Email has become an indispensable communication tool in daily life. However, high volumes of spam waste resources, interfere with productivity, and present severe threats to computer system security and personal privacy. This book introduces research on anti-spam techniques based on the artificial immune system (AIS) to identify and filter spam. It provides a single source of all anti-spam models and algorithms based on the AIS that have been proposed by the author for the past decade in various journals and conferences. Inspired by the biological immune system, the AIS is an adaptive system based on theoretical immunology and observed immune functions, principles, and models for problem solving. Among the variety of anti-spam techniques, the AIS has been highly effective and is becoming one of the most important methods to filter spam. The book also focuses on several key topics related to the AIS, including: Extraction methods inspired by various immune principles Construction approaches based on several concentration methods and models Classifiers based on immune danger theory The immune-based dynamic updating algorithm Implementing AIS-based spam filtering systems The book also includes several experiments and comparisons with state-of-the-art anti-spam techniques to illustrate the excellent performance AIS-based anti-spam techniques. Anti-Spam Techniques Based on Artificial Immune System gives practitioners, researchers, and academics a centralized source of detailed information on efficient models and algorithms of AIS-based anti-spam techniques. It also contains the most current information on the general achievements of anti-spam research and approaches, outlining strategies for designing and applying spam-filtering models.

Language, Nations, and Multilingualism explores the legacy of Herder's ideas about the relationship between language and nationalism in the post-colonial world. Focusing on how anti-colonial and post-colonial nations reconcile their myriad multilingualisms with the Herderian model of one language-one nation, it shows how Herder's model is both attractive and problematic for such nations. Why then does the Herderian model have such valency? How has the Herderian ideal of one nation-one language continued to survive beneath the uncomfortable resolution struck by new multilingual nations as they create fictions of a singular national mother tongue? To what extent is Herder still relevant in our contemporary world? How have different nations negotiated the Herderian ideal in different ways? What does the way in which multilingual post-colonial nations deal with this crisis tell us about a possible alternative framework for understanding the relationship between language and nation? By approaching this investigation from diverse archives across Asia, Africa, Europe, Latin America, and the Caribbean, Language, Nations, and Multilingualism proposes answers to the aforementioned questions from a global perspective that takes into account the specificities of a range of colonial experiences and political regimes. And by extending the discussion backwards in time to offer a more historical reading of the making of modern nations, it allows us to see how multilingualism has always disrupted constructions of monoglot nations.

Language, Nations, and Multilingualism explores the legacy of Herder’s ideas about the relationship between language and nationalism in the post-colonial world. Focusing on how anti-colonial and post-colonial nations reconcile their myriad multilingualisms with the Herderian model of one language-one nation, it shows how Herder’s model is both attractive and problematic for such nations. Why then does the Herderian model have such valency? How has the Herderian ideal of one nation-one language continued to survive beneath the uncomfortable resolution struck by new multilingual nations as they create fictions of a singular national mother tongue? To what extent is Herder still relevant in our contemporary world? How have different nations negotiated the Herderian ideal in different ways? What does the way in which multilingual post-colonial nations deal with this crisis tell us about a possible alternative framework for understanding the relationship between language and nation? By approaching this investigation from diverse archives across Asia, Africa, Europe, Latin America, and the Caribbean, Language, Nations, and Multilingualism proposes answers to the aforementioned questions from a global perspective that takes into account the specificities of a range of colonial experiences and political regimes. And by extending the discussion backwards in time to offer a more historical reading of the making of modern nations, it allows us to see how multilingualism has always disrupted constructions of monoglot nations.

Email has become an indispensable communication tool in daily life. However, high volumes of spam waste resources, interfere with productivity, and present severe threats to computer system security and personal privacy. This book introduces research on anti-spam techniques based on the artificial immune system (AIS) to identify and filter spam. It provides a single source of all anti-spam models and algorithms based on the AIS that have been proposed by the author for the past decade in various journals and conferences. Inspired by the biological immune system, the AIS is an adaptive system based on theoretical immunology and observed immune functions, principles, and models for problem solving. Among the variety of anti-spam techniques, the AIS has been highly effective and is becoming one of the most important methods to filter spam. The book also focuses on several key topics related to the AIS, including: Extraction methods inspired by various immune principles Construction approaches based on several concentration methods and models Classifiers based on immune danger theory The immune-based dynamic updating algorithm Implementing AIS-based spam filtering systems The book also includes several experiments and comparisons with state-of-the-art anti-spam techniques to illustrate the excellent performance AIS-based anti-spam techniques. Anti-Spam Techniques Based on Artificial Immune System gives practitioners, researchers, and academics a centralized source of detailed information on efficient models and algorithms of AIS-based anti-spam techniques. It also contains the most current information on the general achievements of anti-spam research and approaches, outlining strategies for designing and applying spam-filtering models.

Today, the development of robots is making steady advances. In particular, the Robot Operating System (ROS) offers a unified platform that greatly facilitates the development of robots and has become a new hotspot for learning and application in the field of robotics research.This book introduces readers to the key technologies and development methods for ROS-based intelligent robots. Covering both the development history of robots and various aspects of programming robots, it offers effective support for beginners.The book is divided into three parts, the first of which introduces the basics of robots, including their definition, development, composition, and key technologies. In turn, the second part covers the hardware and software components and the implementation of functions such as vision, speech, grasping, and autonomous navigation. These functions need to work together to provide user-friendlier and more intelligent service. The third part shows how to develop robots with different functions in different application scenarios.Combining theoretical and practical aspects, with a strong focus on application, this work can be used as a reference book for robotics-related courses. Moreover, it will benefit all readers who are interested in intelligent robot development, sharing essential insights into developing service robots based on ROS.

GPU-based Parallel Implementation of Swarm Intelligence Algorithms combines and covers two emerging areas attracting increased attention and applications: graphics processing units (GPUs) for general-purpose computing (GPGPU) and swarm intelligence. This book not only presents GPGPU in adequate detail, but also includes guidance on the appropriate implementation of swarm intelligence algorithms on the GPU platform. GPU-based implementations of several typical swarm intelligence algorithms such as PSO, FWA, GA, DE, and ACO are presented and having described the implementation details including parallel models, implementation considerations as well as performance metrics are discussed. Finally, several typical applications of GPU-based swarm intelligence algorithms are presented. This valuable reference book provides a unique perspective not possible by studying either GPGPU or swarm intelligence alone. This book gives a complete and whole picture for interested readers and new comers who will find many implementation algorithms in the book suitable for immediate use in their projects. Additionally, some algorithms can also be used as a starting point for further research.

This two-volume set LNCS 13968 and 13969 constitutes the proceedings of the 14th International Conference on Advances in Swarm Intelligence, ICSI 2023, which took place in Shenzhen, China, China, in July 2023. The theme of this year’s conference was “Serving Life with Swarm Intelligence�.The 81 full papers presented were carefully reviewed and selected from 170 submissions. The papers are organized into 12 cohesive sections covering major topics of swarm intelligence research and its development and applications. The papers of the first part cover topics such as: Swarm Intelligence Computing; Swarm Intelligence Optimization Algorithms; Particle Swarm Optimization Algorithms; Genetic Algorithms; Optimization Computing Algorithms; Neural Network Search & Large-Scale Optimization; Multi-objective Optimization.

This two-volume set LNCS 13968 and 13969 constitutes the proceedings of the 14th International Conference on Advances in Swarm Intelligence, ICSI 2023, which took place in Shenzhen, China, China, in July 2023. The theme of this year’s conference was “Serving Life with Swarm Intelligence�. The 81 full papers presented were carefully reviewed and selected from 170 submissions. The papers are organized into 12 cohesive sections covering major topics of swarm intelligence research and its development and applications. The papers of the second part cover topics such as: Swarm Robotics and UAV; Machine Learning; Data Mining; Routing and Scheduling Problems; Stock Prediction and Portfolio Optimization; ICSI-Optimization Competition.  

This two-volume set, CCIS 1453 and CCIS 1454, constitutes refereed proceedings of the 6th International Conference on Data Mining and Big Data, DMBD 2021, held in Guangzhou, China, in October 2021. The 57 full papers and 28 short papers presented in this two-volume set were carefully reviewed and selected from 258 submissions. The papers present the latest research on advantages in theories, technologies, and applications in data mining and big data. The volume covers many aspects of data mining and big data as well as intelligent computing methods applied to all fields of computer science, machine learning, data mining and knowledge discovery, data science, etc.

This two-volume set, CCIS 1453 and CCIS 1454, constitutes refereed proceedings of the 6th International Conference on Data Mining and Big Data, DMBD 2021, held in Guangzhou, China, in October 2021. The 57 full papers and 28 short papers presented in this two-volume set were carefully reviewed and selected from 258 submissions. The papers present the latest research on advantages in theories, technologies, and applications in data mining and big data. The volume covers many aspects of data mining and big data as well as intelligent computing methods applied to all fields of computer science, machine learning, data mining and knowledge discovery, data science, etc.

In recent years, swarm intelligence has become a popular computational approach among researchers working on optimization problems throughout the globe. Several algorithms inside swarm intelligence have been implemented due to their application to real-world issues and other advantages. A specific procedure, Fireworks Algorithm, is an emerging method that studies the explosion process of fireworks within local areas. Applications of this developing program are undiscovered, and research is necessary for scientists to fully understand the workings of this innovative system. The Handbook of Research on Fireworks Algorithms and Swarm Intelligence is a pivotal reference source that provides vital research on theory analysis, improvements, and applications of fireworks algorithm. While highlighting topics such as convergence rate, parameter applications, and global optimization analysis, this publication explores up-to-date progress on the specific techniques of this algorithm. This book is ideally designed for researchers, data scientists, mathematicians, engineers, software developers, postgraduates, and academicians seeking coverage on this evolutionary computation method.

Swarm Intelligence (SI) is one of the most important and challenging paradigms under the umbrella of computational intelligence. It focuses on the research of collective behaviours of a swarm in nature and/or social phenomenon to solve complicated and difficult problems which cannot be handled by traditional approaches. Thousands of papers are published each year presenting new algorithms, new improvements and numerous real world applications. This makes it hard for researchers and students to share their ideas with other colleagues; follow up the works from other researchers with common interests; and to follow new developments and innovative approaches. This complete and timely collection fills this gap by presenting the latest research systematically and thoroughly to provide readers with a full view of the field of swarm. Students will learn the principles and theories of typical swarm intelligence algorithms; scholars will be inspired with promising research directions; and practitioners will find suitable methods for their applications of interest along with useful instructions. Volume 3 includes 27 chapters presenting real-world applications of swarm intelligence algorithms and related evolutionary algorithms. With contributions from an international selection of leading researchers, Swarm Intelligence is essential reading for engineers, researchers, professionals and practitioners with interests in swarm intelligence.

Swarm Intelligence (SI) is one of the most important and challenging paradigms under the umbrella of computational intelligence. It focuses on the research of collective behaviours of a swarm in nature and/or social phenomenon to solve complicated and difficult problems which cannot be handled by traditional approaches. Thousands of papers are published each year presenting new algorithms, new improvements and numerous real world applications. This makes it hard for researchers and students to share their ideas with other colleagues; follow up the works from other researchers with common interests; and to follow new developments and innovative approaches. This complete and timely collection fills this gap by presenting the latest research systematically and thoroughly to provide readers with a full view of the field of swarm. Students will learn the principles and theories of typical swarm intelligence algorithms; scholars will be inspired with promising research directions; and practitioners will find suitable methods for their applications of interest along with useful instructions. Volume 1 contains 20 chapters presenting the basic principles and current algorithms and methods of well-known swarm intelligence algorithms and efficient improvements from typical particle swarm optimization (PSO), ant colony optimization (ACO) and fireworks algorithm (FWA) as well as other swarm intelligence algorithms for swarm robotics. With contributions from an international selection of leading researchers, Swarm Intelligence is essential reading for engineers, researchers, professionals and practitioners with interests in swarm intelligence.

Swarm Intelligence (SI) is one of the most important and challenging paradigms under the umbrella of computational intelligence. It focuses on the research of collective behaviours of a swarm in nature and/or social phenomenon to solve complicated and difficult problems which cannot be handled by traditional approaches. Thousands of papers are published each year presenting new algorithms, new improvements and numerous real world applications. This makes it hard for researchers and students to share their ideas with other colleagues; follow up the works from other researchers with common interests; and to follow new developments and innovative approaches. This complete and timely collection fills this gap by presenting the latest research systematically and thoroughly to provide readers with a full view of the field of swarm. Students will learn the principles and theories of typical swarm intelligence algorithms; scholars will be inspired with promising research directions; and practitioners will find suitable methods for their applications of interest along with useful instructions. Volume 2 includes 17 chapters covering front-edge research with novel and newly proposed algorithms and methods. With contributions from an international selection of leading researchers, Swarm Intelligence is essential reading for engineers, researchers, professionals and practitioners with interests in swarm intelligence.

The two-volume set of LNCS 10941 and 10942 constitutes the proceedings of the 9th International Conference on Advances in Swarm Intelligence, ICSI 2018, held in Shanghai, China, in June 2018. The total of 113 papers presented in these volumes was carefully reviewed and selected from 197 submissions. The papers were organized in topical sections as follows: theories and models of swarm intelligence; ant colony optimization; particle swarm optimization; artificial bee colony algorithms; genetic algorithms; differential evolution; fireworks algorithms; bacterial foraging optimization; artificial immune system; hydrologic cycle optimization; other swarm-based optimization algorithms; hybrid optimization algorithms; multi-objective optimization; large-scale global optimization; multi-agent systems; swarm robotics; fuzzy logic approaches; planning and routing problems; recommendation in social media; prediction, classification; finding patterns; image enhancement; deep learning.

This book constitutes the refereed proceedings of the Third International Conference on Data Mining and Big Data, DMBD 2018, held in Shanghai, China, in June 2018. The 74 papers presented in this volume were carefully reviewed and selected from 126 submissions. They are organized in topical sections named: database, data preprocessing, matrix factorization, data analysis, visualization, visibility analysis, clustering, prediction, classification, pattern discovery, text mining and knowledge management, recommendation system in social media, deep learning, big data, Industry 4.0, practical applications

This book is devoted to the state-of-the-art in all aspects of fireworks algorithm (FWA), with particular emphasis on the efficient improved versions of FWA. It describes the most substantial theoretical analysis including basic principle and implementation of FWA and modeling and theoretical analysis of FWA. It covers exhaustively the key recent significant research into the improvements of FWA so far. In addition, the book describes a few advanced topics in the research of FWA, including multi-objective optimization (MOO), discrete FWA (DFWA) for combinatorial optimization, and GPU-based FWA for parallel implementation. In sequels, several successful applications of FWA on non-negative matrix factorization (NMF), text clustering, pattern recognition, and seismic inversion problem, and swarm robotics, are illustrated in details, which might shed new light on more real-world applications in future. Addressing a multidisciplinary topic, it will appeal to researchers and professionals in the areas of metahuristics, swarm intelligence, evolutionary computation, complex optimization solving, etc.

Studies on robotics applications have grown substantially in recent years, with swarm robotics being a relatively new area of research. Inspired by studies in swarm intelligence and robotics, swarm robotics facilitates interactions between robots as well as their interactions with the environment. The Handbook of Research on Design, Control, and Modeling of Swarm Robotics is a collection of the most important research achievements in swarm robotics thus far, covering the growing areas of design, control, and modeling of swarm robotics. This handbook serves as an essential resource for researchers, engineers, graduates, and senior undergraduates with interests in swarm robotics and its applications.

This book is devoted to the state-of-the-art in all aspects of fireworks algorithm (FWA), with particular emphasis on the efficient improved versions of FWA. It describes the most substantial theoretical analysis including basic principle and implementation of FWA and modeling and theoretical analysis of FWA. It covers exhaustively the key recent significant research into the improvements of FWA so far. In addition, the book describes a few advanced topics in the research of FWA, including multi-objective optimization (MOO), discrete FWA (DFWA) for combinatorial optimization, and GPU-based FWA for parallel implementation. In sequels, several successful applications of FWA on non-negative matrix factorization (NMF), text clustering, pattern recognition, and seismic inversion problem, and swarm robotics, are illustrated in details, which might shed new light on more real-world applications in future. Addressing a multidisciplinary topic, it will appeal to researchers and professionals in the areas of metahuristics, swarm intelligence, evolutionary computation, complex optimization solving, etc.

This book and its companion volume, LNCS vol. 8794 and 8795 constitute the proceedings of the 5th International Conference on Swarm Intelligence, ICSI 2014, held in Hefei, China in October 2014. The 107 revised full papers presented were carefully reviewed and selected from 198 submissions. The papers are organized in 18 cohesive sections, 3 special sessions and one competitive session covering all major topics of swarm intelligence research and development such as novel swarm-based search methods; novel optimization algorithm; particle swarm optimization; ant colony optimization for travelling salesman problem; artificial bee colony algorithms; artificial immune system; evolutionary algorithms; neural networks and fuzzy methods; hybrid methods; multi-objective optimization; multi-agent systems; evolutionary clustering algorithms; classification methods; GPU-based methods; scheduling and path planning; wireless sensor networks; power system optimization; swarm intelligence in image and video processing; applications of swarm intelligence to management problems; swarm intelligence for real-world application.

This book and its companion volume, LNCS vol. 8794 and 8795 constitute the proceedings of the 5th International Conference on Swarm Intelligence, ICSI 2014, held in Hefei, China in October 2014. The 107 revised full papers presented were carefully reviewed and selected from 198 submissions. The papers are organized in 18 cohesive sections, 3 special sessions and one competitive session covering all major topics of swarm intelligence research and development such as novel swarm-based search methods; novel optimization algorithm; particle swarm optimization; ant colony optimization for travelling salesman problem; artificial bee colony algorithms; artificial immune system; evolutionary algorithms; neural networks and fuzzy methods; hybrid methods; multi-objective optimization; multi-agent systems; evolutionary clustering algorithms; classification methods; GPU-based methods; scheduling and path planning; wireless sensor networks; power system optimization; swarm intelligence in image and video processing; applications of swarm intelligence to management problems; swarm intelligence for real-world application.

This book and its companion volume, LNCS vols. 7928 and 7929 constitute the proceedings of the 4th International Conference on Swarm Intelligence, ICSI 2013, held in Harbin, China in June 2013. The 129 revised full papers presented were carefully reviewed and selected from 268 submissions. The papers are organized in 22 cohesive sections covering all major topics of swarm intelligence research and developments. The topics covered in this volume are: hybrid algorithms, swarm-robot and multi-agent systems, support vector machines, data mining methods, system and information security, intelligent control, wireless sensor network, scheduling and path planning, image and video processing, and other applications.

This book and its companion volume, LNCS vols. 7928 and 7929 constitute the proceedings of the 4th International Conference on Swarm Intelligence, ICSI 2013, held in Harbin, China in June 2013. The 129 revised full papers presented were carefully reviewed and selected from 268 submissions. The papers are organized in 22 cohesive sections covering all major topics of swarm intelligence research and developments. The following topics are covered in this volume: analysis of swarm intelligence based algorithms, particle swarm optimization, applications of particle swarm optimization algorithms, ant colony optimization algorithms, biogeography-based optimization algorithms, novel swarm-based search methods, bee colony algorithms, differential evolution, neural networks, fuzzy methods, evolutionary programming and evolutionary games.

This book and its companion volume, LNCS vols. 7331 and 7332, constitute the Proceedings of the Third International conference on Swarm Intelligence, ICSI 2012, held in Shenzhen, China in June 2012. The 145 full papers presented were carefully reviewed and selected from 247 submissions. The papers are organized in 27 cohesive sections covering all major topics of swarm intelligence research and developments.

This book and its companion volume, LNCS vols. 7331 and 7332, constitute the proceedings of the Third International Conference on Swarm Intelligence, ICSI 2012, held in Shenzhen, China in June 2012. The 145 revised full papers presented were carefully reviewed and selected from 247 submissions. The papers are organized in 27 cohesive sections covering all major topics of swarm intelligence research and developments.