This volume constitutes the refereed and revised post-conference proceedings of the 5th IFIP WG 5.15 International Conference on Information Technology in Disaster Risk Reduction, ITDRR 2020, in Sofia, Bulgaria, in December 2020.* The 18 full papers and 6 short papers presented were carefully reviewed and selected from 52 submissions. The papers focus on various aspects and challenges of coping with disaster risk reduction. The main topics include areas such as natural disasters, remote sensing, big data, cloud computing, Internet of Things, mobile computing, emergency management, disaster information processing, disaster risk assessment and management. *The conference was held virtually.

The field of data mining is receiving significant attention in today's information-rich society, where data is available from different sources and formats, in large volumes, and no longer constitutes a bottleneck for knowledge acquisition. This rich information has paved the way for novel areas of research, particularly in the crime data analysis realm. Data Mining Trends and Applications in Criminal Science and Investigations presents scientific concepts and frameworks of data mining and analytics implementation and uses across various domains, such as public safety, criminal investigations, intrusion detection, crime scene analysis, and suspect modeling. Exploring the diverse ways that data is revolutionizing the field of criminal science, this publication meets the research needs of law enforcement professionals, data analysts, investigators, researchers, and graduate-level students.

This book gathers selected papers presented at the International Conference on Innovations in Information and Communication Technologies (ICI2CT 2020), held at National University of Singapore, Singapore, during 18-19 December 2020. It presents the works on the intersection of the Computer Science and Communication Engineering. Topics covered in the book include communications engineering, Internet and web technology, computer and information science, artificial intelligence, data science and management, and ICT applications.

This book provides an introduction to the field of periodic pattern mining, reviews state-of-the-art techniques, discusses recent advances, and reviews open-source software. Periodic pattern mining is a popular and emerging research area in the field of data mining. It involves discovering all regularly occurring patterns in temporal databases. One of the major applications of periodic pattern mining is the analysis of customer transaction databases to discover sets of items that have been regularly purchased by customers. Discovering such patterns has several implications for understanding the behavior of customers. Since the first work on periodic pattern mining, numerous studies have been published and great advances have been made in this field. The book consists of three main parts: introduction, algorithms, and applications. The first chapter is an introduction to pattern mining and periodic pattern mining. The concepts of periodicity, periodic support, search space exploration techniques, and pruning strategies are discussed. The main types of algorithms are also presented such as periodic-frequent pattern growth, partial periodic pattern-growth, and periodic high-utility itemset mining algorithm. Challenges and research opportunities are reviewed. The chapters that follow present state-of-the-art techniques for discovering periodic patterns in (1) transactional databases, (2) temporal databases, (3) quantitative temporal databases, and (4) big data. Then, the theory on concise representations of periodic patterns is presented, as well as hiding sensitive information using privacy-preserving data mining techniques. The book concludes with several applications of periodic pattern mining, including applications in air pollution data analytics, accident data analytics, and traffic congestion analytics.

This book constitutes the refereed proceedings of two International Workshops held as parallel events of the 16th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2020, in Neos Marmaras, Greece, in June 2020: the 9th Mining Humanistic Data Workshop, MHDW 2020, and the 5th Workshop on 5G-Putting Intelligence to the Network Edge, 5G-PINE 2020.* The 6 full papers and 3 short papers presented at MHDW 2020 were carefully reviewed and selected from 16 submissions; out of the 23 papers submitted to 5G-PINE 2020, 11 were accepted as full papers and 1 as a short paper. The MHDW papers focus on topics such as recommendation systems, sentiment analysis, pattern recognition, data mining, and time series. The papers presented at 5G-PINE focus on the latest AI applications in the telecommunication industry and deal with topics such as the Internet of Things, intelligence fusion in 5G networks, and 5G media. *The workshops were held virtually due to the COVID-19 pandemic.

This comprehensive Guide to Web Development with Java introduces the readers to the three-tiered, Model-View-Controller architecture by using Spring JPA, JSPs, and Spring MVC controllers. These three technologies use Java, so that a student with a background in programming will be able to master them with ease, with the end result of being able to create web applications that use MVC, validate user input,and save data to a database. Topics and features: * Presents web development topics in an accessible, easy-to-follow style, focusing on core information first, and allowing the reader to gain basic understanding before moving forwards * Contains many helpful pedagogical tools for students and lecturers, such as questions and exercises at the end of each chapter, detailed illustrations, chapter summaries, and a glossary * Uses existing powerful technologies that are freely available on the web to speed up web development, such as Spring Boot, Spring MVC, Spring JPA, Hibernate, JSP, JSTL, and Java 1.8 * Discusses HTML, HTML forms, and Cascading Style Sheets * Starts with the simplest technology for web development (JSP) and gradually introduces the reader to more complex topics * Introduces core technologies from the outset, such as the Model-View-Controller architecture * Includes examples for accessing common web services * Provides supplementary examples and tutorials

This proceedings book presents state-of-the-art developments in theory, methodology, and applications of network analysis across sociology, computational science, education research, literature studies, political science, international relations, social media research, and urban studies. The papers comprising this collection were presented at the Fifth 'Networks in the Global World' conference organized by the Centre for German and European Studies of St. Petersburg University and Bielefeld University and held on July 7-9, 2020. This biannual conference series revolves around key interdisciplinary issues in the focus of network analysts, such as the multidimensional approach to social reality, translation of theories and methods across disciplines, and mixing of data and methods. The distinctive features of this book are the emphasis on in-depth linkages between theory, method, and applications, the blend of qualitative and quantitative methods, and the joint consideration of different network levels, types, and contexts. The topics covered by the papers include interrelation of social and cultural structures, constellations of power, and patterns of interaction in areas ranging from various types of communities (local, international, educational, political, and so on) to social media and literature. The book is useful for practicing researchers, graduate and postgraduate students, and educators interested in network analysis of social relations, politics, economy, and culture. Features that set the book apart from others in the field: * The book offers a unique cross-disciplinary blend of computational and ethnographic network analyses applied to a diverse spectrum of spheres, from literature and education to urban planning and policymaking. * Embracing conceptual, methodological, and empirical works, the book is among the few in network analysis to emphasize connections between theory, method, and applications. * The book brings together authors and empirical contexts from all over the globe, with a particular emphasis on European societies.

This book discusses recent research and applications in intelligent service computing in mobile environments. The authors first explain how advances in artificial intelligence and big data have allowed for an array of intelligent services with complex and diverse applications. They then show how this brings new opportunities and challenges for service computing. The book, made up of contributions from academic and industry, aims to present advances in intelligent services, new algorithms and techniques in the field, foundational theory and systems, as well as practical real-life applications. Some of the topics discussed include cognition, modeling, description and verification for intelligent services; discovery, recommendation and selection for intelligent services; formal verification, testing and inspection for intelligent services; and composition and cooperation methods for intelligent services.

This book provides readers the "big picture" and a comprehensive survey of the domain of big data processing systems. For the past decade, the Hadoop framework has dominated the world of big data processing, yet recently academia and industry have started to recognize its limitations in several application domains and thus, it is now gradually being replaced by a collection of engines that are dedicated to specific verticals (e.g. structured data, graph data, and streaming data). The book explores this new wave of systems, which it refers to as Big Data 2.0 processing systems. After Chapter 1 presents the general background of the big data phenomena, Chapter 2 provides an overview of various general-purpose big data processing systems that allow their users to develop various big data processing jobs for different application domains. In turn, Chapter 3 examines various systems that have been introduced to support the SQL flavor on top of the Hadoop infrastructure and provide competing and scalable performance in the processing of large-scale structured data. Chapter 4 discusses several systems that have been designed to tackle the problem of large-scale graph processing, while the main focus of Chapter 5 is on several systems that have been designed to provide scalable solutions for processing big data streams, and on other sets of systems that have been introduced to support the development of data pipelines between various types of big data processing jobs and systems. Next, Chapter 6 focuses on covering the emerging frameworks and systems in the domain of scalable machine learning and deep learning processing. Lastly, Chapter 7 shares conclusions and an outlook on future research challenges. This new and considerably enlarged second edition not only contains the completely new chapter 6, but also offers a refreshed content for the state-of-the-art in all domains of big data processing over the last years. Overall, the book offers a valuable reference guide for professional, students, and researchers in the domain of big data processing systems. Further, its comprehensive content will hopefully encourage readers to pursue further research on the subject.

As the Internet has evolved to become an integral part of modern society, the need for better quality assurance practices in web engineering has heightened. Adherence to and improvement of current standards ensures that overall web usability and accessibility are at optimum efficiency. Design Solutions for Improving Website Quality and Effectiveness is an authoritative reference source for the latest breakthroughs, techniques, and research-based solutions for the overall improvement of the web designing process. Featuring relevant coverage on the analytics, metrics, usage, and security aspects of web environments, this publication is ideally designed for reference use by engineers, researchers, graduate students, and web designers interested in the enhancement of various types of websites.

The goal of this textbook is to provide enough background into the inner workings of the Internet to allow a novice to understand how the various protocols on the Internet work together to accomplish simple tasks, such as a search. By building an Internet with all the various services a person uses every day, one will gain an appreciation not only of the work that goes on unseen, but also of the choices made by designers to make life easier for the user. Each chapter consists of background information on a specific topic or Internet service, and where appropriate a final section on how to configure a Raspberry Pi to provide that service. While mainly meant as an undergraduate textbook for a course on networking or Internet protocols and services, it can also be used by anyone interested in the Internet as a step-by-step guide to building one's own Intranet, or as a reference guide as to how things work on the global Internet

Service delivery in the digital era is all about bringing together innovative ideas from various stakeholders in the private, public, and civil sectors to meet customer expectations. Like any business, government public service entities must provide public service delivery to their customers in an age that is heavily influenced by technological advancements. Information Systems Strategic Planning for Public Service Delivery in the Digital Era is an essential reference source that discusses issues related to public service delivery in the digital era and the degree to which governments may take advantage of the transformational potential of ICT to move towards seamless government, particularly for improving service delivery, democratic responsiveness, and public outreach. The book also provides a pragmatic framework for government entities to define their information systems strategic plan (ISSP), guiding the reader in a step-by-step practical description of the various technical concepts, current and future technology trends, and implementation considerations for formulating their ISSP to ensure the maximum gain from public service delivery. Including research on topics such as human capital, knowledge economy, and block chain technology, this book is ideally designed for academicians, public administrators, government officials, IT consultants.

As the world has entered the era of big data, there is a need to give a semantic perspective to the data to find unseen patterns, derive meaningful information, and make intelligent decisions. This 2-volume handbook set is a unique, comprehensive, and complete presentation of the current progress and future potential explorations in the field of data science and related topics. Handbook of Data Science with Semantic Technologies provides a roadmap for a new trend and future development of data science with semantic technologies. The first volume serves as an important guide towards applications of data science with semantic technologies for the upcoming generation and thus becomes a unique resource for both academic researchers and industry professionals. The second volume provides a roadmap for the deployment of semantic technologies in the field of data science that enables users to create intelligence through these technologies by exploring the opportunities while eradicating the current and future challenges. The set explores the optimal use of these technologies to provide the maximum benefit to the user under one comprehensive source. This set consisting of two separate volumes can be utilized independently or together as an invaluable resource for students, scholars, researchers, professionals, and practitioners in the field.

This book presents papers from the 5th International Conference on Smart Learning Ecosystems and Regional Development, which promotes discussions on R&D work, policies, case studies, entrepreneur experiences, with a particular focus on understanding the relevance of smart learning ecosystems for regional development and social innovation, and how the effectiveness of the relation of citizens and smart ecosystems can be boosted. The book explores how technology-mediated instruments can foster citizens' engagement with learning ecosystems and territories, providing insights into innovative human-centric design and development models/techniques, education/training practices, informal social learning, innovative citizen-driven policies, and technology-mediated experiences and their impact. As such, it will inspire the social innovation sectors and ICT, as well as economic development and deployment strategies and new policies for smarter proactive citizens.

This book gathers a collection of high-quality peer-reviewed research papers presented at the 2nd International Conference on Data and Information Sciences (ICDIS 2019), held at Raja Balwant Singh Engineering Technical Campus, Agra, India, on March 29-30, 2019. In chapters written by leading researchers, developers, and practitioner from academia and industry, it covers virtually all aspects of computational sciences and information security, including central topics like artificial intelligence, cloud computing, and big data. Highlighting the latest developments and technical solutions, it will show readers from the computer industry how to capitalize on key advances in next-generation computer and communication technology.

This book is a compendium of the proceedings of the International Conference on Big-Data and Cloud Computing. The papers discuss the recent advances in the areas of big data analytics, data analytics in cloud, smart cities and grid, etc. This volume primarily focuses on the application of knowledge which promotes ideas for solving problems of the society through cutting-edge big-data technologies. The essays featured in this proceeding provide novel ideas that contribute for the growth of world class research and development. It will be useful to researchers in the area of advanced engineering sciences.

Cluster or co-cluster analyses are important tools in a variety of scientific areas. The introduction of this book presents a state of the art of already well-established, as well as more recent methods of co-clustering. The authors mainly deal with the two-mode partitioning under different approaches, but pay particular attention to a probabilistic approach. Chapter 1 concerns clustering in general and the model-based clustering in particular. The authors briefly review the classical clustering methods and focus on the mixture model. They present and discuss the use of different mixtures adapted to different types of data. The algorithms used are described and related works with different classical methods are presented and commented upon. This chapter is useful in tackling the problem of co-clustering under the mixture approach. Chapter 2 is devoted to the latent block model proposed in the mixture approach context. The authors discuss this model in detail and present its interest regarding co-clustering. Various algorithms are presented in a general context. Chapter 3 focuses on binary and categorical data. It presents, in detail, the appropriated latent block mixture models. Variants of these models and algorithms are presented and illustrated using examples. Chapter 4 focuses on contingency data. Mutual information, phi-squared and model-based co-clustering are studied. Models, algorithms and connections among different approaches are described and illustrated. Chapter 5 presents the case of continuous data. In the same way, the different approaches used in the previous chapters are extended to this situation. Contents 1. Cluster Analysis. 2. Model-Based Co-Clustering. 3. Co-Clustering of Binary and Categorical Data. 4. Co-Clustering of Contingency Tables. 5. Co-Clustering of Continuous Data. About the Authors Gerard Govaert is Professor at the University of Technology of Compiegne, France. He is also a member of the CNRS Laboratory Heudiasyc (Heuristic and diagnostic of complex systems). His research interests include latent structure modeling, model selection, model-based cluster analysis, block clustering and statistical pattern recognition. He is one of the authors of the MIXMOD (MIXtureMODelling) software. Mohamed Nadif is Professor at the University of Paris-Descartes, France, where he is a member of LIPADE (Paris Descartes computer science laboratory) in the Mathematics and Computer Science department. His research interests include machine learning, data mining, model-based cluster analysis, co-clustering, factorization and data analysis. Cluster Analysis is an important tool in a variety of scientific areas. Chapter 1 briefly presents a state of the art of already well-established as well more recent methods. The hierarchical, partitioning and fuzzy approaches will be discussed amongst others. The authors review the difficulty of these classical methods in tackling the high dimensionality, sparsity and scalability. Chapter 2 discusses the interests of coclustering, presenting different approaches and defining a co-cluster. The authors focus on co-clustering as a simultaneous clustering and discuss the cases of binary, continuous and co-occurrence data. The criteria and algorithms are described and illustrated on simulated and real data. Chapter 3 considers co-clustering as a model-based co-clustering. A latent block model is defined for different kinds of data. The estimation of parameters and co-clustering is tackled under two approaches: maximum likelihood and classification maximum likelihood. Hard and soft algorithms are described and applied on simulated and real data. Chapter 4 considers co-clustering as a matrix approximation. The trifactorization approach is considered and algorithms based on update rules are described. Links with numerical and probabilistic approaches are established. A combination of algorithms are proposed and evaluated on simulated and real data. Chapter 5 considers a co-clustering or bi-clustering as the search for coherent co-clusters in biological terms or the extraction of co-clusters under conditions. Classical algorithms will be described and evaluated on simulated and real data. Different indices to evaluate the quality of coclusters are noted and used in numerical experiments.

This book aims to present a survey of a large class of nonlinear dynamical systems exhibiting mixed-mode oscillations (MMOs). It is a sort of a guide to systems related to MMOs that features material from original research papers, including the author's own studies. The material is presented in seven chapters divided into sections. Usually, the first sections are of an introductory nature, explain phenomena, and exhibit numerical results. More advanced investigations are presented in the subsequent sections. Coverage includes * Dynamic behavior of nonlinear systems, * Fundamentals of processes exhibiting MMOs,* Mechanism and function of an structure of MMOs patterns, * Analysis of MMOs in electric circuits and systems, * MMOs in chemistry, biology, and medicine, * MMOs in mechanics and transport vehicles, * MMOs in fractional order systems. This is the first extensive description of these topics and the interpretation of analytical results and those obtained from computer simulations with the MATLAB environment. The book provides the readers with better understanding of the nature of MMOs, richness of their behaviors, and interesting applications.

A fascinating work on the history and development of cryptography, from the Egyptians to WWII. Many of the earliest books, particularly those dating back to the 1900s and before, are now extremely scarce and increasingly expensive. Hesperides Press are republishing these classic works in affordable, high quality, modern editions, using the original text and artwork Contents Include The Beginings of Cryptography From the Middle Ages Onwards Signals, Signs, And Secret Languages Commercial Codes Military Codes and Ciphers Types of Codes and Ciphers Methods of Deciphering Bibliography

Businesses in today's world are adopting technology-enabled operating models that aim to improve growth, revenue, and identify emerging markets. However, most of these businesses are not suited to defend themselves from the cyber risks that come with these data-driven practices. To further prevent these threats, they need to have a complete understanding of modern network security solutions and the ability to manage, address, and respond to security breaches. The Handbook of Research on Intrusion Detection Systems provides emerging research exploring the theoretical and practical aspects of prominent and effective techniques used to detect and contain breaches within the fields of data science and cybersecurity. Featuring coverage on a broad range of topics such as botnet detection, cryptography, and access control models, this book is ideally designed for security analysts, scientists, researchers, programmers, developers, IT professionals, scholars, students, administrators, and faculty members seeking research on current advancements in network security technology.

Information security is moving much higher up the agenda of corporate concerns. The pitfalls lying in wait of corporate information are legion. If information is our most important asset, then we must fortify ourselves for the task of protecting it properly. This book is a compilation of contributed chapters by researches and practitioners addressing issues, trends and challenges facing the management of information security in this new millennium. Information Security Management: Global Challenges in the New Millennium focuses on aspects of information security planning, evaluation, design and implementation.

The book discusses machine learning-based decision-making models, and presents intelligent, hybrid and adaptive methods and tools for solving complex learning and decision-making problems under conditions of uncertainty. Featuring contributions from data scientists, practitioners and educators, the book covers a range of topics relating to intelligent systems for decision science, and examines recent innovations, trends, and practical challenges in the field. The book is a valuable resource for academics, students, researchers and professionals wanting to gain insights into decision-making.