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This book constitutes the thoroughly refereed proceedings of the 5th International Conference on Information and Knowledge Systems, ICIKS 2021, which was held online during June 22-23, 2021.The International Conference on Information and Knowledge Systems (ICIKS 2021) gathered both researchers and practitioners in the fields of Information Systems, Artificial Intelligence, Knowledge Management and Decision Support. ICIKS seeks to promote discussions on various organizational, technological, and socio-cultural aspects of research in the design and use of information and knowledge systems in organizations. The 10 full and 2 short papers presented in this volume were carefully reviewed and selected from 32 submissions. They were organized in topical sections as follows: knowledge systems and decision making; machine learning, recommender systems, and knowledge systems; and security, artificial intelligence, and information systems.

Save time and trouble building object-oriented, functional, and concurrent applications with Scala. The latest edition of this comprehensive cookbook is packed with more than 250 ready-to-use recipes and 1,000 code examples to help you solve the most common problems when working with Scala 3 and its popular libraries.Scala changes the way you think about programming--and that's a good thing. Whether you're working on web, big data, or distributed applications, this cookbook provides recipes based on real-world scenarios for both experienced Scala developers and programmers just learning to use this JVM language. Author Alvin Alexander includes practical solutions from his experience using Scala for component-based, highly scalable applications that support concurrency and distribution.Recipes cover:Strings, numbers, and control structuresClasses, methods, objects, traits, packaging, and importsFunctional programming techniquesScala's wealth of collections classes and methodsBuilding and publishing Scala applications with sbtActors and concurrency with Scala Future and Akka TypedPopular libraries, including Spark, Scala.js, Play Framework, and GraalVMTypes, such as variance, givens, intersections, and unionsBest practices, including pattern matching, modules, and functional error handling

This handbook covers a wide range of topics related to the collection, processing, analysis, and use of geospatial data in their various forms. This handbook provides an overview of how spatial computing technologies for big data can be organized and implemented to solve real-world problems. Diverse subdomains ranging from indoor mapping and navigation over trajectory computing to earth observation from space, are also present in this handbook. It combines fundamental contributions focusing on spatio-textual analysis, uncertain databases, and spatial statistics with application examples such as road network detection or colocation detection using GPUs. In summary, this handbook gives an essential introduction and overview of the rich field of spatial information science and big geospatial data. It introduces three different perspectives, which together define the field of big geospatial data: a societal, governmental, and governance perspective. It discusses questions ofhow the acquisition, distribution and exploitation of big geospatial data must be organized both on the scale of companies and countries. A second perspective is a theory-oriented set of contributions on arbitrary spatial data with contributions introducing into the exciting field of spatial statistics or into uncertain databases. A third perspective is taking a very practical perspective to big geospatial data, ranging from chapters that describe how big geospatial data infrastructures can be implemented and how specific applications can be implemented on top of big geospatial data. This would include for example, research in historic map data, road network extraction, damage estimation from remote sensing imagery, or the analysis of spatio-textual collections and social media. This multi-disciplinary approach makes the book unique.This handbook can be used as a reference for undergraduate students, graduate students and researchers focused on big geospatial data. Professionals can use this book, as well as practitioners facing big collections of geospatial data.

The 24 chapters in this book provides a deep overview of robotics and the application of AI and IoT in robotics. It contains the exploration of AI and IoT based intelligent automation in robotics. The various algorithms and frameworks for robotics based on AI and IoT are presented, analyzed, and discussed. This book also provides insights on application of robotics in education, healthcare, defense and many other fields which utilize IoT and AI. It also introduces the idea of smart cities using robotics.

This unique compendium discusses some core ideas for the development and implementation of machine learning from three different perspectives — the statistical perspective, the artificial neural network perspective and the deep learning methodology.The useful reference text represents a solid foundation in machine learning and should prepare readers to apply and understand machine learning algorithms as well as to invent new machine learning methods. It tells a story outgoing from a perceptron to deep learning highlighted with concrete examples, including exercises and answers for the students.Related Link(s)

This book provides insights into the Third International Conference on Intelligent Systems and Signal Processing (eISSP 2020) held By Electronics & Communication Engineering Department of G H Patel College of Engineering & Technology, Gujarat, India, during 28–30 December 2020. The book comprises contributions by the research scholars and academicians covering the topics in signal processing and communication engineering, applied electronics and emerging technologies, Internet of Things (IoT), robotics, machine learning, deep learning and artificial intelligence. The main emphasis of the book is on dissemination of information, experience and research results on the current topics of interest through in-depth discussions and contribution of researchers from all over world. The book is useful for research community, academicians, industrialists and postgraduate students across the globe.

This book presents best selected papers presented at the International Conference on Paradigms of Computing, Communication and Data Sciences (PCCDS 2020), organized by National Institute of Technology, Kurukshetra, India, during 1–3 May 2020. It discusses high-quality and cutting-edge research in the areas of advanced computing, communications and data science techniques. The book is a collection of latest research articles in computation algorithm, communication and data sciences, intertwined with each other for efficiency.

This book is a collection of outstanding content written by experts working in the field of multimedia security. It provides an insight about various techniques used in multimedia security and identifies its progress in both technological and algorithmic perspectives. In the contemporary world, digitization offers an effective mechanism to process, preserve and transfer all types of information. The incredible progresses in computing and communication technologies augmented by economic feasibility have revolutionized the world. The availability of efficient algorithms together with inexpensive digital recording and storage peripherals have created a multimedia era bringing conveniences to people in sharing the digital data that includes images, audio and video. The ever-increasing pace, at which the multimedia and communication technology is growing, has also made it possible to combine, replicate and distribute the content faster and easier, thereby empowering mankind by having awealth of information at their disposal. However, security of multimedia is giving tough time to the research community around the globe, due to ever-increasing and efficient attacks carried out on multimedia data by intruders, eves-droppers and hackers. Further, duplication, unauthorized use and mal-distribution of digital content have become a serious challenge as it leads to copyright violation and is considered to be the principal reason that refrains the information providers in freely sharing their proprietary digital content. The book is useful for students, researchers and professionals to advance their study.

As industries are rapidly being digitalized and information is being more heavily stored and transmitted online, the security of information has become a top priority in securing the use of online networks as a safe and effective platform. With the vast and diverse potential of artificial intelligence (AI) applications, it has become easier than ever to identify cyber vulnerabilities, potential threats, and the identification of solutions to these unique problems. The latest tools and technologies for AI applications have untapped potential that conventional systems and human security systems cannot meet, leading AI to be a frontrunner in the fight against malware, cyber-attacks, and various security issues. However, even with the tremendous progress AI has made within the sphere of security, it's important to understand the impacts, implications, and critical issues and challenges of AI applications along with the many benefits and emerging trends in this essential field of security-based research. Research Anthology on Artificial Intelligence Applications in Security seeks to address the fundamental advancements and technologies being used in AI applications for the security of digital data and information. The included chapters cover a wide range of topics related to AI in security stemming from the development and design of these applications, the latest tools and technologies, as well as the utilization of AI and what challenges and impacts have been discovered along the way. This resource work is a critical exploration of the latest research on security and an overview of how AI has impacted the field and will continue to advance as an essential tool for security, safety, and privacy online. This book is ideally intended for cyber security analysts, computer engineers, IT specialists, practitioners, stakeholders, researchers, academicians, and students interested in AI applications in the realm of security research.

The book Intelligent Systems and Applications - Proceedings of the 2020 Intelligent Systems Conference is a remarkable collection of chapters covering a wider range of topics in areas of intelligent systems and artificial intelligence and their applications to the real world. The Conference attracted a total of 545 submissions from many academic pioneering researchers, scientists, industrial engineers, students from all around the world. These submissions underwent a double-blind peer review process. Of those 545 submissions, 177 submissions have been selected to be included in these proceedings. As intelligent systems continue to replace and sometimes outperform human intelligence in decision-making processes, they have enabled a larger number of problems to be tackled more effectively.This branching out of computational intelligence in several directions and use of intelligent systems in everyday applications have created the need for such an international conference which serves as a venue to report on up-to-the-minute innovations and developments. This book collects both theory and application based chapters on all aspects of artificial intelligence, from classical to intelligent scope. We hope that readers find the volume interesting and valuable; it provides the state of the art intelligent methods and techniques for solving real world problems along with a vision of the future research.

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.

A practical guide to understanding the latest features of the Rust programming language, useful libraries, and frameworks that will help you design and develop interesting projectsKey FeaturesWork through projects that will help you build high-performance applications with RustDelve into concepts such as error handling, memory management, concurrency, generics, and macros with RustImprove business productivity by choosing the right libraries and frameworks for your applicationsBook DescriptionRust is a community-built language that solves pain points present in many other languages, thus improving performance and safety. In this book, you will explore the latest features of Rust by building robust applications across different domains and platforms.The book gets you up and running with high-quality open source libraries and frameworks available in the Rust ecosystem that can help you to develop efficient applications with Rust. You'll learn how to build projects in domains such as data access, RESTful web services, web applications, 2D games for web and desktop, interpreters and compilers, emulators, and Linux Kernel modules. For each of these application types, you'll use frameworks such as Actix, Tera, Yew, Quicksilver, ggez, and nom. This book will not only help you to build on your knowledge of Rust but also help you to choose an appropriate framework for building your project.By the end of this Rust book, you will have learned how to build fast and safe applications with Rust and have the real-world experience you need to advance in your career.What you will learnAccess TOML, JSON, and XML files and SQLite, PostgreSQL, and Redis databasesDevelop a RESTful web service using JSON payloadsCreate a web application using HTML templates and JavaScript and a frontend web application or web game using WebAssemblyBuild desktop 2D gamesDevelop an interpreter and a compiler for a programming languageCreate a machine language emulatorExtend the Linux Kernel with loadable modulesWho this book is forThis Rust programming book is for developers who want to get hands-on experience with implementing their knowledge of Rust programming, and are looking for expert advice on which libraries and frameworks they can adopt to develop software that typically uses the Rust language.

This book, presented in three volumes, examines �environmental� disciplines in relation to major players in contemporary science: Big Data, artificial intelligence and cloud computing. Today, there is a real sense of urgency regarding the evolution of computer technology, the ever-increasing volume of data, threats to our climate and the sustainable development of our planet. As such, we need to reduce technology just as much as we need to bridge the global socio-economic gap between the North and South; between universal free access to data (open data) and free software (open source). In this book, we pay particular attention to certain environmental subjects, in order to enrich our understanding of cloud computing. These subjects are: erosion; urban air pollution and atmospheric pollution in Southeast Asia; melting permafrost (causing the accelerated release of soil organic carbon in the atmosphere); alert systems of environmental hazards (such as forest fires, prospective modeling of socio-spatial practices and land use); and web fountains of geographical data. Finally, this book asks the question: in order to find a pattern in the data, how do we move from a traditional computing model-based world to pure mathematical research? After thorough examination of this topic, we conclude that this goal is both transdisciplinary and achievable.

This contributed volume discusses essential topics and the fundamentals for Big Data Emergency Management and primarily focusses on the application of Big Data for Emergency Management. It walks the reader through the state of the art, in different facets of the big disaster data field. This includes many elements that are important for these technologies to have real-world impact. This book brings together different computational techniques from: machine learning, communication network analysis, natural language processing, knowledge graphs, data mining, and information visualization, aiming at methods that are typically used for processing big emergency data. This book also provides authoritative insights and highlights valuable lessons by distinguished authors, who are leaders in this field.Emergencies are severe, large-scale, non-routine events that disrupt the normal functioning of a community or a society, causing widespread and overwhelming losses and impacts. Emergency Management is the process of planning and taking actions to minimize the social and physical impact of emergencies and reduces the community's vulnerability to the consequences of emergencies. Information exchange before, during and after the disaster periods can greatly reduce the losses caused by the emergency. This allows people to make better use of the available resources, such as relief materials and medical supplies. It also provides a channel through which reports on casualties and losses in each affected area, can be delivered expeditiously. Big Data-Driven Emergency Management refers to applying advanced data collection and analysis technologies to achieve more effective and responsive decision-making during emergencies.Researchers, engineers and computer scientists working in Big Data Emergency Management, who need to deal with large and complex sets of data will want to purchase this book. Advanced-level students interested in data-driven emergency/crisis/disaster management will also want to purchase this book as a study guide.

As digital media, tools, and techniques continue to impact and advance the humanities, Doing More Digital Humanities provides practical information on how to do digital humanities work. This book offers: A comprehensive, practical guide to the digital humanities. Accessible introductions, which in turn provide the grounding for the more advanced chapters within the book. An overview of core competencies, to help research teams, administrators, and allied groups, make informed decisions about suitable collaborators, skills development, and workflow. Guidance for individuals, collaborative teams, and academic managers who support digital humanities researchers. Contextualized case studies, including examples of projects, tools, centres, labs, and research clusters. Resources for starting digital humanities projects, including links to further readings, training materials and exercises, and resources beyond. Additional augmented content that complements the guidance and case studies in Doing Digital Humanities (Routledge, 2016).

This book presents a remarkable collection of chapters covering a wide range of topics in the areas of Computer Vision, both from theoretical and application perspectives. It gathers the proceedings of the Computer Vision Conference (CVC 2019), held in Las Vegas, USA from May 2 to 3, 2019. The conference attracted a total of 371 submissions from pioneering researchers, scientists, industrial engineers, and students all around the world. These submissions underwent a double-blind peer review process, after which 118 (including 7 poster papers) were selected for inclusion in these proceedings.The book's goal is to reflect the intellectual breadth and depth of current research on computer vision, from classical to intelligent scope. Accordingly, its respective chapters address state-of-the-art intelligent methods and techniques for solving real-world problems, while also outlining future research directions. Topic areas covered include Machine Vision and Learning, Data Science,Image Processing, Deep Learning, and Computer Vision Applications.

The two-volume set CCIS 1332 and 1333 constitutes thoroughly refereed contributions presented at the 27th International Conference on Neural Information Processing, ICONIP 2020, held in Bangkok, Thailand, in November 2020.•For ICONIP 2020 a total of 378 papers was carefully reviewed and selected for publication out of 618 submissions. The 191 papers included in this volume set were organized in topical sections as follows: data mining; healthcare analytics-improving healthcare outcomes using big data analytics; human activity recognition; image processing and computer vision; natural language processing; recommender systems; the 13th international workshop on artificial intelligence and cybersecurity; computational intelligence; machine learning; neural network models; robotics and control; and time series analysis. • The conference was held virtually due to the COVID-19 pandemic.

Data is bigger, arrives faster, and comes in a variety of formatsâ??and it all needs to be processed at scale for analytics or machine learning. But how can you process such varied workloads efficiently? Enter Apache Spark.Updated to include Spark 3.0, this second edition shows data engineers and data scientists why structure and unification in Spark matters. Specifically, this book explains how to perform simple and complex data analytics and employ machine learning algorithms. Through step-by-step walk-throughs, code snippets, and notebooks, youâ??ll be able to:Learn Python, SQL, Scala, or Java high-level Structured APIsUnderstand Spark operations and SQL EngineInspect, tune, and debug Spark operations with Spark configurations and Spark UIConnect to data sources: JSON, Parquet, CSV, Avro, ORC, Hive, S3, or KafkaPerform analytics on batch and streaming data using Structured StreamingBuild reliable data pipelines with open source Delta Lake and SparkDevelop machine learning pipelines with MLlib and productionize models using MLflow

This is the first of three volumes that, together, give an exposition of the mathematics of grades 9–12 that is simultaneously mathematically correct and grade-level appropriate. The volumes are consistent with CCSSM (Common Core State Standards for Mathematics) and aim at presenting the mathematics of K–12 as a totally transparent subject. The present volume begins with fractions, then rational numbers, then introductory geometry that can make sense of the slope of a line, then an explanation of the correct use of symbols that makes sense of “variables”, and finally a systematic treatment of linear equations that explains why the graph of a linear equation in two variables is a straight line and why the usual solution method for simultaneous linear equations “by substitutions” is correct. This book should be useful for current and future teachers of K–12 mathematics, as well as for some high school students and for education professionals.

This book makes the case for a pragmatist approach to the practice of social inquiry and knowledge production. Through diverse examples from multiple disciplines, contributors explore the power of pragmatism to inform a practice of inquiry that is democratic, community-centred, problem-oriented and experimental. Drawing from both classical and neo-pragmatist perspectives, the book advances a pragmatist sensibility in which truth and knowledge are contingent rather than universal, made rather than found, provisional rather than dogmatic, subject to continuous experimentation rather than ultimate proof, and verified in their application in action rather than in the accuracy of their representation of an antecedent reality. The Power of Pragmatism offers a path forward for mobilizing the practice of inquiry and knowledge production on behalf of achieving what Dewey called a sense for the better kind of life to be led.

Because it makes the distribution and transmission of digital information much easier and more cost effective, multimedia has emerged as a top resource in the modern era. In spite of the opportunities that multimedia creates for businesses and companies, information sharing remains vulnerable to cyber attacks and hacking due to the open channels in which this data is being transmitted. Protecting the authenticity and confidentiality of information is a top priority for all professional fields that currently use multimedia practices for distributing digital data. The Handbook of Research on Multimedia Cyber Security provides emerging research exploring the theoretical and practical aspects of current security practices and techniques within multimedia information and assessing modern challenges. Featuring coverage on a broad range of topics such as cryptographic protocols, feature extraction, and chaotic systems, this book is ideally designed for scientists, researchers, developers, security analysts, network administrators, scholars, IT professionals, educators, and students seeking current research on developing strategies in multimedia security.

Kälin and Kochenov's Quality of Nationality Index (QNI) ranks the objective value of all nationalities as legal statuses of attachment to states. Using a wide variety of strictly quantifiable data to gauge the opportunities presented and limitations imposed by nationalities on their holders, the QNI provides a comprehensive ranking of the intrinsic quality of each citizenship status in the world. Both the internal value (economic opportunities, human development and peace and stability) and the external value (including the number and quality of visa-free travel and, crucially, settlement destinations) of all the nationalities in the world are measured, only to reveal the reality that the quality of nationalities is not correlated with the prestige of the issuing states.Beautifully produced, richly illustrated and accompanied by insightful expert commentary, the QNI is the seminal reference for the citizenship aficionados. It is also an invaluable tool to illustrate the huge discrepancies in the value of the nationalities of the world: showcasing first-hand the unequal distribution of rights and opportunities which different nationalities bring to their holders.The full QNI dataset on which this work is based is available in open access on Mendeley.

Advances in Computational Techniques for Biomedical Image Analysis: Methods and Applications focuses on post-acquisition challenges such as image enhancement, detection of edges and objects, analysis of shape, quantification of texture and sharpness, and pattern analysis. It discusses the archiving and transfer of images, presents a selection of techniques for the enhancement of contrast and edges, for noise reduction and for edge-preserving smoothing. It examines various feature detection and segmentation techniques, together with methods for computing a registration or normalization transformation. Advances in Computational Techniques for Biomedical Image Analysis: Method and Applications is ideal for researchers and post graduate students developing systems and tools for health-care systems. - Covers various challenges and common research issues related to biomedical image analysis - Describes advanced computational approaches for biomedical image analysis - Shows how algorithms are applied to a broad range of application areas, including Chest X-ray, breast CAD, lung and chest, microscopy and pathology, etc. - Explores a range of computational algorithms and techniques, such as neural networks, fuzzy sets, and evolutionary optimization - Explores cloud based medical imaging together with medical imaging security and forensics

This book constitutes the refereed proceedings of the 23rd Brazilian Symposium on Formal Methods, SBMF 2020, which was supposed to take place in Ouro Preto, Brazil, in November 2020. Instead the symposium took place virtually due to the COVID-19 pandemic. The 10 regular papers presented together with 3 invited talks in this book were carefully reviewed and selected from 17 submissions. The papers are organized in topical sections such as: experience reports; models, languages and semantics; and software product lines.Chapter ‘Safety Assurance of a High Voltage Controller for an Industrial Robotic System'is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

This book delivers stimulating input for a broad range of researchers, from geographers and ecologists to psychologists interested in spatial perception and physicists researching in complex systems. How can one decide whether one surface or spatial object is more complex than another? What does it require to measure the spatial complexity of small maps, and why does this matter for nature, science and technology? Drawing from algorithmics, geometry, topology, probability and informatics, and with examples from everyday life, the reader is invited to cross the borders into the bewildering realm of spatial complexity, as it emerges from the study of geographic maps, landscapes, surfaces, knots, 3D and 4D objects. The mathematical and cartographic experiments described in this book lead to hypotheses and enigmas with ramifications in aesthetics and epistemology.

Explore how a data storage system works – from data ingestion to representationKey FeaturesUnderstand how artificial intelligence, machine learning, and deep learning are different from one anotherDiscover the data storage requirements of different AI apps using case studiesExplore popular data solutions such as Hadoop Distributed File System (HDFS) and Amazon Simple Storage Service (S3)Book DescriptionSocial networking sites see an average of 350 million uploads daily - a quantity impossible for humans to scan and analyze. Only AI can do this job at the required speed, and to leverage an AI application at its full potential, you need an efficient and scalable data storage pipeline. The Artificial Intelligence Infrastructure Workshop will teach you how to build and manage one.The Artificial Intelligence Infrastructure Workshop begins taking you through some real-world applications of AI. You'll explore the layers of a data lake and get to grips with security, scalability, and maintainability. With the help of hands-on exercises, you'll learn how to define the requirements for AI applications in your organization. This AI book will show you how to select a database for your system and run common queries on databases such as MySQL, MongoDB, and Cassandra. You'll also design your own AI trading system to get a feel of the pipeline-based architecture. As you learn to implement a deep Q-learning algorithm to play the CartPole game, you'll gain hands-on experience with PyTorch. Finally, you'll explore ways to run machine learning models in production as part of an AI application.By the end of the book, you'll have learned how to build and deploy your own AI software at scale, using various tools, API frameworks, and serialization methods.What you will learnGet to grips with the fundamentals of artificial intelligenceUnderstand the importance of data storage and architecture in AI applicationsBuild data storage and workflow management systems with open source toolsContainerize your AI applications with tools such as DockerDiscover commonly used data storage solutions and best practices for AI on Amazon Web Services (AWS)Use the AWS CLI and AWS SDK to perform common data tasksWho this book is forIf you are looking to develop the data storage skills needed for machine learning and AI and want to learn AI best practices in data engineering, this workshop is for you. Experienced programmers can use this book to advance their career in AI. Familiarity with programming, along with knowledge of exploratory data analysis and reading and writing files using Python will help you to understand the key concepts covered.

This is the first volume in a new series on'Great Minds in Regional Science,'which seeks to present a contemporary view on the scientific relevance of the work done by great thinkers in regional science. It presents, among others, Walter Isard, Martin Beckmann and Gunnar Myrdal. Each contribution combines factual biographical information, a description of their major contributions, and a discussion of the broader context of the work, as well as an assessment of its current relevance, scientific recognition and policy impact. The book attempts to fill a gap in our knowledge, and to respond to the growing interest in the formation and development of the field of regional science and its key influential figures.

Big Data is a concept of major relevance in today's world, sometimes highlighted as a key asset for productivity growth, innovation, and customer relationship, whose popularity has increased considerably during the last years. Areas like smart cities, manufacturing, retail, finance, software development, environment, digital media, among others, can benefit from the collection, storage, processing, and analysis of Big Data, leveraging unprecedented data-driven workflows and considerably improved decision-making processes.The concept of a Big Data Warehouse (BDW) is emerging as either an augmentation or a replacement of the traditional Data Warehouse (DW), a concept that has a long history as one of the most valuable enterprise data assets. Nevertheless, research in Big Data Warehousing is still in its infancy, lacking an integrated and validated approach for designing and implementing both the logical layer (data models, data flows, and interoperability between components) and the physical layer (technological infrastructure) of these complex systems.This book addresses models and methods for designing and implementing Big Data Systems to support mixed and complex decision processes, giving special attention to BDWs as a way of efficiently storing and processing batch or streaming data for structured or semi-structured analytical problems.

This book constitutes the refereed proceedings of the 32nd International Conference on Advanced Information Systems Engineering, CAiSE 2020, held in Grenoble, France, in June 2020.• The 33 full papers presented in this volume were carefully reviewed and selected from 185 submissions. The book also contains one invited talk in full paper length. The papers were organized in topical sections named: distributed applications; AI and big data in IS; process mining and analysis; requirements and modeling; and information systems engineering. Abstracts on the CAiSE 2020 tutorials can be found in the back matter of the volume.•The conference was held virtually due to the COVID-19 pandemic.

The two-volume set LNCS 11944-11945 constitutes the proceedings of the 19th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2019, held in Melbourne, Australia, in December 2019. The 73 full and 29 short papers presented were carefully reviewed and selected from 251 submissions. The papers are organized in topical sections on: Parallel and Distributed Architectures, Software Systems and Programming Models, Distributed and Parallel and Network-based Computing, Big Data and its Applications, Distributed and Parallel Algorithms, Applications of Distributed and Parallel Computing, Service Dependability and Security, IoT and CPS Computing, Performance Modelling and Evaluation.

Fundamentals of Satellite Remote Sensing: An Environmental Approach, Third Edition, is a definitive guide to remote sensing systems that focuses on satellite-based remote sensing tools and methods for space-based Earth observation (EO). It presents the advantages of using remote sensing data for studying and monitoring the planet, and emphasizes concepts that make the best use of satellite data. The book begins with an introduction to the basic processes that ensure the acquisition of space-borne imagery, and provides an overview of the main satellite observation systems. It then describes visual and digital image analysis, highlights various interpretation techniques, and outlines their applications to science and management. The latter part of the book covers the integration of remote sensing with Geographic Information System (GIS) for environmental analysis. This latest edition has been written to reflect a global audience and covers the most recent advances incorporated since the publication of the previous book, relating to the acquisition and interpretation of remotely sensed data.New in the Third Edition: Includes additional illustrations in full color. Uses sample images acquired from different ecosystems at different spatial resolutions to illustrate different interpretation techniques. Includes updated EO missions, such as the third generations of geostationary meteorological satellites, the new polar orbiting platforms (Suomi), the ESA Sentinels program, and high-resolution commercial systems. Includes extended coverage of radar and LIDAR processing methods. Includes all new information on near-ground missions, including unmanned aerial vehicles (UAVs). Covers new ground sensors, as well as machine-learning approaches to classification. Adds more focus on land surface characterization, time series, change detection, and ecosystem processes. Extends the interactions of EO data and GIS that cover different environmental problems, with particular relevance to global observation. Fundamentals of Satellite Remote Sensing: An Environmental Approach, Third Edition, details the tools that provide global, recurrent, and comprehensive views of the processes affecting the Earth. As one of CRC's Essential titles, this book and stands out as one of the best in its field and is a must-have for researchers, academics, students, and professionals involved in the field of environmental science, as well as for libraries developing collections on the forefront of this industry.

This open access book is part of the LAMBDA Project (Learning, Applying, Multiplying Big Data Analytics), funded by the European Union, GA No. 809965. Data Analytics involves applying algorithmic processes to derive insights. Nowadays it is used in many industries to allow organizations and companies to make better decisions as well as to verify or disprove existing theories or models. The term data analytics is often used interchangeably with intelligence, statistics, reasoning, data mining, knowledge discovery, and others. The goal of this book is to introduce some of the definitions, methods, tools, frameworks, and solutions for big data processing, starting from the process of information extraction and knowledge representation, via knowledge processing and analytics to visualization, sense-making, and practical applications. Each chapter in this book addresses some pertinent aspect of the data processing chain, with a specific focus on understanding Enterprise Knowledge Graphs, Semantic Big Data Architectures, and Smart Data Analytics solutions. This book is addressed to graduate students from technical disciplines, to professional audiences following continuous education short courses, and to researchers from diverse areas following self-study courses. Basic skills in computer science, mathematics, and statistics are required.

In this book, Cathleen Heil addresses the question of how to conceptually understand children's spatial thought in the context of geometry education. She proposes that in order to help children develop their abilities to successfully grasp and manipulate the spatial relations they experience in their everyday lives, spatial thought should not only be addressed in written or tabletop settings at school. Instead, geometry education should also focus on settings involving real space, such as during reasoning with maps.In a first part of this book, she theoretically addresses the construct of spatial thought at different scales of space from a cognitive psychological point of view and shows that maps can be rich sources for spatial thinking. In a second part, she proposes how to measure children's spatial thought in a paper-and-pencil setting and map-based setting in real space. In a third, empirical part, she examines the relations between children's spatialthought in those two settings both at a manifest and latent level.

Complete recipes spread across 15 chapters to help you overcome commonly faced issues by Python for everybody across the globe. Each recipe takes a problem-solution approach to resolve for effective Python.Key FeaturesDevelop expressive and effective Python programsBest practices and common idioms through carefully explained recipesDiscover new ways to apply Python for data-focused developmentMake use of Python's optional type annotationsBook DescriptionPython is the preferred choice of developers, engineers, data scientists, and hobbyists everywhere. It is a great language that can power your applications and provide great speed, safety, and scalability. It can be used for simple scripting or sophisticated web applications. By exposing Python as a series of simple recipes, this book gives you insight into specific language features in a particular context. Having a tangible context helps make the language or a given standard library feature easier to understand. This book comes with 133 recipes on the latest version of Python 3.8. The recipes will benefit everyone, from beginners just starting out with Python to experts. You'll not only learn Python programming concepts but also how to build complex applications. The recipes will touch upon all necessary Python concepts related to data structures, object oriented programming, functional programming, and statistical programming. You will get acquainted with the nuances of Python syntax and how to effectively take advantage of it. By the end of this Python book, you will be equipped with knowledge of testing, web services, configuration, and application integration tips and tricks. You will be armed with the knowledge of how to create applications with flexible logging, powerful configuration, command-line options, automated unit tests, and good documentation.What you will learnSee the intricate details of the Python syntax and how to use it to your advantageImprove your coding with Python readability through functionsManipulate data effectively using built-in data structuresGet acquainted with advanced programming techniques in PythonEquip yourself with functional and statistical programming featuresWrite proper tests to be sure a program works as advertisedIntegrate application software using PythonWho this book is forThe Python book is for web developers, programmers, enterprise programmers, engineers, and big data scientists. If you are a beginner, this book will get you started. If you are experienced, it will expand your knowledge base. A basic knowledge of programming would help.

Provides a smooth and pleasant transition from first-year calculus to upper-level mathematics courses in real analysis, abstract algebra and number theory Most universities require students majoring in mathematics to take a “transition to higher math” course that introduces mathematical proofs and more rigorous thinking. Such courses help students be prepared for higher-level mathematics course from their onset. Advanced Mathematics: A Transitional Reference provides a “crash course” in beginning pure mathematics, offering instruction on a blendof inductive and deductive reasoning. By avoiding outdated methods and countless pages of theorems and proofs, this innovative textbook prompts students to think about the ideas presented in an enjoyable, constructive setting. Clear and concise chapters cover all the essential topics students need to transition from the'rote-orientated'courses of calculus to the more rigorous'proof-orientated” advanced mathematics courses. Topics include sentential and predicate calculus, mathematical induction, sets and counting, complex numbers, point-set topology, and symmetries, abstract groups, rings, and fields. Each section contains numerous problems for students of various interests and abilities. Ideally suited for a one-semester course, this book: Introduces students to mathematical proofs and rigorous thinking Provides thoroughly class-tested material from the authors own course in transitioning to higher math Strengthens the mathematical thought process of the reader Includes informative sidebars, historical notes, and plentiful graphics Offers a companion website to access a supplemental solutions manual for instructors Advanced Mathematics: A Transitional Reference is a valuable guide for undergraduate students who have taken courses in calculus, differential equations, or linear algebra, but may not be prepared for the more advanced courses of real analysis, abstract algebra, and number theory that await them. This text is also useful for scientists, engineers, and others seeking to refresh their skills in advanced math.

This book constitutes the refereed proceedings of the 26th International Conference on Information and Software Technologies, ICIST 2020, held in Kaunas, Lithuania, in October 2020.The 23 full papers and 7 short papers presented were carefully reviewed and selected from 78 submissions. The papers are organized in topical sections on ​business intelligence for information and software system; software engineering; information technology applications.

This unique compendium presents an introduction to problem solving, information theory, statistical machine learning, stochastic methods and quantum computation. It indicates how to apply quantum computation to problem solving, machine learning and quantum-like models to decision making — the core disciplines of artificial intelligence.Most of the chapters were rewritten and extensive new materials were updated. New topics include quantum machine learning, quantum-like Bayesian networks and mind in Everett many-worlds.

This book constitutes the proceedings of the 13th International Conference on Network and System Security, NSS 2019, held in Sapporo, Japan, in December 2019. The 36 full papers and 7 short papers presented together with 4 invited papers in this book were carefully reviewed and selected from 89 initial submissions. The papers cover a wide range of topics in the field, including authentication, access control, availability, integrity, privacy, confidentiality, dependability and sustainability of computer networks and systems.

This book constitutes the proceedings of the 15th International Conference on Advanced Data Mining and Applications, ADMA 2019, held in Dalian, China in November 2019. The 39 full papers presented together with 26 short papers and 2 demo papers were carefully reviewed and selected from 170 submissions. The papers were organized in topical sections named: Data Mining Foundations; Classification and Clustering Methods; Recommender Systems; Social Network and Social Media; Behavior Modeling and User Profiling; Text and Multimedia Mining; Spatial-Temporal Data; Medical and Healthcare Data/Decision Analytics; and Other Applications.

This book includes original, peer-reviewed research from the 3rd International Conference on Emerging Trends in Electrical, Communication and Information Technologies (ICECIT 2018), held at Srinivasa Ramanujan Institute of Technology, Ananthapuramu, Andhra Pradesh, India in December 2018. It covers the latest research trends and developments in the areas of Electrical Engineering, Electronic and Communication Engineering, and Computer Science and Information.

This book constitutes the refereed proceedings of the third Workshop on Computer Vision Applications, WCVA 2018, held in Conjunction with ICVGIP 2018, in Hyderabad, India, in December 2018. The 10 revised full papers presented were carefully reviewed and selected from 32 submissions. The papers focus on computer vision; industrial applications; medical applications; and social applications.

This book constitutes the refereed proceedings of the 4th International Conference on Digital Economy, ICDEc 2019, held in Beirut, Lebanon, in April 2019. The conference was founded in 2016 to discuss innovative research and projects related to the support role of Information System Technologies in the digital transformation process, business innovation and e-commerce. The 31 papers presented in this volume were carefully reviewed and selected from 89 submissions. The theme of ICDEc 2019 was “Digital Economy: Emerging Technologies and Business Innovation”. The papers were organized in topical sections named: digital transformation; e-finance; social media communication; intelligent systems; e-commerce and business analytics; e-learning and cloud education; e-commerce and digital economy; data science; digital marketing; and digital business model.

This book addresses the latest research advances, innovations, and applications in the field of urban drainage and water management as presented by leading researchers, scientists and practitioners from around the world at the 11th International Conference on Urban Drainage Modelling (UDM), held in Palermo, Italy from 23 to 26 September, 2018. The conference was promoted and organized by the University of Palermo, Italy and the International Working Group on Data and Models, with the support of four of the world's leading organizations in the water sector: the International Water Association (IWA), International Association for Hydro-Environment Engineering and Research (IAHR), Environmental & Water Resources Institute (EWRI) - ASCE, and the International Environmental Modelling and Software Society (iEMSs). The topics covered are highly diverse and include drainage and impact mitigation, water quality, rainfall in urban areas, urban hydrologic and hydraulic processes, tools, techniques and analysis in urban drainage modelling, modelling interactions and integrated systems, transport and sewer processes (incl. micropollutants and pathogens), and water management and climate change. The conference's primary goal is to offer a forum for promoting discussions amongst scientists and professionals on the interrelationships between the entire water cycle, environment and society.

Gain expertise in ML techniques with AWS to create interactive apps using SageMaker, Apache Spark, and TensorFlow.Key FeaturesBuild machine learning apps on Amazon Web Services (AWS) using SageMaker, Apache Spark and TensorFlowLearn model optimization, and understand how to scale your models using simple and secure APIsDevelop, train, tune and deploy neural network models to accelerate model performance in the cloudBook DescriptionAWS is constantly driving new innovations that empower data scientists to explore a variety of machine learning (ML) cloud services. This book is your comprehensive reference for learning and implementing advanced ML algorithms in AWS cloud.As you go through the chapters, you'll gain insights into how these algorithms can be trained, tuned and deployed in AWS using Apache Spark on Elastic Map Reduce (EMR), SageMaker, and TensorFlow. While you focus on algorithms such as XGBoost, linear models, factorization machines, and deep nets, the book will also provide you with an overview of AWS as well as detailed practical applications that will help you solve real-world problems. Every practical application includes a series of companion notebooks with all the necessary code to run on AWS. In the next few chapters, you will learn to use SageMaker and EMR Notebooks to perform a range of tasks, right from smart analytics, and predictive modeling, through to sentiment analysis. By the end of this book, you will be equipped with the skills you need to effectively handle machine learning projects and implement and evaluate algorithms on AWS.What you will learnManage AI workflows by using AWS cloud to deploy services that feed smart data productsUse SageMaker services to create recommendation modelsScale model training and deployment using Apache Spark on EMRUnderstand how to cluster big data through EMR and seamlessly integrate it with SageMakerBuild deep learning models on AWS using TensorFlow and deploy them as servicesEnhance your apps by combining Apache Spark and Amazon SageMakerWho this book is forThis book is for data scientists, machine learning developers, deep learning enthusiasts and AWS users who want to build advanced models and smart applications on the cloud using AWS and its integration services. Some understanding of machine learning concepts, Python programming and AWS will be beneficial.

Get started with Apache Flink, the open source framework that powers some of the world's largest stream processing applications. With this practical book, you'll explore the fundamental concepts of parallel stream processing and discover how this technology differs from traditional batch data processing.Longtime Apache Flink committers Fabian Hueske and Vasia Kalavri show you how to implement scalable streaming applications with Flink's DataStream API and continuously run and maintain these applications in operational environments. Stream processing is ideal for many use cases, including low-latency ETL, streaming analytics, and real-time dashboards as well as fraud detection, anomaly detection, and alerting. You can process continuous data of any kind, including user interactions, financial transactions, and IoT data, as soon as you generate them.Learn concepts and challenges of distributed stateful stream processingExplore Flink's system architecture, including its event-time processing mode and fault-tolerance modelUnderstand the fundamentals and building blocks of the DataStream API, including its time-based and statefuloperatorsRead data from and write data to external systems with exactly-once consistencyDeploy and configure Flink clustersOperate continuously running streaming applications

This open access book constitutes the refereed proceedings of the 15th International Conference on Semantic Systems, SEMANTiCS 2019, held in Karlsruhe, Germany, in September 2019. The 20 full papers and 8 short papers presented in this volume were carefully reviewed and selected from 88 submissions. They cover topics such as: web semantics and linked (open) data; machine learning and deep learning techniques; semantic information management and knowledge integration; terminology, thesaurus and ontology management; data mining and knowledge discovery; semantics in blockchain and distributed ledger technologies.

This book constitutes the refereed proceedings of the 19th International Conference on Engineering Applications of Neural Networks, EANN 2019, held in Xersonisos, Crete, Greece, in May 2019.The 35 revised full papers and 5 revised short papers presented were carefully reviewed and selected from 72 submissions. The papers are organized in topical sections on AI in energy management - industrial applications; biomedical - bioinformatics modeling; classification - learning; deep learning; deep learning - convolutional ANN; fuzzy - vulnerability - navigation modeling; machine learning modeling - optimization; ML - DL financial modeling; security - anomaly detection; 1st PEINT workshop.

The two-volume set of LNCS 11778 and 11779 constitutes the refereed proceedings of the 18th International Semantic Web Conference, ISWC 2019, held in Auckland, New Zealand, in October 2019. The ISWC conference is the premier international forum for the Semantic Web / Linked Data Community.The total of 74 full papers included in this volume was selected from 283 submissions. The conference is organized in three tracks: for the Research Track 42 full papers were selected from 194 submissions; the Resource Track contains 21 full papers, selected from 64 submissions; and the In-Use Track features 11 full papers which were selected from 25 submissions to this track.The chapter'The SEPSES knowledge graph: An integrated resource for cybersecurity'is open access under a CC BY 4.0 license at link.springer.com.

The five-volume set LNCS 11536, 11537, 11538, 11539 and 11540 constitutes the proceedings of the 19th International Conference on Computational Science, ICCS 2019, held in Faro, Portugal, in June 2019.The total of 65 full papers and 168 workshop papers presented in this book set were carefully reviewed and selected from 573 submissions (228 submissions to the main track and 345 submissions to the workshops). The papers were organized in topical sections named: Part I: ICCS Main Track Part II: ICCS Main Track; Track of Advances in High-Performance Computational Earth Sciences: Applications and Frameworks; Track of Agent-Based Simulations, Adaptive Algorithms and Solvers; Track of Applications of Matrix Methods in Artificial Intelligence and Machine Learning; Track of Architecture, Languages, Compilation and Hardware Support for Emerging and Heterogeneous Systems Part III: Track of Biomedical and Bioinformatics Challenges for Computer Science; Track of Classifier Learning from Difficult Data; Track of Computational Finance and Business Intelligence; Track of Computational Optimization, Modelling and Simulation; Track of Computational Science in IoT and Smart Systems Part IV: Track of Data-Driven Computational Sciences; Track of Machine Learning and Data Assimilation for Dynamical Systems; Track of Marine Computing in the Interconnected World for the Benefit of the Society; Track of Multiscale Modelling and Simulation; Track of Simulations of Flow and Transport: Modeling, Algorithms and Computation Part V: Track of Smart Systems: Computer Vision, Sensor Networks and Machine Learning; Track of Solving Problems with Uncertainties; Track of Teaching Computational Science; Poster Track ICCS 2019Chapter “Comparing Domain-decomposition Methods for the Parallelization of Distributed Land Surface Models” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

Gain the key language concepts and programming techniques of Scala in the context of big data analytics and Apache Spark. The book begins by introducing you to Scala and establishes a firm contextual understanding of why you should learn this language, how it stands in comparison to Java, and how Scala is related to Apache Spark for big data analytics. Next, you'll set up the Scala environment ready for examining your first Scala programs. This is followed by sections on Scala fundamentals including mutable/immutable variables, the type hierarchy system, control flow expressions and code blocks.The author discusses functions at length and highlights a number of associated concepts such as functional programming and anonymous functions. The book then delves deeper into Scala's powerful collections system because many of Apache Spark's APIs bear a strong resemblance to Scala collections. Along the way you'll see thedevelopment life cycle of a Scala program. This involves compiling and building programs using the industry-standard Scala Build Tool (SBT). You'll cover guidelines related to dependency management using SBT as this is critical for building large Apache Spark applications. Scala Programming for Big Data Analytics concludes by demonstrating how you can make use of the concepts to write programs that run on the Apache Spark framework. These programs will provide distributed and parallel computing, which is critical for big data analytics.What You Will LearnSee the fundamentals of Scala as a general-purpose programming languageUnderstand functional programming and object-oriented programming constructs in ScalaUse Scala collections and functions Develop, package and run Apache Spark applications for big data analyticsWho ThisBook Is ForData scientists, data analysts and data engineers who intend to use Apache Spark for large-scale analytics.