The three-volume set LNCS 13042, LNCS 13043 and LNCS 13044 constitutes the refereed proceedings of the 19th International Conference on Theory of Cryptography, TCC 2021, held in Raleigh, NC, USA, in November 2021. The total of 66 full papers presented in this three-volume set was carefully reviewed and selected from 161 submissions. They cover topics on proof systems, attribute-based and functional encryption, obfuscation, key management and secure communication.

This book constitutes the thoroughly refereed post-conference proceedings of the 21st Japanese Conference on Discrete and Computational Geometry and Graphs, JCDCGGG 2018, held in Quezon City, Philippines, in September 2018. The total of 14 papers included in this volume was carefully reviewed and selected from 25 submissions. The papers feature advances made in the field of computational geometry and focus on emerging technologies, new methodology and applications, graph theory and dynamics.

This book constitutes the refereed proceedings of the 15th Symposium and Summer School on Service-Oriented Computing, SummerSOC 2021, held in September 2021. Due to the COVID-19 pandemic the conference was held online. The 9 full and 2 short papers were carefully reviewed and selected from 24 submissions. The papers are organized in topical secions on quantum computing; advanced application architecture; service-based applications.

Data storage has grown such that distributed storage over a number of systems is now commonplace. This has given rise to an increase in the complexity of ensuring data loss does not occur, particularly where failure is due to the failure of individual nodes within the storage system. Redundancy was the main tool to combat this, but with huge increases in data, minimization of the overhead associated with this technique caused major concern. In a large data center, a third concern arose, namely the need for efficient recovery from the failure of a single storage unit.In this monograph, the authors give a comprehensive overview of the role of differing types of codes in addressing the issues in large distributed storage systems. They introduce the reader to regenerative codes, locally recoverable codes and locally regenerative codes; the three main classes of codes used in such systems. They give an exhaustive overview of how these codes were created, their uses and the developments and improvements of the codes in the last decade.This in-depth review gives the reader an accessible and complete overview of the modern codes used in distributed storage systems today. It is a one-stop source for students, researchers and practitioners working on any such system.

Hamming distance and rank metric have long been used in coding theory. The sum-rank metric naturally extends these over fields. They have attracted significant attention for their applications in distributed storage systems, multishot network coding, streaming over erasure channels, and multi-antenna wireless communication. In this monograph, the authors provide a tutorial introduction to the theory and applications of sum-rank metric codes over finite fields. At the heart of the monograph is the construction of linearized Reed-Solomon codes, a general construction of maximum sum-rank distance (MSRD) codes with polynomial field sizes. These are specialized classical Reed-Solomon and Gabidulin code constructions in the Hamming and rank metrics, respectively and produce an efficient Welch-Berlekamp decoding algorithm. The authors proceed to develop applications of these codes in distributed storage systems, network coding, and multi-antenna communication are developed before surveying other families of codes in the sum-rank metric, including convolutional codes and subfield subcodes are described, and recent results in the general theory of codes in the sum-rank metric.This tutorial on the topic provides the reader with a comprehensive introduction to both the theory and practices of this important class of codes used in many storage and communication systems. It will be a valuable resource for students, researchers and practising engineers alike.

Common information measures the amount of matching variables in two or more information sources. It is ubiquitous in information theory and related areas such as theoretical computer science and discrete probability. However, because there are multiple notions of common information, a unified understanding of the deep interconnections between them is lacking. In this monograph the authors fill this gap by leveraging a small set of mathematical techniques that are applicable across seemingly disparate problems. The reader is introduced in Part I to the operational tasks and properties associated with the two main measures of common information, namely Wyner's and Gacs-Koerner-Witsenhausen's (GKW). In the subsequent two Parts, the authors take a deeper look at each of these. In Part II they discuss extensions to Wyner's common information from the perspective of distributed source simulation, including the Renyi common information. In Part III, GKW common information comes under the spotlight. Having laid the groundwork, the authors seamlessly transition to discussing their connections to various conjectures in information theory and discrete probability. This monograph provides students and researchers in Information Theory with a comprehensive resource for understanding common information and points the way forward to creating a unified set of techniques applicable over a wide range of problems.

This comprehensive guide, by pioneers in the field, brings together, for the first time, everything a new researcher, graduate student or industry practitioner needs to get started in molecular communication. Written with accessibility in mind, it requires little background knowledge, and provides a detailed introduction to the relevant aspects of biology and information theory, as well as coverage of practical systems. The authors start by describing biological nanomachines, the basics of biological molecular communication and the microorganisms that use it. They then proceed to engineered molecular communication and the molecular communication paradigm, with mathematical models of various types of molecular communication and a description of the information and communication theory of molecular communication. Finally, the practical aspects of designing molecular communication systems are presented, including a review of the key applications. Ideal for engineers and biologists looking to get up to speed on the current practice in this growing field.

This book is specially designed to refresh and elevate the level of understanding of the foundational background in probability and distributional theory required to be successful in a graduate-level statistics program. Advanced undergraduate students and introductory graduate students from a variety of quantitative backgrounds will benefit from the transitional bridge that this volume offers, from a more generalized study of undergraduate mathematics and statistics to the career-focused, applied education at the graduate level. In particular, it focuses on growing fields that will be of potential interest to future M.S. and Ph.D. students, as well as advanced undergraduates heading directly into the workplace: data analytics, statistics and biostatistics, and related areas.

This book constitutes the proceedings of the 17th Conference on Computability in Europe, CiE 2021, organized by the University of Ghent in July 2021. Due to COVID-19 pandemic the conference was held virtually. The 48 full papers presented in this volume were carefully reviewed and selected from 50 submissions. CiE promotes the development of computability-related science, ranging over mathematics, computer science and applications in various natural and engineering sciences, such as physics and biology, as well as related fields, such as philosophy and history of computing. CiE 2021 had as its motto Connecting with Computability, a clear acknowledgement of the connecting and interdisciplinary nature of the conference series which is all the more important in a time where people are more than ever disconnected from one another due to the COVID-19 pandemic.

The book is a concise, self-contained and fully updated introduction to automata theory - a fundamental topic of computer sciences and engineering. The material is presented in a rigorous yet convincing way and is supplied with a wealth of examples, exercises and down-to-the earth convincing explanatory notes. An ideal text to a spectrum of one-term courses in computer sciences, both at the senior undergraduate and graduate students.

This book constitutes the refereed proceedings of the Cryptographer's Track at the RSA Conference 2022, CT-RSA 2022, held in San Francisco, CA, USA, in February 2022.* The 24 full papers presented in this volume were carefully reviewed and selected from 87 submissions. CT-RSA is the track devoted to scientific papers on cryptography, public-key to symmetric-key cryptography and from crypto-graphic protocols to primitives and their implementation security. *The conference was held as a hybrid event.

Due to its longevity and enormous information density, DNA is an attractive medium for archival data storage. Natural DNA more than 700.000 years old has been recovered, and about 5 grams of DNA can in principle hold a Zetabyte of digital information, orders of magnitude more than what is achieved on conventional storage media. Thanks to rapid technological advances, DNA storage is becoming practically feasible, as demonstrated by a number of experimental storage systems, making it a promising solution for our society's increasing need of data storage. Nevertheless, all the systems suffer from having random noise introduced making the task of reliably storing and retrieving information in DNA challenging. This raises a natural information-theoretic question: how much information can be reliably stored on and reconstructed from millions of short noisy sequences? In this book the authors address this question by discussing the fundamental limits of storing information on DNA. Motivated by current technological constraints on DNA synthesis and sequencing, they propose a probabilistic channel model that captures three key distinctive aspects of the DNA storage systems: (1) the data is written onto many short DNA molecules that are stored in an unordered fashion; (2) the molecules are corrupted by noise and (3) the data is read by randomly sampling from the DNA pool. In building an information-theoretic foundation for the analysis of these channels, developing tools for achievability and converse arguments as they go, the authors introduce the reader to the fascinating and promising field of DNA storage. This book provides a concise and in-depth starting point for students, researchers and practitioners covering the history of the DNA Storage development, discusses the various systems available to date and focuses on the challenges posed in the current state of research in the field.

With the development of Big Data platforms for managing massive amount of data and wide availability of tools for processing these data, the biggest limitation is the lack of trained experts who are qualified to process and interpret the results. This textbook is intended for graduate students and experts using methods of cluster analysis and applications in various fields. Suitable for an introductory course on cluster analysis or data mining, with an in-depth mathematical treatment that includes discussions on different measures, primitives (points, lines, etc.) and optimization-based clustering methods, Cluster Analysis and Applications also includes coverage of deep learning based clustering methods. With clear explanations of ideas and precise definitions of concepts, accompanied by numerous examples and exercises together with Mathematica programs and modules, Cluster Analysis and Applications may be used by students and researchers in various disciplines, working in data analysis or data science.

This book proposes tools for analysis of multidimensional and metric data, by establishing a state-of-the-art of the existing solutions and developing new ones. It mainly focuses on visual exploration of these data by a human analyst, relying on a 2D or 3D scatter plot display obtained through Dimensionality Reduction. Performing diagnosis of an energy system requires identifying relations between observed monitoring variables and the associated internal state of the system. Dimensionality reduction, which allows to represent visually a multidimensional dataset, constitutes a promising tool to help domain experts to analyse these relations. This book reviews existing techniques for visual data exploration and dimensionality reduction such as tSNE and Isomap, and proposes new solutions to challenges in that field. In particular, it presents the new unsupervised technique ASKI and the supervised methods ClassNeRV and ClassJSE. Moreover, MING, a new approach for local map quality evaluation is also introduced. These methods are then applied to the representation of expert-designed fault indicators for smart-buildings, I-V curves for photovoltaic systems and acoustic signals for Li-ion batteries.

This book constitutes revised selected papers from the workshops of the 4th Asia-Pacific Web and Web-Age Information Management International Joint Conference on Web and Big Data, APWeb-WAIM 2020: The Third International Workshop on Knowledge Graph Management and Applications, KGMA 2020; The Second International Workshop on Semi-structured Big Data Management and Applications, SemiBDMA 2020, and The First International Workshop on Deep Learning in Large-scale Unstructured Data Analytics, DeepLUDA 2020, held in Tianjin, China, in September 2020. Due to the COVID-19 pandemic the conference was held online. The 13 papers were thoroughly reviewed and selected from the numerous submissions and present recent research on the theory, design, and implementation of data management systems.

The three-volume set LNCS 13042, LNCS 13043 and LNCS 13044 constitutes the refereed proceedings of the 19th International Conference on Theory of Cryptography, TCC 2021, held in Raleigh, NC, USA, in November 2021. The total of 66 full papers presented in this three-volume set was carefully reviewed and selected from 161 submissions. They cover topics on proof systems, attribute-based and functional encryption, obfuscation, key management and secure communication.

Proceedings of the 2019 International Conference on Information and Knowledge Engineering (IKE'19) held July 29th - August 1st, 2019 in Las Vegas, Nevada.

This book constitutes the refereed proceedings of the First International Workshop on Cyber-Physical Security for Critical Infrastructures Protection, CPS4CIP 2020, which was organized in conjunction with the European Symposium on Research in Computer Security, ESORICS 2020, and held online on September 2020.The 14 full papers presented in this volume were carefully reviewed and selected from 24 submissions. They were organized in topical sections named: security threat intelligence; data anomaly detection: predict and prevent; computer vision and dataset for security; security management and governance; and impact propagation and power traffic analysis. The book contains 6 chapters which are available open access under a CC-BY license.

Die Chancen, die Big Data und Digitalisierung bieten, bringen fur Unternehmen und ihre Funktionsbereiche weitreichende AEnderungen mit sich - so auch fur das Controlling. Die Autoren analysieren die aufgabenbezogenen Trends im Controllingumfeld und leiten die Anforderungen ab, die sich daraus fur das Kompetenzprofil des Controllers ergeben. Ausgewahlte Angebote zur Weiterbildung und Kompetenzerweiterung als klassisches Weiterbildungsangebot oder als Studiengang runden die Analyse ab.