Atlas of Macroscopes
A fascinating data adventure through the lens of macroscopes, which offer us illuminating and holistic views of our ever-changing world. In Atlas of Macroscopes, Katy B繹rner, Elizabeth Record, and Todd Theriault take you on an epic data adventure. You will explore data landscapes, designed as uniquely interactive spaces, and learn more about our world and your place in it. You will gain new perspectives on how to gather, understand, and communicate data, as well as how to best use it. You will discover what it means to "touch" data that informs and inspires. Transcending the static nature of the maps featured in the initial trilogy, this fourth Atlas showcases 40 real-life macroscopes, or interactive data visualizations, that were displayed in the first decade (2015-2024) of the traveling exhibit Places & Spaces: Mapping Science. Encompassing vast amounts of data, macroscopes give us holistic views of complex systems or networks. They provide an entry point for scientists and laypeople alike, and empower us to engage directly with large datasets and to conduct our own lines of questioning. As interactive tools, macroscopes connect data creators and users. As portals to continuously evolving data, macroscopes can serve as windows to the dynamics of any terrain--personal or professional, local or global--and offer key insights into our surroundings and even our place in the universe. While big data is creating new ways to view and understand information, macroscopes help us see the big picture as we seek to better navigate our ever-changing world.
Text, Speech, and Dialogue
This conference volume constitutes the proceedings of the 28th International Conference on Engineering on Text, Speech, and Dialogue, TSD 2025, held in Erlangen, Germany, in August 2025. The 60 full papers were presented in this volume were carefully reviewed and selected from 122 submissions. They focus on speech and language technologies and computer processing of speech and language related data.
Database and Expert Systems Applications
The two-volume set LNCS 16046-16047 constitutes the proceedings of the 36th International Conference on Database and Expert Systems Applications, DEXA 2025, held in Bangkok, Thailand, in August 25-27, 2025. The 35 full and 22 short papers presented in this set together with 3 invited talks were carefully reviewed and selected from 123 submissions. They were organized in topical sections as follows: Part I: Industrial Keynote; Invited Talks; Large Language Models; Data Quality; Machine Learning /Artificial Intelligence Applications; Classification Techniques. Part II: Image Processing, Analytics, and Vision Systems; Recommender Techniques; Data Integration; Optimisation Methods; Graph Applications; Analytics; Security/Privacy; Benchmarks and Surveys.
Text, Speech, and Dialogue
This conference volume constitutes the proceedings of the 28th International Conference on Engineering on Text, Speech, and Dialogue, TSD 2025, held in Erlangen, Germany, in August 2025. The 60 full papers were presented in this volume were carefully reviewed and selected from 122 submissions. They focus on speech and language technologies and computer processing of speech and language related data.
The Official MongoDB Guide
The official guide to MongoDB architecture, tools, and cloud features, written by leading MongoDB subject matter experts to help you build secure, scalable, high-performance applicationsKey Features: - Design resilient, secure solutions with high performance and scalability- Streamline development with modern tooling, indexing, and AI-powered workflows- Deploy and optimize in the cloud using advanced MongoDB Atlas features- Purchase of the print or Kindle book includes a free PDF eBookBook Description: Delivering secure, scalable, and high-performance applications is never easy, especially when systems must handle growth, protect sensitive data, and perform reliably under pressure. The Official MongoDB Guide addresses these challenges with guidance from MongoDB's top subject matter experts, so you learn proven best practices directly from those who know the technology inside out.This book takes you from core concepts and architecture through to advanced techniques for data modeling, indexing, and query optimization, supported by real-world patterns that improve performance and resilience. It offers practical coverage of developer tooling, IDE integrations, and AI-assisted workflows that will help you work faster and more effectively.Security-focused chapters walk you through authentication, authorization, encryption, and compliance, while chapters dedicated to MongoDB Atlas showcase its robust security features and demonstrate how to deploy, scale, and leverage platform-native capabilities such as Atlas Search and Atlas Vector Search.By the end of this book, you'll be able to design, build, and manage MongoDB applications with the confidence that comes from learning directly from the experts shaping the technology.What You Will Learn: - Build secure, scalable, and high-performance applications- Design efficient data models and indexes for real workloads- Write powerful queries to sort, filter, and project data- Protect applications with authentication and encryption- Accelerate coding with AI-powered and IDE-based tools- Launch, scale, and manage MongoDB Atlas with confidence- Unlock advanced features like Atlas Search and Atlas Vector Search- Apply proven techniques from MongoDB's own engineering leadersWho this book is for: This book is for developers, database professionals, architects, and platform teams who want to get the most out of MongoDB. Whether you're building web apps, APIs, mobile services, or backend systems, the concepts covered here will help you structure data, improve performance, and deliver value to your users. No prior experience with MongoDB is required, but familiarity with databases and programming will be helpful.Table of Contents- Introduction to MongoDB- MongoDB Architecture- Developer Tools- Data Modeling and Index Optimization- Queries- Database Operations and Security- Security- MongoDB Atlas - Part 1- MongoDB Atlas - Part 2
High Performance with MongoDB
Practical strategies to help you design, optimize, and operate MongoDB deployments for performance, resilience, and growthKey Features: - Identify and fix performance bottlenecks with practical diagnostic and optimization strategies- Optimize schema design, indexing, storage, and system resources for real-world workloads- Scale confidently with in-depth coverage of replication, sharding, and cluster management techniques- Purchase of the print or Kindle book includes a free PDF eBookBook Description: With data as the new competitive edge, performance has become the need of the hour. As applications handle exponentially growing data and user demand for speed and reliability rises, three industry experts distill their decades of experience to offer you guidance on designing, building, and operating databases that deliver fast, scalable, and resilient experiences.MongoDB's document model and distributed architecture provide powerful tools for modern applications, but unlocking their full potential requires a deep understanding of architecture, operational patterns, and tuning best practices. This MongoDB book takes a hands-on approach to diagnosing common performance issues and applying proven optimization strategies from schema design and indexing to storage engine tuning and resource management.Whether you're optimizing a single replica set or scaling a sharded cluster, this book provides the tools to maximize deployment performance. Its modular chapters let you explore query optimization, connection management, and monitoring or follow a complete learning path to build a rock-solid performance foundation. With real-world case studies, code examples, and proven best practices, you'll be ready to troubleshoot bottlenecks, scale efficiently, and keep MongoDB running at peak performance in even the most demanding production environments.What You Will Learn: - Diagnose and resolve common performance bottlenecks in deployments- Design schemas and indexes that maximize throughput and efficiency- Tune the WiredTiger storage engine and manage system resources for peak performance- Leverage sharding and replication to scale and ensure uptime- Monitor, debug, and maintain deployments proactively to prevent issues- Improve application responsiveness through client driver configurationWho this book is for: This book is for developers, database administrators, system architects, and DevOps engineers focused on performance optimization of MongoDB. Whether you're building high-throughput applications, managing deployments in production, or scaling distributed systems, you'll gain actionable insights. Basic knowledge of MongoDB is assumed, with chapters designed progressively to support learners at all levels.Table of Contents- Systems and MongoDB Architecture- Schema Design for Performance- Indexes- Client Libraries- Replication- Sharding- Storage Engine- Operating System and System Resources- Transactions- Aggregations- Managing Connections and Network Performance- Advanced Indexing and Query Concepts- Using Change Streams- Monitoring and Observability- Debugging Performance Issues
MongoDB Essentials
Get started fast with MongoDB architecture, core operations, and AI-powered tools for building intelligent applicationsKey Features: - Quickly grasp the MongoDB architecture and distributed design principles- Learn practical data modeling, CRUD operations, and aggregation techniques- Explore AI-enabled tools for building intelligent applications with MongoDB- Purchase of the print or Kindle book includes a free PDF eBookBook Description: Modern applications demand flexibility, speed, and intelligence, and MongoDB delivers all three. This mini guide wastes no time, offering a concise, practical introduction to handling data flexibly and efficiently with MongoDB. MongoDB Essentials helps developers, architects, database administrators, and decision makers get started quickly and confidently.The book introduces MongoDB's core principles, from the document data model to its distributed architecture, including replica sets and sharding. It then helps you build hands-on skills such as installing MongoDB, designing effective data schemas, performing CRUD operations, and working with the aggregation pipeline. You'll discover performance tips along the way and learn how AI-enhanced tools like Atlas Search and Atlas Vector Search power intelligent application development.With clear explanations and a practical approach, this book gives you the foundation and skills you need to start working with MongoDB right away.What You Will Learn: - Understand MongoDB's document model and architecture- Set up local MongoDB deployments quickly- Design schemas tailored to application access patterns- Perform CRUD and aggregation operations efficiently- Use tools to optimize query performance and scalability- Explore AI-powered features such as Atlas Search and Atlas Vector SearchWho this book is for: This book is for anyone looking to explore MongoDB, including students, developers, system architects, managers, database administrators, and decision makers who want to familiarize themselves with what a modern database can offer. Whether you're building your first application or exploring what MongoDB can do for you, this book is the idea starting point for your MongoDB journey.Table of Contents- MongoDB Architecture- Getting Started with MongoDB- Data Modeling- CRUD Operations- Aggregations- Performance Strategies and Tools- MongoDB and AI
Big Data Analytics and Knowledge Discovery
This book constitutes the proceedings of the 27th International Conference on Big Data Analytics and Knowledge Discovery, DaWaK 2025, held in Bangkok, Thailand, during August 25-27, 2025. The 12 full and 14 short papers included in the proceedings were carefully reviewed and selected from 62 submissions. The proceedings also contain one keynote talk, one invited talk and one tutorial. The papers were organized in topical sections as follows: Data mining and knowledge discovery; sequential data analytics and recommendation systems; graph data processing and analytics; data management and indices; Large language Models (LLMs); and Neural Networks.
Database and Expert Systems Applications - Dexa 2025 Workshops
This volume constitutes the refereed proceedings of the 7th International Workshop on AI System Engineering: Math, Modelling and Software, AISys 2025 and the First International Workshop on Optimisation of Industrial Production with AI Algorithms, AI4IP, co-located with the 36th International Conference on Database and Expert Systems Applications, DEXA 2025, which took place in Bangkok, Thailand, during August 25-27, 2025.The 11 full papers were thoroughly reviewed and selected from a total of 23 submissions. They are organized in topical sections as follows: AI System Engineering: Math, Modelling and Software; and Optimization of Industrial Production with AI Algorithms.
Blockchain Technology
This new volume explores the role of blockchain technology in promoting higher effectivenessin new business modeling in different industries, considering it as a key enabler of Industry 5.0solutions that incorporate lean, transparent, traceable, and trustworthy mechanisms not only inlogistics but also in other aspects of business processes.The volume looks at the incorporation of blockchain technology in conjunction with artificialintelligence in diverse business sectors. Chapters consider the use of blockchain technology inthe banking and finance sector; in the fashion industry; in the tourism, travel, and hospitalityindustries; in the national defense industry; for advertising and marketing; and, of course, inthe logistics industry for enhancing green supply chains with blockchain technology, where it isbeing used to bring new levels of trust between trading partners and to promote end-to-endvisibility.The volume looks at how blockchain technology is revolutionizing many industries by providingthe means to automate processes, eliminate intermediaries, and provide real-time data access, thus reducing administrative burdens, minimizing errors, and improving overall efficiency.
Bisociative Literature-Based Discovery
This monograph introduces the field of bisociative literature-based discovery (LBD) by first explaining the underlying LBD principles and techniques, followed by the presentation of bisociative LBD techniques and applications developed by the authors. LBD is a process of uncovering new knowledge by analyzing and connecting disparate pieces of information from different sources of literature. Selected techniques include conventional natural language processing (NLP) approaches, as well as outlier-based, concept-based, network-based, and embeddings-based LBD approaches. Reproducibility aspects of bisociative LBD research are also covered, addressing all steps of the bisociative LBD process: data acquisition, text preprocessing, hypothesis discovery, and evaluation. The monograph is targeted at researchers, students, and domain experts interested in knowledge exploration, information retrieval, text mining, data science or semantic technologies. By covering texts, relations, networks, and ontologies, this work empowers domain experts to transcend their knowledge silos when confronted with varied data formats in their research practice. The monograph's open science approach with tutorials in Python allows for code reuse and experiment replicability.
Data Preparation and Analysis
Data science is an evolving field, and the ability to effectively prepare and analyze data is a critical skill for any aspiring professional. This book serves as a comprehensive introduction to the foundational concepts and tools of data science, making it ideal for beginners and aspiring data professionals.This book provides a structured and comprehensive learning path, beginning with a broad introduction to data science, its applications, and fundamental analysis methods. You will then explore the core Python libraries for data manipulation, NumPy for efficient numerical operations, and Pandas for powerful data structuring and transformation. The book dedicates significant focus to real-world data challenges, walking you through the crucial steps of data gathering, preparation, and cleaning; addressing issues like scalability, missing data, and inconsistencies. The book concludes with three real-world projects that apply the concepts in practical settings, making you proficient in the entire end-to-end data preparation and analysis pipeline. You will have a solid command of essential tools and techniques, empowering you to confidently tackle and derive meaningful insights from diverse datasets in any professional setting.WHAT YOU WILL LEARN● Implement ML models using NumPy, Pandas, Matplotlib, or scikit-learn.● Gain a solid foundation in data science, principles, algorithms, and methodologies.● Learn to frame real-world problems as ML tasks. ● Implement data cleaning for consistency and missing data.● Conduct exploratory data analysis with descriptive statistics.● Uncover data patterns using clustering and association techniques.● Design and create effective time series visualizations.WHO THIS BOOK IS FORThis book is ideal for students, programmers, and software engineers who want to learn data science from scratch. It assumes basic programming proficiency, but no prior data science knowledge is required to follow the comprehensive, hands-on curriculum.
Architecting Data Solutions with Snowflake
Modern businesses need scalable, cost-efficient data platforms; however, traditional, fragmented systems are complex and expensive. Snowflake provides a modern, cloud-native, fully managed solution, simplifying data architecture while delivering performance and flexibility. This book helps readers leverage Snowflake's full potential for advanced, scalable data solutions.This book begins by walking you through Snowflake account configuration and its unique three-layered architecture, introducing key architectural pillars. The book covers building data engineering pipelines using various methods like Snowpipe and Snowpark, differentiating between ETL and ELT patterns. Finally, you will learn to architect diverse data patterns, such as data warehouses, data lakes, data mesh, and lakehouses, and explore Snowpark for machine learning, Snowflake Horizon, Cortex, and building generative AI and LLM solutions.This book equips you with the knowledge to design and implement modern data solutions, including data warehouses, lakes, and mesh patterns, using Snowflake. You will be well-equipped to tackle complex data architecture challenges and drive innovation in any data-driven environment.WHAT YOU WILL LEARN● Learn to design data platform solutions with Snowflake.● Design scalable and cost-effective data architectures.● Implement efficient data ingestion and extraction pipelines.● Implement modern data patterns, including data warehouse, data lake, and data mesh, using Snowflake's flexible architecture.● Apply modern data governance and security practices.● Design AI/ML workloads using Snowflake Cortex.WHO THIS BOOK IS FORThis book is designed for data enthusiasts, architects, and engineers who are looking to build modern, cloud-native data platforms using Snowflake. Whether you are designing your first data solution or optimizing complex enterprise architectures, this book offers practical insights, patterns, and real-world examples to elevate your data skills.
Data Rookies Labs
Learn Data Analytics Through Visual, Hands-On Labs with OrangeData Rookies Labs: Intro to Analytics with Orange offers a practical, no-code introduction to data science using the intuitive Orange platform. Designed for beginners, this workbook guides students through real-world tasks like classification, clustering, association rules, data cleaning, visualization, and text mining-all using drag-and-drop workflows.Each lab provides step-by-step instructions, screenshots, and sample datasets to help students understand how data is used to generate insights and drive decisions. With no programming required, it's ideal for high school, college, or adult learners looking to build foundational data literacy through an interactive, visual approach.Perfect for classrooms or self-paced study, this book helps learners think like data analysts-no coding required.
Data Rookies Labs Data Mining with Orange
Discover Orange: Visual, No-Code Data Mining for BeginnersStep into data science without writing a single line of code. This hands-on workbook uses Orange, a powerful visual data-mining tool built on Python, to guide you through clustering, classification, and association techniques. With drag-and-drop workflows and intuitive widgets, you'll explore, clean, and model data step-by-step-no programming required.Perfect for beginners, students, and instructors, these structured labs make complex analytics approachable and fun, building real-world skills that translate directly into data science careers. Orange turns data mining into an engaging, visual learning experience-ideal for anyone ready to get started.
Data Rookies Labs Intro to Analytics with Orange
Learn Data Analytics Through Visual, Hands-On Labs with OrangeData Rookies Labs: Intro to Analytics with Orange offers a practical, no-code introduction to data science using the intuitive Orange platform. Designed for beginners, this workbook guides students through real-world tasks like classification, clustering, association rules, data cleaning, visualization, and text mining-all using drag-and-drop workflows.Each lab provides step-by-step instructions, screenshots, and sample datasets to help students understand how data is used to generate insights and drive decisions. With no programming required, it's ideal for high school, college, or adult learners looking to build foundational data literacy through an interactive, visual approach.Perfect for classrooms or self-paced study, this book helps learners think like data analysts-no coding required.FULL resources are available from the publisher for teaching or self study.
Fundamentals of Metadata Management
Whether it's to adhere to regulations, access markets by meeting specific standards, or devise data analytics and AI strategies, companies today are busy implementing metadata repositories--metadata tools about the IT, data, information, and knowledge in your company. Until now, most of these repositories have been implemented in isolation from one another, but that practice lies at the core of problems with data management in many companies today. Author Ole Olesen-Bagneux, chief evangelist at Actian, shows you how to masterfully manage your metadata repositories by properly coordinating them. That requires a data discovery team to increase insights for all key players in enterprise data management, from the CIO and CDO to enterprise and data architects. Coordinating these repositories will help you and your organization democratize data and excel at data management. This book shows you how. Learn what metadata repositories are and what they do Explore which data to represent in these repositories Set up a data discovery team to make data searchable Learn how to manage and coordinate repositories in a meta grid Increase innovation by setting up a functional data marketplace Make information security and data protection more robust Gain a deeper understanding of your company IT landscape Activate real enterprise architecture based on evidence
Data Rookies Labs Data Wrangling with R
Learn R by Doing. Data Wrangling with R is a hands-on workbook designed for beginners learning R through practical data cleaning and transformation. With over 20 structured labs, you'll tackle real-world tasks like filtering, sorting, formatting, handling missing data, reshaping datasets, and using packages like dplyr. Clear examples, built-in exercises, and both base R and tidyverse approaches help you build core wrangling skills essential for any data analyst working in R.NOTE extensive teaching resources - code, exercises, slides are available from the publisher for self-study and course use.
Data Rookies Data Wrangling Essentials
Start your data journey by mastering the messy middle-data wrangling. This beginner-friendly book walks you through the core skills every data analyst needs such as fixing missing values, combining tables with SQL, transforming variables, and modifying datasets for analysis. With real-world examples, no-code workflows, and plain explanations, you'll learn the concepts of how to prepare data that's ready for insights. Pair this book with companion books with lab exercises to practice (available in R and Orange), slides, solution guides and more available resources at our website to bring your learning data analytics to life.Full resources are available from the publisher - slides, answers, quizzes, worksheets - for teaching and self study.
Data Rookies Intro to Data Analytics
Jumpstart your journey into data with this clear, approachable introduction designed for absolute beginners. Whether you're a student, educator, or curious career-changer, this book walks you through essential concepts-from wrangling data and reading charts to understanding AI, ethics, and career paths-using real-world examples and plain language.Pair this book with companion books with lab exercises to practice (available in R and Orange), slides, solution guides and more available resources at our website to bring your learning data analytics to life.
Data Rookies Labs Intro to Analytics with R
A Hands-On Introduction to Data Analytics using RData Rookies Labs: Intro to Analytics with R is a guided lab workbook designed to help students learn data science by doing. Through 22 structured labs, learners use R and RStudio to explore topics including descriptive statistics, regression, sampling, data visualization, SQL, classification, sentiment analysis, and more. Each lab provides clear instructions, working code examples, and practice exercises focused on real-world tasks. Students learn to manipulate, analyze, and visualize data using base R, the Tidyverse, and common analytics packages.Built for classrooms and independent study alike, this workbook provides a strong foundation in applied analytics using R-no fluff, no shortcuts, just real code and real skills.FULL resources - code, worksheets, markdown exercises for students, slides, answer keys and more - are available from the publisher for self-study or class use.
Data Rookies Intro to Data Analytics
Jumpstart your journey into data with this clear, approachable introduction designed for absolute beginners. Whether you're a student, educator, or curious career-changer, this book walks you through essential concepts-from wrangling data and reading charts to understanding AI, ethics, and career paths-using real-world examples and plain language.Pair this book with companion books with lab exercises to practice (available in R and Orange), slides, solution guides and more available resources at our website to bring your learning data analytics to life.
Data Rookies Data Mining Basics
Jumpstart your journey into data mining with this clear, beginner-friendly guide. Whether you're a student, educator, or career-changer, this book makes complex ideas approachable. You'll explore the foundations of clustering, classification, and association using real-world examples, practical explanations, and plain language-no prior experience required.Pair this book with companion books with lab exercises to practice (available in R and Orange), slides, solution guides and more available resources at our website to bring your learning data analytics to life.
Data Rookies Labs Intro to Analytics with R
A Hands-On Introduction to Data Analytics using RData Rookies Labs: Intro to Analytics with R is a guided lab workbook designed to help students learn data science by doing. Through 22 structured labs, learners use R and RStudio to explore topics including descriptive statistics, regression, sampling, data visualization, SQL, classification, sentiment analysis, and more. Each lab provides clear instructions, working code examples, and practice exercises focused on real-world tasks. Students learn to manipulate, analyze, and visualize data using base R, the Tidyverse, and common analytics packages.Built for classrooms and independent study alike, this workbook provides a strong foundation in applied analytics using R-no fluff, no shortcuts, just real code and real skills.Full supplementary resources available from the publisher (answers, slides, worksheets) ready to teach or for self-study.
Data Rookies Labs Data Mining with R
Unlock the power of R and dive into real-world data mining. This hands-on workbook guides you through clustering, classification, and association techniques using approachable language, engaging labs, and no programming prerequisites. Ideal for beginners, students, and instructors alike, you'll learn to explore, normalize, and model data step-by-step-building skills that transfer directly into data science careers. R isn't just a language here-it's a gateway to applied analytics, made accessible through structured, beginner-friendly labs.Extensive resources are available from the publisher (slides, data, code, worksheets).
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.
Portable High-Performance Indexing for Vector Product Format Spatial Databases
Geo-spatial databases have an overall performance problem because of their complexity and large size. For this reason, many researchers seek new ways to improve the overall performance of geo-spatial databases. Typically, these research efforts are focused on complex indexing structures and query processing methods to capture the relationships between the individual features of fully-functional geo-spatial databases. Visualization applications, such as combat simulators and mission planning tools, suffer from the general performance problems associated with geo-spatial databases. This research focuses on building a high-performance geo-spatial database for visualization applications. The main approach is to simplify the complex data model and to index it with high-performance indexing structures. Complex features are reduced to simple primitives, then indexed using a combination of a disk-based array and B]-Trees. Test results show that there is a significant performance improvement gained by the new data model and indexing schema for low to medium zoom levels. For high zoom levels, there is a performance drop due to the indexing schema's overhead.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.
Network Visualization Design Using Prefuse Visualization Toolkit
Visualization of network simulation events or network visualization is an effective and low cost method to evaluate the health and status of a network and analyze network designs, protocols, and network algorithms. This research designed and developed a network event visualization framework using an open source general visualization toolkit. This research achieved three major milestones during the development of this framework: A robust network simulator trace file parser, multiple network visualization layouts--including user-defined layouts, and precise visualization timing controls and integrated display of network statistics. The toolkit design is readily extensible allowing developers to easily expand the framework to meet research-specific visualization goals.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.
Extensible Multi-Agent System for Heterogeneous Database Association Rule Mining and Unification
The main purpose of this research is to provide an extensible architecture that provides flexibility in the addition of a data source for data mining operations.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.
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.
Extensible Multi-Agent System for Heterogeneous Database Association Rule Mining and Unification
The main purpose of this research is to provide an extensible architecture that provides flexibility in the addition of a data source for data mining operations.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.
Network Visualization Design Using Prefuse Visualization Toolkit
Visualization of network simulation events or network visualization is an effective and low cost method to evaluate the health and status of a network and analyze network designs, protocols, and network algorithms. This research designed and developed a network event visualization framework using an open source general visualization toolkit. This research achieved three major milestones during the development of this framework: A robust network simulator trace file parser, multiple network visualization layouts--including user-defined layouts, and precise visualization timing controls and integrated display of network statistics. The toolkit design is readily extensible allowing developers to easily expand the framework to meet research-specific visualization goals.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.
Getting Started with the Graph Query Language (GQL)
Learn how to build and query graph databases with this first comprehensive guide to ISO-standard GQL featuring 50+ hands-on examples and a real-world case study that will change the way you work with connected dataKey Features: - Go beyond theory and apply key concepts and syntax through interactive tutorials and practical examples via the GQL Playground- Leverage advanced features of GQL to manipulate graph data efficiently- Explore GQL applications in data analytics and discover how to leverage graph knowledge in real-world scenarios- Purchase of the print or Kindle book includes a free PDF eBookBook Description: Graph Query Language is becoming the go-to standard for graph databases, especially with its support for interconnected analytics and GenAI capabilities. This book comes from a team of industry veterans who know exactly how to break down the fundamental GQL concepts, graph terms, definitions, catalog systems, and everything that matters in actual work.You'll get to grips with graph data types, value expressions, graph matching patterns, and modifying statements through practical GQL examples. With access to the GQL Playground via Ultipa Graph, you'll get hands-on experience querying and manipulating graph data.Once you've got the basics down, you'll tackle advanced GQL topics such as path modes, complex path matching patterns, shortest path queries, composite statements, session and transaction commands, and procedures. You'll also learn to create extensions and understand the design of graph databases to solve industry issues. The authors cover techniques like property graphs to help you optimize your graph queries and offer insights into the future of GQL and graph technology.By the end of this book, you'll confidently query and update graph data, run graph algorithms, and create visualizations. Plus, you'll apply your learnings to a real-world use case of money flow analysis for assessing bank client behaviors and detecting transaction risks.What You Will Learn: - Experiment with GQL syntax on GQL Playground, including MATCH, RETURN, INSERT, UPDATE, and DELETE- Work with operators, functions, and variables in an organized fashion- Become familiar with complex topics such as varying path matching modes, repeated variables, shortest path, procedures, and transactions- Enhance execution speed through indexing or caching systems- Understand how to manage access control effectively- Tackle real-world issues with a case study focused on money transaction analyticsWho this book is for: This book is for graph database developers, DBAs, programmers, data engineers, and analysts who want to learn the new graph database standard GQL. A basic understanding of graph and relational databases, data models, knowledge of SQL basics, and programming will make the content easy to grasp. While it is designed to be accessible even if you don't have a background in graph theory, familiarity with concepts like nodes, edges, relationships, and the distinction between directed and undirected graphs will enhance your learning experience.Table of Contents- Evolution Towards Graph Databases- Key Concepts of GQL- Getting Started- Basic GQL Statements- Operators and Logical Control- Functions- Advanced Clauses- Transaction Management- Sessions Management- Conformance to GQL Standard- Beyond the GQL Standard- A Case Study- The Evolving Landscape of GQL- Glossary and Resources
Strategic DevOps
DevOps is not something you can buy or install, even if some product names might suggest otherwise. This book helps you connect the dots between DevOps culture, technical execution, and business value, offering a practical framework to scale your organization in a world increasingly shaped by rapid change and the growing influence of AI.While DevOps principles apply broadly, we focus on the developer, operator, and business triad to keep things grounded and actionable. We explore how DevOps culture influences everything from planning and automation to testing, cybersecurity, and observability. Along the way, we take a step back from the technical, asking: what does value actually mean?, and how can DevOps culture create, protect, and scale it?Scaling technology is easy. Scaling people and culture is the real challenge, and this is where DevOps shines. After reading this book, you will move from mindset to execution, tying culture, metrics, and value together to understand how technical and human systems shape an organization's success.WHAT YOU WILL LEARN● Implementing DevOps culture principles. ● Fostering collaboration and breaking organizational silos.● Automation to development, deployment, and maintenance of a product or service.● Integrating cybersecurity via shift left/right, threat modeling, and Zero Trust.● Establishing useful metrics and KPIs for data-driven continuous improvement.● Implementing observability, monitoring, alerting, and post-mortems for system health.● Enabling better decision-making in organizations and businesses. WHO THIS BOOK IS FORThis book is for engineers, operators, and business leaders seeking to understand and scale value through DevOps culture. With a focus on why, those without a coding background can engage meaningfully, grasping most of the content. The book provides clear and actionable insights into how people, mindset, and culture shape organizational success.
Transforming Academic Libraries
The book comprises the proceedings of the International Conference on Academic Libraries (ICAL 2023) in the context of developing a vision for the next generation of libraries which will contribute to nation-building and give a competitive edge to the country in becoming a knowledge economy. The book provides a quality reading and exchange of ideas to all stakeholders to deliberate, dwell, and brainstorm upon the diverse and enormous role that academic libraries may play in enhancing the higher education landscape in developed and developing countries with particular reference to India by 2030. The book includes literature and opportunities to identify the strengths and gaps in the academic library system and to suggest new management models, mechanisms, policies, and national and international programs for reshaping academic libraries into next-generation libraries for higher education.
Intelligent and Fuzzy Systems
Artificial Intelligence in Human-Centric, Resilient & Sustainable Industries This book focuses on benefiting artificial intelligent tools in our business and social life under emerging conditions. Human-centric, resilient, and sustainable industries are built on ideals like human-centricity, ecological advantages, or social benefits. The mission of human-centric artificial intelligence is to improve people's lives by offering solutions that boost productivity, accessibility to resources, security, well-being, and general quality of life. The latest intelligent methods and techniques on human-centric, resilient, and sustainable industries are introduced by theory and applications. This book covers the chapters of world-wide known experts on machine learning, medical image processing, process intelligence, process mining, and others. The intended readers are intelligent systems researchers, lecturers, M.Sc. and Ph.D. students trying to develop approaches giving human needs, values, and viewpoints top priority through artificial intelligent systems.
Optimal Estimation and Information Fusion: Theory and Algorithms
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.
Proceedings of the 11th Conference on Sound and Music Technology
This book presents selected papers at the 11th Conference on Sound and Music Technology (CSMT) held in October 2024, Wuhan, China. CSMT is a multidisciplinary conference focusing on audio processing and understanding with bias on music and acoustic signals. The primary aim of the book is to promote the collaboration between art society and technical society in China. In this book, the paper included covers a wide range topic from speech, signal processing, music understanding, machine learning, and signal processing for advanced medical diagnosis and treatment applications, which demonstrates the target of CSMT merging arts and science research together. Its content caters to scholars, researchers, engineers, artists, and education practitioners not only from academia but also industry, who are interested in audio/acoustics analysis signal processing, music, sound, and artificial intelligence (AI).
Digital Transformation in Sports
The sports industry is one of the most robust and competitive sectors in the world. Over the last decade, the integration of technology into sports has dramatically transformed the dynamics of how the sports industry operates. Sports analytics (i.e., the integration of data science and sports) is at the forefront of this digital transformation. Sports analytics encompasses the applications of innovative technologies and advanced analytical techniques to assess and enhance performance of players and teams, improve decision-making across diverse aspects, and bolster competitive advantages and strategies.Digital Transformation in Sports explores the key driving forces and emerging trends that are fueling the digital transformation of the sports industry. It presents a collection of chapters that delve into state-of-the-art research and real-world applications of sports analytics, providing a diverse perspective on its transformative impact across different sports sectors. It showcases how advanced technologies such as the Internet of Things (IoT), machine learning (ML), and artificial intelligence (AI) are revolutionizing player performance, strategic decision-making, fan engagement, and operational efficiency. For example, by utilizing sensors, wearable technologies, tracking devices, and 5G networks, IoT technologies can collect an unprecedented amount of data in real time and enable the near-instantaneous transmission of this data to the centralized platforms for analysis. Sophisticated analytics powered by AI and ML enable the extraction of actionable insights from this raw data, transforming it into valuable intelligence that drives better decision-making.By offering a bridge between theoretical frameworks and practical applications, this book demonstrates how such concepts as technology acceptance theories inform the successful implementation and adoption of analytics solutions. By drawing upon interdisciplinary insights, the chapters provide valuable tools and frameworks for researchers, analysts, practitioners, and stakeholders, delivering actionable guidance to harness the full potential of analytics in the rapidly evolving sports landscape.
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.
Topic Modeling
As a well-known text mining tool, topic modeling can effectively discover the latent semantic structure of text data. Extracting topics from documents is also one of the fundamental challenges in natural language processing. Although topic models have seen significant achievements over the past three decades, there remains a scarcity of methods that effectively model temporal aspect. Moreover, many contemporary topic models continue to grapple with the issue of noise contamination, particularly in social media data. This book presents several approaches designed to address these two limitations. Initially, traditional lifelong topic models aim to accumulate knowledge learned from experience for future task. However, the sequence of topics extracted by these methods may shift over time, leading to semantic misalignment between the topic representations across document streams. Such misalignment can degrade the performances of various downstream tasks, including online document classification and dynamic information retrieval at the topic level. Additionally, the challenge of coherent topic modeling is particularly relevant due to the noise and large scale of social media datasets. Messages on social media platforms often consists of only a few words, resulting in a lack of significant context. Models applied directly to this type of text frequently encounter the problem of feature sparsity, which can yield unsatisfactory outcomes. In the context of emotion detection, public emotions are known to fluctuate across different topics, and topics can evoke public emotion. Thus, there is a strong interconnection between topic discovery and emotion detection. Jointly modeling topics and emotions is a suitable strategy for these tasks. This book also examines the impact of topics on emotion detection and other related areas.
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.
