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This book constitutes the refereed proceedings of the 4th International Symposium on Mobile Internet Security, MobiSec 2019, held in Taichung, Taiwan, in October 2019.The 13 revised full papers presented were carefully reviewed and selected from 44 submissions. The papers are organized in the topical sections: mobile internet security; mobile application and security; vehicular network security; deep learning applications.

This book constitutes the refereed proceedings of the International Workshop on Altmetrics for Research Outputs Measurements and Scholarly Information Management, AROSIM 2018, held in Singapore, in January 2018. The 7 revised full papers presented together with two keynote papers and one introduction paper were carefully reviewed and selected from 20 submissions. The workshop will investigate how social media based metrics along with traditional and non-traditional metrics can advance the state-of-the-art in measuring research outputs.

This book constitutes the thoroughly refereed post-conference proceedings of the International Conference for Smart Health, ICSH 2015, held in Phoenix, AZ, USA, in November 2015. The 33 papers presented together were carefully reviewed and selected from 43 submissions. The conference focused on topics and issues including medical monitoring and information extraction, clinical and medical data mining, health data analysis and management, big data and smart health, and healthcare intelligent systems and clinical practice.

This book constitutes the proceedings of the 11th International Conference on Advances in Swarm Intelligence, ICSI 2020, held in July 2020 in Belgrade, Serbia. Due to the COVID-19 pandemic the conference was held virtually. The 63 papers included in this volume were carefully reviewed and selected from 127 submissions. The papers are organized in 12 cohesive topical sections as follows: Swarm intelligence and nature-inspired computing; swarm-based computing algorithms for optimization; particle swarm optimization; ant colony optimization; brain storm optimization algorithm; bacterial foraging optimization; genetic algorithm and evolutionary computation; multi-objective optimization; machine learning; data mining; multi-agent system and robotic swarm, and other applications.

This book constitutes the refereed proceedings of the 25th International Conference on Applications of Natural Language to Information Systems, NLDB 2020, held in Saarbrücken, Germany, in June 2020.• The 15 full papers and 10 short papers were carefully reviewed and selected from 68 submissions. The papers are organized in the following topical sections: semantic analysis; question answering and answer generation; classification; sentiment analysis; personality, affect and emotion; retrieval, conversational agents and multimodal analysis. •The conference was held virtually due to the COVID-19 pandemic.

This book constitutes the refereed proceedings of the 12th International Conference on Reversible Computation, RC 2020, held in Oslo, Norway, in July 2020. The 17 full papers included in this volume were carefully reviewed and selected from 22 submissions. The papers are organized in the following topical sections: theory and foundation; programming languages; circuit synthesis; evaluation of circuit synthesis; and applications and implementations.

This book constitutes the proceedings of the 18th Russian Conference on Artificial Intelligence, RCAI 2020, held in Moscow, Russia, in October 2020. The 27 full papers and 8 short papers presented in this volume were carefully reviewed and selected from 140 submissions. The conference deals with a wide range of topics, including data mining and knowledge discovery, text mining, reasoning, decisionmaking, natural language processing, vision, intelligent robotics, multi-agent systems,machine learning, AI in applied systems, and ontology engineering.

This book constitutes the proceedings of the 21st International Conference on Information Security, ISC 2018, held in Guildford, UK, in September 2018. The 26 full papers presented in this volume were carefully reviewed and selected from 59 submissions. The book also includes one invited talk in full-paper length. The papers were organized in topical sections named: software security; symmetric ciphers and cryptanalysis; data privacy and anonymization; outsourcing and assisted computing; advanced encryption; privacy-preserving applications; advanced signatures; and network security.

This open access book constitutes the proceedings of the 7th International Conference on Principles of Security and Trust, POST 2018, which took place in Thessaloniki, Greece, in April 2018, held as part of the European Joint Conference on Theory and Practice of Software, ETAPS 2018. The 13 papers presented in this volume were carefully reviewed and selected from 45 submissions. The papers are organized in topical sections named: information flow and non-intereference; leakage, information flow, and protocols; smart contracts and privacy; firewalls and attack-defense trees.

This book is Open Access under a CC BY licence. The LNCS 10805 and 10806 proceedings set constitutes the proceedings of the 24th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2018, which took place in Thessaloniki, Greece, in April 2018, held as part of the European Joint Conference on Theory and Practice of Software, ETAPS 2018. The total of 43 full and 11 short papers presented in these volumes was carefully reviewed and selected from 154submissions. The papers are organized in topical sections as follows: Part I: theorem proving; SAT and SMT I; deductive verification; software verification and optimization; model checking; and machine learning. Part II: concurrent and distributed systems; SAT and SMT II; security and reactive systems; static and dynamic program analysis; hybrid and stochastic systems; temporal logic and mu-calculus; 7th Competition on Software Verification – SV-COMP.

This book constitutes the proceedings of the 36th International Conference on Advanced Information Systems Engineering, CAiSE 2024, which was held in Limassol, Cyprus, during June 3-7, 2024. The 36 full papers included in these proceedings were carefully reviewed and selected from 180 submissions. They were organized in topical sections as follows: Process alignment, comparison and discovery; process discovery, monitoring and correction; graphs and graph networks; process modelling and management; prediction, monitoring and planning; data preparation, sharing, and architecture; requirements; process and decision mining; event and process discovery; session trust, security and risk; social aspects and LLMs; model-driven engineering and quantum workflows.

This book constitutes the refereed proceedings of the 34th International Conference on Advanced Information Systems Engineering, CAiSE 2022, which was held in Leuven, Belgium, during June 6-10, 2022.The 31 full papers included in these proceedings were selected from 203 submissions. They were organized in topical sections as follows: Process mining; sustainable and explainable applications; tools and methods to support research and design; process modeling; natural language processing techniques in IS engineering; process monitoring and simulation; graph and network models; model analysis and comprehension; recommender systems; conceptual models, metamodels and taxonomies; and services engineering and digitalization.

This book constitutes the proceedings of the 13th International Conference on Verification and Evaluation of Computer and Communication Systems ( VECoS 2019), held in Porto, Portugal, in October 2019. The 7 full papers in this volume, presented together with two invited talks, were carefully reviewed and selected from 13 submissions. The aim of the VECoS conference is to bring together researchers and practitioners in the areas of verification, control, performance, and dependability evaluation in order to discuss state of the art and challenges in modern computer and communication systems in which functional and extra-functional properties are strongly interrelated. Thus, the main motivation for VECoS is to encourage the cross-fertilization between various formal verification and evaluation approaches, methods and techniques, and especially those developed for concurrent and distributed hardware/software systems.

This book explains how all persons with Western European ancestry are related through a Unifying Ancestry. The author presents the knowledge metrics needed to derive the best representation for a Unifying Ancestry. The book uses example lineages to historically notable persons including relationships to U.S. Presidents, royal families, actors, and singers in order to demonstrate these points. This third edition is based upon expanded data, applying the algorithms to validate the Unifying Ancestry to a 348,844-person Research Genealogy. The author successfully demonstrates that a Unifying Ancestry with 38,533 persons is sufficient to identify familial relationships between Western Europeans.

Technical debt is an often-overlooked problem that the software industry needs to take more seriously. All organizations are impacted by it, most wish that they had less of it, but need help in understanding the nature of the beast. This book aims to clear up any misconceptions and show you how to implement a sound technical debt management program to suit your company's needs. You'll learn the greatest challenge in solving the technical debt dilemma is not to find solutions to it, but rather to find solutions to the human and organizational issues that lead to that debt. For example, convincing senior stakeholders of the importance of addressing technical debt, getting stakeholders to acknowledge how their actions lead to unintentional debt, and enabling teams to prioritize technical debt over short-term goals. Therefore, this book is divided into three parts: defining technical debt, understanding technical debt, and tackling technical debt. It begins by explaining why technical debt should not be considered a technical problem, but rather a problem of how trade-off decisions are made. You'll then examine how making decisions using the affect heuristic, more commonly known as a “gut feeling,” can lead to unnecessary technical debt, followed by some techniques for combating your vulnerability to this trap. Reducing your organization's level of technical debt is not easy. Taming Your Dragon will show you how to implement a technical debt management program. What You Will Learn Review a new paradigm based on technical debt being a combination of trade-off problems and system problems Understand the many ways that technical debt adversely affects an organization's ability to deliver IT change Create an effective process for addressing technical debt See why analogies are important Who This Book Is For Software teams supporting DevOps, managers, and other business stakeholders looking to implement a technical debt management program.

This book contains contributions presented at the 13th International Conference on Complex Networks (CompleNet), April 19–22, 2022. CompleNet is an international conference on complex networks that brings together researchers and practitioners from diverse disciplines—from sociology, biology, physics, and computer science—who share a passion to better understand the interdependencies within and across systems. CompleNet is a venue to discuss ideas and findings about all types of networks, from biological to technological and to informational and social. It is this interdisciplinary nature of complex networks that CompleNet aims to explore and celebrate.

This book illustrates how to achieve effective dimension reduction and data clustering. The authors explain how to accomplish this by utilizing the advanced dynamic graph learning technique in the era of big data. The book begins by providing background on dynamic graph learning. The authors discuss why it has attracted considerable research attention in recent years and has become well recognized as an advanced technique. After covering the key topics related to dynamic graph learning, the book discusses the recent advancements in the area. The authors then explain how these techniques can be practically applied for several purposes, including feature selection, feature projection, and data clustering.

The study of what can be computed by a team of autonomous mobile robots, originally started in robotics and AI, has become increasingly popular in theoretical computer science (especially in distributed computing), where it is now an integral part of the investigations on computability by mobile entities. The robots are identical computational entities located and able to move in a spatial universe; they operate without explicit communication and are usually unable to remember the past; they are extremely simple, with limited resources, and individually quite weak. However, collectively the robots are capable of performing complex tasks, and form a system with desirable fault-tolerant and self-stabilizing properties. The research has been concerned with the computational aspects of such systems. In particular, the focus has been on the minimal capabilities that the robots should have in order to solve a problem. This book focuses on the recent algorithmic results in the field of distributed computing by oblivious mobile robots (unable to remember the past). After introducing the computational model with its nuances, we focus on basic coordination problems: pattern formation, gathering, scattering, leader election, as well as on dynamic tasks such as flocking. For each of these problems, we provide a snapshot of the state of the art, reviewing the existing algorithmic results. In doing so, we outline solution techniques, and we analyze the impact of the different assumptions on the robots'computability power. Table of Contents: Introduction / Computational Models / Gathering and Convergence / Pattern Formation / Scatterings and Coverings / Flocking / Other Directions

While the classic model checking problem is to decide whether a finite system satisfies a specification, the goal of parameterized model checking is to decide, given finite systems ����(n) parameterized by n ∈ ℕ, whether, for all n ∈ ℕ, the system ����(n) satisfies a specification. In this book we consider the important case of ����(n) being a concurrent system, where the number of replicated processes depends on the parameter n but each process is independent of n. Examples are cache coherence protocols, networks of finite-state agents, and systems that solve mutual exclusion or scheduling problems. Further examples are abstractions of systems, where the processes of the original systems actually depend on the parameter. The literature in this area has studied a wealth of computational models based on a variety of synchronization and communication primitives, including token passing, broadcast, and guarded transitions. Often, different terminology is used in the literature, and results are based on implicit assumptions. In this book, we introduce a computational model that unites the central synchronization and communication primitives of many models, and unveils hidden assumptions from the literature. We survey existing decidability and undecidability results, and give a systematic view of the basic problems in this exciting research area.

Providing a shared memory abstraction in distributed systems is a powerful tool that can simplify the design and implementation of software systems for networked platforms. This enables the system designers to work with abstract readable and writable objects without the need to deal with the complexity and dynamism of the underlying platform. The key property of shared memory implementations is the consistency guarantee that it provides under concurrent access to the shared objects. The most intuitive memory consistency model is atomicity because of its equivalence with a memory system where accesses occur serially, one at a time. Emulations of shared atomic memory in distributed systems is an active area of research and development. The problem proves to be challenging, and especially so in distributed message passing settings with unreliable components, as is often the case in networked systems. We present several approaches to implementing shared memory services with the help of replication on top of message-passing distributed platforms subject to a variety of perturbations in the computing medium.

This book contains contributions presented at the 12th International Conference on Complex Networks (CompleNet), 24-26 May 2021. CompleNet is an international conference on complex networks that brings together researchers and practitioners from diverse disciplines—from sociology, biology, physics, and computer science—who share a passion to better understand the interdependencies within and across systems. CompleNet is a venue to discuss ideas and findings about all types networks, from biological, to technological, to informational and social. It is this interdisciplinary nature of complex networks that CompleNet aims to explore and celebrate.

This textbook describes the hands-on application of data science techniques to solve problems in manufacturing and the Industrial Internet of Things (IIoT). Monitoring and managing operational performance is a crucial activity for industrial and business organisations. The emergence of low-cost, accessible computing and storage, through Industrial Digital Technologies (IDT) and Industry 4.0, has generated considerable interest in innovative approaches to doing more with data. Data science, predictive analytics, machine learning, artificial intelligence and general approaches to modelling, simulating and visualising industrial systems have often been considered topics only for research labs and academic departments.This textbook debunks the mystique around applied data science and shows readers, using tutorial-style explanations and real-life case studies, how practitioners can develop their own understanding of performance to achieve tangible business improvements. All exercises can be completed with commonly available tools, many of which are free to install and use.Readers will learn how to use tools to investigate, diagnose, propose and implement analytics solutions that will provide explainable results to deliver digital transformation.

Want to use the power of R sooner rather than later? Don't have time to plow through wordy texts and online manuals? Use this book for quick, simple code to get your projects up and running. It includes code and examples applicable to many disciplines. Written in everyday language with a minimum of complexity, each chapter provides the building blocks you need to fit R's astounding capabilities to your analytics, reporting, and visualization needs. CRAN Recipes recognizes how needless jargon and complexity get in your way. Busy professionals need simple examples and intuitive descriptions; side trips and meandering philosophical discussions are left for other books. Here R scripts are condensed, to the extent possible, to copy-paste-run format. Chapters and examples are structured to purpose rather than particular functions (e.g., “dirty data cleanup” rather than the R package name “janitor”). Everyday language eliminatesthe need to know functions/packages in advance. What You Will LearnCarry out input/output; visualizations; data munging; manipulations at the group level; and quick data explorationHandle forecasting (multivariate, time series, logistic regression, Facebook's Prophet, and others)Use text analytics; sampling; financial analysis; and advanced pattern matching (regex)Manipulate data using DPLYR: filter, sort, summarize, add new fields to datasets, and apply powerful IF functionsCreate combinations or subsets of files using joinsWrite efficient code using pipes to eliminate intermediate steps (MAGRITTR) Work with string/character manipulation of all types (STRINGR)Discover counts, patterns, and how to locate whole wordsDo wild-card matching, extraction, and invert-matchWork with dates using LUBRIDATEFix dirty data; attractive formatting; bad habits to avoid Who This Book Is For Programmers/data scientists with at least some prior exposure to R.

Mikhail Zhilkin, a data scientist who has worked on projects ranging from Candy Crush games to Premier League football players'physical performance, shares his strong views on some of the best and, more importantly, worst practices in data analytics and business intelligence. Why data science is hard, what pitfalls analysts and decision-makers fall into, and what everyone involved can do to give themselves a fighting chance—the book examines these and other questions with the skepticism of someone who has seen the sausage being made. Honest and direct, full of examples from real life, Data Science Without Makeup: A Guidebook for End-Users, Analysts and Managers will be of great interest to people who aspire to work with data, people who already work with data, and people who work with people who work with data—from students to professional researchers and from early-career to seasoned professionals.Mikhail Zhilkin is a data scientist at Arsenal FC. He has previously worked on the popular Candy Crush mobile games and in sports betting.

Semantische Technologien haben mit der Entwicklung von datenbasierten Systemen wie Neuronale Netze, Deep Learning und Machine Learning ihre Bedeutung nicht verloren, sondern werden als effiziente wissensbasierte Systeme immer wichtiger. Denn intelligente Systeme der Zukunft müssen nicht nur in der Lage sein zu sagen, was sie entschieden haben, sondern auch wie sie zu dieser Entscheidung gekommen sind. Solche Systeme sind jedoch nur mit Hilfe von wissensbasierten Systemen auf der Grundlage von semantischen Technologien erreichbar. Heute reichen die Anwendungen von semantischen Systemen von der semantischen Suche, Knowledge Graphs, Chatbots, NLP, in der Medizin bis zur Telekommunikation, Verwaltung und Robotik. Semantische Technologien werden spätestens mit dem Voranschreiten des Internet of Things (IoT) und Industrie 4.0 Anwendungen allgegenwärtig sein. Dies ist unumgänglich, denn ohne sie ist auch die Interoperabilität unter Maschinen und insbesondere unter Roboter für eine intelligente Zusammenarbeit und Produktion nicht so einfach umsetzbar. Dafür gibt es bereits heute zahlreiche Beispiele aus der Industrie.