The Entity-relationship Model
In "The Entity-relationship Model: A Basis for the Enterprise View of Data," Peter P.S. Chen presents the foundational concepts of the Entity-Relationship (ER) model. This seminal work, originally published in 1976, introduces a high-level data model designed to facilitate database design and data management within organizations. Chen's ER model offers a structured approach to representing data entities, attributes, and relationships, providing a clear and intuitive framework for understanding and organizing complex data structures. The book explores the principles behind the ER model, illustrating how it can be used to create a comprehensive enterprise view of data. It emphasizes the importance of effective communication between database designers, users, and managers, and demonstrates how the ER model can serve as a common language for defining data requirements and designing robust database systems. This work remains a crucial resource for anyone involved in database design, data modeling, and information management.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Multilingual Phoneme Models for Rapid Speech Processing System Development
Current speech recognition systems tend to be developed only for commercially viable languages. The resources needed for a typical speech recognition system include hundreds of hours of transcribed speech for acoustic models and 10 to 100 million words of text for language models; both of these requirements can be costly in time and money. The goal of this research is to facilitate rapid development of speech systems to new languages by using multilingual phoneme models to alleviate requirements for large amounts of transcribed speech. The GlobalPhone database, which contains transcribed speech from 15 languages, is used as source data to derive multilingual phoneme models. Various bootstrapping processes are used to develop an Arabic speech recognition system starting from monolingual English models, International Phonetic Association (IPA) based multilingual models, and data-driven multilingual models. The Kullback-Leibler distortion measure is used to derive datadriven phoneme clusters. It was found that multilingual bootstrapping methods outperform monolingual English bootstrapping methods on the Arabic evaluation data initially, and after three iterations of bootstrapping all systems show similar performance levels. Applications of this research are in speech recognition, word spotting, information retrieval, and speech-to-speech translation.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Generating Executable Persistent Data Storage/Retrieval Code From Object-Oriented Specifications
This research creates a methodology and corresponding prototype for the transformation of object-oriented (00) specifications to represent the corresponding relational schemas that are used to automatically generate database design language (DDL). The transformation design decisions and specifications are then used to generate database manipulation language (DML) that can be embedded within the software application code generated from the same 00 specifications. This concept of developing a model for producing compliable and executable code from formal software specifications has long been a goal of software engineers. Previous research at the Air Force Institute of Technology (AFIT) has not focused on the representation of persistent data from 00 software specifications. Relational databases are historically among the most popular methods of managing persistent data associated with software systems.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Design and Implementation of Replicated Object Layer
One of the widely used techniques for construction of fault tolerant applications is the replication of resources so that if one copy fails sufficient copies may still remain operational to allow the application to continue to function. This thesis involves the design and implementation of an object oriented framework for replicating data on multiple sites and across different platforms. Our approach, called the Replicated Object Layer (ROL) provides a mechanism for consistent replication of data over dynamic networks. ROL uses the Reliable Multicast Protocol (RMP) as a communication protocol that provides for reliable delivery, serialization and fault tolerance. Besides providing type registration, this layer facilitates distributed atomic transactions on replicated data. A novel algorithm called the RMP Commit Protocol, which commits transactions efficiently in reliable multicast environment is presented. ROL provides recovery procedures to ensure that site and communication failures do not corrupt persistent data, and male the system fault tolerant to network partitions. ROL will facilitate building distributed fault tolerant applications by performing the burdensome details of replica consistency operations, and making it completely transparent to the application.Replicated databases are a major class of applications which could be built on top of ROL.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Parallel Data Mining With the Message Passing Interface Standard on Clusters of Personal Computers
Piles of personal computers (PoPCs) have begun to challenge the performance of the traditional Massively Parallel Processors (MPPs) and the less traditional networks of workstations (NOWs) as platforms for parallel computing. Large clusters of PCs have reached and at times exceeded the performance of modern MPPs at a fraction of the cost. Built with commodity components, these clusters can be constructed for about half the cost of a comparable NOW. The primary competing operating systems (O/S) in use on PoPCs are Linux and Windows NT. This thesis investigation compares the performance of an NT cluster with that of a Linux cluster, a NOW, and an MPP. A comparison of the MPI tools available for NT is also accomplished. These comparisons are made using the Pallas benchmark suite for MPI and a parallel data mining algorithm. This data mining technique, known as the Genetic Rule and Classifier Construction Environment (GRaCCE), uses a genetic algorithm to mine decision rules from data.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Modeling Information Quality Expectation in Unmanned Aerial Vehicle Swarm Sensor Databases
Swarming Unmanned Aerial Vehicles (UAVs) are the future of Intelligence, Surveillance and Reconnaissance (ISR). Swarms of hundreds of these vehicles, each equipped with multiple sensors, will one day fill the skies over hostile areas. As the sensors collect hundreds of gigabytes of data, telemetry data links will be unable to transmit the complete data picture to the ground in real time. The collected data will be stored on board the UAVs and selectively downloaded through queries issued from analysts on the ground. Analysts expect to find relevant sensor data within the collection of acquired sensor data. This expectation is not a quantified value, rather a confidence that this relevant data exists. An expectation of the likely quality of the available sensor information is determined by the user through the use of the methods and tools developed in this thesis.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Reducing Electrical Power Demand in US Air Force Data Centers
The growing demand for information technology drives the creation of more data centers. This equipment requires a great deal of electricity, either to power the equipment or the air conditioning to cool the equipment. The solution to this problem will require investment in new technologies to reduce the electricity required to provide the same computing power and the same amount of cooling. Before any technology upgrade is purchased, some serious political hurdles need to be addressed.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Multilingual Phoneme Models for Rapid Speech Processing System Development
Current speech recognition systems tend to be developed only for commercially viable languages. The resources needed for a typical speech recognition system include hundreds of hours of transcribed speech for acoustic models and 10 to 100 million words of text for language models; both of these requirements can be costly in time and money. The goal of this research is to facilitate rapid development of speech systems to new languages by using multilingual phoneme models to alleviate requirements for large amounts of transcribed speech. The GlobalPhone database, which contains transcribed speech from 15 languages, is used as source data to derive multilingual phoneme models. Various bootstrapping processes are used to develop an Arabic speech recognition system starting from monolingual English models, International Phonetic Association (IPA) based multilingual models, and data-driven multilingual models. The Kullback-Leibler distortion measure is used to derive datadriven phoneme clusters. It was found that multilingual bootstrapping methods outperform monolingual English bootstrapping methods on the Arabic evaluation data initially, and after three iterations of bootstrapping all systems show similar performance levels. Applications of this research are in speech recognition, word spotting, information retrieval, and speech-to-speech translation.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Data-Centric Business and Applications
This book provides a comprehensive insight into contemporary management challenges shaped by digital transformation, operational excellence, and data-driven human resource strategies. It presents innovative frameworks for decision-making, workforce optimization, and financial innovation by integrating theoretical perspectives with real-world applications. With contributions from international scholars, it offers fresh perspectives on emerging technologies, sustainability, and business intelligence. Designed for academics, professionals, and policymakers, the book serves as a valuable resource for understanding and implementing effective management strategies in the digital era.
MongoDB in Action, Third Edition
Deliver flexible, scalable, and high-performance data storage that's perfect for AI and other modern applications with MongoDB 8.0 and MongoDB Atlas multi-cloud data platform. In MongoDB 8.0 in Action, Third Edition you'll find comprehensive coverage of the latest version of MongoDB 8.0 and the MongoDB Atlas multi-cloud data platform. Learn to utilize MongoDB's flexible schema design for data modeling, scale applications effectively using advanced sharding features, integrate full-text and vector-based semantic search, and more. This totally revised new edition delivers engaging hands-on tutorials and examples that put MongoDB into action! In MongoDB 8.0 in Action, Third Edition you'll: - Master new features in MongoDB 8.0 - Create your first, free Atlas cluster using the Atlas CLI - Design scalable NoSQL databases with effective data modeling techniques - Master Vector Search for building GenAI-driven applications - Utilize advanced search capabilities in MongoDB Atlas, including full-text search - Build Event-Driven Applications with Atlas Stream Processing - Deploy and manage MongoDB Atlas clusters both locally and in the cloud using the Atlas CLI - Leverage the Atlas SQL interface for familiar SQL querying - Use MongoDB Atlas Online Archive for efficient data management - Establish robust security practices including encryption - Master backup and restore strategies - Optimize database performance and identify slow queries MongoDB 8.0 in Action, Third Edition offers a clear, easy-to-understand introduction to everything in MongoDB 8.0 and MongoDB Atlas--including new advanced features such as embedded config servers in sharded clusters, or moving an unsharded collection to a different shard. The book also covers Atlas stream processing, full text search, and vector search capabilities for generative AI applications. Each chapter is packed with tips, tricks, and practical examples you can quickly apply to your projects, whether you're brand new to MongoDB or looking to get up to speed with the latest version. About the technology MongoDB is the database of choice for storing structured, semi-structured, and unstructured data like business documents and other text and image files. MongoDB 8.0 introduces a range of exciting new features--from sharding improvements that simplify the management of distributed data, to performance enhancements that stay resilient under heavy workloads. Plus, MongoDB Atlas brings vector search and full-text search features that support AI-powered applications. About the book MongoDB 8.0 in Action, Third Edition you'll learn how to take advantage of all the new features of MongoDB 8.0, including the powerful MongoDB Atlas multi-cloud data platform. You'll start with the basics of setting up and managing a document database. Then, you'll learn how to use MongoDB for AI-driven applications, implement advanced stream processing, and optimize performance with improved indexing and query handling. Hands-on projects like creating a RAG-based chatbot and building an aggregation pipeline mean you'll really put MongoDB into action! What's inside - The new features in MongoDB 8.0 - Get familiar with MongoDB's Atlas cloud platform - Utilizing sharding enhancements - Using vector-based search technologies - Full-text search capabilities for efficient text indexing and querying About the reader For developers and DBAs of all levels. No prior experience with MongoDB required. About the author Arek Borucki is a MongoDB Champion, certified MongoDB and MongoDB Atlas administrator with expertise in distributed systems, NoSQL databases, and Kubernetes. Table of Contents Part 1 1 Understanding the world of MongoDB 2 Getting started with Atlas and MongoDB data 3 Communicating with MongoDB 4 Executing CRUD operations 5 Designing a MongoDB schema 6 Building aggregation
Learning Tableau 2025 - Sixth Edition
Explore the full potential of Tableau and learn how to draw valuable insights from data directly from a Tableau Visionary and Zen MasterKey Features: - Learn Tableau's foundational principles while exploring new AI features like Tableau Pulse and Agent- Transform complex datasets into interactive insights with Tableau Prep- Gain deeper insights using geospatial analysis and advanced methods- Purchase of the print or Kindle book includes a free PDF eBookBook Description: Tableau 2025 marks a new era in data visualization and analysis, bringing together advanced AI integrations and dynamic user experiences. This sixth edition, written by Tableau Visionary and Zen Master Joshua Miligan, is an end-to-end guide to mastering the latest innovations in Tableau that transform raw data into actionable insights.This edition introduces groundbreaking features like Tableau AI (including Tableau Pulse and Tableau Agent), enhancing your analytical capabilities with AI-driven data exploration and automated insights. With detailed walkthroughs, you'll learn to build dynamic dashboards that respond to your data in real time and work with sophisticated AI functionalities that predict trends and model scenarios.Whether you're a seasoned data professional or new to Tableau, this book provides the tools you need to leverage Tableau's full potential. From integrating diverse data sources using the enhanced data model to employing advanced geospatial functions for detailed mapping, every chapter is packed with expert knowledge and practical applications designed to put powerful analytics at your fingertips.What You Will Learn: - Implement advanced AI features to streamline data analysis- Build and customize dynamic dashboards for interactive data storytelling- Leverage new geospatial functions for comprehensive mapping- Enhance data prep with Tableau Prep's new features- Integrate and analyze data from multiple sources effectively- Share your data stories to build a culture of trust and actionWho this book is for: This Tableau book is for aspiring BI developers and data analysts, data scientists, researchers, and anyone else who wants to gain a deeper understanding of data using Tableau. This book takes you from the ground up, so you won't need any prior experience with Tableau before you dive in, but a full Tableau license (or 14-day demo license) is essential to be able to make use of all the exercises.Table of Contents- Taking Off with Tableau- Connecting to Data and Tableau- Moving Beyond Basic Visualization- Starting an Adventure with Calculations- Leveraging Level of Detail Calculations- Diving Deep with Table Calculations- Making Visualizations that Look Great and Work Well- Telling a Data Story with Dashboards- Visual Analytics: Trends, Clustering, Distributions and Forecasting- Advanced Visualization- Dynamic Dashboards- Exploring Mapping and Advanced Geospatial Features- Understanding the Tableau Data Model, Joins, and Blends- Structuring Messy Data to Work Well in Tableau- Taming Data with Tableau Prep- Extending Tableau: Extensions and Scripts- AI-Assisted Analysis: Tableau Agent and Tableau Pulse
Adversarial Deep Generative Techniques for Early Diagnosis of Neurological Conditions and Mental Health Practises
Management of Digital Ecosystems
This book constitutes the proceedings of the 16th International Conference on Management of Digital EcoSystems, MEDES 2024, held in Naples, Italy, during November 2024. The 23 full papers and 10 Short papers included in this book were carefully reviewed and selected from 65 submissions. They were organized in topical sections as follows: Energy and Environment; Recommendation Systems; Social Networks and Emotion Recognition; Medical and Health Issues; Cybersecurity and Privacy; Data Mining Operations; Parallel and Distributed Systems; Network Aspects, and Applications.
Excel Spreadsheet Tools for Analyzing Groundwater Level Records and Displaying Information in ArcMap
When beginning hydrologic investigations, a first action is often to gather existing sources of well information, compile this information into a single dataset, and visualize this information in a geographic information system (GIS) environment. This report presents tools (macros) developed using Visual Basic for Applications (VBA) for Microsoft Excel 2007 to assist in these tasks. One tool combines multiple datasets into a single worksheet and formats the resulting data for use by the other tools. A second tool produces summary information about the dataset, such as a list of unique site identification numbers, the number of water-level observations for each, and a table of the number of sites with a listed number of water-level observations. A third tool creates subsets of the original dataset based on user-specified options and produces a worksheet with water-level information for each well in the subset, including the average and standard deviation of water-level observations and maximum decline and rise in water levels between any two observations, among other information. This water-level information worksheet can be imported directly into ESRI ArcMap as an 'XY Data' file, and each of the fields of summary well information can be used for custom display. A separate set of VBA tools distributed in an additional Excel workbook creates hydrograph charts of each of the wells in the data subset produced by the aforementioned tools and produces portable document format (PDF) versions of the hydrograph charts. These PDF hydrographs can be hyperlinked to well locations in ArcMap or other GIS applications.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Excel Spreadsheet Tools for Analyzing Groundwater Level Records and Displaying Information in ArcMap
When beginning hydrologic investigations, a first action is often to gather existing sources of well information, compile this information into a single dataset, and visualize this information in a geographic information system (GIS) environment. This report presents tools (macros) developed using Visual Basic for Applications (VBA) for Microsoft Excel 2007 to assist in these tasks. One tool combines multiple datasets into a single worksheet and formats the resulting data for use by the other tools. A second tool produces summary information about the dataset, such as a list of unique site identification numbers, the number of water-level observations for each, and a table of the number of sites with a listed number of water-level observations. A third tool creates subsets of the original dataset based on user-specified options and produces a worksheet with water-level information for each well in the subset, including the average and standard deviation of water-level observations and maximum decline and rise in water levels between any two observations, among other information. This water-level information worksheet can be imported directly into ESRI ArcMap as an 'XY Data' file, and each of the fields of summary well information can be used for custom display. A separate set of VBA tools distributed in an additional Excel workbook creates hydrograph charts of each of the wells in the data subset produced by the aforementioned tools and produces portable document format (PDF) versions of the hydrograph charts. These PDF hydrographs can be hyperlinked to well locations in ArcMap or other GIS applications.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Searching for Patterns
Original edition reissued in 2023 with new cover. This is a print on demand title and is not held in stock. The delivery leadtimes will be longer. Data mining is about finding patterns hidden inside data. It's how the supermarket knows when your kids leave home or when your granny comes to visit; it's how the credit card company detects fraud and how your insurance company decides whether to cover you.Searching For Patterns guides you through the techniques used to do this and the people behind them, in an easily accessible and entertaining way. Data mining is mathematical, but all the maths in this book has been kept separate from the main text, so you can skip it if you want.
Big Data in Finance: Transforming the Financial Landscape
New Paradigms in Big Data Technology and Business Analytics
"New Paradigms in Big Data Technology and Business Analytics" emphasize the integration of Big Data Technology and Business Analytics enables organizations to transform vast volumes of data into strategic insights, driving smarter decisions, operational efficiency, and innovative growth. This volume presents a comprehensive exploration of the evolving landscape of Big Data Technology and Business Analytics, showcasing transformative approaches that are reshaping industries and research alike. It highlights the integration of advanced tools such as artificial intelligence, machine learning, data mining, and cloud infrastructure to drive intelligent decision-making and operational efficiency. Focusing on both theoretical frameworks and real-world case studies, this book explores into five essential domains: Big Data Infrastructure and Technologies, Data Mining and Machine Learning, Big Data Applications and Case Studies, Business Intelligence and Decision Support, and Data Governance and Ethics. By merging theoretical knowledge with practical applications, this book equips educators, researchers, practitioners, and students with actionable insights into how data-driven strategies can unlock sustainable growth and innovation across sectors. With a forward-thinking vision, it addresses key issues like data privacy, algorithmic fairness, and strategic deployment of analytics in diverse environments. By blending emerging technologies with practical applications, this book serves as a roadmap for anyone aiming to harness the full potential of big data to reshape modern business and society.
Neural Information Processing
The eleven-volume set LNCS 15286-15295 constitutes the refereed proceedings of the 31st International Conference on Neural Information Processing, ICONIP 2024, held in Auckland, New Zealand, in December 2024. The 318 regular papers presented in the proceedings set were carefully reviewed and selected from 1301 submissions. They focus on four main areas, namely: theory and algorithms; cognitive neurosciences; human-centered computing; and applications.
Infrastructures of Reality: Metaverse Stories, Spaces, Bodies
This open access book focuses on two dimensions of the development of the metaverse that are crucial to 'reality', namely spatiality and embodiment. Metaversal technologies are thought to fundamentally affect both our spaces and bodies, which are two central aspects of the constitution of social reality. Both spatiality and embodiment are core elements of world-making that are being pulled into the ambit of metaversal projects. On the one hand, metaversal technologies are profoundly spatial in the sense that they render space in virtual form or overlay digital layers onto pre-existing physical spaces. On the other hand, metaversal technologies are directly geared towards the body in that they not only seek to extend or expand our embodied senses and emplace our bodies in virtual spaces, but they also seek to capture their behaviours and actions on a far more granular level. This can create new opportunities in terms of work, social interaction, and leisure, but can also open our bodies up to new, tech-driven interventions and control. Whether in the form of VR or AR, such technologies not only reproduce space but also rely on making spaces more legible and open to automated interventions. Taken together, the 'metaversification' of spaces and bodies gives rise to crucial questions about the goals and implications of metaversal developments by large technology companies and about the relationship between the developments of the metaverse and AI systems. Drawing on our combined background and expertise in Science and Technology Studies and the History of Media and Communication, we critically analyse the development of metaversal technologies and platforms by discussing a broad set of developments and examples from a wide range of technology and gaming companies. Written in clear, concise, and accessible language, and combining and applying novel theoretical frameworks and concepts to a currently emergent phenomenon, this book will find a large audience not only within academic and professional circles but also in popular culture.
From Chaos to Clarity
A radical wake up call for world overloaded with data and how data visualisation could be the answer In From Chaos to Clarity: How Data Visualisation Can Save the World, celebrated data visualisation creator James Eagle reveals how our data-saturated age harbours hidden dangers that places humanity in peril. He looks at how masterful visual storytelling might be our salvation. Through vivid examples and profound insights, James Eagle exposes the data pollution clouding modern life, whilst demonstrating how thoughtful, human-centred data visuals can cut through the noise, sharpen our collective understanding and light the path toward a more discerning future. Inside the book: How to unlock the human side of data visualisation by using empathy and storytelling Understanding our brain's deep connection to pictures and stories, and why this matters in this digital age Ways data visualisation can restore our human understanding of this world and tackle misinformation This is a must-read urgent message on how data visualisation is needed to confront data overload and misuse. From Chaos to Clarity is perfect for professionals in finance, engineering, science, mathematics and health, as well as journalists, writers, data scientists, and anyone interested in visual storytelling, reclaiming truth and sharpening our collective thinking to tackling some of the biggest challenges we face in this world.
Digital Transformation in Sports
This book examines the digital transformation of the sports industry. It explores the digital and technological changes that will shape the sports industry for years to come. Topics covered include digital innovation, AI, machine learning, optimization, data privacy and security, organizational behavior, and globalization.
Automatic Question Generation
This book provides an overview of the fundamentals of Automatic Question Generation (AQG) for computational linguistics researchers, test developers, and educators. The author presents a variety of AQG system architectures, including generating questions from syntactic analyses, semantic resources, neural architectures, ontologies and knowledge graphs, and large language models. The advantages and pitfalls of a variety of AQG evaluation methods, including multi-aspect ratings by human experts, end-users, as well as crowd-sourcing and automatic evaluation techniques are discussed. The book also provides a roadmap of options for AQG targeted orientation, content selection, and focusing decisions. Machine learning opportunities for training systems to generate questions based on human-generated examples are also explored. This book offers greater depth and breadth than previous surveys of AQG. Readers will gain a comprehensive knowledge of current research, examples of applications of AQG, and inspiration for future directions for innovation and application.
Legaltech and Legal-AI in Business
This book offers an interdisciplinary scientific study and ecosystem description of organizational and institutional mechanisms for the introduction of artificial intelligence technologies, digital technologies and robotic systems in the legal support of business processes, the development of regulatory mechanisms to protect the rights of business entities in the digital economy, and the formation of the sixth technological mode. This book includes the study of legal support of the main and promising areas of business, in the regulation of which robotics, digital technologies, and artificial intelligence are actively used to increase efficiency, protect the rights of participants, minimize business risks, improve quality, and stimulate innovation in companies and high-tech production. This book provides applied recommendations for preventing and managing business risks in the context of the application of artificial intelligence and robotics in law.
An Introduction to the Theory of Observational Studies
This book is an introduction to the theory of causal inference in observational studies. An observational study draws inferences about the effects caused by treatments or preventable exposures when randomized experimentation is unethical or infeasible. An observational study is distinguished from an experiment by the problems that follow from the absence of randomized assignment of individuals to treatments. Observational studies are common in most fields that study the effects of treatments or policies on people, including public health and epidemiology, economics and public policy, medicine and clinical psychology, and criminology and empirical legal studies. After Part I reviews causal inference in randomized experiments, the twelve short chapters in Parts II, III and IV introduce modern topics: the propensity score, ignorable treatment assignment, the principal unobserved covariate, algorithms for optimal matching, randomized reassignment techniques for appraising the covariate balance achieved by matching, covariance adjustment, sensitivity analysis, design sensitivity, ways to design an observational study to be insensitive to larger unmeasured biases, the large sample efficiency of a sensitivity analysis, quasi-experimental devices that provide observable information about unmeasured biases, evidence factors and complementary analyses to address unmeasured biases. The book is accessible to anyone who has completed an undergraduate course in mathematical statistics. The subject is developed with the aid of two simple empirical examples concerning the health benefits or harms caused by consuming alcohol. The data for these examples and their reanalyses are freely available in an R package, iTOS, associated with Introduction to the Theory of Observational Studies.
Quantum Level Business Model: A New Managerial Perspective
Data Analytics for Smart Robotics and Its Applications
By offering a deep dive into the integration of robotics and IoT, this book provides actionable insights for developing autonomous systems that address complex real-world challenges in sectors such as healthcare, agriculture, education, manufacturing, and smart cities. It explores practical applications of the Internet of Robotic Things (IoRT), enabling readers to leverage its transformative potential to create smarter, more efficient environments. The book introduces a fresh perspective by combining the fields of robotics and IoT into a cohesive framework, underpinned by innovations in edge computing, cloud robotics, and Industry 4.0. Unlike traditional approaches, it emphasizes the convergence of these technologies to foster novel solutions for remote automation and data-driven intelligence. Covering topics like data management, machine learning, Hadoop, and IoRT applications, this book provides a comprehensive scope that balances theoretical foundations with real-world implementations. It is tailored for academic researchers, practitioners, and educators aiming to stay at the forefront of IoRT innovation and its practical deployment. With its unique approach and broad applicability, this book is an essential guide for exploring cutting-edge IoRT technologies, overcoming integration challenges, and inspiring the development of advanced systems that redefine how technology interacts with the physical world.
Signal in the Noise
Signal in the Noise: Mastering the Art and Science of Data-Driven Discovery is an essential guide for navigating today's data-rich world, where the real challenge lies not in gathering information but in extracting meaningful insights from the chaos. This book equips readers with the critical thinking, technical skills, and ethical awareness needed to transform raw data into powerful discoveries.Blending rigorous analysis with practical wisdom, it explores the full spectrum of data science from statistical reasoning and machine learning to causal inference, time series forecasting, and complex systems. Alongside cutting-edge methodologies, the book confronts the ethical dilemmas of algorithmic bias, privacy, and responsible innovation, ensuring readers are prepared to wield data as a force for good.Whether you're a data scientist, business leader, researcher, or curious learner, Signal in the Noise provides the framework to distinguish true patterns from randomness and make smarter, more impactful decisions in an increasingly data-driven world.
Cybersecurity Career Compass
Cybersecurity Career Compass: Navigate Your Path from Beginner to CISOIn today's digital-first world, cybersecurity is not just a technical field-it's a mission-critical discipline that touches every industry. Yet, for many aspiring professionals, breaking into the cybersecurity space can feel like stepping into a labyrinth of confusing roles, certifications, tools, and specializations. Cybersecurity Career Compass is here to light the way.Whether you're starting fresh, transitioning careers, or seeking to rise to leadership roles like Chief Information Security Officer (CISO), this book is your practical, insightful guide to building and navigating a successful cybersecurity career.A Comprehensive, Actionable FrameworkStructured around five core cybersecurity domains-Security Principles, Business Continuity & Disaster Recovery, Incident Response, Access Controls, and Network Security-this book delivers clarity where most resources provide only complexity. Each chapter breaks down vital concepts, tools, frameworks, and real-world applications, helping you not only understand cybersecurity but thrive in it.Domain 1: Security Principles - Learn the foundations of cybersecurity including CIA Triad, risk management, and ethical conduct.Domain 2: Business Continuity, Disaster Recovery, & Incident Response - Discover how to keep businesses resilient in the face of cyber threats.Domain 3: Access Controls - Understand the models and mechanisms that safeguard digital assets.Domain 4: Network Security - Explore essential protocols, OSI model, firewalls, antivirus strategies, and infrastructure protection.Domain 5: Security Operations - From cryptography to secure data disposal, build habits and systems for operational security excellence.Your Roadmap to the Certified in Cybersecurity (CC) CertificationThis book is aligned with the Certified in Cybersecurity (CC) exam from ISC2, the globally recognized leader in cybersecurity certifications. If you're preparing for this foundational exam-or considering it-Cybersecurity Career Compass will strengthen your conceptual understanding and boost your confidence.Best of all, ISC2 is currently offering the CC certification exam for free, making it a no-cost, high-value credential to launch your career.Career Guidance Rooted in Real-World StrategyMore than a technical manual, this book also addresses: Entry-level job readiness, mapped to the CIA Triad and ISO 27001 principles.The soft skills needed to excel-communication, problem-solving, adaptability.Long-term growth strategies to reach executive roles like CISO.How to align your values, motivations, and goals with the right cybersecurity path.Whether you prefer to read straight through or focus on chapters that match your interests or certification goals, this book adapts to your needs and stage of career development.Why Choose Cybersecurity Career Compass?Designed for beginners and career switchers, no prior experience neededComplements ISC2's CC exam preparation and career launchFocuses on real-world skills, not just theoryEncourages growth across both technical and leadership dimensionsHelps you align cybersecurity with your personal purpose and career mission Take control of your cybersecurity journey. Equip yourself with the skills, insights, and direction you need to succeed - whether you're aiming for your first analyst job or climbing toward executive leadership. Let this book be your compass.
Cross-Linguistic Mediated Communication: Hybrid Text Production English-Spanish
Hybrid text production today comprises machine translation chunks, human-produced paragraphs modelled on the writer's L1, and generative AI contributions via prompting. This book explores how corpus-based cross-linguistic studies can contribute to building and optimising Natural Language Generation in multilingual contexts. The aim is to show how rich linguistic annotation can provide valuable data to enhance and refine hybrid text production. Corpus data are mined from CLANES, a multilayer English-Spanish comparable corpus annotated for PoS, semantic, rhetorical and pragmatic information. The study highlights the implications of leveraging LLMs for the automatic generation of domain-specific texts. It also addresses the new challenges and opportunities raised by AI-enhanced data augmentation and post-editing, stressing the need for human control over text generation.
Proceedings of the International Conferences on Digital Technology Driven Engineering 2024
This book gathers the latest advances, innovations, and applications in the field of engineering optimization and architectural design, presented at the 1st International Conference on ADDitively Manufactured OPTimized Structures by means of Machine Learning (ADDOPTML), held in Amman, Jordan, on October 1-4, 2024, jointly with conferences OPTARCH2024 and OPT-ii2024. It covers topics such as machine learning-based design manufacturing process for civil structures, additive manufacturing optimized structural elements, holistic machine learning aided, linear, nonlinear, stochastic, parametric, discrete and dynamic programming--modelling, hybrid methods with metaheuristics, machine learning, game theory, mathematical programming, constraint programming, co-evolutionary, emergent nature-inspired algorithms such as quantum computing and artificial immune systems. Written by leading researchers and engineers, and selected by means of a rigorous international peer-review process, the contributions highlight numerous exciting ideas that will spur novel research directions and foster multidisciplinary collaborations.
Advances on Intelligent Computing and Data Science II
This book presents the proceedings of the 4th International Conference on Advanced Computing and Informatics (ICACIn'24). The conference, held on December 16-17, 2024, at STEAMhouse, Birmingham City University (UK), with a parallel session at Hassan II University (Morocco), attracted submissions by researchers in 20 countries. Out of 91 submissions, 46 high-quality papers were selected, presenting the latest advancements and cutting-edge developments in computing and informatics. The book covers a wide range of advanced computing topics, including data science, big data analytics, the Internet of Things (IoT), smart computing, artificial intelligence, machine learning, cybersecurity, intelligent communication systems, health informatics, and information systems. Designed for researchers, practitioners, and graduate students, this book serves as a valuable resource for exploring advanced intelligent computing techniques and their real-world applications.
Generalized Linear Models
Since they were first formulated in 1972, generalized linear models have enjoyed a veritable boom, with numerous applications in insurance, economics and biostatistics. Today, they are still the subject of a great deal of research. This book provides an overview of the theory of generalized linear models. Particular attention is paid to the problems of censoring, missing data and excess zeros. Didactic and accessible, Generalized Linear Models is illustrated with exercises and numerous R codes. With all the necessary prerequisites introduced in a step-by-step fashion, this book is aimed at students (at master's or engineering school level), as well as teachers and practitioners of mathematics and statistical modeling.
Neural Information Processing
The eleven-volume set LNCS 15286-15295 constitutes the refereed proceedings of the 31st International Conference on Neural Information Processing, ICONIP 2024, held in Auckland, New Zealand, in December 2024. The 318 regular papers presented in the proceedings set were carefully reviewed and selected from 1301 submissions. They focus on four main areas, namely: theory and algorithms; cognitive neurosciences; human-centered computing; and applications.
Trends and Applications in Knowledge Discovery and Data Mining
This book constitutes the refereed proceedings of five workshops that were held in conjunction with the 29th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2025, held in Sydney, New South Wales, Australia, during June 10-13, 2025. The 31 papers presented in here were carefully reviewed and selected from 54 submissions. This volume includes the proceedings from the following Workshops: Workshop on Advanced Data-Driven Techniques for Urban Resilience (ADUR 2025) Workshop of Foundational AI for Pervasive Computing (FairPC 2025) Workshop on Graph Learning with Foundation Models (GLFM 2025) Workshop on Pattern Mining and Machine Learning for Bioinformatics (PM4B 2025) Workshop on Research and Applications of Foundation Models for Data Mining and Affective Computing (RAFDA 2025)
Proceedings of the International Conferences on Digital Technology Driven Engineering 2024
This book gathers the latest advances, innovations, and applications in the field of optimization-driven architectural design, presented at the 2nd International Conference on Optimization Driven Architectural Design, held in Amman, Jordan, on October 1-4, 2024, jointly with conferences OPT-ii2024 and ADDOPTML2024. It covers topics such as optimization software, evolutionary algorithms & swarm optimization, robust design optimization & reliability based design optimization, optimization in micro- and nano-mechanics, multiscale & additive manufacturing, multidisciplinary and multiphysics design optimization, multiple criteria decision making and optimization, generative and parametric design, parallel and distributed computing in optimization. Written by leading researchers and engineers, and selected by means of a rigorous international peer-review process, the contributions highlight numerous exciting ideas that will spur novel research directions and foster multidisciplinary collaborations.
Proceedings of the International Conferences on Digital Technology Driven Engineering 2024
This book gathers the latest advances, innovations, and applications in the field of engineering optimization, presented at the 2nd Engineering and Applied Sciences Optimization (OPT-ii) and held in Amman, Jordan, on October 1-4, 2024, jointly with conferences OPTARCH2024 and ADDOPTML2024. It covers topics such as shape and topology optimization, structural optimization, optimization in micro- and nano-mechanics, lifecycle design optimization and structural health monitoring, multidisciplinary and multiphysics design optimization, multiple criteria decision making and optimization. Written by leading researchers and engineers, and selected by means of a rigorous international peer-review process, the contributions highlight numerous exciting ideas that will spur novel research directions and foster multidisciplinary collaborations.
Digital and Information Technologies in Economics and Management
This book addresses issues of networks and systems related to the use of information technologies in economics and management of various sectors. The IV International Scientific and Practical Conference "Digital and Information Technologies in Economics and Management" (DITEM2024) was held on November 20-22, 2024. A distinctive feature of the conference is that it featured presentations by authors from Korea, Japan, Turkey, Azerbaijan, Turkmenistan, Uzbekistan and Russia. Researchers from different countries presented the process of transition to new information technologies of various network and system structures and sectors. The book made it possible to develop new scientific recommendations on the use of information, computer, digital and intellectual technologies and networks in industry and fields of activity that can be useful to state and regional authorities, international and supranational organizations, the scientific and professional community.
The Age Of Data
The Age of Data offers a sweeping examination of how the relentless surge of information is fundamentally transforming every aspect of human civilization. In this meticulously researched work, the author traces the extraordinary journey of data from its humble beginnings as simple record-keeping to its current status as the most valuable commodity in the digital economy. The book presents a compelling narrative that intertwines technological evolution with profound societal shifts, demonstrating how data analytics and artificial intelligence are reshaping industries, governments, and individual lives in ways both revolutionary and unsettling.Through vivid case studies and penetrating analysis, the author illuminates how data-driven decision making has become the cornerstone of modern enterprises, from Silicon Valley tech giants to Wall Street investment firms. The work explores the dual nature of our data-centric world - celebrating its remarkable capacity to solve complex global challenges while sounding urgent warnings about privacy erosion, algorithmic bias, and the concentration of power in the hands of data oligarchs.Particular attention is given to the ethical quandaries emerging at the frontiers of big data applications, including predictive policing, personalized medicine, and social credit systems. The author provides a balanced perspective on these developments, neither embracing uncritical techno-optimism nor descending into dystopian despair. Instead, readers are equipped with the critical thinking tools needed to navigate an increasingly quantified world where every click, purchase, and movement leaves a digital footprint.The concluding chapters look beyond today's horizon to envision a future where data literacy becomes as essential as traditional literacy, where quantum computing unlocks currently unimaginable analytical capabilities, and where society must establish new norms for data ownership and governance. The Age of Data ultimately serves as both an indispensable guide to understanding our present moment and a provocative roadmap for shaping a more equitable digital future. This comprehensive treatment makes the book essential reading for business leaders shaping data strategies, policymakers crafting regulatory frameworks, and citizens seeking to understand their place in the new data ecosystem.
Data Architecture
The success of today's most advanced technologies-AI, machine learning, data mesh, and analytics-depends on one critical element: a solid foundation of high-quality, well-architected data.In Data Architecture: Building the Foundation, bestselling author Bill Inmon and seasoned data expert Dave Rapien deliver a definitive guide to creating, managing, and evolving a data architecture that truly supports modern business needs. Whether you're implementing AI, driving business analytics, or transforming legacy systems, this book equips you with the foundational strategies and architectural principles to make it work with a focus on sustainability and scalability.This comprehensive guide helps readers understand why most organizations struggle with fractured, incomplete, and inaccessible data-and what can be done about it. You'll explore the role of a data architect, the essential elements of a solid data foundation, and how to integrate structured, textual, and analog data into a unified, coherent framework. From metadata and data lineage to integrity, accessibility, and completeness, each chapter delivers practical knowledge that drives real business value.Aimed at data architects, analysts, business leaders, and IT professionals, this book answers the question: What does a truly usable, scalable, and business-aligned data architecture look like? Readers will learn how to assess and transform legacy data systems, build effective data models, and implement robust data governance and integration strategies.The book delves into how to use Extract, Classify, and Load (ECL) to harmonize disparate datasets across business units. It also explores the different types of data-structured, textual, and analog-and how each requires different techniques for transformation and analysis. If you're wrestling with data quality issues or trying to make sense of disconnected systems, this is the roadmap you've been missing.You'll gain an understanding of metadata management, naming conventions, and data completeness, while also mastering the crucial role of data accuracy, atomicity, and relatability in enabling trustworthy AI, predictive modeling, and operational efficiency. Practical insights into data currency, integration, and the probability of access ensure that you're not just managing data, but unlocking its potential.With clear explanations, real-world examples, and strategic frameworks, Data Architecture helps you bridge the gap between IT and business, enabling informed decision-making and future-proofed technology investments. Learn how to transform your data into a trusted asset that drives innovation, not frustration.In addition to covering the technical aspects, the authors underscore the business value of good architecture. By aligning your data foundation with business goals-such as improving profitability, customer engagement, and operational efficiency-you can unlock powerful insights and avoid the classic pitfalls of garbage-in, garbage-out.Whether you're building your first data strategy or looking to modernize an aging infrastructure, Data Architecture: Building the Foundation is the essential reference for aligning your technology with your goals-and building a future-proof foundation that actually delivers on the promise of modern data.
Neural Information Processing
The eleven-volume set LNCS 15286-15296 constitutes the refereed proceedings of the 31st International Conference on Neural Information Processing, ICONIP 2024, held in Auckland, New Zealand, in December 2024.The 318 regular papers presented in the proceedings set were carefully reviewed and selected from 1301 submissions. They focus on four main areas, namely: theory and algorithms; cognitive neurosciences; human-centered computing; and applications.
