last ten years with a growing population and economy. The field of library and information science/management has also grown in educational and research developments as information increasingly has become a part of people's everyday social and life processes. This book is directly relevant to information scientists, information professionals and librarians, social scientists and people interested in understanding more about the trends and research in library and information science/management in the European region. Undergraduate and graduate students, academics, educators, and information professionals interested in library and information science will find this book of particular benefit.

1. Lossless Coding.- 2.Universal Coding on Finite Alphabets.- 3.Universal Coding on Infinite Alphabets.- 4.Model Order Estimation.- Notation.- Index.

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 final volume, Learning, builds on the foundational topics established in volume I to provide a thorough introduction to learning methods, addressing techniques such as least-squares methods, regularization, online learning, kernel methods, feedforward and recurrent neural networks, meta-learning, and adversarial attacks. A consistent structure and pedagogy is employed throughout this volume to reinforce student understanding, with over 350 end-of-chapter problems (including complete solutions for instructors), 280 figures, 100 solved examples, datasets and downloadable Matlab code. Supported by sister volumes Foundations and Inference, 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, data and inference.

New Research in Information Behaviour, co-edited by Professor Amanda Spink and Dr. Jannica Heinstrom provides an understanding of the new directions, leading edge theories and models in information behaviour. Information behaviour is conceptualized as complex human information related processes that are embedded within an individual's everyday social and life processes. The book presents chapters by a range of scholars who show new research directions that often challenge the established views and paradigms of information behaviour studies. Beginning with an evolutionary framework, the book builds our understanding of information behaviours over various epochs of human existence from the Palaeolithic Era and within pre-literate societies, to contemporary behaviours by 21st century humans. Drawing upon social and psychological science theories the book presents a more integrated and holistic approach understanding of information behaviours. This book is directly relevant to information scientists, information professionals and librarians, social and evolutionary psychologists, social scientists and people interested in understanding more about their own information behaviours.

This book gives a detailed survey of the main results on bent functions over finite fields, presents a systematic overview of their generalizations, variations and applications, considers open problems in classification and systematization of bent functions, and discusses proofs of several results. This book uniquely provides a necessary comprehensive coverage of bent functions.It serves as a useful reference for researchers in discrete mathematics, coding and cryptography. Students and professors in mathematics and computer science will also find the content valuable, especially those interested in mathematical foundations of cryptography. It can be used as a supplementary text for university courses on discrete mathematics, Boolean functions, or cryptography, and is appropriate for both basic classes for under-graduate students and advanced courses for specialists in cryptography and mathematics.

This volume collects contributions written by different experts in honor of Prof. Jaime Munoz Masque. It covers a wide variety of research topics, from differential geometry to algebra, but particularly focuses on the geometric formulation of variational calculus; geometric mechanics and field theories; symmetries and conservation laws of differential equations, and pseudo-Riemannian geometry of homogeneous spaces. It also discusses algebraic applications to cryptography and number theory. It offers state-of-the-art contributions in the context of current research trends. The final result is a challenging panoramic view of connecting problems that initially appear distant.

A new class of provably capacity achieving error-correction codes, polar codes are suitable for many problems, such as lossless and lossy source coding, problems with side information, multiple access channel, etc. The first comprehensive book on the implementation of decoders for polar codes, the authors take a tutorial approach to explain the practical decoder implementation challenges and trade-offs in either software or hardware. They also demonstrate new trade-offs in latency, throughput, and complexity in software implementations for high-performance computing and GPGPUs, and hardware implementations using custom processing elements, full-custom application-specific integrated circuits (ASICs), and field-programmable-gate arrays (FPGAs). Presenting a good overview of this research area and future directions, High-Speed Decoders for Polar Codes is perfect for any researcher or SDR practitioner looking into implementing efficient decoders for polar codes, as well as students and professors in a modern error correction class. As polar codes have been accepted to protect the control channel in the next-generation mobile communication standard (5G) developed by the 3GPP, the audience includes engineers who will have to implement decoders for such codes and hardware engineers designing the backbone of communication networks.

This book presents methods to improve information security for protected communication. It combines and applies interdisciplinary scientific engineering concepts, including cryptography, chaos theory, nonlinear and singular optics, radio-electronics and self-changing artificial systems. It also introduces additional ways to improve information security using optical vortices as information carriers and self-controlled nonlinearity, with nonlinearity playing a key "evolving" role. The proposed solutions allow the universal phenomenon of deterministic chaos to be discussed in the context of information security problems on the basis of examples of both electronic and optical systems. Further, the book presents the vortex detector and communication systems and describes mathematical models of the chaos oscillator as a coder in the synchronous chaotic communication and appropriate decoders, demonstrating their efficiency both analytically and experimentally. Lastly it discusses the cryptologic features of analyzed systems and suggests a series of new structures for confident communication.

This book provides a systematic and comparative description of the vast number of research issues related to the quality of data and information. It does so by delivering a sound, integrated and comprehensive overview of the state of the art and future development of data and information quality in databases and information systems. To this end, it presents an extensive description of the techniques that constitute the core of data and information quality research, including record linkage (also called object identification), data integration, error localization and correction, and examines the related techniques in a comprehensive and original methodological framework. Quality dimension definitions and adopted models are also analyzed in detail, and differences between the proposed solutions are highlighted and discussed. Furthermore, while systematically describing data and information quality as an autonomous research area, paradigms and influences deriving from other areas, such as probability theory, statistical data analysis, data mining, knowledge representation, and machine learning are also included. Last not least, the book also highlights very practical solutions, such as methodologies, benchmarks for the most effective techniques, case studies, and examples. The book has been written primarily for researchers in the fields of databases and information management or in natural sciences who are interested in investigating properties of data and information that have an impact on the quality of experiments, processes and on real life. The material presented is also sufficiently self-contained for masters or PhD-level courses, and it covers all the fundamentals and topics without the need for other textbooks. Data and information system administrators and practitioners, who deal with systems exposed to data-quality issues and as a result need a systematization of the field and practical methods in the area, will also benefit from the combination of concrete practical approaches with sound theoretical formalisms.

Universal codes efficiently compress sequences generated by stationary and ergodic sources with unknown statistics, and they were originally designed for lossless data compression. In the meantime, it was realized that they can be used for solving important problems of prediction and statistical analysis of time series, and this book describes recent results in this area. The first chapter introduces and describes the application of universal codes to prediction and the statistical analysis of time series; the second chapter describes applications of selected statistical methods to cryptography, including attacks on block ciphers; and the third chapter describes a homogeneity test used to determine authorship of literary texts. The book will be useful for researchers and advanced students in information theory, mathematical statistics, time-series analysis, and cryptography. It is assumed that the reader has some grounding in statistics and in information theory.

This book focuses on how to apply network coding at different layers in wireless networks - including MAC, routing, and TCP - with special focus on cognitive radio networks. It discusses how to select parameters in network coding (e.g., coding field, number of packets involved, redundant information ration) in order to be suitable for the varying wireless environments. The author explores how to deploy network coding in MAC to improve network performance and examine joint network coding with opportunistic routing to improve the successful rate of routing. In regards to TCP and network coding, the author considers transport layer protocol working with network coding to overcome the transmission error rate, particularly with how to use the ACK feedback of TCP to enhance the efficiency of network coding. The book pertains to researchers and postgraduate students, especially whose interests are in opportunistic routing and TCP in cognitive radio networks.

This book focuses on the different representations and cryptographic properties of Booleans functions, presents constructions of Boolean functions with some good cryptographic properties. More specifically, Walsh spectrum description of the traditional cryptographic properties of Boolean functions, including linear structure, propagation criterion, nonlinearity, and correlation immunity are presented. Constructions of symmetric Boolean functions and of Boolean permutations with good cryptographic properties are specifically studied. This book is not meant to be comprehensive, but with its own focus on some original research of the authors in the past. To be self content, some basic concepts and properties are introduced. This book can serve as a reference for cryptographic algorithm designers, particularly the designers of stream ciphers and of block ciphers, and for academics with interest in the cryptographic properties of Boolean functions.

This book provides a comprehensive introduction to advanced topics in the computational and algorithmic aspects of number theory, focusing on applications in cryptography. Readers will learn to develop fast algorithms, including quantum algorithms, to solve various classic and modern number theoretic problems. Key problems include prime number generation, primality testing, integer factorization, discrete logarithms, elliptic curve arithmetic, conjecture and numerical verification. The author discusses quantum algorithms for solving the Integer Factorization Problem (IFP), the Discrete Logarithm Problem (DLP), and the Elliptic Curve Discrete Logarithm Problem (ECDLP) and for attacking IFP, DLP and ECDLP based cryptographic systems. Chapters also cover various other quantum algorithms for Pell's equation, principal ideal, unit group, class group, Gauss sums, prime counting function, Riemann's hypothesis and the BSD conjecture. Quantum Computational Number Theory is self-contained and intended to be used either as a graduate text in computing, communications and mathematics, or as a basic reference in the related fields. Number theorists, cryptographers and professionals working in quantum computing, cryptography and network security will find this book a valuable asset.