Logistics and Supply Chain Management
This book constitutes selected and revised papers from the 7th International Conference Logistics and Supply Chain Management, held in December 2020 in Tehran, Iran. Due to the COVID-19 pandemic the conference was held online. The 17 full papers and 2 short papers pressented were thoroughly reviewed and selected out of 70 submissions. The papers are organized in the topical sections on ​information technology in supply chain management; production/scheduling and transportation in supply chain management; sustainable and resilient supply chain management; humanitarian supply chain management.
Machine Translation
This book constitutes the refereed proceedings of the 17th China Conference on Machine Translation, CCMT 2020, held in Xining, China, in October 2021. The 10 papers presented in this volume were carefully reviewed and selected from 25 submissions and focus on all aspects of machine translation, including preprocessing, neural machine translation models, hybrid model, evaluation method, and post-editing.
The Little Book of Artificial Intelligence
This book is a brief introduction to artificial intelligence. It is intended for readers, in business, education, government, and self-edification. The author would like to thank his wife Margaret for helping with the manuscript. As in most disciplines, some of the subject matter is new and some of the subject matter is not so new, especially to persons trained in the subject of computers. A person with a degree in computer science should know it already. Artificial intelligence is an important subject to the modern world, and some disciplines have already benefitted greatly from it. The reader can survey the subject matter in any order he or she pleases. The busy executive can benefit greatly from it their parent organization. Executives in finance and banking can use to understand what is going on in their endeavors. Artificial intelligence is not only software but uses specially prepared software to take intellectual benefit in understanding what his or her data systems are doing. Artificial intelligence is something for the future from self-driving vehicles to self-managed business.
Blockchain for International Security
This book intersects the distributed ledger technology (DLT) community with the international security community. Given the increasing application of blockchain technology in the fields of business and international development, there is a growing body of study on other use cases. For instance, can blockchain have a significant role in preserving and improving international security? This book explores this question in the context of preventing the proliferation of some of the most dangerous materials in the world-items that if not secured can lend to the development of weapons of mass destruction. It considers how blockchain can increase efficiencies in the global trade of nuclear and chemical materials and technology, thereby increasing assurances related to compliance with international nonproliferation and disarmament treaties.
Computational Mechanics
Computational mechanics is the study of mechanics through computational methods. This book on computational mechanics deals with numerical and computational modeling and their applications that can solve problems in mechanical engineering. This field has three main sub-fields which are mathematics, computer science and mechanics. Different approaches, evaluations, methodologies and advanced studies on this field have been included in this book. It elucidates concepts and innovative models around prospective developments with respect to computational mechanics. The book is appropriate for students seeking detailed information in this area as well as for experts. It will help the readers in keeping pace with the rapid changes in this field.
Monte Carlo Search
This book constitutes the refereed proceedings of the First Workshop on Monte Carlo Search, MCS 2020, organized in conjunction with IJCAI 2020. The event was supposed to take place in Yokohama, Japan, in July 2020, but due to the Covid-19 pandemic was held virtually on January 7, 2021. The 9 full papers of the specialized project were carefully reviewed and selected from 15 submissions. The following topics are covered in the contributions: discrete mathematics in computer science, games, optimization, search algorithms, Monte Carlo methods, neural networks, reinforcement learning, machine learning.
The Analytic Detective
Following the clues that lead to increased sales or greater profits takes more than uncovering big data. Without effective data translation and communication, even the most sophisticated analytic effort can end in confusion - and your data insights won't impact company decision making.With practical advice for every data analyst, this is your guide to navigating all aspects of client interaction and communicating straightforward solutions to affect company-wide change - from the back room to the board room. You'll learn: How to hit the Analytic Trifecta to ensure you're producing useful findings.How to design a clear story that summarizes business analytics.Different analyst behaviors for the 10 specific client types.Strategies to employ when a client challenges your analysis.How successful analysts get their work noticed. Become an irreplaceable analytic asset to your team. Get The Analytic Detective to start collaborating for more data-fueled results and more recognition in your career.
Discriminating Data
How big data and machine learning encode discrimination and create agitated clusters of comforting rage. In Discriminating Data, Wendy Hui Kyong Chun reveals how polarization is a goal--not an error--within big data and machine learning. These methods, she argues, encode segregation, eugenics, and identity politics through their default assumptions and conditions. Correlation, which grounds big data's predictive potential, stems from twentieth-century eugenic attempts to "breed" a better future. Recommender systems foster angry clusters of sameness through homophily. Users are "trained" to become authentically predictable via a politics and technology of recognition. Machine learning and data analytics thus seek to disrupt the future by making disruption impossible. Chun, who has a background in systems design engineering as well as media studies and cultural theory, explains that although machine learning algorithms may not officially include race as a category, they embed whiteness as a default. Facial recognition technology, for example, relies on the faces of Hollywood celebrities and university undergraduates--groups not famous for their diversity. Homophily emerged as a concept to describe white U.S. resident attitudes to living in biracial yet segregated public housing. Predictive policing technology deploys models trained on studies of predominantly underserved neighborhoods. Trained on selected and often discriminatory or dirty data, these algorithms are only validated if they mirror this data. How can we release ourselves from the vice-like grip of discriminatory data? Chun calls for alternative algorithms, defaults, and interdisciplinary coalitions in order to desegregate networks and foster a more democratic big data.
Algorithms on Trees and Graphs
This book introduces graph algorithms on an intuitive basis followed by a detailed exposition in a literate programming style, with correctness proofs as well as worst-case analyses. Full C++ implementations of all algorithms presented are given using the LEDA library of efficient data structures and algorithms.
Advances in Computer Graphics
This book constitutes the refereed proceedings of the 38th Computer Graphics International Conference, CGI 2021, held virtually in September 2021.The 44 full papers presented together with 9 short papers were carefully reviewed and selected from 131 submissions. The papers are organized in the following topics: computer animation; computer vision; geometric computing; human poses and gestures; image processing; medical imaging; physics-based simulation; rendering and textures; robotics and vision; visual analytics; VR/AR; and engage.
Upper-class English in Natural and Audiovisual Dialogue
This volume deals with the language of the British upper class in natural face-to-face dialogue and how this is rendered fictionally in audiovisual media. Its main aim is that of reorganising the sparse information on the topic that is found in previous scholarly studies through a qualitative methodological approach. After focusing on the linguistic description and evolution of the upper-class sociolect, the study offers original insights on the language of the Royal Family and its representation in the TV series The Crown. The results from this research, which combines the disciplines of sociolinguistics and dialectology applied to the audiovisual text, will hopefully open a new path in the study of language of elite groups in Britain, arguably an under-researched topic.
Communicating with Data
Data is a fantastic raw resource for powering change in an organization, but all too often the people working in those organizations don't have the necessary skills to communicate with data effectively. With this practical book, subject matter experts will learn ways to develop strong, persuasive points when presenting data to different groups in their organizations. Author Carl Allchin shows anyone how to find data sources and develop data analytics, and teaches those with more data expertise how to visualize data to convey findings to key business leaders more effectively. Once both your business and data experts possess the skills to work with data and interpret its significance, you can deal with questions and challenges in departments across your organization. Learn the fundamental data skills required to work with data Use data visualization to influence change in your organization Learn how to apply data techniques to effectively work with data end to end Understand how to communicate data points clearly and persuasively Appreciate why different stakeholders often have divergent needs and views Create a playbook for using data with different departments
Beyond Planar Graphs
Chapter 1: Introduction.- Chapter 2: Quantitative Restrictions on Crossing Patterns.- Chapter 3: Quasi-planar Graphs.- Chapter 4: 1-Planar Graphs.- Chapter 5: Algorithms for 1-planar Graphs.- Chapter 6: ^= 2.- Chapter 8: Fan-Planarity.- Chapter 9: Right Angle Crossing Drawings of Graphs.- Chapter 10: Angular Resolutions.- Chapter 11: Crossing Layout in Non-Planar Graph Drawings.- Chapter 12: Beyond Clustered Planarity.- Chapter: Simultaneous Embedding.
Attribute-Based Encryption and Access Control
This book covers a broader scope of Attribute-Based Encryption (ABE), from the background knowledge, to specific constructions, theoretic proofs, and applications. The goal is to provide in-depth knowledge usable for college students and researchers who want to have a comprehensive understanding of ABE schemes and novel ABE-enabled research and applications. The specific focus is to present the development of using new ABE features such as group-based access, ID-based revocation, and attributes management functions such as delegation, federation, and interoperability. These new capabilities can build a new ABE-based Attribute-Based Access Control (ABAC) solution that can incorporate data access policies and control into ciphertext. This book is also ideal for IT companies to provide them with the most recent technologies and research on how to implement data access control models for mobile and data-centric applications, where data access control does not need to rely on a fixed access control infrastructure. It's also of interested to those working in security, to enable them to have the most recent developments in data access control such as ICN and Blockchain technologies.Features Covers cryptographic background knowledge for ABE and ABAC Features various ABE constructions to achieve integrated access control capabilities Offers a comprehensive coverage of ABE-based ABAC Provides ABE applications with real-world examples Advances the ABE research to support new mobile and data-centric applications
Microsoft Power BI Cookbook - Second Edition
Publisher's note: This edition from 2021 is outdated and does not cover the most recent Power BI updates. A new third edition, updated to the latest release is now available in colorPurchase of the print or Kindle book includes a free eBook in the PDF format.Key Features: - Update your knowledge with new recipes for query optimization, aggregation tables, Power BI API, and paginated reports- Work with recipes across diverse Power BI platforms including the Power BI Service and Mobile Applications- Implement custom solutions with M and DAX languages through actionable guidance and proven development techniquesBook Description: The complete everyday reference guide to Power BI, written by an internationally recognized Power BI expert duo, is back with a new and updated edition.Packed with revised practical recipes, Microsoft Power BI Cookbook, Second Edition, helps you navigate Power BI tools and advanced features. It also demonstrates the use of end-to-end solutions that integrate those features to get the most out of Power BI. With the help of the recipes in this book, you'll gain advanced design and development insight, practical tips, and guidance on enhancing existing Power BI projects.The updated recipes will equip you with everything you need to know to implement evergreen frameworks that will stay relevant as Power BI updates. You'll familiarize yourself with Power BI development tools and services by going deep into the data connectivity, transformation, modeling, visualization, and analytical capabilities of Power BI. By the end of this book, you'll make the most of Power BI's functional programming languages of DAX and M and deliver powerful solutions to common business intelligence challenges.What You Will Learn: - Cleanse, stage, and integrate your data sources with Power Query (M)- Remove data complexities and provide users with intuitive, self-service BI capabilities- Build business logic and analysis into your solutions via the DAX programming language and dashboard-ready calculations- Implement aggregation tables to accelerate query performance over large data sources- Create and integrate paginated reports- Understand the differences and implications of DirectQuery, live connections, Import, and Composite model datasets- Integrate other Microsoft data tools into your Power BI solutionWho this book is for: If you're a BI professional who wants to up their knowledge of Power BI and offer more value to their organization, then this book is for you. Those looking for quick solutions to common Power BI problems will also find this book an extremely useful resource. Please be aware that this is not a beginner's guide; you'll need a solid understanding of Power BI and experience working with datasets before you dive in. Table of Contents- Configuring Power BI Tools- Accessing and Retrieving Data- Building a Power BI Data Model- Authoring Power BI Reports- Working in the Service- Getting Serious with Date Intelligence- Parameterizing Power BI Solutions- Implementing Dynamic User-Based Visibility in Power BI- Applying Advanced Analytics and Custom Visuals- Administering and Monitoring Power BI- Enhancing and Optimizing Existing Power BI Solutions- Deploying and Distributing Power BI Content- Integrating Power BI with Other Applications
High Performance MySQL
How can you realize MySQL's full power? With High Performance MySQL, you'll learn advanced techniques for everything from setting service-level objectives to designing schemas, indexes, and queries to tuning your server, operating system, and hardware to achieve your platform's full potential. This guide also teaches database administrators safe and practical ways to scale applications through replication, load balancing, high availability, and failover. Updated to reflect recent advances in cloud- and self-hosted MySQL, InnoDB performance, and new features and tools, this revised edition helps you design a relational data platform that will scale with your business. You'll learn best practices for database security along with hard-earned lessons in both performance and database stability. Dive into MySQL's architecture, including key facts about its storage engines Learn how server configuration works with your hardware and deployment choices Make query performance part of your software delivery process Examine enhancements to MySQL's replication and high availability Compare different MySQL offerings in managed cloud environments Explore MySQL's full stack optimization from application-side configuration to server tuning Turn traditional database management tasks into automated processes
Practical Python Data Wrangling and Data Quality
The world around us is full of data that holds unique insights and valuable stories, and this book will help you uncover them. Whether you already work with data or want to learn more about its possibilities, the examples and techniques in this practical book will help you more easily clean, evaluate, and analyze data so that you can generate meaningful insights and compelling visualizations. Complementing foundational concepts with expert advice, author Susan E. McGregor provides the resources you need to extract, evaluate, and analyze a wide variety of data sources and formats, along with the tools to communicate your findings effectively. This book delivers a methodical, jargon-free way for data practitioners at any level, from true novices to seasoned professionals, to harness the power of data. Use Python 3.8+ to read, write, and transform data from a variety of sources Understand and use programming basics in Python to wrangle data at scale Organize, document, and structure your code using best practices Collect data from structured data files, web pages, and APIs Perform basic statistical analyses to make meaning from datasets Visualize and present data in clear and compelling ways
Database and Expert Systems Applications - DEXA 2021 Workshops
This volume constitutes the refereed proceedings of the workshops held at the 32nd International Conference on Database and Expert Systems Applications, DEXA 2021, held in a virtual format in September 2021: The 12th International Workshop on Biological Knowledge Discovery from Data (BIOKDD 2021), the 5th International Workshop on Cyber-Security and Functional Safety in Cyber-Physical Systems (IWCFS 2021), the 3rd International Workshop on Machine Learning and Knowledge Graphs (MLKgraphs 2021), the 1st International Workshop on Artificial Intelligence for Clean, Affordable and Reliable Energy Supply (AI-CARES 2021), the 1st International Workshop on Time Ordered Data (ProTime2021), and the 1st International Workshop on AI System Engineering: Math, Modelling and Software (AISys2021). Due to the COVID-19 pandemic the conference and workshops were held virtually. The 23 papers were thoroughly reviewed and selected from 50 submissions, and discuss a range of topics including: knowledge discovery, biological data, cyber security, cyber-physical system, machine learning, knowledge graphs, information retriever, data base, and artificial intelligence.
Rough Sets
The volume LNAI 12872 constitutes the proceedings of the International Joint Conference on Rough Sets, IJCRS 2021, Bratislava, Slovak Republic, in September 2021. The conference was held as a hybrid event due to the COVID-19 pandemic. The 13 full paper and 7 short papers presented were carefully reviewed and selected from 26 submissions, along with 5 invited papers. The papers are grouped in the following topical sections: core rough set models and methods, related methods and hybridization, and areas of applications.
Web Information Systems and Applications
This book constitutes the proceedings of the 18th International Conference on Web Information Systems and Applications, WISA 2021, held in Kaifeng, China, in September 2021. The 49 full papers and 18 short papers presented were carefully reviewed and selected from 206 submissions. The papers are grouped in topical sections on world wide web, query processing and algorithm, natural language processing, machine learning, data mining, data privacy and security.
Big Data Analytics and Knowledge Discovery
This volume LNCS 12925 constitutes the papers of the 23rd International Conference on Big Data Analytics and Knowledge Discovery, held in September 2021. Due to COVID-19 pandemic it was held virtually. The 12 full papers presented together with 15 short papers in this volume were carefully reviewed and selected from a total of 71 submissions.The papers reflect a wide range of topics in the field of data integration, data warehousing, data analytics, and recently big data analytics, in a broad sense. The main objectives of this event are to explore, disseminate, and exchange knowledge in these fields.
Data Science
This two volume set (CCIS 1451 and 1452) constitutes the refereed proceedings of the 7th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2021 held in Taiyuan, China, in September 2021.The 81 papers presented in these two volumes were carefully reviewed and selected from 256 submissions. The papers are organized in topical sections on big data management and applications; social media and recommendation systems; infrastructure for data science; basic theory and techniques for data science; machine learning for data science; multimedia data management and analysis; ​social media and recommendation systems; data security and privacy; applications of data science; education research, methods and materials for data science and engineering; research demo.
Data Science
This two volume set (CCIS 1451 and 1452) constitutes the refereed proceedings of the 7th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2021 held in Taiyuan, China, in September 2021.The 81 papers presented in these two volumes were carefully reviewed and selected from 256 submissions. The papers are organized in topical sections on big data management and applications; social media and recommendation systems; infrastructure for data science; basic theory and techniques for data science; machine learning for data science; multimedia data management and analysis; ​social media and recommendation systems; data security and privacy; applications of data science; education research, methods and materials for data science and engineering; research demo.
Linking Theory and Practical of Digital Libraries
This book constitutes the proceedings of the 25th International Conference on Theory and Practice of Digital Libraries, TPDL 2021, held in September 2021. Due to COVID-10 pandemic the conference was held virtually.The 10 full papers, 3 short papers and 13 other papers presented were carefully reviewed and selected from 53 submissions. TPDL 2021 attempts to facilitate establishing connections and convergences between diverse research communities such as Digital Humanities, Information Sciences and others that could benefit from ecosystems offered by digital libraries and repositories. This edition of TPDL was held under the general theme of "Linking Theory and Practice". The papers are organized in topical sections as follows: Document and Text Analysis; Data Repositories and Archives; Linked Data and Open Data; User Interfaces and Experience.
Masterclass Enterprise Architecture Management
This textbook provides a hands-on introduction to enterprise architecture management. It guides the reader through the applications of methods and tools to typical business problems by presenting enterprise architecture frameworks and by sharing experiences from industry.The structure of the book represents the typical stages of the journey of an enterprise architect. Chapter 1 addresses the central question of what to achieve with the introduction of an enterprise architecture. Chapter 2 then introduces concepts and visualizations for business architecture that help with understanding the business. In chapter 3 the development of an application architecture is outlined, which provides transparency on information systems and their business context. Next, chapter 4 presents visual tools to analyze, improve and eventually optimize the application landscape. Chapter 5 discusses both traditional organizational as well as collaborative approaches to enterprise architecture management. Eventually, several established enterprise architecture frameworks like TOGAF, Zachmann, ArchiMate, and IAF are described in chapter 6. The book concludes with a summary and an outlook on future research potential in chapter 7. Based on their experiences through several years of teaching, the authors introduce students step-by-step to enterprise architecture development and management. Their book is intended as a guide for master classes at universities and includes lots of exercises and references for further reading.
Understanding and Defending Against Russia’s Malign and Subversive Information Efforts in Europe
As targets of information aggression, the United States and its European allies must protect themselves against the effects of psychological manipulation and influence. The authors describe apparent efforts by Russia and its agents to use information to shape Russia's operating environment, and they identify possible defensive approaches for United States European Command and its partners.
Visual Analytics for Data Scientists
This textbook presents the main principles of visual analytics and describes techniques and approaches that have proven their utility and can be readily reproduced. Special emphasis is placed on various instructive examples of analyses, in which the need for and the use of visualisations are explained in detail.The book begins by introducing the main ideas and concepts of visual analytics and explaining why it should be considered an essential part of data science methodology and practices. It then describes the general principles underlying the visual analytics approaches, including those on appropriate visual representation, the use of interactive techniques, and classes of computational methods. It continues with discussing how to use visualisations for getting aware of data properties that need to be taken into account and for detecting possible data quality issues that may impair the analysis. The second part of the book describes visual analytics methods and workflows, organised by various data types including multidimensional data, data with spatial and temporal components, data describing binary relationships, texts, images and video. For each data type, the specific properties and issues are explained, the relevant analysis tasks are discussed, and appropriate methods and procedures are introduced. The focus here is not on the micro-level details of how the methods work, but on how the methods can be used and how they can be applied to data. The limitations of the methods are also discussed and possible pitfalls are identified.The textbook is intended for students in data science and, more generally, anyone doing or planning to do practical data analysis. It includes numerous examples demonstrating how visual analytics techniques are used and how they can help analysts to understand the properties of data, gain insights into the subject reflected in the data, and build good models that can be trusted. Based on several years of teaching related courses at the City, University of London, the University of Bonn and TU Munich, as well as industry training at the Fraunhofer Institute IAIS and numerous summer schools, the main content is complemented by sample datasets and detailed, illustrated descriptions of exercises to practice applying visual analytics methods and workflows.
Database and Expert Systems Applications
This two-volume set, LNCS 12923 and 12924, constitutes the thoroughly refereed proceedings of the 5th International Conference on Database and Expert Systems Applications, DEXA 2021. Due to COVID-19 pandemic, the conference was held virtually. The 37 full papers presented together with 31 short papers in these volumes were carefully reviewed and selected from a total of 149 submissions. The papers are organized around the following topics: big data; data analysis and data modeling; data mining; databases and data management; information retrieval; prediction and decision support.
Transactions on Large-Scale Data- And Knowledge-Centered Systems XLIX
Temporal Aggregation of Spanning Event Stream: An Extended Framework to Handle the Many Stream Models.- Reducing the Cost of Aggregation in Crowdsourcing.- A Partitioning Approach for Skyline Queries in Presence of Partial and Dynamic Orders.- Ensuring License Compliance in Linked Data with Query Relaxation.
The Enrichment Game
Getting the most from your data requires winning the Enrichment game. Learn the game rules and fit the "pieces," processes, and people together to achieve a high score in data quality and data useability.First, demonstrate the value of the data our organizations gather, protect, and, in some cases, share. Second, enrich the available data by providing more context on the meaning of the data. Chief data officers, data strategists, data architects, data managers, data scientists, business analysts, and data governance and business intelligence professionals all play the game, and therefore need to read this book to understand how to "win." Understand your data and the insights possible from this data, and you win the game. Organizations must understand how data answers questions, performs research, provides insights, forecasts the future, and recommends new ways of doing business. To do this successfully, we enrich data from one application with data from other applications or outside sources, and create an enrichment platform for knowledge workers. Those who can do this successfully can show data in ways that are unexpected and surprising.In addition to learning about enrichment, this book shares invaluable analogies to explain data management and Agile practices. The Boxer analogy, for example, explains why agility is useless without stability. Likewise, agile principles become chaotic if changing an unstable environment without best practices for keeping track of where your data came from, where it is going, and how to derive insights. Are you ready to get the most from your data? Play the enrichment game!
A Review of Public Data about Terrorism and Targeted Violence to Meet U.S. Department of Homeland Security Mission Needs
The U.S. Department of Homeland Security's (DHS?s) Strategic Framework for Countering Terrorism and Targeted Violence calls for better data resources. Researchers reviewed DHS needs, existing resources, and alignment between those needs and resources. They document their findings and recommendations here: Available resources might meet current needs, but new resources will be required as needs evolve.
Azure Stack Hub Demystified
Deploy, configure, administer, and run Microsoft Azure Stack HubKey Features: Understand the topics required for the Microsoft Azure AZ-600 examConfigure and provide services from Microsoft Azure Stack HubImplement data center integration with Microsoft Azure Stack HubBook Description: Azure Stack Hub is the on-premise offering from Microsoft, which provides Azure Cloud services within a customer's own data center. It provides consistent processes between on-site and the cloud, allowing developers to test locally and deploy to the cloud in exactly the same manner. Azure Stack Hub Demystified provides complete coverage of deploying, configuring, administrating, and running Microsoft Azure Stack Hub efficiently.Firstly, you will learn how to deploy Azure Stack Hub within an organization. As you progress, you'll understand configuration and the different services provided by the platform. The book also focuses on the underlying architecture and connectivity options for the modern data center. Later, you will understand various approaches to DevOps and their implementation, and learn key topics for the AZ-600 exam.By the end of this Azure book, you will have a thorough understanding of Azure Stack Hub and the services that are provided by the platform, along with the confidence and information you need to be able to pass the AZ-600 exam.What You Will Learn: Understand the architecture of Azure Stack HubGet up to speed with the management and administration of Azure Stack HubExplore how to administer virtual networking within your Azure StackBecome well versed in using the Azure Stack Hub support model and updating Azure Stack HubUnderstand how licensing and billing is done with Azure Stack HubDiscover the tools that can be used to implement security within Azure Stack HubFocus on how DevOps practices can be incorporated with Azure Stack HubWho this book is for: If you are an Azure Administrator and Azure Stack Hub Operator who provides or is looking to provide cloud services to end users or customers within their own data center, then this book is for you. This book will also be beneficial to those who are preparing for Exam AZ-600: Configuring and Operating a Hybrid Cloud with Microsoft Azure Stack Hub.
Database and Expert Systems Applications
This two-volume set, LNCS 12923 and 12924, constitutes the thoroughly refereed proceedings of the 5th International Conference on Database and Expert Systems Applications, DEXA 2021. Due to COVID-19 pandemic, the conference was held virtually. The 37 full papers presented together with 31 short papers in these volumes were carefully reviewed and selected from a total of 149 submissions. The papers are organized around the following topics: big data; data analysis and data modeling; data mining; databases and data management; information retrieval; prediction and decision support.
Tools F羹r Social Listening Und Sentiment-Analyse
Mit diesem Buch lernen Sie, wie Sie Social Listening und Sentiment-Analyse professionell einsetzen k繹nnen. Der Leser erh瓣lt Schritt-f羹r-Schritt-Beschreibungen f羹r verschiedene Einsatzszenarien, gekoppelt mit ?bungsaufgaben und n羹tzlichen Materialien, darunter ein Merkblatt f羹r Kennzahlen, eine Checkliste f羹r die Toolauswahl und ein Glossar f羹r Fachbegriffe. Dieses Lehr- und Praxisbuch verdeutlicht anhand von Anwendungsszenarien und Praxisbeispielen, wie Tools und Technologien f羹r Social Listening und Sentiment-Analyse f羹r die Analyse deutschsprachiger Online-Textdaten angewandt werden k繹nnen und welche Vorteile diese bringen. Der Leser erh瓣lt einen ?berblick 羹ber wichtige Funktionalit瓣ten aktuell verf羹gbarer Social-Listening-Tools und deren Einsatzm繹glichkeiten.
Building Microservices with Micronaut(R)
Explore different aspects of building modular microservices such as development, testing, maintenance, and deployment using the Micronaut frameworkKey Features: Learn how to build scalable, fast, and resilient microservices with this concise guideExplore the many advantages of using reflection-free, compile-time dependency injections and aspect-oriented programmingBuild cloud-native applications easily with the Micronaut frameworkBook Description: The open source Micronaut(R) framework is a JVM-based toolkit designed to create microservices quickly and easily. This book will help full-stack and Java developers build modular, high-performing, and reactive microservice-based apps using the Micronaut framework.You'll start by building microservices and learning about the core components, such as ahead-of-time compilation, reflection-less dependency injection, and reactive baked-in HTTP clients and servers. Next, you will work on a real-time microservice application and learn how to integrate Micronaut projects with different kinds of relational and non-relational databases. You'll also learn how to employ different security mechanisms to safeguard your microservices and integrate microservices using event-driven architecture in the Apache Kafka ecosystem. As you advance, you'll get to grips with automated testing and popular testing tools. The book will help you understand how you can easily handle microservice concerns in Micronaut projects, such as service discovery, API documentation, distributed configuration management, fallbacks, and circuit breakers. Finally, you'll explore the deployment and maintenance aspects of microservices and get up to speed with the Internet of Things (IoT) using the Framework.By the end of this book, you'll be able to build, test, deploy, and maintain your own microservice apps using the framework.What You Will Learn: Understand why the Micronaut framework is best suited for building microservicesBuild web endpoints and services in the Micronaut frameworkSafeguard microservices using Session, JWT, and OAuth in Micronaut projectsGet to grips with event-driven architecture in Micronaut applicationsDiscover how to automate testing at various levels using built-in tools and testing frameworksDeploy your microservices to containers and cloud platformsBecome well-versed with distributed logging, tracing, and monitoring in Micronaut projectsGet hands-on with the IoT using Alexa and the Micronaut frameworkWho this book is for: This book is for developers who have been building microservices on traditional frameworks such as Spring Boot and are looking for a faster alternative. Intermediate-level knowledge of Java programming and implementing web services development in Java is required.
Collaboration Technologies and Social Computing
This volume constitutes the proceedings of the 27th International Conference on Collaboration Technologies and Social Computing, CollabTech 2021, held August/September 2021. Due to VOVID-19 pandemic is was held virtually. The 5 full and 4 work-in-process papers presented in this volume were carefully reviewed and selected from 19 submissions. The papers focus on innovative technical, human and organizational approaches to expand collaboration support including computer science, management science, design science, cognitive and social science.
New Trends in Database and Information Systems
This book constitutes thoroughly reviewed and selected short papers presented at the 25th East-European Conference on Advances in Databases and Information Systems, ADBIS 2021, as well as papers presented at doctoral consortium and ADBIS 2021 workshops. Due to the COVID-19 the conference and satellite events were held in hybrid mode. The 11 full papers and 18 short papers were carefully reviewed and selected from 97 total submissions. This volume presents the papers that have been accepted for the following satellite events: Workshop on Intelligent Data - From Data to Knowledge, DOING 2021; International Symposium on Data-Driven Process Discovery and Analysis, SIMPDA 2021; Workshop on Modern Approaches in Data Engineering and Information System Design, MADEISD 2021; Workshop on Advances in Data Systems Management, Engineering, and Analytics, MegaData 2021; Workshop on Computational Aspects of Network Science, CAoNS 2021; Doctoral Consortium.
Data Modeling with SAP Bw/4hana 2.0
Gain practical guidance for implementing data models on the SAP BW/4HANA platform using modern modeling concepts. You will walk through the various modeling scenarios such as exposing HANA tables and views through BW/4HANA, creating virtual and hybrid data models, and integrating SAP and non-SAP data into a single data model. Data Modeling with SAP BW/4HANA 2.0 gives you the skills you need to use the new SAP BW/HANA features and objects, covers modern modelling concepts, and equips you with the practical knowledge of how to use the best of the HANA and BW/4HANA worlds. What You Will Learn Discover the new modeling features in SAP BW/4HANA Combine SAP HANA and SAP BW/4HANA artifacts Leverage virtualization when designing and building data models Build hybrid data models combining InfoObject, OpenODS, and a field-based approach Integrate SAP and non-SAP data into single modelWho This Book Is For BI consultants, architects, developers, and analysts working in the SAP BW/4HANA environment.
Spatial Data and Intelligence
This book constitutes the proceedings of the Second International Conference on Spatial Data and Intelligence, SpatialDI 2021, which was held during April 22-24, 2021 in Hangzhou, China.The 14 full papers and 7 short papers presented in this volume were carefully reviewed and selected from 72 submissions. They are organized in the topical sections named: traffic management, data science, and city analysis.
Guide to Intelligent Data Science
Making use of data is not anymore a niche project but central to almost every project. With access to massive compute resources and vast amounts of data, it seems at least in principle possible to solve any problem. However, successful data science projects result from the intelligent application of: human intuition in combination with computational power; sound background knowledge with computer-aided modelling; and critical reflection of the obtained insights and results.Substantially updating the previous edition, then entitled Guide to Intelligent Data Analysis, this core textbook continues to provide a hands-on instructional approach to many data science techniques, and explains how these are used to solve real world problems. The work balances the practical aspects of applying and using data science techniques with the theoretical and algorithmic underpinnings from mathematics and statistics. Major updates on techniques and subject coverage (including deep learning) are included.Topics and features: guides the reader through the process of data science, following the interdependent steps of project understanding, data understanding, data blending and transformation, modeling, as well as deployment and monitoring; includes numerous examples using the open source KNIME Analytics Platform, together with an introductory appendix; provides a review of the basics of classical statistics that support and justify many data analysis methods, and a glossary of statistical terms; integrates illustrations and case-study-style examples to support pedagogical exposition; supplies further tools and information at an associated website.This practical and systematic textbook/reference is a "need-to-have" tool for graduate and advanced undergraduate students and essential reading for all professionals who face data science problems. Moreover, it is a "need to use, need to keep" resource following one's exploration of thesubject.
Logical Methods
Many believe mathematics is only about calculations, formulas, numbers, and strange letters. But mathematics is much more than just crunching numbers or manipulating symbols. Mathematics is about discovering patterns, uncovering hidden structures, finding counterexamples, and thinking logically. Mathematics is a way of thinking. It is an activity that is both highly creative and challenging. This book offers an introduction to mathematical reasoning for beginning university or college students, providing a solid foundation for further study in mathematics, computer science, and related disciplines. Written in a manner that directly conveys the sense of excitement and discovery at the heart of doing science, its 25 short and visually appealing chapters cover the basics of set theory, logic, proof methods, combinatorics, graph theory, and much more. In the book you will, among other things, find answers to: What is a proof? What is a counterexample?What does it mean to say that something follows logically from a set of premises?What does it mean to abstract over something?How can knowledge and information be represented and used in calculations?What is the connection between Morse code and Fibonacci numbers?Why could it take billions of years to solve Hanoi's Tower? Logical Methods is especially appropriate for students encountering such concepts for the very first time. Designed to ease the transition to a university or college level study of mathematics or computer science, it also provides an accessible and fascinating gateway to logical thinking for students of all disciplines.
The DataOps Revolution
DataOps is a new way of delivering data and analytics that is proven to get results. It enables IT and users to collaborate in the delivery of solutions that help organisations to embrace a data-driven culture. The DataOps Revolution: Delivering the Data-Driven Enterprise is a narrative about real world issues involved in using DataOps to make data-driven decisions in modern organisations. The book is built around real delivery examples based on the author's own experience and lays out principles and a methodology for business success using DataOps. Presenting practical design patterns and DataOps approaches, the book shows how DataOps projects are run and presents the benefits of using DataOps to implement data solutions. Best practices are introduced in this book through the telling of a story, which relates how a lead manager must find a way through complexity to turn an organisation around. This narrative vividly illustrates DataOps in action, enabling readers to incorporate best practices into everyday projects. The book tells the story of an embattled CIO who turns to a new and untested project manager charged with a wide remit to roll out DataOps techniques to an entire organisation. It illustrates a different approach to addressing the challenges in bridging the gap between IT and the business. The approach presented in this story lines up to the six IMPACT pillars of the DataOps model that Kinaesis (www.kinaesis.com) has been using through its consultants to deliver successful projects and turn around failing deliveries. The pillars help to organise thinking and structure an approach to project delivery. The pillars are broken down and translated into steps that can be applied to real-world projects that can deliver satisfaction and fulfillment to customers and project team members.
Big Data, IoT, and Machine Learning
The idea behind this book is to simplify the journey of aspiring readers and researchers to understand Big Data, IoT and Machine Learning. It also includes various real-time/offline applications and case studies in the fields of engineering, computer science, information security and cloud computing using modern tools. This book consists of two sections: Section I contains the topics related to Applications of Machine Learning, and Section II addresses issues about Big Data, the Cloud and the Internet of Things. This brings all the related technologies into a single source so that undergraduate and postgraduate students, researchers, academicians and people in industry can easily understand them. Features Addresses the complete data science technologies workflow Explores basic and high-level concepts and services as a manual for those in the industry and at the same time can help beginners to understand both basic and advanced aspects of machine learning Covers data processing and security solutions in IoT and Big Data applications Offers adaptive, robust, scalable and reliable applications to develop solutions for day-to-day problems Presents security issues and data migration techniques of NoSQL databases
Digital Transformation of Collaboration
This proceedings is focused on the emerging concept of Collaborative Innovation Networks (COINs). COINs are at the core of collaborative knowledge networks, distributed communities taking advantage of the wide connectivity and the support of communication technologies, spanning beyond the organizational perimeter of companies on a global scale. The book presents the refereed conference papers from the 7th International Conference on COINs, October 8-9, 2019, in Warsaw, Poland. It includes papers for both application areas of COINs, (1) optimizing organizational creativity and performance, and (2) discovering and predicting new trends by identifying COINs on the Web through online social media analysis. Papers at COINs19 combine a wide range of interdisciplinary fields such as social network analysis, group dynamics, design and visualization, information systems and the psychology and sociality of collaboration, and intercultural analysis through the lens of online social media. They will cover most recent advances in areas from leadership and collaboration, trend prediction and data mining, to social competence and Internet communication.
Data Processing with Optimus
Written by the core Optimus team, this comprehensive guide will help you to understand how Optimus improves the whole data processing landscape Key Features: Load, merge, and save small and big data efficiently with OptimusLearn Optimus functions for data analytics, feature engineering, machine learning, cross-validation, and NLPDiscover how Optimus improves other data frame technologies and helps you speed up your data processing tasksBook Description: Optimus is a Python library that works as a unified API for data cleaning, processing, and merging data. It can be used for handling small and big data on your local laptop or on remote clusters using CPUs or GPUs.The book begins by covering the internals of Optimus and how it works in tandem with the existing technologies to serve your data processing needs. You'll then learn how to use Optimus for loading and saving data from text data formats such as CSV and JSON files, exploring binary files such as Excel, and for columnar data processing with Parquet, Avro, and OCR. Next, you'll get to grips with the profiler and its data types - a unique feature of Optimus Dataframe that assists with data quality. You'll see how to use the plots available in Optimus such as histogram, frequency charts, and scatter and box plots, and understand how Optimus lets you connect to libraries such as Plotly and Altair. You'll also delve into advanced applications such as feature engineering, machine learning, cross-validation, and natural language processing functions and explore the advancements in Optimus. Finally, you'll learn how to create data cleaning and transformation functions and add a hypothetical new data processing engine with Optimus.By the end of this book, you'll be able to improve your data science workflow with Optimus easily.What You Will Learn: Use over 100 data processing functions over columns and other string-like valuesReshape and pivot data to get the output in the required formatFind out how to plot histograms, frequency charts, scatter plots, box plots, and moreConnect Optimus with popular Python visualization libraries such as Plotly and AltairApply string clustering techniques to normalize stringsDiscover functions to explore, fix, and remove poor quality dataUse advanced techniques to remove outliers from your dataAdd engines and custom functions to clean, process, and merge dataWho this book is for: This book is for Python developers who want to explore, transform, and prepare big data for machine learning, analytics, and reporting using Optimus, a unified API to work with Pandas, Dask, cuDF, Dask-cuDF, Vaex, and Spark. Although not necessary, beginner-level knowledge of Python will be helpful. Basic knowledge of the CLI is required to install Optimus and its requirements. For using GPU technologies, you'll need an NVIDIA graphics card compatible with NVIDIA's RAPIDS library, which is compatible with Windows 10 and Linux.
Multimedia Technology and Enhanced Learning
This two-volume book constitutes the refereed proceedings of the 3rd International Conference on Multimedia Technology and Enhanced Learning, ICMTEL 2021, held in April 2021. Due to the COVID-19 pandemic the conference was held virtually. The 97 revised full papers have been selected from 208 submissions. They describe new learning technologies which range from smart school, smart class and smart learning at home and which have been developed from new technologies such as machine learning, multimedia and Internet of Things.
Concurrent Data Processing in Elixir
Learn different ways of writing concurrent code in Elixir and increase your application's performance, without sacrificing scalability or fault-tolerance. Most projects benefit from running background tasks and processing data concurrently, but the world of OTP and various libraries can be challenging. Which Supervisor and what strategy to use? What about GenServer? Maybe you need back-pressure, but is GenStage, Flow, or Broadway a better choice? You will learn everything you need to know to answer these questions, start building highly concurrent applications in no time, and write code that's not only fast, but also resilient to errors and easy to scale. Whether you are building a high-frequency stock trading application or a consumer web app, you need to know how to leverage concurrency to build applications that are fast and efficient. Elixir and the OTP offer a range of powerful tools, and this guide will show you how to choose the best tool for each job, and use it effectively to quickly start building highly concurrent applications. Learn about Tasks, supervision trees, and the different types of Supervisors available to you. Understand why processes and process linking are the building blocks of concurrency in Elixir. Get comfortable with the OTP and use the GenServer behaviour to maintain process state for long-running jobs. Easily scale the number of running processes using the Registry. Handle large volumes of data and traffic spikes with GenStage, using back-pressure to your advantage. Create your first multi-stage data processing pipeline using producer, consumer, and producer-consumer stages. Process large collections with Flow, using MapReduce and more in parallel. Thanks to Broadway, you will see how easy it is to integrate with popular message broker systems, or even existing GenStage producers. Start building the high-performance and fault-tolerant applications Elixir is famous for today. What You Need: You'll need Elixir 1.9] and Erlang/OTP 22+ installed on a Mac OS X, Linux, or Windows machine.
Closing the Analytics Talent Gap
How can we recruit out of your program? We have a project - how do we reach out to your students? If we do research together who owns it? We have employees who need to "upskill" in analytics - can you help me with that? How much does all of this cost? Managers and executives are increasingly asking university professors such questions as they deal with a critical shortage of skilled data analysts. At the same time, academics are asking such questions as: How can I bring a "real" analytical project in the classroom? How can I get "real" data to help my students develop the skills necessary to be a "data scientist? Is what I am teaching in the classroom aligned with the demands of the market for analytical talent? After spending several years answering almost daily e-mails and telephone calls from business managers asking for staffing help and aiding fellow academics with their analytics teaching needs, Dr. Jennifer Priestley of Kennesaw State University and Dr. Robert McGrath of the University of New Hampshire wrote Closing the Analytics Talent Gap: An Executive's Guide to Working with Universities. The book builds a bridge between university analytics programs and business organizations. It promotes a dialog that enables executives to learn how universities can help them find strategically important personnel and universities to learn how they can develop and educate this personnel. Organizations are facing previously unforeseen challenges related to the translation of massive amounts of data - structured and unstructured, static and in-motion, voice, text, and image - into information to solve current challenges and anticipate new ones. The advent of analytics and data science also presents universities with unforeseen challenges of providing learning through application. This book helps both organizations with finding "data natives" and universities with educating students to develop the facility to work in a multi-faceted and complex data environment. .　　
