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Computer Science (R0)

Noel Crespi

Adam T. Drobot

Roberto Minerva

The Digital Twin

Part I. The Landscape, Implications, and Assumptions.- Chap&amp;nbsp;1. The Digital Twin: Why and What?.- Chap&amp;nbsp;2. DT and Digital Revolution.- Chap&amp;nbsp;3. Business models design for the Digital Twin.- Chap&amp;nbsp;4. The evolution and history of the Digital Twin.-&amp;nbsp;Part II. Technologies.- Chap&amp;nbsp;5. Representing the DT: New devices, new interfaces.- Chap&amp;nbsp;6. Where the data come from? Relation between IoT and DT.- Chap&amp;nbsp;7. AI for DT:&amp;nbsp; from data to knowledge.- Chap&amp;nbsp;8. Simulation.- Chap&amp;nbsp;9. Architectures and Implementations.- Chap&amp;nbsp;10. Network for Digital Twin.- Chap&amp;nbsp;11. Managing the unmanageable.- Chap&amp;nbsp;12. Security and DT.-&amp;nbsp;Section III The Digital Twin in Operation.- Chap&amp;nbsp;13. Making the DT Operational in Enterprise Processes.- Chap&amp;nbsp;14. Making the DT Operational in a Large Ecosystem.-&amp;nbsp;Section IV Vertical Domains for Digital Twin Applications.- Chap&amp;nbsp;15. The Digital Twin in Manufacturing.- Chap&amp;nbsp;16. The Digital Twin for&amp;nbsp; Operations, Maintenance, Repair, and Overhaul.-&amp;nbsp;Chap&amp;nbsp;17. The Digital Twin for Display, Education, and Curation.- Chap&amp;nbsp;18. Prognostication and&amp;nbsp; Prediction, Prevention, and Prescription.-&amp;nbsp;Chap&amp;nbsp;19. The Digital Twin in Human Activities and Nature: the eHealth example.- Chap&amp;nbsp;20. The Digital Twin in Complex Systems.-&amp;nbsp;Section V Conclusion.- Chap&amp;nbsp;21. Future Evolution of the Digital Twin.- Chap&amp;nbsp;22. DT in Action and lesson learnt.

A town spoke. Something larger answered.

In September 2025, a township board in rural Michigan voted to reject a data center. Two days later, the developer sued. Within three weeks, the project was approved anyway.

THIS IS SERVER COUNTRY tells-through vivid narrative and clear-eyed analysis-the story of America's largest private infrastructure buildout. A trillion dollars. Six hundred projects. A power grid racing to keep up.

This book follows the people caught in the buildout, explains how the machines actually work, and asks why farmland instead of shuttered factories. It traces the current backward from silicon in Taiwan to sandy loam in Saline-and reveals who builds, who benefits, and who pays, where local zoning meets great-power politics.

The book covers: How AI inference works and why it demands unprecedented compute power. 
Why data centers choose farmland, not cities. 
The trillion-dollar capital wave reshaping American infrastructure. 
State incentive wars and community resistance. 
The nuclear renaissance and natural gas reality.
Export controls and the geopolitics of AI.



The railroads opened the West. The interstates created the suburbs. The AI boom follows the same pattern, at faster speed-but to what end, we know not yet.

AI, Power, and the Remaking of Rural America

This Is Server Country

A Comprehensive Introduction

Financial Technology

This book examines how strategic thinking is evolving in response to the realities of the digital economy. Traditional strategy frameworks, built for slower, more stable environments, no longer capture the complexity of today’s business landscape, where innovation is constant, data is abundant, and competition is shaped by digital platforms and ecosystems.
Focusing on the global digital banking sector—one of the most digitally advanced industries—the book draws on original research, including interviews with 39 senior strategy leaders. It explores how organisations are navigating strategy in practice, highlighting shifts in decision-making, organisational logic, and the role of technology in shaping strategic options.
Rather than proposing that classical strategy be discarded, the book argues for its adaptation. It offers a grounded, research-based view of how organisations are integrating agility, experimentation, and digital infrastructure into their strategic processes. The goal is not to replace strategic theory, but to update it—reflecting the conditions of a digital-first economy.
This book bridges multiple disciplines, including strategic management, organisational theory, information systems, and innovation. While its case focus is on digital banking, the insights are relevant across sectors facing digital transformation.
Designed for scholars, practitioners, and educators, this book provides both empirical depth and conceptual clarity. It contributes to the growing conversation about what strategy means in an environment defined by speed, fluidity, and ongoing technological change.

This book examines how strategic thinking is evolving in response to the realities of the digital economy. Traditional strategy frameworks, built for slower, more stable environments, no longer capture the complexity of today’s business landscape, where innovation is constant, data is abundant, and competition is shaped by digital platforms and ecosystems.Focusing on the global digital banking sector—one of the most digitally advanced industries—the book draws on original research, including interviews with 39 senior strategy leaders. It explores how organisations are navigating strategy in practice, highlighting shifts in decision-making, organisational logic, and the role of technology in shaping strategic options.Rather than proposing that classical strategy be discarded, the book argues for its adaptation. It offers a grounded, research-based view of how organisations are integrating agility, experimentation, and digital infrastructure into their strategic processes. The goal is not to replace strategic theory, but to update it—reflecting the conditions of a digital-first economy.This book bridges multiple disciplines, including strategic management, organisational theory, information systems, and innovation. While its case focus is on digital banking, the insights are relevant across sectors facing digital transformation.Designed for scholars, practitioners, and educators, this book provides both empirical depth and conceptual clarity. It contributes to the growing conversation about what strategy means in an environment defined by speed, fluidity, and ongoing technological change.

Strategy and Processes in Digital Banking

Digital Economy Dynamics

Intelligent Urban Infrastructure: Smart Solutions for Sustainable Cities explores how emerging digital technologies are reshaping the design, management, and sustainability of modern cities. This comprehensive volume examines the integration of Artificial Intelligence (AI), Internet of Things (IoT), data analytics, and intelligent automation into critical urban systems such as transportation, energy, water management, healthcare, and public safety. It presents a forward-looking perspective on how infrastructure can evolve to become more adaptive, resilient, and environmentally responsible. The book highlights practical frameworks and technology-driven content that demonstrate measurable improvements in efficiency, cost optimization, and environmental performance. Designed for researchers, postgraduate students, urban planners, engineers, policymakers, and industry professionals, this book serves as a valuable reference for those seeking to understand and implement intelligent infrastructure solutions that enable smarter, greener, and more liveable cities worldwide.

Smart Solutions for Sustainable Cities

Intelligent Urban Infrastructure

Your AI isn't broken. Your playbook is.

AI project failures don't come from bad models. They come from old habits. Lock AI down like software and you kill its value. Let it roam and it drifts. Mistakes ship and scale. WISER is the field manual for teams operationalizing AI.

Written by Robb Wilson and Anthony Franco, practitioners with twenty years of shared experience building systems for over half the Fortune 100, The WISER Method delivers a systematic approach to AI implementation built on AI First Principles, an open-source framework of twelve constraints governing how AI systems succeed and fail.

Inside: a full-length narrative case study following one company from discovery through deployment. Twenty-six Plays with objectives, inputs, steps, success criteria, adaptations, and pitfalls. Over twenty downloadable templates. Advanced frameworks for risk, autonomy, measurement, and knowing when to rebuild.

For leaders: roughly 80 pages of strategic foundation to sponsor well and recognize when things go wrong. For practitioners: the entire book is your workbook.

Five canons. One method. Built by people who ship.

Build What Matters with AI First Principles

WISER Method Master Playbook

Accelerating Innovation in the Age of Artificial Intelligence

SuperCreativity

New Information Communication Technologies in the Digital Era

Master's Thesis from the year 2025 in the subject Leadership and Human Resources - Recruiting, grade: 1,2, University of Applied Sciences Dortmund, language: English, abstract: This master's thesis explores the role of artificial intelligence (AI) in modern recruitment processes with a particular focus on applicants' trust. As digitalization and AI increasingly transform the world of work, organizations are adopting AI-supported recruiting tools to enhance efficiency, standardization, and data-driven decision-making. At the same time, the use of AI in personnel selection raises important questions regarding transparency, fairness, and acceptance from the applicants' perspective.

The objective of this thesis is to examine how applicants perceive AI-assisted recruitment processes and which aspects are relevant for the development of trust in this context. To address this research objective, a qualitative research design was chosen. Semi-structured interviews were conducted with participants who had either experienced AI-supported recruitment processes or reflected on their expectations toward such processes.

The empirical data were analyzed using qualitative content analysis following Kuckartz' approach. This method allows for a systematic examination of subjective perceptions, attitudes, and evaluations, while combining theory-driven and data-driven coding. The analysis focuses on applicants' experiences with different forms of AI usage in recruitment, their expectations toward human and technological decision-making, and their assessment of AI-supported processes within the broader candidate journey.

By linking theoretical concepts of trust in technology with empirical insights from applicants, this thesis contributes to the growing body of literature on AI in recruiting. In addition, it provides a structured foundation for further academic research and offers valuable insights for organizations seeking to better understand applicant perspectives on AI-supported recruitment processes.

Artificial intelligence in the recruitment process. How can companies gain applicants' trust?

The accelerating global demand for sustainable solutions has catalyzed the integration of emerging technologies with sustainability-driven innovations. This book explores the intersection of technology, engineering, and environmental responsibility through six critical themes: Artificial Intelligence and Machine Learning for Sustainability, Cloud Computing Technologies, Sustainable Energy Technologies, Sustainable Materials and the Built Environment, Sustainable Actions, and Innovative Engineering and Technology.Artificial intelligence and machine learning play a pivotal role in optimizing resource management and enabling low-carbon decision-making, while cloud computing technologies provide scalable platforms for collaboration and innovation. Sustainable energy technologies such as solar, wind, and bioenergy are examined as vital pathways toward clean power generation. The discussion extends to sustainable materials and the built environment, emphasizing eco-friendly design and circular economy principles. The book also highlights sustainable actions driven by policy, behavioral change, and community engagement. Together, these domains represent a multidisciplinary pathway toward achieving global sustainability goals, fostering a balance between technological advancement and ecological preservation.This book is a key resource for leaders, academia, policymakers, professionals, and researchers to advance sustainable development through science, technology, and engineering. It provides valuable insights for integrating AI, renewable energy, and sustainable engineering into practical applications for a greener future.

Emerging Frontiers in Sustainable Energy, Smart Systems, and Green Technology

Shared Intelligence

Coming of Age

Gen AI is changing the way you work. So why is your team stuck in neutral?The adoption of generative AI is now widespread, yet it is still typically used on an individual basis: one person, one screen, one task. Meanwhile, the most important work in organizations happens in teams. The transformative potential of enhancing teamwork with gen AI is too big to ignore; fortunately, you can make AI-enabled collaboration real right now and see immediate results.The HBR Guide to Generative AI for Teams is packed with practical tips, prompts, and case studies to elevate team-based work. Whether you're a team leader, manage AI transformation initiatives, or facilitate group work of any kind, you'll learn how to: <ul><li>Bring gen AI into any meeting, workshop, or session</li><li>Run better brainstorms, business reviews, and retrospectives</li><li>Leverage gen AI as a team member, not just a notetaker</li><li>Use your team's collective judgment to avoid pitfalls</li><li>Reach team outcomes that were impossible before gen AI</li><li>Establish a new "humans+AI" way of working in teams</li></ul>Arm yourself with the advice you need to succeed on the job, with the most trusted brand in business. Packed with how-to essentials from leading experts, the HBR Guides provide smart answers to your most pressing work challenges.

HBR Guide to Generative AI for Teams

Boost your AI quotient for AI-ready leadership.Most leaders know that AI can deliver efficiency gains, making it a company priority in a challenging business environment. But the pace of change is outstripping their ability to adapt. More than 75% of leaders report that AI is creating challenges they have never faced before and these new challenges, anxieties and uncertainty about the future are creating a 'readiness gap'.AI-Q, your AI Quotient, is both a new metric for assessing readiness and a framework for building it. Use the AI-Q MAP (Mindset, Abilities and Practices) to: <ul> <li> assess where you are today </li> <li> identify the critical gaps, and </li> <li> build the leadership and organizational capabilities you need to ensure your AI investments deliver returns. </li> </ul>Futurist and economist Athena Peppes draws on research from leading institutions and expert interviews to offer a new approach to AI-readiness, the new critical leadership capability in the human+AI era.

The new leadership imperative for the Human+AI era

AI-Q

The Digital Twin

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