This book constitutes the refereed post-conference proceedings of the 28th International Workshopon Combinatorial Algorithms, IWOCA 2017, held in Newcastle, NSW, Australia, in July 2017.The 30 regular papers presented in this volume together with 5 invited talks were carefully reviewed and selected from 55 submissions. They were organized in topical sessions named: approximation algorithms and hardness; computational complexity; computational geometry; graphs and combinatorics; graph colourings, labellings and power domination; heuristics; mixed integer programming; polynomial algorithms; privacy; and string algorithms.

An authoritative guide to an in-depth analysis of various state-of-the-art data clustering approaches using a range of computational intelligence techniques Recent Advances in Hybrid Metaheuristics for Data Clustering offers a guide to the fundamentals of various metaheuristics and their application to data clustering. Metaheuristics are designed to tackle complex clustering problems where classical clustering algorithms have failed to be either effective or efficient. The authors noted experts on the topic provide a text that can aid in the design and development of hybrid metaheuristics to be applied to data clustering. The book includes performance analysis of the hybrid metaheuristics in relationship to their conventional counterparts. In addition to providing a review of data clustering, the authors include in-depth analysis of different optimization algorithms. The text offers a step-by-step guide in the build-up of hybrid metaheuristics and to enhance comprehension. In addition, the book contains a range of real-life case studies and their applications. This important text: Includes performance analysis of the hybrid metaheuristics as related to their conventional counterparts Offers an in-depth analysis of a range of optimization algorithms Highlights a review of data clustering Contains a detailed overview of different standard metaheuristics in current use Presents a step-by-step guide to the build-up of hybrid metaheuristics Offers real-life case studies and applications Written for researchers, students and academics in computer science, mathematics, and engineering, Recent Advances in Hybrid Metaheuristics for Data Clustering provides a text that explores the current data clustering approaches using a range of computational intelligence techniques.

This book constitutes the refereed proceedings of the 18th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2018, held in Parma, Italy, in April 2018, co-located with the Evo* 2018 events EuroGP, EvoMUSART and EvoApplications. The 12 revised full papers presented were carefully reviewed and selected from 37 submissions. The papers cover a wide spectrum of topics, ranging from the foundations of evolutionary computation algorithms and other search heuristics, to their accurate design and application to both single- and multi-objective combinatorial optimization problems. Fundamental and methodological aspects deal with runtime analysis, the structural properties of fitness landscapes, the study of metaheuristics core components, the clever design of their search principles, and their careful selection and configuration by means of automatic algorithm configuration and hyper-heuristics. Applications cover conventional academic domains such as NK landscapes, binary quadratic programming, traveling salesman, vehicle routing, or scheduling problems, and also include real-world domains in clustering, commercial districting and winner determination.

Now in its second edition, this textbook provides an introduction and overview of number theory based on the density and properties of the prime numbers. This unique approach offers both a firm background in the standard material of number theory, as well as an overview of the entire discipline. All of the essential topics are covered, such as the fundamental theorem of arithmetic, theory of congruences, quadratic reciprocity, arithmetic functions, and the distribution of primes. New in this edition are coverage of p-adic numbers, Hensel's lemma, multiple zeta-values, and elliptic curve methods in primality testing. Key topics and features include: A solid introduction to analytic number theory, including full proofs of Dirichlet's Theorem and the Prime Number Theorem Concise treatment of algebraic number theory, including a complete presentation of primes, prime factorizations in algebraic number fields, and unique factorization of ideals Discussion of the AKS algorithm, which shows that primality testing is one of polynomial time, a topic not usually included in such texts Many interesting ancillary topics, such as primality testing and cryptography, Fermat and Mersenne numbers, and Carmichael numbers The user-friendly style, historical context, and wide range of exercises that range from simple to quite difficult (with solutions and hints provided for select exercises) make Number Theory: An Introduction via the Density of Primes ideal for both self-study and classroom use. Intended for upper level undergraduates and beginning graduates, the only prerequisites are a basic knowledge of calculus, multivariable calculus, and some linear algebra. All necessary concepts from abstract algebra and complex analysis are introduced where needed.

This book discusses the security issues in a wide range of wireless devices and systems, such as RFID, Bluetooth, ZigBee, GSM, LTE, and GPS. It collects the findings of recent research by the UnicornTeam at 360 Technology, and reviews the state-of-the-art literature on wireless security. The book also offers detailed case studies and theoretical treatments - specifically it lists numerous laboratory procedures, results, plots, commands and screenshots from real-world experiments. It is a valuable reference guide for practitioners and researchers who want to learn more about the advanced research findings and use the off-the-shelf tools to explore the wireless world.

Gain the basics of Ruby's map, reduce, and select functions and discover how to use them to solve data-processing problems. This compact hands-on book explains how you can encode certain complex programs in 10 lines of Ruby code, an astonishingly small number. You will walk through problems and solutions which are effective because they use map, reduce, and select. As you read Ruby Data Processing, type in the code, run the code, and ponder the results. Tweak the code to test the code and see how the results change. After reading this book, you will have a deeper understanding of how to break data-processing problems into processing stages, each of which is understandable, debuggable, and composable, and how to combine the stages to solve your data-processing problem. As a result, your Ruby coding will become more efficient and your programs will be more elegant and robust. What You Will Learn Discover Ruby data processing and how to do it using the map, reduce, and select functions Develop complex solutions including debugging, randomizing, sorting, grouping, and more Reverse engineer complex data-processing solutions Who This Book Is For Those who have at least some prior experience programming in Ruby and who have a background and interest in data analysis and processing using Ruby.

This book features a collection of revised and significantly extended versions of the papers accepted for presentation at the 6th International Workshop on New Frontiers in Mining Complex Patterns, NFMCP 2017, held in conjunction with ECML-PKDD 2017 in Skopje, Macedonia, in September 2017. The book is composed of five parts: feature selection and induction; classification prediction; clustering; pattern discovery; applications. The workshop was aimed at discussing and introducing new algorithmic foundations and representation formalisms in complex pattern discovery. Finally, it encouraged the integration of recent results from existing fields, such as Statistics, Machine Learning and Big Data Analytics.

Are you looking for new lectures for your course on algorithms, combinatorial optimization, or algorithmic game theory? Maybe you need a convenient source of relevant, current topics for a graduate student or advanced undergraduate student seminar? Or perhaps you just want an enjoyable look at some beautiful mathematical and algorithmic results, ideas, proofs, concepts, and techniques in discrete mathematics and theoretical computer science? Gems of Combinatorial Optimization and Graph Algorithms is a handpicked collection of up-to-date articles, carefully prepared by a select group of international experts, who have contributed some of their most mathematically or algorithmically elegant ideas. Topics include longest tours and Steiner trees in geometric spaces, cartograms, resource buying games, congestion games, selfish routing, revenue equivalence and shortest paths, scheduling, linear structures in graphs, contraction hierarchies, budgeted matching problems, and motifs in networks. This volume is aimed at readers with some familiarity of combinatorial optimization, and appeals to researchers, graduate students, and advanced undergraduate students alike.

This book is about the computational aspects of invariant theory. Of central interest is the question how the invariant ring of a given group action can be calculated. Algorithms for this purpose form the main pillars around which the book is built. There are two introductory chapters, one on Groebner basis methods and one on the basic concepts of invariant theory, which prepare the ground for the algorithms. Then algorithms for computing invariants of finite and reductive groups are discussed. Particular emphasis lies on interrelations between structural properties of invariant rings and computational methods. Finally, the book contains a chapter on applications of invariant theory, covering fields as disparate as graph theory, coding theory, dynamical systems, and computer vision. The book is intended for postgraduate students as well as researchers in geometry, computer algebra, and, of course, invariant theory. The text is enriched with numerous explicit examples which illustrate the theory and should be of more than passing interest. More than ten years after the first publication of the book, the second edition now provides a major update and covers many recent developments in the field. Among the roughly 100 added pages there are two appendices, authored by Vladimi r Popov, and an addendum by Norbert A'Campo and Vladimir Popov.

This book constitutes the refereed proceedings of the 25th International Symposium on String Processing and Information Retrieval, SPIRE 2018, held in Lima, Peru, in October 2018. The 22 full papers and 6 short papers presented were carefully reviewed and selected from 51 submissions. They focus on fundamental studies on string processing and information retrieval, as well as on computational biology.

This book constitutes revised selected papers from the 10th International Symposium on Foundations and Practice of Security, FPS 2017, held in Nancy, France in October 2017. The 20 papers presented in this volume were carefully reviewed and selected from 53 submissions. The papers were organized in topical sections named: access control; formal verification; privacy; physical security; network security, encrypted DBs and blockchain; vulnerability analysis and deception systems; and defence against attacks and anonymity.

The book is a collection of high-quality peer-reviewed research papers presented in the International Conference on Artificial Intelligence and Evolutionary Computations in Engineering Systems (ICAIECES 2017). The book discusses wide variety of industrial, engineering and scientific applications of the emerging techniques. Researchers from academia and industry have presented their original work and ideas, information, techniques and applications in the field of communication, computing and power technologies.

This book constitutes the proceedings of the 12th International Workshop on Algorithms and Computation, WALCOM 2018, held in Dhaka, Bangladesh, in March 2018. The 22 full papers presented were carefully reviewed and selected from 50 submissions. The papers cover diverse areas of algorithms and computation, such as approximation algorithms, computational geometry, combinatorial algorithms, computational biology, computational complexity, data structures, graph and network algorithms, and online algorithms.

This book explores the updated version of the GLOBAL algorithm which contains improvements for a local search algorithm and new Java implementations. Efficiency comparisons to earlier versions and on the increased speed achieved by the parallelization, are detailed. Examples are provided for students as well as researchers and practitioners in optimization, operations research, and mathematics to compose their own scripts with ease. A GLOBAL manual is presented in the appendix to assist new users with modules and test functions. GLOBAL is a successful stochastic multistart global optimization algorithm that has passed several computational tests, and is efficient and reliable for small to medium dimensional global optimization problems. The algorithm uses clustering to ensure efficiency and is modular in regard to the two local search methods it starts with, but it can also easily apply other local techniques. The strength of this algorithm lies in its reliability and adaptive algorithm parameters. The GLOBAL algorithm is free to download also in the earlier Fortran, C, and MATLAB implementations.

The big data tsunami changes the perspective of industrial and academic research in how they address both foundational questions and practical applications. This calls for a paradigm shift in algorithms and the underlying mathematical techniques. There is a need to understand foundational strengths and address the state of the art challenges in big data that could lead to practical impact. The main goal of this book is to introduce algorithmic techniques for dealing with big data sets. Traditional algorithms work successfully when the input data fits well within memory. In many recent application situations, however, the size of the input data is too large to fit within memory. Models of Computation for Big Data, covers mathematical models for developing such algorithms, which has its roots in the study of big data that occur often in various applications. Most techniques discussed come from research in the last decade. The book will be structured as a sequence of algorithmic ideas, theoretical underpinning, and practical use of that algorithmic idea. Intended for both graduate students and advanced undergraduate students, there are no formal prerequisites, but the reader should be familiar with the fundamentals of algorithm design and analysis, discrete mathematics, probability and have general mathematical maturity.

The book focuses on the state-of-the-art technologies pertaining to advances in soft computing, intelligent system and applications. The Proceedings of ASISA 2016 presents novel and original work in soft computing, intelligent system and applications by the experts and budding researchers. These are the cutting edge technologies that have immense application in various fields. The papers discuss many real world complex problems that cannot be easily handled with traditional mathematical methods. The exact solution of the problems at hand can be achieved with soft computing techniques. Soft computing represents a collection of computational techniques inheriting inspiration from evolutionary algorithms, nature inspired algorithms, bio-inspired algorithms, neural networks and fuzzy logic.

This book constitutes the refereed proceedings of the 16th Ibero-American Conference on Artificial Intelligence, IBERAMIA 2018, held in Trujillo, Peru,in November 2018. The 41 papers presented were carefully reviewed and selected from 92 submissions. The papers are organized in the following topical sections: Knowledge Engineering, Knowledge Representation and Reasoning under Uncertainty., Multiagent Systems., Game Theory and Economic Paradigms, Game Playing and Interactive Entertainment, Ambient Intelligence, Machine Learning Methods, Cognitive Modeling,General AI, Knowledge Engineering, Computational Sustainability and AI, Heuristic Search and Optimization and much more.

This book constitutes the proceedings of the 31st Australasian Joint Conference on Artificial Intelligence, AI 2018, held in Wellington, New Zealand, in December 2018. The 50 full and 26 short papers presented in this volume were carefully reviewed and selected from 125 submissions. The paper were organized in topical sections named: agents, games and robotics; AI applications and innovations; computer vision; constraints and search; evolutionary computation; knowledge representation and reasoning; machine learning and data mining; planning and scheduling; and text mining and NLP.

This book introduces readers to selected issues in distributed systems, and primarily focuses on principles, not on technical details. Though the systems discussed are based on existing (von Neumann) computer architectures, the book also touches on emerging processing paradigms. Uniquely, it approaches system components not only as static constructs, but also "in action," exploring the different states they pass through. The author's teaching experience shows that newcomers to the field, students and even IT professionals can far more readily grasp the essence of distributed algorithmic structures in action, than on the basis of static descriptions.

This book constitutes the refereed proceedings of the 20th International Conference on Information and Communications Security, ICICS 2018, held in Lille, France, in October 2018. The 39 revised full papers and 11 short papers presented were carefully selected from 202 submissions. The papers are organized in topics on blockchain technology, malware, botnet and network security, real-world cryptography, encrypted computing, privacy protection, signature schemes, attack analysis and detection, searchable encryption and identity-based cryptography, verifiable storage and computing, applied cryptography, supporting techniques, formal analysis and cryptanalysis, attack detection, and security management.

A major challenge for modern software systems is to become more cost-effective, while being versatile, flexible, resilient, energy-efficient, customizable, and configurable when reacting to run-time changes that may occur within the system itself, its environment or requirements. One of the most promising approaches to achieving such properties is to equip the software system with self-adaptation capabilities. Despite recent advances in this area, one key aspect that remains to be tackled in depth is the provision of assurances. Originating from a Dagstuhl seminar held in December 2013, this book constitutes the third volume in the series "Software Engineering for Self-Adaptive Systems", and looks specifically into the provision of assurances. Opening with an overview chapter on Research Challenges, the book presents 13 further chapters written and carefully reviewed by internationally leading researchers in the field. The book is divided into topical sections on research challenges, evaluation, integration and coordination, and reference architectures and platforms.

This book constitutes the proceedings of the 11th International Conference on Swarm Intelligence, ANTS 2018, held in Rome, Italy, in October 2018. The 24 full papers and 12 short papers presented in this volume were carefully reviewed and selected from 69 submissions. They are devoted to the field of swarm intelligence as a whole, without any bias towards specific research directions.

Biological systems are extensively studied as interactions forming complex networks. Reconstructing causal knowledge from, and principles of, these networks from noisy and incomplete data is a challenge in the field of systems biology. Based on an online course hosted by the Santa Fe Institute Complexity Explorer, this book introduces the field of Algorithmic Information Dynamics, a model-driven approach to the study and manipulation of dynamical systems . It draws tools from network and systems biology as well as information theory, complexity science and dynamical systems to study natural and artificial phenomena in software space. It consists of a theoretical and methodological framework to guide an exploration and generate computable candidate models able to explain complex phenomena in particular adaptable adaptive systems, making the book valuable for graduate students and researchers in a wide number of fields in science from physics to cell biology to cognitive sciences.

This book constitutes the thoroughly refereed proceedings of the National Conference of Theoretical Computer Science, NCTCS 2018, held in Shanghai, China, in October 2018. The 11 full papers presented were carefully reviewed and selected from 31 submissions. They present relevant trends of current research in the area of algorithms and complexity, software theory and method, data science and machine learning theory.

This book presents a holistic view on compiler assisted practical secure multi-party computation (MPC) over Boolean circuits. It discusses that two or more parties jointly evaluate a function over their inputs in such a way that each party keeps its input unknown to the other parties in MPC. MPC provides a generic way to construct Privacy-Enhancing Technologies, which protect sensitive data during processing steps in untrusted environments. A major obstacle in the past was to generate MPC applications by hand. Recently, special compilers have been developed to build all kinds of applications. This book also explains in detail how efficient MPC applications can be created automatically from ANSI-C, thus, bridging the areas of cryptography, compilation and hardware synthesis. It also gives an insight into the requirements for creating efficient applications for MPC and is hence of interest to not only researchers in the area of MPC but also developers realizing practical applications with MPC. For a better understanding of the complete compile chain from ANSI-C to circuits, which is the 'machine code' of MPC, the authors first give the necessary background information on MPC protocols, Boolean logic, and logic synthesis. Then the authors describe the various compilation steps required to translate any code into an adequate circuit description. Afterwards, the authors introduce a variety of optimization techniques for two classes of MPC protocols, namely techniques that improve the runtime of applications in constant- and multi-round MPC protocols. The authors also illustrate how efficient parallelization of MPC protocols can be achieved using the assistance of compilers. It presents the effectiveness of the proposed techniques by giving a detailed evaluation on benchmarking applications. Most of the aforementioned techniques are implemented in our open source compiler that is accompanying this book and allows to study compilation for MPC in practice.Researchers who are interested in practical secure multi-party computation (MPC), and developers who are interested in realizing MPC applications in practice will find this book useful as a reference, as well as advanced-level students in computer science.