Business Modeling and Software Design
This book constitutes the refereed proceedings of the 12h International Symposium on Business Modeling and Software Design, BMSD 2022, which took place in Fribourg, Switzerland, in June 2022.The 12 full and 9 short papers included in this book were carefully reviewed and selected from a total of 56 submissions. BMSD is a leading international forum that brings together researchers and practitioners interested in business modeling and its relation to software design. Particular areas of interest are: Business Processes and Enterprise Engineering; Business Models and Requirements; Business Models and Services; Business Models and Software; Information Systems Architectures and Paradigms; Data Aspects in Business Modeling and Software Development; Blockchain-Based Business Models and Information Systems; IoT and Implications for Enterprise Information Systems. Each year, a special theme is chosen, for making presentations and discussions more focused.The BMSD 2022 theme is: Information Systems Engineering and Trust.
Data Science
This two volume set (CCIS 1628 and 1629) constitutes the refereed proceedings of the 8th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2022 held in Chengdu, China, in August, 2022. The 65 full papers and 26 short papers presented in these two volumes were carefully reviewed and selected from 261 submissions. The papers are organized in topical sections on: Big Data Mining and Knowledge Management; Machine Learning for Data Science; Multimedia Data Management and Analysis.
Data Science
This two volume set (CCIS 1628 and 1629) constitutes the refereed proceedings of the 8th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2022 held in Chengdu, China, in August, 2022. The 65 full papers and 26 short papers presented in these two volumes were carefully reviewed and selected from 261 submissions. The papers are organized in topical sections on: Big Data Management and Applications; Data Security and Privacy; Applications of Data Science; Infrastructure for Data Science; Education Track; Regulatory Technology in Finance.
Human Aspects of Information Security and Assurance
This book constitutes the proceedings of the 16th IFIP WG 11.12 International Symposium on Human Aspects of Information Security and Assurance, HAISA 2022, held in Mytilene, Lesbos, Greece, in July 2022. The 25 papers presented in this volume were carefully reviewed and selected from 30 submissions. They are organized in the following topical sections: cyber security education and training; cyber security culture; privacy; and cyber security management.
Reverse Mathematics
Reverse mathematics studies the complexity of proving mathematical theorems and solving mathematical problems. Typical questions include: Can we prove this result without first proving that one? Can a computer solve this problem? A highly active part of mathematical logic and computability theory, the subject offers beautiful results as well as significant foundational insights.This text provides a modern treatment of reverse mathematics that combines computability theoretic reductions and proofs in formal arithmetic to measure the complexity of theorems and problems from all areas of mathematics. It includes detailed introductions to techniques from computable mathematics, Weihrauch style analysis, and other parts of computability that have become integral to research in the field. Topics and features: Provides a complete introduction to reverse mathematics, including necessary background from computability theory, second order arithmetic, forcing, induction, and model constructionOffers a comprehensive treatment of the reverse mathematics of combinatorics, including Ramsey's theorem, Hindman's theorem, and many other resultsProvides central results and methods from the past two decades, appearing in book form for the first time and including preservation techniques and applications of probabilistic argumentsIncludes a large number of exercises of varying levels of difficulty, supplementing each chapterThe text will be accessible to students with a standard first year course in mathematical logic. It will also be a useful reference for researchers in reverse mathematics, computability theory, proof theory, and related areas.Damir D. Dzhafarov is an Associate Professor of Mathematics at the University of Connecticut, CT, USA. Carl Mummert is a Professor of Computer and Information Technology at Marshall University, WV, USA.
Computer, Communication, and Signal Processing
This book constitutes the refereed proceedings of the 6th International Conference on Computer, Communication, and Signal Processing, ICCSP 2022, held in Chennai, India, in February 2022.* The 21 full and 2 short papers presented in this volume were carefully reviewed and selected from 111 submissions. The papers are categorized into topical sub-headings: artificial intelligence and machine learning; Cyber security; and internet of things.*The conference was held as a virtual event due to the COVID-19 pandemic.
Serverless ETL and Analytics with AWS Glue
Build efficient data lakes that can scale to virtually unlimited size using AWS GlueKey Features: Learn to work with AWS Glue to overcome typical implementation challenges in data lakesCreate and manage serverless ETL pipelines that can scale to manage big dataWritten by AWS Glue community members, this practical guide shows you how to implement AWS Glue in no timeBook Description: Organizations these days have gravitated toward services such as AWS Glue that undertake undifferentiated heavy lifting and provide serverless Spark, enabling you to create and manage data lakes in a serverless fashion. This guide shows you how AWS Glue can be used to solve real-world problems along with helping you learn about data processing, data integration, and building data lakes.Beginning with AWS Glue basics, this book teaches you how to perform various aspects of data analysis such as ad hoc queries, data visualization, and real-time analysis using this service. It also provides a walk-through of CI/CD for AWS Glue and how to shift left on quality using automated regression tests. You'll find out how data security aspects such as access control, encryption, auditing, and networking are implemented, as well as getting to grips with useful techniques such as picking the right file format, compression, partitioning, and bucketing. As you advance, you'll discover AWS Glue features such as crawlers, Lake Formation, governed tables, lineage, DataBrew, Glue Studio, and custom connectors. The concluding chapters help you to understand various performance tuning, troubleshooting, and monitoring options.By the end of this AWS book, you'll be able to create, manage, troubleshoot, and deploy ETL pipelines using AWS Glue.What You Will Learn: Apply various AWS Glue features to manage and create data lakesUse Glue DataBrew and Glue Studio for data preparationOptimize data layout in cloud storage to accelerate analytics workloadsManage metadata including database, table, and schema definitionsSecure your data during access control, encryption, auditing, and networkingMonitor AWS Glue jobs to detect delays and loss of dataIntegrate Spark ML and SageMaker with AWS Glue to create machine learning modelsWho this book is for: This book is for ETL developers, data engineers, and data analysts who want to understand how AWS Glue can help you solve your business problems. Basic knowledge of AWS data services is assumed.
Codeless Time Series Analysis with KNIME
Perform time series analysis using KNIME Analytics Platform, covering both statistical methods and machine learning-based methodsKey Features: Gain a solid understanding of time series analysis and its applications using KNIMELearn how to apply popular statistical and machine learning time series analysis techniquesIntegrate other tools such as Spark, H2O, and Keras with KNIME within the same applicationBook Description: This book will take you on a practical journey, teaching you how to implement solutions for many use cases involving time series analysis techniques.This learning journey is organized in a crescendo of difficulty, starting from the easiest yet effective techniques applied to weather forecasting, then introducing ARIMA and its variations, moving on to machine learning for audio signal classification, training deep learning architectures to predict glucose levels and electrical energy demand, and ending with an approach to anomaly detection in IoT. There's no time series analysis book without a solution for stock price predictions and you'll find this use case at the end of the book, together with a few more demand prediction use cases that rely on the integration of KNIME Analytics Platform and other external tools.By the end of this time series book, you'll have learned about popular time series analysis techniques and algorithms, KNIME Analytics Platform, its time series extension, and how to apply both to common use cases.What You Will Learn: Install and configure KNIME time series integrationImplement common preprocessing techniques before analyzing dataVisualize and display time series data in the form of plots and graphsSeparate time series data into trends, seasonality, and residualsTrain and deploy FFNN and LSTM to perform predictive analysisUse multivariate analysis by enabling GPU training for neural networksTrain and deploy an ML-based forecasting model using Spark and H2OWho this book is for: This book is for data analysts and data scientists who want to develop forecasting applications on time series data. While no coding skills are required thanks to the codeless implementation of the examples, basic knowledge of KNIME Analytics Platform is assumed. The first part of the book targets beginners in time series analysis, and the subsequent parts of the book challenge both beginners as well as advanced users by introducing real-world time series applications.
Principles of Data Management
Data is a valuable corporate asset and its effective management is vital to success. This professional guide covers all the key areas of data management, including database development and corporate data modelling. The new edition adds chapters on linked data, concept systems and big data and artificial intelligence.
The Data Governance Imperative
Attention to corporate information has never been more important than now. The ability to generate accurate business intelligence, accurate financial reports and to understand your business relies on better processes and personal commitment to clean data. Every byte of data that resides inside your company, and some that resides outside its walls, has the potential to make you stronger by giving you the agility, speed and intelligence that none of your competitors yet have. Data governance is the term given to changing the hearts and minds of your company to see the value of such information quality. The Data Governance Imperative is a business person's view of data governance. This practical book covers both strategies and tactics around managing a data governance initiative. The author, Steve Sarsfield, works for a major enterprise software company and is a leading expert in data quality and data governance, focusing on the business perspectives that are important to data champions, front-office employees, and executives. Steve runs an award-winning and world-recognized blog called the Data Governance and Data Quality Insider, offering practical wisdom.
Designing Data Spaces
This open access book provides a comprehensive view on data ecosystems and platform economics from methodical and technological foundations up to reports from practical implementations and applications in various industries. To this end, the book is structured in four parts: Part I "Foundations and Contexts" provides a general overview about building, running, and governing data spaces and an introduction to the IDS and GAIA-X projects. Part II "Data Space Technologies" subsequently details various implementation aspects of IDS and GAIA-X, including eg data usage control, the usage of blockchain technologies, or semantic data integration and interoperability. Next, Part III describes various "Use Cases and Data Ecosystems" from various application areas such as agriculture, healthcare, industry, energy, and mobility. Part IV eventually offers an overview of several "Solutions and Applications", eg including products and experiences from companies like Google, SAP, Huawei, T-Systems, Innopay and many more. Overall, the book provides professionals in industry with an encompassing overview of the technological and economic aspects of data spaces, based on the International Data Spaces and Gaia-X initiatives. It presents implementations and business cases and gives an outlook to future developments. In doing so, it aims at proliferating the vision of a social data market economy based on data spaces which embrace trust and data sovereignty.
Designing Data Spaces
This open access book provides a comprehensive view on data ecosystems and platform economics from methodical and technological foundations up to reports from practical implementations and applications in various industries. To this end, the book is structured in four parts: Part I "Foundations and Contexts" provides a general overview about building, running, and governing data spaces and an introduction to the IDS and GAIA-X projects. Part II "Data Space Technologies" subsequently details various implementation aspects of IDS and GAIA-X, including eg data usage control, the usage of blockchain technologies, or semantic data integration and interoperability. Next, Part III describes various "Use Cases and Data Ecosystems" from various application areas such as agriculture, healthcare, industry, energy, and mobility. Part IV eventually offers an overview of several "Solutions and Applications", eg including products and experiences from companies like Google, SAP, Huawei, T-Systems, Innopay and many more. Overall, the book provides professionals in industry with an encompassing overview of the technological and economic aspects of data spaces, based on the International Data Spaces and Gaia-X initiatives. It presents implementations and business cases and gives an outlook to future developments. In doing so, it aims at proliferating the vision of a social data market economy based on data spaces which embrace trust and data sovereignty.
Database Systems for Advanced Applications. Dasfaa 2022 International Workshops
This volume constitutes the papers of several workshops which were held in conjunction with the 27th International Conference on Database Systems for Advanced Applications, DASFAA 2022, held as virtual event in April 2022. The 30 revised full papers presented in this book were carefully reviewed and selected from 65 submissions. DASFAA 2022 presents the following five workshops: - First workshop on Pattern mining and Machine learning in Big complex Databases (PMBD 2021) - 6th International Workshop on Graph Data Management and Analysis (GDMA 2022) - First International Workshop on Blockchain Technologies (IWBT2022) - 8th International Workshop on Big Data Management and Service (BDMS 2022) - First workshop on Managing Air Quality Through Data Science - 7th International Workshop on Big Data Quality Management (BDQM 2022).
Advances in Enterprise Engineering XV
This book constitutes the proceedings of the 11th Enterprise Engineering Working Conference, EEWC 2021, which was held online on November 12, 2021, and December 16-17, 2021.EEWC aims at addressing the challenges that modern and complex enterprises are facing in a rapidly changing world. The participants of the working conference share a belief that dealing with these challenges requires rigorous and scientific solutions, focusing on the design and engineering of enterprises. The goal of EEWC is to stimulate interaction between the different stakeholders, scientists as well as practitioners, interested in making Enterprise Engineering a reality. The 5 full papers and 3 short papers presented in this volume were carefully reviewed and selected from 16 submissions. The volume also contains 2 keynote papers.
Computer Information Systems and Industrial Management
This book constitutes the proceedings of the 21st International Conference on Computer Information Systems and Industrial Management Applications, CISIM 2022, held in Barranquilla, Colombia, in July 2022. The 28 papers presented together with 3 keynotes were carefully reviewed and selected from 68 submissions. The main topics covered by the chapters in this book are biometrics, security systems, multimedia, classification and clustering, and industrial management as well as interesting papers on computer information systems as applied to wireless networks, computer graphics, and intelligent systems.
Mathematical Foundations of Data Science Using R
The aim of the book is to help students become data scientists. Since this requires a series of courses over a considerable period of time, the book intends to accompany students from the beginning to an advanced understanding of the knowledge and skills that define a modern data scientist. The book presents a comprehensive overview of the mathematical foundations of the programming language R and of its applications to data science.
Advances in Knowledge Discovery and Data Mining
The 3-volume set LNAI 13280, LNAI 13281 and LNAI 13282 constitutes the proceedings of the 26th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2022, which was held during May 2022 in Chengdu, China. The 121 papers included in the proceedings were carefully reviewed and selected from a total of 558 submissions. They were organized in topical sections as follows: Part I: Data Science and Big Data Technologies, Part II: Foundations; and Part III: Applications.
Tidy Modeling with R
Get going with tidymodels, a collection of R packages for modeling and machine learning. Whether you're just starting out or have years of experience with modeling, this practical introduction shows data analysts, business analysts, and data scientists how the tidymodels framework offers a consistent, flexible approach for your work. RStudio engineers Max Kuhn and Julia Silge demonstrate ways to create models by focusing on an R dialect called the tidyverse. Software that adopts tidyverse principles shares both a high-level design philosophy and low-level grammar and data structures, so learning one piece of the ecosystem makes it easier to learn the next. You'll understand why the tidymodels framework has been built to be used by a broad range of people. With this book, you will: Learn the steps necessary to build a model from beginning to end Understand how to use different modeling and feature engineering approaches fluently Examine the options for avoiding common pitfalls of modeling, such as overfitting Learn practical methods to prepare your data for modeling Tune models for optimal performance Use good statistical practices to compare, evaluate, and choose among models
Emerging Computing Paradigms
EMERGING COMPUTING PARADIGMS A holistic overview of major new computing paradigms of the 21st Century In Emerging Computing Paradigms: Principles, Advances and Applications, international scholars offer a compendium of essential knowledge on new promising computing paradigms. The book examines the characteristics and features of emerging computing technologies and provides insight into recent technological developments and their potential real-world applications that promise to shape the future. This book is a useful resource for all those who wish to quickly grasp new concepts of, and insights on, emerging computer paradigms and pursue further research or innovate new novel applications harnessing these concepts. Key Features Presents a comprehensive coverage of new technologies that have the potential to shape the future of our world--quantum computing, computational intelligence, advanced wireless networks and blockchain technology Revisits mainstream ideas now being widely adopted, such as cloud computing, the Internet of Things (IoT) and cybersecurity Offers recommendations and practical insights to assist the readers in the application of these technologies Aimed at IT professionals, educators, researchers, and students, Emerging Computing Paradigms: Principles, Advances and Applications is a comprehensive resource to get ahead of the curve in examining and exploiting emerging new concepts and technologies. Business executives will also find the book valuable and gain an advantage over competitors in harnessing the concepts examined therein.
Database Systems for Advanced Applications
The three-volume set LNCS 13245, 13246 and 13247 constitutes the proceedings of the 26th International Conference on Database Systems for Advanced Applications, DASFAA 2022, held online, in April 2021. The total of 72 full papers, along with 76 short papers, are presented in this three-volume set was carefully reviewed and selected from 543 submissions. Additionally, 13 industrial papers, 9 demo papers and 2 PhD consortium papers are included. The conference was planned to take place in Hyderabad, India, but it was held virtually due to the COVID-19 pandemic.
Sport Business Analytics
Developing and implementing a systematic analytics strategy can result in a sustainable competitive advantage within the sport business industry. This timely and relevant book provides practical strategies to collect data and then convert that data into meaningful, value-added information and actionable insights. Its primary objective is to help sport business organizations utilize data-driven decision-making to generate optimal revenue from such areas as ticket sales and corporate partnerships. To that end, the book includes in-depth case studies from such leading sports organizations as the Orlando Magic, Tampa Bay Buccaneers, Duke University, and the Aspire Group.The core purpose of sport business analytics is to convert raw data into information that enables sport business professionals to make strategic business decisions that result in improved company financial performance and a measurable and sustainable competitive advantage. Readers will learn about the role of big data and analytics in: Ticket pricing Season ticket member retention Fan engagement Sponsorship valuation Customer relationship management Digital marketing Market research Data visualization. This book examines changes in the ticketing marketplace and spotlights innovative ticketing strategies used in various sport organizations. It shows how to engage fans with social media and digital analytics, presents techniques to analyze engagement and marketing strategies, and explains how to utilize analytics to leverage fan engagement to enhance revenue for sport organizations.Filled with insightful case studies, this book benefits both sports business professionals and students. The concluding chapter on teaching sport analytics further enhances its value to academics.
Building IoT Visualizations using Grafana
The IoT developer's complete guide to building powerful dashboards, analyzing data, and integrating with other platformsKey Features: Connect devices, store and manage data, and build powerful data visualizationsIntegrate Grafana with other systems, such as Prometheus, OpenSearch, and LibreNMSLearn about message brokers and data forwarders to send data from sensors and systems to different platformsBook Description: Grafana is a powerful open source software that helps you to visualize and analyze data gathered from various sources. It allows you to share valuable information through unclouded dashboards, run analytics, and send notifications.Building IoT Visualizations Using Grafana offers how-to procedures, useful resources, and advice that will help you to implement IoT solutions with confidence. You'll begin by installing and configuring Grafana according to your needs. Next, you'll acquire the skills needed to implement your own IoT system using communication brokers, databases, and metric management systems, as well as integrate everything with Grafana. You'll learn to collect data from IoT devices and store it in databases, as well as discover how to connect databases to Grafana, make queries, and build insightful dashboards. Finally, the book will help you implement analytics for visualizing data, performing automation, and delivering notifications.By the end of this Grafana book, you'll be able to build insightful dashboards, perform analytics, and deliver notifications that apply to IoT and IT systems.What You Will Learn: Install and configure Grafana in different types of environmentsEnable communication between your IoT devices using different protocolsBuild data sources by ingesting data from IoT devicesGather data from Grafana using different types of data sourcesBuild actionable insights using plugins and analyticsDeliver notifications across several communication channelsIntegrate Grafana with other platformsWho this book is for: This book is for IoT developers who want to build powerful visualizations and analytics for their projects and products. Technicians from the embedded world looking to learn how to build systems and platforms using open source software will also benefit from this book. If you have an interest in technology, IoT, open source, and related subjects then this book is for you. Basic knowledge of administration tasks on Linux-based systems, IP networks and network services, protocols, ports, and related topics will help you make the most out of this book.
Mastering Microsoft Power BI - Second Edition
Plan, design, develop, and manage robust Power BI solutions to generate meaningful insights and make data-driven decisions.Purchase of the print or Kindle book includes a free eBook in the PDF format.Key FeaturesMaster the latest dashboarding and reporting features of Microsoft Power BICombine data from multiple sources, create stunning visualizations and publish Power BI apps to thousands of usersGet the most out of Microsoft Power BI with real-world use cases and examplesBook DescriptionMastering Microsoft Power BI, Second Edition, provides an advanced understanding of Power BI to get the most out of your data and maximize business intelligence. This updated edition walks through each essential phase and component of Power BI, and explores the latest, most impactful Power BI features. Using best practices and working code examples, you will connect to data sources, shape and enhance source data, and develop analytical data models. You will also learn how to apply custom visuals, implement new DAX commands and paginated SSRS-style reports, manage application workspaces and metadata, and understand how content can be staged and securely distributed via Power BI apps. Furthermore, you will explore top report and interactive dashboard design practices using features such as bookmarks and the Power KPI visual, alongside the latest capabilities of Power BI mobile applications and self-service BI techniques. Additionally, important management and administration topics are covered, including application lifecycle management via Power BI pipelines, the on-premises data gateway, and Power BI Premium capacity. By the end of this Power BI book, you will be confident in creating sustainable and impactful charts, tables, reports, and dashboards with any kind of data using Microsoft Power BI.What you will learnBuild efficient data retrieval and transformation processes with the Power Query M language and dataflowsDesign scalable, user-friendly DirectQuery, import, and composite data modelsCreate basic and advanced DAX measuresAdd ArcGIS Maps to create interesting data storiesBuild pixel-perfect paginated reportsDiscover the capabilities of Power BI mobile applicationsManage and monitor a Power BI environment as a Power BI administratorScale up a Power BI solution for an enterprise via Power BI Premium capacityWho this book is forBusiness Intelligence professionals and intermediate Power BI users looking to master Power BI for all their data visualization and dashboarding needs will find this book useful. An understanding of basic BI concepts is required and some familiarity with Microsoft Power BI will be helpful to make the most out of this book.Table of ContentsPlanning Power BI ProjectsPreparing Data sourcesConnecting to Sources and Transforming Data with MDesigning Import, DirectQuery, and Composite Data ModelsDeveloping DAX Measures and Security RolesPlanning Power BI ReportsCreating and Formatting VisualizationsApplying Advanced AnalyticsDesigning DashboardsManaging Workspaces and ContentManaging the On-Premises Data GatewayDeploying Paginated ReportsCreating Power BI Apps and Content DistributionAdministering Power BI for an OrganizationBuilding Enterprise BI with Power BI Premium
Optical Switching
OPTICAL SWITCHING Comprehensive coverage of optical switching technologies and their applications in optical networks Optical Switching: Device Technology and Applications in Networks delivers an accessible exploration of the evolution of optical networks with clear explanations of the current state-of-the-art in the field and modern challenges in the development of Internet-of-Things devices. A variety of optical switches--including MEMS-based, magneto, photonic, and SOA-based--are discussed, as is the application of optical switches in networks. The book is written in a tutorial style, easily understood by both undergraduate and graduate students. It describes the fundamentals and recent developments in optical switch networks and examines the architectural and design challenges faced by those who design and construct emerging optical switch networks, as well as how to overcome those challenges. The book offers ways to assess and analyze systems and applications, comparing a variety of approaches available to the reader. It also provides: A thorough introduction to switch characterization, including optical, electro optical, thermo optical, magneto optical, and acoustic-optic switches Comprehensive explorations of MEMS-based, SOA-based, liquid crystal, photonic crystal, and optical electrical optical (OEO) switches Practical discussions of quantum optical switches, as well as nonlinear optical switches In-depth examinations of the application of optical switches in networks, including switch fabric control and optical switching for high-performance computing Perfect for researchers and professionals in the fields of telecommunications, Internet of Things, and optoelectronics, Optical Switching: Device Technology and Applications in Networks will also earn a place in the libraries of advanced undergraduate and graduate students studying optical networks, optical communications, and sensor applications.
Human Aspects of Information Security and Assurance
This book constitutes the proceedings of the 15th IFIP WG 11.12 International Symposium on Human Aspects of Information Security and Assurance, HAISA 2021, held virtually in July 2021.The 18 papers presented in this volume were carefully reviewed and selected from 30 submissions. They are organized in the following topical sections: attitudes and perspectives; cyber security education; and people and technology.
Oracle Database Programming with Java
Databases have become an integral part of modern life. Today's society is an information-driven society, and database technology has a direct impact on all aspects of daily life. Decisions are routinely made by organizations based on the information collected and stored in databases. Database management systems such as Oracle are crucial to apply data in industrial or commercial systems. Equally crucial is a graphical user interface (GUI) to enable users to access and manipulate data in databases. The Apache NetBeans IDE with Java is an ideal candidate for developing a GUI with programming functionality. Oracle Database Programming with Java: Ideas, Designs, and Implementations is written for college students and software programmers who want to develop practical and commercial database programming with Java and relational databases such as Oracle Database XE 18c. The book details practical considerations and applications of database programming with Java and is filled with authentic examples as well as detailed explanations. Advanced topics in Java Web, like Java Web Applications and Java Web Services, are covered in real project examples to show how to handle the database programming issues in the Apache NetBeans IDE environment. This book features: A real sample database, CSE _ DEPT, which is built with Oracle SQL Developer, provided and used throughout the book Step by step, detailed illustrations and descriptions of how to design and build a practical relational database Fundamental and advanced Java database programming techniques practical to both beginning students and experienced programmers Updated Java desktop and Web database programming techniques, such as Java Enterprise Edition 7, JavaServer Pages, JavaServer Faces, Enterprise Java Beans, Web applications and Web services, including GlassFish and Tomcat Web servers More than 30 real database programming projects with detailed illustrations Actual JDBC APIs and JDBC drivers, along with code explanations Homework and selected solutions for each chapter to strengthen and improve students' learning and understanding of the topics they have studied
Analyzing Spatial Models of Choice and Judgment
With recent advances in computing power and the widespread availability of preference, perception and choice data, such as public opinion surveys and legislative voting, the empirical estimation of spatial models using scaling and ideal point estimation methods has never been more accessible.The second edition of Analyzing Spatial Models of Choice and Judgment demonstrates how to estimate and interpret spatial models with a variety of methods using the open-source programming language R. Requiring only basic knowledge of R, the book enables social science researchers to apply the methods to their own data. Also suitable for experienced methodologists, it presents the latest methods for modeling the distances between points. The authors explain the basic theory behind empirical spatial models, then illustrate the estimation technique behind implementing each method, exploring the advantages and limitations while providing visualizations to understand the results. This second edition updates and expands the methods and software discussed in the first edition, including new coverage of methods for ordinal data and anchoring vignettes in surveys, as well as an entire chapter dedicated to Bayesian methods. The second edition is made easier to use by the inclusion of an R package, which provides all data and functions used in the book. David A. Armstrong II is Canada Research Chair in Political Methodology and Associate Professor of Political Science at Western University. His research interests include measurement, Democracy and state repressive action. Ryan Bakker is Reader in Comparative Politics at the University of Essex. His research interests include applied Bayesian modeling, measurement, Western European politics, and EU politics. Royce Carroll is Professor in Comparative Politics at the University of Essex. His research focuses on measurement of ideology and the comparative politics of legislatures and political parties. Christopher Hare is Assistant Professor in Political Science at the University of California, Davis. His research focuses on ideology and voting behavior in US politics, political polarization, and measurement. Keith T. Poole is Philip H. Alston Jr. Distinguished Professor of Political Science at the University of Georgia. His research interests include methodology, US political-economic history, economic growth and entrepreneurship. Howard Rosenthal is Professor of Politics at NYU and Roger Williams Straus Professor of Social Sciences, Emeritus, at Princeton. Rosenthal's research focuses on political economy, American politics and methodology.
Web Engineering
This book constitutes the thoroughly refereed proceedings of the 22nd International Conference on Web Engineering, ICWE 2022, held in Bari, Italy, in July 2022. The 23 revised full papers and 5 short papers presented were carefully reviewed and selected from 81 submissions. The books also contains 6 demonstration and poster papers, 7 symposium and 5 tutorial papers. They are organized in topical sections named: recommender systems based on web technology; social web applications; web applications modelling and engineering; web big data and web data analytics; web mining and knowledge extraction; web security and privacy; web user interfaces.
Digital Business and Intelligent Systems
This book constitutes the refereed proceedings of the 15th International Baltic Conference on Digital Business and Intelligent Systems, Baltic DB&IS 2022, held in Riga, Latvia, in July 2022. The 16 revised full papers and 1 short paper presented were carefully reviewed and selected from 42 submissions. The papers are centered around topics like architectures and quality of information systems, artificial intelligence in information systems, data and knowledge engineering, enterprise and information systems engineering, security of information systems.
Natural Language Processing and Information Systems
This book constitutes the refereed proceedings of the 27th International Conference on Applications of Natural Language to Information Systems, NLDB 2022, held in Valencia, Spain in June 2022. The 28 full papers and 20 short papers were carefully reviewed and selected from 106 submissions. The papers are organized in the following topical sections: Sentiment Analysis and Social Media; Text Classification; Applications; Argumentation; Information Extraction and Linking; User Profiling; Semantics; Language Resources and Evaluation.
Observability Engineering
Observability is critical for building, changing, and understanding the software that powers complex modern systems. Teams that adopt observability are much better equipped to ship code swiftly and confidently, identify outliers and aberrant behaviors, and understand the experience of each and every user. This practical book explains the value of observable systems and shows you how to practice observability-driven development. Authors Charity Majors, Liz Fong-Jones, and George Miranda from Honeycomb explain what constitutes good observability, show you how to improve upon what you're doing today, and provide practical dos and don'ts for migrating from legacy tooling, such as metrics, monitoring, and log management. You'll also learn the impact observability has on organizational culture (and vice versa). You'll explore: How the concept of observability applies to managing software at scale The value of practicing observability when delivering complex cloud native applications and systems The impact observability has across the entire software development lifecycle How and why different functional teams use observability with service-level objectives How to instrument your code to help future engineers understand the code you wrote today How to produce quality code for context-aware system debugging and maintenance How data-rich analytics can help you debug elusive issues
Fundamentals of Data Engineering
Data engineering has grown rapidly in the past decade, leaving many software engineers, data scientists, and analysts looking for a comprehensive view of this practice. With this practical book, you'll learn how to plan and build systems to serve the needs of your organization and customers by evaluating the best technologies available through the framework of the data engineering lifecycle. Authors Joe Reis and Matt Housley walk you through the data engineering lifecycle and show you how to stitch together a variety of cloud technologies to serve the needs of downstream data consumers. You'll understand how to apply the concepts of data generation, ingestion, orchestration, transformation, storage, and governance that are critical in any data environment regardless of the underlying technology. This book will help you: Get a concise overview of the entire data engineering landscape Assess data engineering problems using an end-to-end framework of best practices Cut through marketing hype when choosing data technologies, architecture, and processes Use the data engineering lifecycle to design and build a robust architecture Incorporate data governance and security across the data engineering lifecycle
Knowledge Discovery from Multi-Sourced Data
This book addresses several knowledge discovery problems on multi-sourced data where the theories, techniques, and methods in data cleaning, data mining, and natural language processing are synthetically used. This book mainly focuses on three data models: the multi-sourced isomorphic data, the multi-sourced heterogeneous data, and the text data. On the basis of three data models, this book studies the knowledge discovery problems including truth discovery and fact discovery on multi-sourced data from four important properties: relevance, inconsistency, sparseness, and heterogeneity, which is useful for specialists as well as graduate students. Data, even describing the same object or event, can come from a variety of sources such as crowd workers and social media users. However, noisy pieces of data or information are unavoidable. Facing the daunting scale of data, it is unrealistic to expect humans to "label" or tell which data source is more reliable.Hence, it is crucial to identify trustworthy information from multiple noisy information sources, referring to the task of knowledge discovery. At present, the knowledge discovery research for multi-sourced data mainly faces two challenges. On the structural level, it is essential to consider the different characteristics of data composition and application scenarios and define the knowledge discovery problem on different occasions. On the algorithm level, the knowledge discovery task needs to consider different levels of information conflicts and design efficient algorithms to mine more valuable information using multiple clues. Existing knowledge discovery methods have defects on both the structural level and the algorithm level, making the knowledge discovery problem far from totally solved.
Document Analysis Systems
This book constitutes the refereed proceedings of the 15th IAPR International Workshop on Document Analysis Systems, DAS 2022, held in La Rochelle, France, in May 2022.The full papers presented were carefully reviewed and selected from numerous submissions addressing key techniques of document analysis.
Intelligent Systems for Stability Assessment and Control of Smart Power Grids
Power systems are evolving towards the Smart Grid paradigm, featured by large-scale integration of renewable energy resources, e.g. wind and solar power, deeper participation of demand side, and enhanced interaction with electric vehicles. While these emerging elements are inherently stochastic in nature, they are creating a challenge to the system's stability and its control. In this context, conventional analysis tools are becoming less effective, and necessitate the use alternative tools that are able to deal with the high uncertainty and variability in the smart grid. Smart Grid initiatives have facilitated wide-spread deployment of advanced sensing and communication infrastructure, e.g. phasor measurement units at grid level and smart meters at household level, which collect tremendous amount of data in various time and space scales. How to fully utilize the data and extract useful knowledge from them, is of great importance and value to support the advanced stability assessment and control of the smart grid. The intelligent system strategy has been identified as an effective approach to meet the above needs. This book presents the cutting-edge intelligent system techniques and their applications for stability assessment and control of power systems. The major topics covered in this book are: Intelligent system design and algorithms for on-line stability assessment, which aims to use steady-state operating variables to achieve fast stability assessment for credible contingencies. Intelligent system design and algorithms for preventive stability control, which aims at transparent and interpretable decision-making on preventive control actions to manipulate system operating condition against possible contingencies. Intelligent system design and algorithms for real-time stability prediction, which aims to use synchronized measurements to foresee the stability status under an ongoing disturbance. Intelligent system design and algorithms for emergency stability control, which aims at fast decision-making on stability control actions at emergency stage where instability is propagating.　 Methodologies and algorithms for improving the robustness of intelligent systems against missing-data issues. This book is a reference and guide for researchers, students, and engineers who seek to study and design intelligent systems to resolve stability assessment and control problems in the smart grid age.
Developing High-Frequency Trading Systems
Use your programming skills to create and optimize high-frequency trading systems in no time with Java, C++, and PythonKey Features- Learn how to build high-frequency trading systems with ultra-low latency- Understand the critical components of a trading system- Optimize your systems with high-level programming techniquesBook DescriptionThe world of trading markets is complex, but it can be made easier with technology. Sure, you know how to code, but where do you start? What programming language do you use? How do you solve the problem of latency? This book answers all these questions. It will help you navigate the world of algorithmic trading and show you how to build a high-frequency trading (HFT) system from complex technological components, supported by accurate data.Starting off with an introduction to HFT, exchanges, and the critical components of a trading system, this book quickly moves on to the nitty-gritty of optimizing hardware and your operating system for low-latency trading, such as bypassing the kernel, memory allocation, and the danger of context switching. Monitoring your system's performance is vital, so you'll also focus on logging and statistics. As you move beyond the traditional HFT programming languages, such as C++ and Java, you'll learn how to use Python to achieve high levels of performance. And what book on trading is complete without diving into cryptocurrency? This guide delivers on that front as well, teaching how to perform high-frequency crypto trading with confidence.By the end of this trading book, you'll be ready to take on the markets with HFT systems.What you will learnWho this book is forThis book is for software engineers, quantitative developers or researchers, and DevOps engineers who want to understand the technical side of high-frequency trading systems and the optimizations that are needed to achieve ultra-low latency systems. Prior experience working with C++ and Java will help you grasp the topics covered in this book more easily.Table of Contents- Fundamentals of a High-Frequency Trading System- The Critical Components of a Trading System- Understanding the Trading Exchange Dynamics- HFT System Foundations - From Hardware to OS- Networking in Motion- HFT Optimization - Architecture and Operating System- HFT Optimization - Logging, Performance, and Networking- C++ - The Quest for Microsecond Latency- Java and JVM for Low-Latency Systems- Python - Interpreted but Open to High Performance- High Frequency FPGA and Crypto
Advanced Analytics with Pyspark
The amount of data being generated today is staggering and growing. Apache Spark has emerged as the de facto tool to analyze big data and is now a critical part of the data science toolbox. Updated for Spark 3.0, this practical guide brings together Spark, statistical methods, and real-world datasets to teach you how to approach analytics problems using PySpark, Spark's Python API, and other best practices in Spark programming. Data scientists Akash Tandon, Sandy Ryza, Uri Laserson, Sean Owen, and Josh Wills offer an introduction to the Spark ecosystem, then dive into patterns that apply common techniques-including classification, clustering, collaborative filtering, and anomaly detection, to fields such as genomics, security, and finance. This updated edition also covers NLP and image processing. If you have a basic understanding of machine learning and statistics and you program in Python, this book will get you started with large-scale data analysis. Familiarize yourself with Spark's programming model and ecosystem Learn general approaches in data science Examine complete implementations that analyze large public datasets Discover which machine learning tools make sense for particular problems Explore code that can be adapted to many uses
Technologies and Applications for Big Data Value
This open access book explores cutting-edge solutions and best practices for big data and data-driven AI applications for the data-driven economy. It provides the reader with a basis for understanding how technical issues can be overcome to offer real-world solutions to major industrial areas.The book starts with an introductory chapter that provides an overview of the book by positioning the following chapters in terms of their contributions to technology frameworks which are key elements of the Big Data Value Public-Private Partnership and the upcoming Partnership on AI, Data and Robotics. The remainder of the book is then arranged in two parts. The first part "Technologies and Methods" contains horizontal contributions of technologies and methods that enable data value chains to be applied in any sector. The second part "Processes and Applications" details experience reports and lessons from using big data and data-driven approaches in processes and applications. Its chapters are co-authored with industry experts and cover domains including health, law, finance, retail, manufacturing, mobility, and smart cities. Contributions emanate from the Big Data Value Public-Private Partnership and the Big Data Value Association, which have acted as the European data community's nucleus to bring together businesses with leading researchers to harness the value of data to benefit society, business, science, and industry.The book is of interest to two primary audiences, first, undergraduate and postgraduate students and researchers in various fields, including big data, data science, data engineering, and machine learning and AI. Second, practitioners and industry experts engaged in data-driven systems, software design and deployment projects who are interested in employing these advanced methods to address real-world problems.
SQL Server Advanced Troubleshooting and Performance Tuning
This practical book provides a comprehensive overview of troubleshooting and performance tuning best practices for Microsoft SQL Server. Database engineers, including database developers and administrators, will learn how to identify performance issues, troubleshoot the system in a holistic fashion, and properly prioritize tuning efforts to attain the best system performance possible. Author Dmitri Korotkevitch, Microsoft Data Platform MVP and Microsoft Certified Master (MCM), explains the interdependencies between SQL Server database components. You'll learn how to quickly diagnose your system and discover the root cause of any issue. Techniques in this book are compatible with all versions of SQL Server and cover both on-premises and cloud-based SQL Server installations. Discover how performance issues present themselves in SQL Server Learn about SQL Server diagnostic tools, methods, and technologies Perform health checks on SQL Server installations Learn the dependencies between SQL Server components Tune SQL Server to improve performance and reduce bottlenecks Detect poorly optimized queries and inefficiencies in query execution plans Find inefficient indexes and common database design issues Use these techniques with Microsoft Azure SQL databases, Azure SQL Managed Instances, and Amazon RDS for SQL Server
Integration of Constraint Programming, Artificial Intelligence, and Operations Research
This book constitutes the proceedings of the 19th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, CPAIOR 2022, which was held in Los Angeles, CA, USA, in June 2022.The 28 regular papers presented were carefully reviewed and selected from a total of 60 submissions. The conference program included a Master Class on the topic "Bridging the Gap between Machine Learning and Optimization".
Big Data Privacy and Security in Smart Cities
This book highlights recent advances in smart cities technologies, with a focus on new technologies such as biometrics, blockchains, data encryption, data mining, machine learning, deep learning, cloud security, and mobile security. During the past five years, digital cities have been emerging as a technology reality that will come to dominate the usual life of people, in either developed or developing countries. Particularly, with big data issues from smart cities, privacy and security have been a widely concerned matter due to its relevance and sensitivity extensively present in cybersecurity, healthcare, medical service, e-commercial, e-governance, mobile banking, e-finance, digital twins, and so on. These new topics rises up with the era of smart cities and mostly associate with public sectors, which are vital to the modern life of people. This volume summarizes the recent advances in addressing the challenges on big data privacy and security in smart cities and points out the future research direction around this new challenging topic.
Technologies and Applications for Big Data Value
This open access book explores cutting-edge solutions and best practices for big data and data-driven AI applications for the data-driven economy. It provides the reader with a basis for understanding how technical issues can be overcome to offer real-world solutions to major industrial areas.The book starts with an introductory chapter that provides an overview of the book by positioning the following chapters in terms of their contributions to technology frameworks which are key elements of the Big Data Value Public-Private Partnership and the upcoming Partnership on AI, Data and Robotics. The remainder of the book is then arranged in two parts. The first part "Technologies and Methods" contains horizontal contributions of technologies and methods that enable data value chains to be applied in any sector. The second part "Processes and Applications" details experience reports and lessons from using big data and data-driven approaches in processes and applications. Its chapters are co-authored with industry experts and cover domains including health, law, finance, retail, manufacturing, mobility, and smart cities. Contributions emanate from the Big Data Value Public-Private Partnership and the Big Data Value Association, which have acted as the European data community's nucleus to bring together businesses with leading researchers to harness the value of data to benefit society, business, science, and industry.The book is of interest to two primary audiences, first, undergraduate and postgraduate students and researchers in various fields, including big data, data science, data engineering, and machine learning and AI. Second, practitioners and industry experts engaged in data-driven systems, software design and deployment projects who are interested in employing these advanced methods to address real-world problems.
Integer Programming and Combinatorial Optimization
This book constitutes the refereed proceedings of the 23rd International Conference on Integer Programming and Combinatorial Optimization, IPCO 2022, held in Eindhoven, The Netherlands, in June 2022. The 33 full papers presented were carefully reviewed and selected from 93 submissions addressing key techniques of document analysis. IPCO is under the auspices of the Mathematical Optimization Society, and it is an important forum for presenting the latest results of theory and practice of the various aspects of discrete optimization.
Web and Wireless Geographical Information Systems
This book constitutes the refereed proceedings of the 18th International Symposium on Web and Wireless Geographical Information Systems, W2GIS 2022, held in Konstanz, Germany, in April 2022. The 7 full papers presented together with 6 short papers in the volume were carefully reviewed and selected from 16 submissions. The papers cover topics that range from mobile GIS and Location-Based Services to Spatial Information Retrieval and Wireless Sensor Networks.
Human Language Technology. Challenges for Computer Science and Linguistics
This book constitutes the refereed proceedings of the 9th Language and Technology Conference: Challenges for Computer Science and Linguistics, LTC 2019, held in Poznan, Poland, in May 2019. The 24 revised papers presented in this volume were carefully reviewed and selected from 67 submissions. The papers are categorized into the following topical sub-headings: Speech Processing; Language Resources and Tools; Computational Semantics; Emotions, Decisions and Opinions; Digital Humanities; Evaluation; and Legal Aspects.
Research in Computational Molecular Biology
This book constitutes the proceedings of the 26th Annual Conference on Research in Computational Molecular Biology, RECOMB 2022, held in San Diego, CA, USA in May 2022. The 17 regular and 23 short papers presented were carefully reviewed and selected from 188 submissions. The papers report on original research in all areas of computational molecular biology and bioinformatics.
Practical Cockroachdb
Get a practical introduction to CockroachDB. This book starts with installation and foundational concepts and takes you through to creating clusters that are ready for production environments. You will learn how to create, optimize, and operate CockroarchDB clusters in single and multi-region environments. You will encounter anti-patterns to avoid, as well as testing techniques for integration and load testing. The book explains why CockroachDB exists, goes over its major benefits, and quickly transitions into installing and configuring CockroachDB. Just as quickly, you'll be creating databases, getting data into those databases, and querying that data from your applications. You'll progress to data privacy laws such as GDPR and CCPA, and learn how CockroachDB's global distribution features can help you comply with ever-shifting data sovereignty regulations. From there, you'll move into deployment topologies, guidance on integration testing and load testing, best practices, and a readiness checklist for production deployments. What You Will LearnDeploy and interact with CockroachDBDesign and optimize databases and tablesChoose the correct data types for modeling your dataProtect data with database and table encryptionAchieve compliance with international data privacy regulationsScale your databases in a way that enhances their performanceMonitor changes to the data and health of your databasesWho This Book Is ForDevelopers and database administrators who want to provide a secure, reliable, and effortlessly distributed home for their data; those who wish to use a modern tool to tackle the kinds of scaling challenges that have previously required dedicated teams of people to solve; anyone who wants to leverage their database to solve non-trivial, real-world challenges while protecting their data and users
