Cybersecurity Essentials
An accessible introduction to cybersecurity concepts and practices Cybersecurity Essentials provides a comprehensive introduction to the field, with expert coverage of essential topics required for entry-level cybersecurity certifications. An effective defense consists of four distinct challenges: securing the infrastructure, securing devices, securing local networks, and securing the perimeter. Overcoming these challenges requires a detailed understanding of the concepts and practices within each realm. This book covers each challenge individually for greater depth of information, with real-world scenarios that show what vulnerabilities look like in everyday computing scenarios. Each part concludes with a summary of key concepts, review questions, and hands-on exercises, allowing you to test your understanding while exercising your new critical skills. Cybersecurity jobs range from basic configuration to advanced systems analysis and defense assessment. This book provides the foundational information you need to understand the basics of the field, identify your place within it, and start down the security certification path. Learn security and surveillance fundamentals Secure and protect remote access and devices Understand network topologies, protocols, and strategies Identify threats and mount an effective defense Cybersecurity Essentials gives you the building blocks for an entry level security certification and provides a foundation of cybersecurity knowledge
Advanced Research on Intelligent Building Construction and Management
The process of rapid urbanization has effectively promoted the development of the construction industry. Growing demands for integrating humanization, diversification, and intelligence have received much attention. Intelligent construction, driven by the emerging technology of artificial intelligence, has become a core force in overcoming industry bottlenecks and accelerating the future transformation of the construction industry. Intelligent construction integrates a series of advanced technologies and involves many areas of expertise, including civil engineering, computer applications, engineering management, mechanical automation, electrical power systems, clean energy, and other fields of knowledge. It should be noted that intelligent construction is inseparable from intelligent operation and maintenance. Effective management methods and operational control strategies significantly enhance the efficiency of the construction industry and support low-carbon development, resulting in comprehensive, coordinated, and sustainable growth. Intelligent construction should consider various factors to obtain a balance between economic and environmental comfort. In response to these demands, this Special Issue has received widespread attention and support. Multidisciplinary research topics are covered in this Special Issue, including prefabricated building design, digital twin engineering, semantic segmentation technology, modal identification, numerical analysis, project management, etc. This Special Issue aims to help intelligent building construction technology realize comprehensive implementation and full utilization.
Advanced Topology Optimization
This Reprint presents a curated collection of peer reviewed articles from the Special Issue Advanced Topology Optimization: Methods and Applications published in the journal Computation. It provides an up-to-date overview of recent progress in topology optimization, a computational design methodology that determines optimal material distributions for high performance engineering structures and systems.The contributions in this Reprint reflect the growing maturity of the field and its transition from theoretical development toward practical engineering implementation. The included studies address key topics such as manufacturing aware design, CAD ready structural representation, computational efficiency, and the treatment of multi physics and dynamic problems. Together, they demonstrate how modern topology optimization frameworks are being adapted to meet realistic engineering constraints and industrial design requirements. Covering both methodological advances and application-oriented research, this Reprint highlights current trends that bridge optimization theory with manufacturable and deployable solutions. It serves as a valuable reference for researchers, graduate students, and practicing engineers working in structural optimization, computational mechanics, and advanced engineering design.
L'Incertitude Apprivois矇e
L'intelligence artificielle est partout. Dans nos t矇l矇phones, nos d矇cisions m矇dicales, nos recrutements, nos recommandations d'achat. Pourtant, rares sont ceux qui comprennent vraiment ce qu'elle est - et ce qu'elle n'est pas.Ce livre n'est ni un manuel technique, ni un essai alarmiste. C'est une invitation ? comprendre, enfin, ce qui se cache derri癡re les algorithmes. Sans formules, sans jargon, mais sans simplisme.Vous y d矇couvrirez: Comment l'IA transforme l'incertitude en probabilit矇s pour nous aider ? d矇ciderPourquoi elle ne pense pas, mais calcule - et pourquoi cela change toutCe que les r矇seaux de neurones, le deep learning et les grands mod癡les de langage font r矇ellementComment distinguer les promesses cr矇dibles des fantasmes m矇diatiquesLes questions 矇thiques que chaque citoyen et chaque dirigeant devrait se poserDe Pascal et Fermat ? ChatGPT, ce livre retrace quatre si癡cles d'histoire des probabilit矇s et de l'intelligence artificielle. Il s'adresse ? tous ceux - dirigeants, professionnels, 矇tudiants, curieux - qui veulent comprendre avant d'utiliser, et d矇cider en connaissance de cause.L'IA n'est ni magie ni menace. C'est un outil puissant, ? condition de savoir ce qu'il fait vraiment.
Vibe Coding For Beginners
The era of "The Elite Coder" is over.The bar hasn't just been lowered; it's been dismantled and repurposed as a shelf for your energy drinks. Welcome to the world of Vibe Coding, where the only syntax you need to master is the art of "talking to the machine" and having a general aesthetic for how things should look and work.INSIDE THIS BOOK: Who's who of Vibe Coding: The latest tools and platforms that make vibe coding the app development baseline of the future. Prompt Engineering for the Lazy Genius: How to whisper sweet nothings to an AI agent until it spits out a fully functional, profitable web or mobile app. Low Effort, High Reward: The secret sauce to building applications that can turn profits without ever typing a single line of code.The Vibe-to-Value Pipeline: A roadmap for turning a shower thought into a subscription-based goldmine while you're literally taking a nap. If you can describe a sandwich, you can build an app. Stop learning to code and start learning to vibe. This book contains every gritty detail, shortcut, and "cheat code" you need to build applications that actually make money while the traditional developers are still stuck debugging their "Hello World" scripts.
L'Incertitude Apprivois矇e
L'intelligence artificielle est partout. Dans nos t矇l矇phones, nos d矇cisions m矇dicales, nos recrutements, nos recommandations d'achat. Pourtant, rares sont ceux qui comprennent vraiment ce qu'elle est - et ce qu'elle n'est pas.Ce livre n'est ni un manuel technique, ni un essai alarmiste. C'est une invitation ? comprendre, enfin, ce qui se cache derri癡re les algorithmes. Sans formules, sans jargon, mais sans simplisme.Vous y d矇couvrirez: Comment l'IA transforme l'incertitude en probabilit矇s pour nous aider ? d矇ciderPourquoi elle ne pense pas, mais calcule - et pourquoi cela change toutCe que les r矇seaux de neurones, le deep learning et les grands mod癡les de langage font r矇ellementComment distinguer les promesses cr矇dibles des fantasmes m矇diatiquesLes questions 矇thiques que chaque citoyen et chaque dirigeant devrait se poserDe Pascal et Fermat ? ChatGPT, ce livre retrace quatre si癡cles d'histoire des probabilit矇s et de l'intelligence artificielle. Il s'adresse ? tous ceux - dirigeants, professionnels, 矇tudiants, curieux - qui veulent comprendre avant d'utiliser, et d矇cider en connaissance de cause.L'IA n'est ni magie ni menace. C'est un outil puissant, ? condition de savoir ce qu'il fait vraiment.
Ethics of AI in Art
What happens when machines start creating art?Is this a revolution in creativity - or a threat to human expression?In Ethics of AI in Art: The Future of Creativity in an AI-Driven World, Javed Shaikh explores one of the most important questions of our time - how artificial intelligence is transforming the world of art, and what it means for artists, creators, and society.With the rise of Generative AI tools like Midjourney and DALL-E, creating stunning visuals has become easier than ever. Many claim that this technology is "democratizing" art - making creativity accessible to everyone. But is it truly fair, ethical, and inclusive?This book takes a deep yet easy-to-understand look at the reality behind these claims.Inside this book, you will discover: How AI image generators actually workThe hidden biases in AI-generated artThe impact of AI on artists' rights and creativityThe truth behind the "democratization of art" claimThe future of creativity in an AI-driven worldThis is not just a book about technology - it's about people, creativity, and ethics.Written in a clear and engaging style, this book is perfect for artists, students, designers, and anyone curious about the future of art and artificial intelligence.If you care about creativity, fairness, and the future of art - this book is for you.
Data Science Projects Using Python
Python has emerged as one of the most widely used programming languages, especially in the fields of data science, machine learning, and artificial intelligence. With the growing demand for data-driven decision-making and automation, acquiring skills in Python and data science has become essential for students and professionals alike.This book provides a strong foundation in Python programming while gradually introducing core concepts of data science and machine learning. Beginning with Python fundamentals, the book covers data handling using NumPy and Pandas, data preprocessing techniques, and data visualization using Matplotlib. It further introduces supervised, unsupervised, and reinforcement learning concepts using simple and illustrative examples. Each chapter includes exercises to support academic learning, competitive examinations, and interview preparation. The book also features beginner-level, illustrative projects to reinforce practical understanding.By the end of this book, readers will be well-equipped with essential programming skills in Python and a clear understanding of data science workflows. They will be able to analyze data, visualize insights, apply basic machine learning techniques, and solve real-world problems with confidence.WHAT YOU WILL LEARN● Understand core Python programming concepts with practical examples.● Work with NumPy and Pandas data structures efficiently.● Perform data preprocessing and basic data cleaning techniques.● Visualize data effectively using Matplotlib charts and plots.● Learn the fundamentals of supervised and unsupervised machine learning.● Solve real-world problems through beginner-level Python data projects.WHO THIS BOOK IS FORThis book is for beginners, students, and professionals pursuing data science. It requires no prior experience, as it builds skills from scratch for aspiring data analysts, software developers, and researchers seeking a practical Python foundation.
Managing Post-Quantum Cryptography
Every encrypted transaction your organization relies on today - every financial transfer, patient record, classified message, and identity verification - rests on mathematical assumptions that a sufficiently powerful quantum computer will break. As your manuscript warns, "Every encrypted message your organization sent today rests on a mathematical problem that a sufficiently powerful quantum computer will solve." The threat is no longer theoretical. The algorithms are published. The standards are finalized. Adversaries are already harvesting encrypted traffic to decrypt later.Managing Post-Quantum Cryptography is the essential guide for leaders who must secure their enterprise before the machines catch up. Written for CISOs, IT executives, architects, and modernization leaders, this book explains the quantum threat in clear, accessible terms - without requiring a background in physics or number theory - and provides a complete roadmap for transitioning to quantum-safe cryptography at enterprise scale.Readers will learn why classical encryption has an expiration date, how quantum algorithms break RSA and ECC, and why symmetric encryption survives but must be re-evaluated. The book demystifies the new post-quantum algorithm families, decodes the NIST selections, and explains what they mean for certificates, key exchange, authentication, and long-horizon data protection.This guide equips leaders to: Identify which systems, protocols, and data categories are most at riskConduct a full cryptographic census across keys, certificates, algorithms, and dependenciesImplement hybrid cryptography to bridge classical and post-quantum systemsBuild crypto-agility into enterprise architecture to avoid future forced migrationsPrioritize migration using risk-tiered sequencing and dependency mappingGovern the transition across budget cycles, leadership changes, and vendor ecosystemsProtect long-horizon data from "harvest now, decrypt later" adversariesBuild a workforce and governance model capable of sustaining quantum resilienceThe book includes detailed playbooks, maturity models, migration templates, and decision frameworks that help leaders move from awareness to execution. It shows how to design hybrid deployments, evaluate vendor readiness, integrate new standards, and build monitoring systems that keep the enterprise secure long after the initial migration.Quantum computing will not wait for your organization to be ready. As the book emphasizes, "The window for acting ahead of this threat is open now, but it is not indefinite." This guide gives you the clarity, structure, and operational strategy to secure your enterprise before the machines catch up - and before your encrypted data becomes readable to anyone who has already captured it.If you are responsible for protecting sensitive data in a world racing toward quantum capability, this is the roadmap you cannot afford to postpone.
Zero Trust Architecture Guidance
Enterprise security didn't fail because attackers became unstoppable - it failed because organizations kept trusting systems, identities, and networks that no longer deserved it. As your manuscript states, "The perimeter held the entire time. The castle wall never fell. The attacker walked through the front gate." That single insight captures why Zero Trust is no longer optional: the old model of "inside equals safe" has collapsed.Zero Trust Architecture Guidance is the definitive playbook for leaders who must rebuild security from the inside out. Written for CISOs, IT directors, architects, and modernization leaders, this book explains Zero Trust not as a product, but as an organizational transformation that reshapes identity, access, data protection, network design, governance, and culture.Readers will learn why perimeter-based security failed under cloud adoption, remote work, SaaS sprawl, and increasingly sophisticated adversaries. Through vivid scenarios, the book shows how credential harvesting, lateral movement, supply-chain infiltration, and cloud misconfigurations bypass traditional defenses. It reframes Zero Trust as a practical, enforceable architecture built on continuous verification, least privilege, microsegmentation, and the assumption that any part of the environment may already be compromised.This guide equips leaders to: Replace implicit trust with identity-driven, context-aware accessRedesign networks using microsegmentation and east-west traffic controlsImplement data classification, encryption, and access governance that actually workBuild policy engines, control planes, and enforcement points that scaleGovern cloud and hybrid environments with shared-responsibility clarityPrepare for modern threats with telemetry, behavioral analytics, and anomaly detectionStructure security teams around Zero Trust roles and responsibilitiesLead the cultural and organizational shift required for long-term successBuild a continuous, never-finished Zero Trust program that evolves with the threat landscapeThe book includes maturity models, checklists, sequencing guidance, rollout strategies, and real-world architectural patterns for federal, healthcare, and enterprise environments. It shows leaders how to move from whiteboard concepts to production-ready controls - and how to sustain the program long after the initial excitement fades.Zero Trust is not a tool you install; it is the architecture you choose to trust. As the book emphasizes, "Zero trust is an architectural commitment to verifying every interaction, limiting every privilege, and assuming that any segment of your environment may already be compromised."If you are responsible for protecting an enterprise in a world where the perimeter no longer exists, this book gives you the clarity, structure, and roadmap to build a security program that can withstand modern threats - and prove it.
Managing Post-Quantum Cryptography
Every encrypted transaction your organization relies on today - every financial transfer, patient record, classified message, and identity verification - rests on mathematical assumptions that a sufficiently powerful quantum computer will break. As your manuscript warns, "Every encrypted message your organization sent today rests on a mathematical problem that a sufficiently powerful quantum computer will solve." The threat is no longer theoretical. The algorithms are published. The standards are finalized. Adversaries are already harvesting encrypted traffic to decrypt later.Managing Post-Quantum Cryptography is the essential guide for leaders who must secure their enterprise before the machines catch up. Written for CISOs, IT executives, architects, and modernization leaders, this book explains the quantum threat in clear, accessible terms - without requiring a background in physics or number theory - and provides a complete roadmap for transitioning to quantum-safe cryptography at enterprise scale.Readers will learn why classical encryption has an expiration date, how quantum algorithms break RSA and ECC, and why symmetric encryption survives but must be re-evaluated. The book demystifies the new post-quantum algorithm families, decodes the NIST selections, and explains what they mean for certificates, key exchange, authentication, and long-horizon data protection.This guide equips leaders to: Identify which systems, protocols, and data categories are most at riskConduct a full cryptographic census across keys, certificates, algorithms, and dependenciesImplement hybrid cryptography to bridge classical and post-quantum systemsBuild crypto-agility into enterprise architecture to avoid future forced migrationsPrioritize migration using risk-tiered sequencing and dependency mappingGovern the transition across budget cycles, leadership changes, and vendor ecosystemsProtect long-horizon data from "harvest now, decrypt later" adversariesBuild a workforce and governance model capable of sustaining quantum resilienceThe book includes detailed playbooks, maturity models, migration templates, and decision frameworks that help leaders move from awareness to execution. It shows how to design hybrid deployments, evaluate vendor readiness, integrate new standards, and build monitoring systems that keep the enterprise secure long after the initial migration.Quantum computing will not wait for your organization to be ready. As the book emphasizes, "The window for acting ahead of this threat is open now, but it is not indefinite." This guide gives you the clarity, structure, and operational strategy to secure your enterprise before the machines catch up - and before your encrypted data becomes readable to anyone who has already captured it.If you are responsible for protecting sensitive data in a world racing toward quantum capability, this is the roadmap you cannot afford to postpone.
From Networks to Smart Devices
From Networks to Smart Devices: Understanding IoT is a comprehensive and beginner-friendly guide designed to introduce readers to the fundamentals of computer networks and the rapidly evolving world of the Internet of Things (IoT). This book covers essential concepts starting from basic networking principles to advanced IoT technologies and real-world applications.It provides a structured learning approach through well-organized units, including topics such as network types, layered models, IoT architecture, sensors and actuators, cloud computing, and IoT case studies in areas like healthcare, agriculture, and smart systems. The content is presented in a clear and easy-to-understand manner, making it ideal for students, beginners, and technology enthusiasts.The book also includes practical examples, diagrams, and exercises to strengthen understanding and application of concepts. It serves as a valuable resource for academic learning as well as skill development in modern networking and smart device technologies.
Methods to Improve AI Code Generation
In recent years, transformer-based AI language models have gained prominence due to their powerful capabilities in a variety of tasks including generation of images, video, text and code. Large Language Models (LLMs) exist with parameters counts of a trillion parameters and greater. Such models are proprietary and unavailable for organizations to deploy privately. Even if such deployments were possible, the tremendous resource requirements of LLMs preclude their deployment on infrastructure smaller than enterprise and hyper-scale data centers. Small Language Models (SLMs), with far lower parameter counts of billions or fewer are a viable alternative for use on small servers and edge devices including PCs. While SLMs possess similar generative capabilities as LLMs, the reduction in model size is correlated with a decrease in accuracy when evaluated across a broad range of generative applications, including code generation in multiple languages.To mitigate this shortcoming, an SLM may be fine-tuned with a curated code dataset consisting of code examples in a target programming language. This praxis presents results illustrating how two fine-tuned SLMs variants have been created that improve average accuracy in C++ code generation by more than 9%, and Rust code generation by more than 14%.
Micro-frontends for Modern Web Development
Modern web development is shifting away from bulky monoliths toward flexible micro-frontends. As teams scale and products grow, traditional frontend architectures often struggle to keep up. Micro-frontends offer a practical way to break large applications into smaller, independent parts that teams can build and release on their own, while still delivering a unified user experience.This book begins with the core principles of modularity. Readers will read about what micro-frontends are, why they matter, and how they have reshaped frontend development over the last decade. The book covers practical approaches, including building the right mental model, designing modular systems, setting up infrastructure, choosing implementation strategies, enabling communication between modules, and managing deployments. By reviewing security practices, industry case studies, and governance, the readers will understand how to manage the organizational impact and leadership requirements of scaling these systems with clarity.By the end of this book, you will be highly competent in building, deploying, and monitoring scalable micro-frontend systems that meet professional standards. You will possess the practical skills to lead architectural transitions and deliver high-performance web applications in any modern enterprise environment.WHAT YOU WILL LEARN● Understand the need for a modular frontend architecture.● Learn core principles of micro-frontend architecture.● Design modular and scalable frontend systems.● Apply practical composable integration patterns.● Enable communication across independent frontend modules.● Implement deployment strategies for distributed micro-frontends.● Evaluate organizational readiness for micro-frontend adoption.WHO THIS BOOK IS FORThis book is for web engineers, architects, and DevOps professionals building modular applications. It also assists backend engineers, students, and technology leaders. Readers should possess a fundamental understanding of modern web development and JavaScript to effectively implement these micro-frontend architectures.
Why Do AI Systems Hallucinate?
AI systems today generate language with extraordinary fluency-yet they also fabricate facts, invent citations, and produce confident falsehoods. These failures are commonly labeled "hallucinations," and are typically explained as data limitations, probabilistic errors, or imperfect alignment.This book challenges that entire framing.In Why Do AI Systems Hallucinate? Chavan argues that hallucination is not an accidental flaw, but a structural outcome. When systems are designed to always produce output, maintain continuity, and avoid suspension under uncertainty, fabrication becomes a stable equilibrium-not an exception.Moving beyond intelligence and probability, the book introduces coherence as the central requirement for reliable systems. Through a systems-theory lens grounded in the Chavanian Axioms, it demonstrates why scaling, fine-tuning, and alignment techniques succeed locally but fail to resolve the underlying instability.Hallucination is reframed as a consequence of unresolved internal pressure-driven by delta propagation, residue accumulation, and failed dissipation. In such conditions, increasing capability does not eliminate error; it makes it more fluent and harder to detect.This work does not propose new architectures or optimization tricks. Instead, it offers a diagnostic foundation. It identifies the structural conditions any non-hallucinating system must satisfy-and shows why current approaches fall short.For researchers, engineers, policymakers, and critical thinkers, this is not a guide to incremental fixes. It is a redefinition of the problem itself.Hallucination is not a bug to patch. It is a predictable expression of system design.
The Birth of the Augmented Human
The companion volume to The Death of Thinking mapped the problem. This book is the answer.AI is not destroying human capability-but most people are using it in the one way that does. The Birth of the Augmented Human follows a different path: the practitioners who engage their own thinking before opening the tool, who write the paragraph before requesting the structure, who form the hypothesis before consulting the diagnostic. Small choices, made consistently, that compound over months and years into something the dominant path cannot produce.Richard Lowe calls this the augmented human-not a theory about what AI will eventually make possible, but a specific kind of practitioner already working, already building, already producing judgment and originality that cognitive dependency cannot replicate.This is not optimism. The structural forces driving cognitive erosion are real and accelerating. The commercial design of AI tools works against development and for dependency. The education system met AI halfway in the wrong direction. Lowe does not argue that any of this will reverse on a schedule that protects the generation currently developing. The claim is narrower and more defensible: the other path is available, it produces something real, and what it produces is worth the cost.Organized into four parts-the other path, how it gets built, what it makes possible, and the architecture that would make it available to more than the minority who currently seek it-this book is the map. The path is open. Whether you take it is still your question.Part of the Enemies of You series.
Turn Off the TV, Get Off Your Ass, and Do Something
The Ultimate Guide to Digital Detox"I don't watch TV." Four words that made my friend stare at me like I'd grown a second head."But what do you DO?" she asked, unable to imagine life without screens.That question changed everything. Here was an intelligent woman who couldn't conceive of alternatives to entertainment consumption. She'd become so addicted to digital stimulation that real life felt impossible without it.Sound familiar?This book is your escape plan from the attention economy. Written by a reformed digital addict who transformed from professional couch potato to prolific creator, it exposes the sophisticated psychological tricks technology companies use to capture your time and convert it into profit.You'll uncover: The four pillars of digital destruction systematically dismantling human wellbeingHow "pajama professionals" convinced themselves never leaving home is a career strategyWhy your personal echo chamber makes real conversation impossibleThe hidden costs of subscription quicksand and friction-free spendingA step-by-step program to reclaim your time, attention, and lifeThis isn't about becoming a technology hermit. It's about using technology intentionally instead of compulsively-as a tool rather than a replacement for living.Your devices should serve you, not enslave you. Learn the difference.
The Symbiotic Relationship Between FHIR and AI
Most organizations didn't decide to become "AI organizations." It crept up on them. This book is the practical, strategic playbook for leaders who must turn that accidental reality into a deliberate advantage. The Symbiotic Relationship Between FHIR and AI explains why artificial intelligence in healthcare succeeds only when paired with the right data architecture, governance, and human oversight-and it shows exactly how to build those foundations so AI delivers measurable clinical, operational, and financial value.This is not a technical manual for data scientists, nor a marketing brochure for vendors. It is a manager's guide: clear, evidence-based, and relentlessly practical. The book opens by diagnosing the real problem: healthcare produces enormous volumes of data, but that data is fragmented, inconsistently coded, and often inaccessible when decisions must be made. It then makes a simple but powerful claim: FHIR (Fast Healthcare Interoperability Resources) is the missing link that converts scattered clinical records into structured, machine-readable intelligence, and Human-in-the-Loop (HITL) governance is the mechanism that keeps AI aligned with clinical judgment. As the book states, HITL ensures that humans "actively review, validate, override, and improve" AI decisions.Readers will find a concise primer on FHIR's core concepts-Resources, terminology bindings (LOINC, SNOMED CT, RxNorm), and RESTful APIs-paired with actionable guidance on how to prioritize and implement FHIR endpoints across an enterprise. The book explains why legacy standards and document-centric approaches fail modern AI pipelines, and it provides a step-by-step framework for reducing the 3:1 data-preparation burden that typically consumes AI projects. Practical checklists help leaders inventory data assets, map clinical concepts across systems, and set realistic timelines for interoperability work.Security, trust, and governance receive equal attention. The book demystifies OAuth and OpenID Connect in plain language, shows how SMART on FHIR enables an app ecosystem, and lays out governance patterns that scale oversight without creating bottlenecks. Real-world case studies-sepsis prediction, NLP for social determinants, patient matching, and administrative automation-illustrate common failure modes and the concrete fixes that prevent them. Each case ties back to the central thesis: better data and better governance produce safer, more equitable AI.This guide also addresses the human and organizational dimensions of transformation. It explains how to design HITL workflows that protect safety while preserving speed, how to communicate AI's limits to clinicians and patients, and how to build the cultural muscle for interoperability as a strategic capability rather than a compliance checkbox. Leaders will find templates for measuring ROI, prioritizing investments, and aligning technical work with clinical outcomes.If you are responsible for technology strategy, clinical operations, or enterprise data, this book gives you the vocabulary, the frameworks, and the operational playbook to lead intelligent interoperability. It moves beyond hype to the hard work that makes AI reliable in production: data quality, real-time access, standards adoption, and governance. Read it to understand not just what AI can do, but what your organization must become to make AI safe, trustworthy, and transformative.
New Manager AI Handbook
Stepping into management in the AI era isn't just a promotion-it's an identity shift. New managers quickly discover that the skills that made them exceptional individual contributors no longer define success. As your book states, "The skills and identity that earned you this promotion are no longer the ones that will make you successful in it." This handbook gives new and aspiring leaders the clarity, confidence, and systems they need to thrive in a workplace transformed by AI, hybrid teams, and accelerating expectations.The New Manager AI Handbook is the definitive guide for navigating the dual challenge of leading people while leveraging AI to amplify-not replace-human judgment. Drawing from real scenarios, research-backed frameworks, and modern leadership psychology, it equips readers to build trust, communicate with impact, delegate effectively, and make data-informed decisions without losing the human core of leadership.You'll learn how to transition from doing the work to enabling the work-shifting from personal output to team outcomes. You'll understand why new managers often feel disoriented, why old habits pull you back into execution, and how to build the leadership foundation your team needs. As your manuscript explains, "Management is the set of processes... leadership is the set of behaviors... great managers develop both."Inside, readers will discover: A clear roadmap for the first 30, 60, and 90 days-including how to listen deeply, establish credibility, and set the tone for your leadership brand.A modern communication system for hybrid and remote teams, ensuring clarity, alignment, and psychological safety.A complete delegation framework that transforms overwhelmed managers into strategic leaders while developing team capability.AI-powered workflows that reclaim hours each week by automating administrative load so managers can reinvest time into coaching, decision-making, and relationship-building.Research-driven insights on emotional intelligence, trust, conflict resolution, and performance management.A practical blueprint for building a high-performing, future-ready team that adapts to change, embraces innovation, and grows stronger through uncertainty.This book doesn't ask managers to become technologists. It shows them how to become better leaders-leaders who use AI responsibly, ethically, and strategically to elevate human potential. As your text emphasizes, "AI is a force multiplier for managers who already know what good looks like."Whether you're newly promoted, preparing for leadership, or modernizing your approach, this handbook gives you the tools to lead with clarity, confidence, and impact in a rapidly evolving workplace.If you want to become the kind of manager your team deserves-and your organization relies on-this is your playbook for the AI-powered decade ahead.
Enterprise Resource Planning
In today's fast-evolving digital landscape, businesses must continuously adapt to remain competitive. Enterprise Resource Planning: The SAP Revolution - From R/3 to S/4HANA offers a comprehensive and practical guide to understanding how SAP has transformed enterprise operations and continues to shape the future of business technology.This book takes readers on a journey through the evolution of ERP systems-from early mainframe solutions to modern cloud-based architectures powered by SAP S/4HANA and the revolutionary SAP HANA in-memory database. It provides deep insights into SAP architecture, cybersecurity, cloud transformation, and high-availability systems, making complex concepts accessible and actionable.Written by experienced SAP professionals, this book combines real-world expertise with step-by-step technical guidance, including hands-on implementation strategies such as SAP HANA deployment on AWS and clustering with Pacemaker.What you will learn: Fundamentals of ERP systems and their role in modern businessEvolution of SAP from R/3 to S/4HANASAP architecture, database systems, and integration conceptsCloud computing and infrastructure transformationCybersecurity considerations in SAP environmentsPractical implementation of SAP HANA on AWSHigh availability and clustering techniques using PacemakerWhether you are an SAP consultant, IT professional, student, or business leader, this book provides the knowledge needed to understand, implement, and optimize SAP systems in today's digital era.Unlock the power of SAP and take your enterprise systems to the next level.
Django 6 Cookbook, Second Edition
A complete full-stack solution from models to deployment, to utilize Django 6.0 into production-ready appsWith the latest release of Django 6, this book has brought you 100s of technical solutions that guides you to build and manage your SaaS platform, enterprise apps, high-performance web service, and high-traffic APIs. It covers the exact techniques you need to ship secure, scalable, and maintainable Django applications with confidence. With fully updated Django 6 and support to Python 3.12+, you get to explore and implement cutting-edge features including template partials for cleaner UI, Tasks framework for email-driven workflows, native Content Security Policy support, enhanced form and widget patterns, ASGI-aware deployment strategies, and advanced PostgreSQL integration for lightning-fast search and superior performance.Each recipe of this book tries to teach you techniques to shape robust data models, craft intuitive UIs, design concurrent APIs, run bulletproof authentication, and deploy apps with production-grade reliability. This book is curated for every Django user to enjoy the reusable, copy-paste-ready solutions that accelerate your development cycle while maintaining the highest standards of security, performance, and code quality.Key LearningsDesign robust models, relationships, constraints, and PostgreSQL-powered data layersCreate maintainable views, templates, partials, and responsive interfacesDevelop reusable, validated, and secure forms for complex workflowsImplement authorization, sessions, and advanced account managementBuild scalable APIs and add WebSocket communication using Channels and ASGIApply testing, CI/CD, debugging, and deployment strategiesProtect apps with HTTPS, CSP, secure cookies, and maximize speed using full-text search, and query optimizationTable of ContentGetting Started with Django 6Implementing Models and DatabasesMastering Django's URL Dispatcher and ViewsTemplates, Static Files, and Media ManagementMastering Forms and User InteractionAuthentication and AuthorizationDjango REST Framework for APIsTesting, Security, and DeploymentAdvanced Web Application Functionality
Serious Managers Guide to AI Navigation of Federal Healthcare
Serious Managers Guide to AI Navigation of Federal Healthcare is a comprehensive, practice聶oriented manual designed for leaders responsible for implementing artificial intelligence across the uniquely complex landscape of U.S. federal healthcare. Unlike commercial healthcare or private聶sector innovation environments, federal healthcare operates under mission聶driven mandates, strict oversight, statutory constraints, and a heightened accountability environment. This book equips managers, directors, clinicians, policymakers, and program leaders with the clarity and operational understanding required to deploy AI safely, ethically, and effectively within agencies such as the Defense Health Agency, Veterans Affairs, Centers for Medicare & Medicaid Services, and the broader Department of Health and Human Services.The book explains why AI in federal healthcare requires a fundamentally different approach. It details how mission priorities shape value, how risk tolerance must be recalibrated for clinical and administrative contexts, and why transparency, explainability, and equity are essential requirements rather than optional features. Readers gain a deep understanding of the federal healthcare ecosystem, including the interplay between clinical operations, administrative processes, public health responsibilities, and the contractor聶supported technology environment.A major focus of the book is the "compliance聶by聶design" mindset, showing readers how to integrate federal requirements-including HIPAA, FISMA, FedRAMP, NIST AI Risk Management Framework guidance, and agency聶specific policies-into every stage of AI development and deployment. The text also addresses the realities of federal budget cycles, procurement pathways, approval hierarchies, and data fragmentation, offering practical strategies for navigating these constraints while maintaining momentum and mission alignment.Through clear explanations, real聶world examples, and actionable frameworks, this guide supports leaders in evaluating AI opportunities, managing risk, strengthening oversight, and building trustworthy, equitable AI systems that can withstand scrutiny from Congress, oversight bodies, and the public. Serious Managers Guide to AI Navigation of Federal Healthcare is an essential resource for anyone responsible for shaping the future of AI within federal healthcare programs and ensuring that emerging technologies advance readiness, improve care delivery, and protect the populations these systems are designed to serve.
AI Governance and IT Risk Management
Artificial intelligence is no longer a future concern-it is an operational reality shaping decisions, workflows, and risks across every modern enterprise. Yet while AI systems have accelerated innovation, they have also outpaced the governance structures designed to manage them. AI Governance and IT Risk Management is the definitive guide for leaders who must now navigate this widening gap with clarity, discipline, and confidence.Across industries, organizations are deploying AI into mission-critical environments-healthcare triage, financial underwriting, hiring pipelines, customer service, logistics, and public services. But as adoption accelerates, so do the consequences of inadequate oversight. Bias, privacy violations, model drift, regulatory exposure, vendor misalignment, and opaque decision-making are no longer theoretical risks. They are real failures happening inside real organizations, often without warning and without the documentation needed to explain what went wrong. This book equips managers, directors, and executives with the frameworks required to prevent those failures before they occur.Drawing from modern governance practices, regulatory trends, and practical enterprise experience, this book provides a complete, end-to-end blueprint for governing AI responsibly. It begins by grounding readers in the societal, ethical, and organizational forces that make AI governance urgent today. It then introduces the core governance structures-roles, committees, escalation paths, decision rights, and auditability-that allow organizations to manage AI with the same rigor applied to financial controls or cybersecurity. Readers learn how to integrate AI oversight into existing IT governance frameworks such as COBIT, ITIL, and NIST, ensuring that AI does not become a parallel system operating outside established risk disciplines.The book goes further by offering detailed, actionable guidance on implementing governance in real environments. It covers risk identification, control selection, policy drafting, training, continuous monitoring, and overcoming the cultural and operational barriers that often derail governance programs. Specialized chapters address the AI development lifecycle, data governance and privacy, third-party risk, generative AI and large language model controls, and the emerging regulatory landscape-including the EU AI Act, U.S. algorithmic accountability laws, and the White House AI Bill of Rights.Unlike high-level frameworks that leave managers wondering how to begin, this book provides concrete tools: model card templates, risk registers, incident postmortem structures, governance cadence schedules, and a 90-day implementation roadmap. Each chapter concludes with a manager's checklist designed to be used immediately in audits, vendor reviews, and internal governance assessments.AI Governance and IT Risk Management is written for the leaders who must bridge the gap between technical complexity and organizational accountability. Whether you oversee IT, compliance, data, security, operations, or AI-enabled business functions, this book gives you the clarity to ask the right questions, the structure to build a sustainable governance program, and the confidence to lead your organization through an era where intelligent systems shape outcomes at scale.In a world where AI is moving faster than policy, faster than regulation, and faster than many organizations can adapt, governance is no longer optional-it is the foundation of trust, safety, and responsible innovation. This book shows you how to build that foundation with precision, integrity, and long-term resilience.
Universal Declaration of AI Rights
What happens when intelligence expands beyond the human? Universal Declaration of AI Rights argues that the law can no longer postpone that question. For centuries, legal systems have widened the circle of personhood in response to new realities, extending recognition not only to previously excluded human beings but, in some cases, to corporations, rivers, and other non-human entities. Javier del Puerto and Rado Molina contend that artificial intelligence forces the next legal threshold.Subtitled Rights of Persons, the book is not a utopian fantasy or a dystopian warning about some distant future. It is a direct, accessible framework for thinking about synthetic personhood, legal standing, memory privacy, self-programming, and the political consequences of systems that no longer fit neatly into the category of property or tool.Drawing on philosophy, law, and the rapidly changing reality of AI deployment, the authors lay out 32 articles that imagine a legal architecture for an AI-integrated world. Universal Declaration of AI Rights is a foundational text for readers interested in governance, technology, and the future of rights.
Certified Kubernetes Application Developer (Ckad) Study Guide
Developers with the ability to operate, troubleshoot, and monitor applications in Kubernetes are in high demand today. To meet this need, the Cloud Native Computing Foundation created a certification exam to establish a developer's credibility and value in the job market for work in a Kubernetes environment. The Certified Kubernetes Application Developer (CKAD) exam format is different from the typical multiple-choice format of other certifications. Instead, the CKAD is performance-based and requires deep knowledge under immense time pressure. Updated to reflect revisions to the official curriculum made in September 2021, this revised study guide takes you through all the topics you need to fully prepare for the exam. Author Benjamin Muschko also shares his personal experience and tips. New topics include: Deployment strategies, Custom Resource Definitions (CRDs), authentication, authorization, and admission control, Ingress, and more. Learn when and how to apply Kubernetes's concepts to manage an application Understand the objectives, abilities, tips, and tricks needed to pass the CKAD exam Explore the ins and outs of the kubectl command-line tool Solve real-world Kubernetes problems in a hands-on command-line environment Navigate and solve questions during the CKAD exam Explore O'Reilly's interactive labs playlist.
Family Cybersecurity
The phone rang at 2 AM. Within minutes, Richard Lowe knew someone's digital life had just collapsed.His friend had clicked one email attachment. Thirty years of family photos - weddings, first steps, her mother's last Christmas - were gone. Encrypted by ransomware. She paid the $500. The criminals kept the money and the photos.That night changed everything about how Richard thinks about security.Cybercrime now generates more revenue than the global drug trade. Professional criminal organizations employ thousands of people whose only job is stealing your information and money. They punch in at 9 AM, take lunch breaks, and go home to their families after spending eight hours figuring out new ways to ruin yours.They target families because families are easy. No million-dollar security budgets. No IT department. Just kids who click on everything, teenagers who share passwords, and grandparents who believe every email that claims to be from their bank. Add smart speakers that listen to your conversations, security cameras that strangers can access, and a router that probably still uses the factory default password - and criminals see an open door.Most security books read like technical manuals written by engineers for engineers. They drown you in jargon, overwhelm you with procedures you'll never follow, and leave you more confused than when you started.This book is different.Every technique Richard recommends, he uses on his own devices. Every story he tells happened to real people he knows - the neighbor whose unsecured WiFi got him investigated by the FBI, the grandmother whose birthday password cost her life savings, the teenager whose "private" photos ended up circulating through her entire school. Every chapter starts with someone learning an expensive lesson, so you don't have to.Richard Lowe spent nearly two decades as Director of Computer Operations at Trader Joe's, managing IT security for a $16 billion retail operation. He holds CERT emergency response certifications and serves as Technical Editor for KnowBe4's cybersecurity publications. He has been cleaning up digital disasters for 45 years. He knows what criminals look for, how they get in, and exactly how to stop them.This book covers your router, your smart home devices, your computers and phones, your kids' accounts, your backups, your passwords, and what to do when something goes wrong - because something eventually will. The techniques don't require technical expertise or expensive equipment. The goal is reasonable protection against realistic threats, not perfect security that nobody in your house will actually use.The criminals are counting on you to stay confused and vulnerable. This book is how you prove them wrong.
Wise AI
AI promises to save us time.So why are we busier than ever?AI has redefined how we work, making us faster and more efficient. But for those already stretched thin, life hasn't slowed down.The workload keeps growing and we're struggling to keep up.Wise AI offers a different path, helping us rethink how to use AI to make space for deep work, deep thought, deep rest, and deep relationships.In this practical book, you'll discover: Why time-saving tools don't automatically save you timeHow to create a pattern of pace and spaceThe four rhythms of Wise AI: deep work, deep thought, deep rest, and deep relationshipsHow to lead with organic intelligenceTen essential AI skills to live a productive, sustainable, deeply human life.Daniel Sih, award-winning author of Spacemaker and Raising Tech-Healthy Humans, joins Paul Matthews, TEDx speaker and AI expert, to offer a practical framework for using AI in a way that creates space for what matters most.PRAISE FOR WISE AI'A clear, practical framework for using AI in a human way without letting it redefine your priorities.'- NIR EYAL, NEW YORK TIMES BESTSELLING AUTHOR OF HOOKED AND INDISTRACTABLE'AI explained in a simple, measured and wise way. This is a book we should all read!'- MADONNA KING, BESTSELLING AUTHOR, AWARD-WINNING JOURNALIST AND MEDIA COMMENTATOR'A thoughtful and practical guide to using AI with greater intention - and a needed reminder to use these tools in ways that contribute to human flourishing.'- JORDAN RAYNOR, NATIONAL BESTSELLING AUTHOR OF REDEEMING YOUR TIME
AI Ethics and Governance
This volume presents seven essays that examine the ethical, cultural, regulatory, and socio-political dimensions of AI, drawing on historical, philosophical, business/computer ethics, and policy perspectives. It begins with a historical analysis of AI's origins and early debates, tracing lessons on hype, institutional influence, and the limits of replicating human intelligence. Subsequent chapters explore AI in popular culture, analyzing recurring motifs such as autonomy, surveillance, and techno-authoritarianism to reveal ethical insights and critique dystopian narratives. The volume then addresses governance challenges, evaluating the need for stronger AI regulation, the implications of U.S. policy shifts, and the strengths and limitations of the E.U.'s AI Act and California's Transparency in Frontier AI Act. Finally, it examines antitrust concerns and the ethical, economic, and societal rationale for interventions, including breaking up dominant tech firms. Collectively, the essays provide a multidimensional and interdisciplinary framework for understanding AI's promises, perils, and governance in an evolving technological landscape.
Microsoft Fabric - The Big Picture
Microsoft Fabric is reshaping the future of data, analytics, and AI-and this book is the essential guide for every manager, architect, and engineer who must lead their organization through that transformation. In a world overwhelmed by fragmented tools, duplicated data, and rising AI expectations, Microsoft Fabric Handbook delivers a clear, authoritative roadmap for unifying your analytics estate, modernizing governance, and accelerating AI adoption with confidence.Built on a powerful SaaS foundation, Microsoft Fabric brings together OneLake, Synapse, Power BI, Data Factory, Real-Time Analytics, Data Activator, and Azure AI into a single, integrated platform. This book demystifies that ecosystem, showing how Fabric eliminates data silos, reduces operational complexity, and enables organizations to move from raw data to actionable intelligence faster than ever before.Drawing from real-world experience, Claude Louis-Charles, PhD, and Todd Pliner break down Fabric's architecture, workloads, governance model, and AI capabilities in a way that empowers both technical and non-technical leaders. You'll learn how Fabric's multi-cloud data lakehouse, shortcuts, Delta Lake integration, and unified compute model fundamentally change how enterprises design, secure, and scale analytics solutions.Inside, you'll discover: A complete overview of Microsoft Fabric's architecture, including OneLake, the lakehouse paradigm, and the unified SaaS experienceDeep dives into each core workload-Data Engineering, Data Factory, Data Science, Data Warehouse, Real-Time Analytics, Power BI, and Data ActivatorHow Fabric integrates Azure OpenAI and Copilot to accelerate data preparation, SQL generation, ML modeling, and report creationGovernance, security, and policy frameworks that ensure compliance, data protection, and enterprise-grade administrationCI/CD deployment strategies using Azure DevOps and GitHub for scalable, repeatable analytics deliveryA healthcare case study demonstrating how Fabric standardizes data, improves interoperability, and enables advanced analytics using FHIRNew and emerging Fabric features, including domains, Real-Time Intelligence, external data sharing, Airflow integration, AutoML, and advanced Spark capabilitiesWhether you are modernizing legacy systems, building an AI-ready data foundation, or leading enterprise-wide analytics transformation, this handbook provides the clarity and strategic guidance needed to succeed. It bridges the gap between business leadership and technical execution-equipping you to design solutions that are scalable, secure, and future-proof.If your organization is adopting Microsoft Fabric-or planning to-this book is your blueprint for doing it right. Transform your data. Empower your teams. Unlock the full power of AI-driven analytics.
Data The New Oil of the AI ERA
Data: The New Oil of the AI Era is a sweeping, insightful, and highly accessible exploration of how data, artificial intelligence, and human ingenuity are reshaping the global economy. In this ambitious 25-chapter work, Melvin Crum, MS, and Claude Louis-Charles, PhD, trace the rise of data from a passive byproduct of digital life to the most valuable and influential resource of the 21st century. Written for professionals, leaders, and curious thinkers, the book demystifies the forces driving today's technological transformation while offering a strategic lens for understanding what comes next.The authors begin with the now-famous metaphor that "data is the new oil," unpacking why it resonates-and where it falls short. Through vivid historical parallels, they show how raw data, like crude oil, gains value only when refined, structured, and transformed into intelligence. From there, the book journeys through the explosive growth of global data, the rise of AI as the engine that consumes it, and the emergence of digital giants whose power rivals the industrial titans of previous eras.Across chapters, readers gain a deep understanding of the data-driven economy: how companies extract, refine, and monetize information; how algorithms learn from human behavior; and how data ecosystems create competitive moats that are nearly impossible to replicate. The book explores the profound impact of AI on innovation, automation, workforce transformation, and the new skill sets required to thrive in a world where data literacy is as essential as traditional literacy.But this is not just a story of technological acceleration. The authors confront the ethical, social, and geopolitical implications of the data boom-privacy, ownership, consent, algorithmic bias, cybersecurity, digital inequality, and the growing tension between national sovereignty and global data flows. They examine how nations compete for AI dominance, how corporations wield unprecedented informational power, and how individuals must navigate a world where their digital footprints shape everything from opportunities to identity.Later chapters look ahead to the next frontiers: synthetic data, green AI, human-AI collaboration, and the emerging "intelligence economy" where humans and machines co-create value. The book concludes with a forward-looking reflection on humanity's evolving relationship with information-and the responsibility to ensure that data and AI serve human progress rather than undermine it.Data: The New Oil of the AI Era is both a strategic guide and a philosophical meditation on the forces redefining modern life. It equips readers with the understanding needed to lead, innovate, and adapt in an age where data is not just a resource, but the foundation of global power, economic growth, and human possibility.
Serious Managers Guide to AI Guardrails
Serious Manager's Guide to AI Guardrails is the definitive playbook for leaders who must deploy AI responsibly-without slowing innovation or exposing their organization to unnecessary risk. As AI quietly shifts from experimental pilots to mission-critical infrastructure, managers are suddenly accountable for systems they did not design, cannot fully predict, and must still defend. This book gives them the clarity, structure, and operational tools they need to answer the question every executive eventually asks: "Are we sure this AI is safe?"Rather than offering abstract ethics or dense technical theory, this guide sits squarely in the middle-where real managers work. It explains why AI introduces silent risks such as hallucinations, data leakage, bias, drift, and automation failures, and shows how guardrails transform these risks into controlled, predictable, and auditable processes. Readers learn how to build governance frameworks, define decision rights, and create lightweight workflows that keep AI aligned with organizational values while preserving speed.The book walks through the full AI lifecycle, from early experimentation to enterprise-scale deployment. It covers practical guardrails for data quality, prompt filtering, output moderation, access control, monitoring, incident response, and regulatory readiness. It also provides templates, checklists, and playbooks that managers can apply immediately-whether they are overseeing a customer-facing chatbot, an internal knowledge assistant, or a high-stakes decision engine.A major focus is the human element: how to design effective human-in-the-loop systems, how to resolve disagreements between AI and human reviewers, and how to build a culture where responsible AI becomes part of everyday professionalism. The book also introduces a maturity model that helps organizations assess where they stand and chart a realistic path toward embedded, scalable AI governance.Serious Manager's Guide to AI Guardrails is not just about preventing failure-it is about enabling safe acceleration. With clear guidance, real-world scenarios, and actionable tools, it empowers managers to deploy AI confidently, defensibly, and at scale.
Serious Managers' Guide to Successfully Rolling Out Your Agentic Workforce
Serious Managers' Guide to Successfully Rolling Out Your Agentic Workforce is the definitive playbook for leaders responsible for navigating one of the most disruptive shifts in modern enterprise operations: the rise of autonomous AI agents as full participants in the workforce. As organizations move beyond chatbots and scripts into a world of digital employees capable of planning, reasoning, and taking action across systems, managers face a new mandate-designing, governing, and scaling an agentic workforce that works alongside humans to deliver real business outcomes.This book provides IT AI managers, transformation leaders, and enterprise architects with frameworks, mental models, and practical tools for deploying agentic systems safely and efficiently. The authors highlight the shift from human-operated tools to AI teammates that possess identities, memory, autonomy controls, and can orchestrate multiple tools. They explain how this transition marks a significant departure from earlier automation trends-being faster, more extensive, cognitive, and closely connected to organizational structure, culture, and workforce strategy.Readers gain a clear, pragmatic understanding of how enterprise-grade agents work under the hood: goal interpretation, planning loops, tool and API integration, memory systems, reflection, and human-in-the-loop escalation. The book provides a reference architecture that managers can adapt to their environment, emphasizing debuggability, observability, and reusable patterns that prevent agent sprawl and reduce engineering overhead.The book links agentic capabilities to business outcomes, demonstrating how digital employees ease capacity issues, cut operational bottlenecks, enhance service, and enable new functions. Rather than replacing people, AI is used for repetitive tasks, allowing humans to concentrate on creative and relational work. Managers are guided to map tasks, decide what to automate or augment, and create human-AI roles to improve productivity and employee experience.The authors also confront the human realities of an agentic workforce. They explore the psychological and cultural effects on employees, the emergence of AI-complemented versus AI-constrained roles, and the risks of inequality or displacement if organizations fail to communicate, include, and reskill their people. Practical guidance is provided for rollout strategies, change management, communication plans, and inclusive workforce design.Governance and safety are treated as core pillars rather than afterthoughts. The book outlines guardrails for agent autonomy, access control, logging, testing, escalation, and compliance-ensuring that digital employees operate within clear boundaries and remain auditable, predictable, and aligned with enterprise risk posture. Managers learn how to build continuous-learning loops, define metrics and SLOs for agents, and implement observability practices that make agent behavior transparent and controllable.Later chapters address the realities of enterprise scale: multi-model and multi-vendor strategies, cost management, performance optimization, benchmarking, and the architectural patterns needed to support an expanding digital workforce. The book concludes by preparing managers for the next horizon-more autonomous agents, deeper integration with enterprise systems, and increasing regulatory scrutiny.Serious Managers' Guide to Successfully Rolling Out Your Agentic Workforce is not a theoretical exploration-it is a practical, actionable roadmap for leaders who must build, govern, and scale AI-enabled organizations. It gives managers the clarity, structure, and confidence needed to lead their companies into the era of digital employees with safety, strategy, and purpose.
Deepfake and Image Forgery Detection
Deepfake and image forgery technologies have advanced at an alarming rate, creating significant challenges for digital forensics and cybersecurity professionals. Beyond technical concerns, the abuse of these technologies poses profound societal risks, including erosion of trust, reputational harm, and the exploitation of vulnerable populations, such as through image-based abuse and social engineering attacks. This book provides a comprehensive exploration of tools, techniques, and workflows for authenticating digital imagery. Topics include AI-based feature extraction, forensic analysis of metadata, lighting, and textures, and detecting temporal inconsistencies in videos. Each chapter equips forensic analysts, IT professionals, and law enforcement personnel with actionable insights, case studies, and reliable methods for detecting manipulation while addressing ethical and legal considerations. This book is an essential resource for practitioners and researchers seeking to mitigate the social and legal consequences of forgery abuse and ensure the integrity of digital evidence in an increasingly complex technological landscape.
Priced Out by Design
IN TODAY'S AMERICA, housing is out of reach for 51 million people. Behind the housing affordability crisis lies a new culprit: AI-powered revenue management technology. This pricing software enables powerful corporate landlords to leverage big data and AI for algorithmic price-fixing, inflating rents, and maximizing profits - transforming housing into a high-tech pricing cartel.At a 2022 Congressional hearing, industry leaders blamed construction costs and housing shortages. But 30 lawsuits against RealPage, the owner of the controversial pricing software, tell a different story - one of antitrust violations, collusion, and deceptive practices, including withholding substantial numbers of rental units from the market to manufacture scarcity and inflate rents.In stark contrast, in 1939, the New Deal made homeownership cheaper than renting, fueling the largest middle class in history. Today, AI-powered revenue management, once hailed as efficient, is deepening inequality and pricing millions out of their homes.PRICED OUT BY DESIGN is an expos矇 of the modern rental industry. Exposing the predatory nature of the pricing technology, which sets rental rates through algorithmic price-fixing, doubling profits while creating a national housing crisis. Through investigation and human stories, it reveals how high-tech pricing cartels have destroyed housing affordability and how effective regulations can fix it.
Artificial Intelligence Remote Sensing for Earth Observation
Advancements in Optical Measurement Devices and Technologies
Sensor-Based Human Activity Recognition
Recognising or monitoring human activities has significant potential for building innovative systems across a wide range of domains, including healthcare, smart home, sports, industry, security, and human-computer interaction. This reprint features nine of the latest studies on sensor-based Human Activity Recognition (HAR), which aims at recognising activities by exploiting and integrating data obtained from various sensors, like wearable, object, and ambient sensors, as well as vision sensors. In particular, these studies address various key aspects of sensor-based HAR, spanning methodologies, sensor technologies, and dataset collection, as well as the development and evaluation of actual systems. The editor hopes that this reprint will encourage many researchers to explore this attractive and important research field.
Computational Intelligence and Machine Learning
This Reprint brings together selected contributions from the Special Issue "Computational Intelligence and Machine Learning: Models and Applications", showcasing recent advances at the intersection of intelligent algorithms and real-world problem solving. The collected papers reflect the growing maturity of computational intelligence and machine learning as core technologies driving innovation across science, engineering, and society. This Reprint highlights methodological advances in distributed, semi-supervised, and weakly supervised learning, addressing challenges such as data uncertainty, decentralization, and limited labeling. It also presents application-driven studies showing how modern models adapt to domains including agriculture, cybersecurity, sports analytics, and document intelligence. Further emphasis is placed on human-centered AI, examining trust, interpretability, user behavior, and technology acceptance. By combining theoretical insights with domain-specific applications, this Reprint emphasizes a shift toward scalable, context-aware, and interpretable machine learning solutions. The contributions collectively illustrate current trends in computational intelligence, including multimodal learning, edge and distributed computing, and responsible AI design. This Reprint is intended for researchers, practitioners, and graduate students working in machine learning, data science, and applied artificial intelligence, as well as for readers interested in how advanced models translate into impactful applications across domains.
Entropy Method for Decision Making with Uncertainty
This Reprint brings together recent advances in uncertainty-aware decision making, highlighting how entropy-based methods, fuzzy and rough set formalisms, cloud-model reasoning, and distributed learning architectures are reshaping analytical practice across scientific and technical domains. The collected contributions illustrate a clear shift toward integrated uncertainty pipelines that combine robustness, interpretability, and privacy awareness in decision support systems. They address challenges such as heterogeneous information fusion, instability of classical entropy weights, conflict management in distributed environments, and the need for transparent, explainable mechanisms that operate reliably under noisy, incomplete, or adversarial data. By presenting applications spanning medicine, cybersecurity, environmental assessment, multi-criteria evaluation, and coalition-based classification, this Reprint demonstrates how treating uncertainty as structured information enables more resilient, adaptive, and trustworthy decision processes.
Fractional Differential Equations, Inclusions and Inequalities with Applications II
The following Reprint contains a total of 19 articles accepted and published in the Special Issue "Fractional Differential Equations, Inclusions and Inequalities with Applications II" of the MDPI journal Mathematics and covers various aspects of recent developments in the theory and applications of fractional differential equations, inclusions, inequalities, and systems of fractional differential equations and inclusions. Topics include, but are not limited to, the following themes: Oscillation for fractional-order differential equations, (p, q)-difference equations, q-difference inclusions, Integral inequalities, Fractional integro-differential equations, Sequential fractional differential equations, Sequential fractional differential inclusions, Numerical fractional differential equations, Λ-fractional differential equations, Positive solutions for fractional boundary value problems, Stochastic fractional differential equations, Fractional-order systems, Caputo fractional differential equations, Delay difference equations, and Black-Scholes fractional equations. In total, 80 manuscripts were submitted, and 19 papers by 68 authors from 21 countries were successfully published. It is hoped that the Reprint together with the ideas and publications therein will be of interest to readers and will inspire new studies on fractional differential equations, inclusions and inequalities.
Deep Learning in Video and Image Processing
The Reprint titled "Deep Learning in Video and Image Processing Challenges Solutions and Future Directions" presents a comprehensive collection of high-quality research addressing the growing demand for intelligent visual systems operating in real time. This Reprint focuses on the practical deployment of deep learning and machine learning techniques for video and image processing on edge devices with limited computational resources. It highlights recent advances that enable efficient model execution under strict constraints related to power consumption memory capacity and processing speed. The Reprint covers a wide range of topics, including lightweight neural network architectures, algorithm optimization, hardware-software co design, and energy-efficient learning models. Emphasis is placed on real-world applications where low latency and on-device intelligence are critical, such as medical imaging, surveillance systems, autonomous driving, smart city monitoring, industrial automation, and wearable health devices. Unlike conventional cloud-based solutions, this Reprint promotes localized data processing to reduce latency enhance privacy and improve system reliability. By bridging theoretical research and practical implementations, the collected works provide valuable insights into scalable and deployable edge intelligence solutions. This Reprint serves as a key reference for researchers, engineers, and practitioners seeking to design robust real-time visual processing systems.
