Computer und IT
Microsoft Power Platform Solution Architect Certification Companion
This comprehensive guide book equips you with the knowledge and confidence needed to prep for the exam and thrive as a Power Platform Solution Architect.The book starts with a foundation for successful solution architecture, emphasizing essential skills such as requirements gathering, governance, and security. You will learn to navigate customer discovery, translate business needs into technical requirements, and design solutions that address both functional and non-functional needs. The second part of the book delves into the Microsoft Power Platform ecosystem, offering an in-depth look at its core components—Power Apps, Power Automate, Power BI, Microsoft Copilot, and Robotic Process Automation (RPA).Detailed insights into data modeling, security strategies, and AI integration will guide you in building scalable, secure solutions. Coverage of application life cycle management, which empowers solution architects to design, implement, and deploy Power Platform solutions effectively, is discussed next. You will then go through real-world scenarios, giving you a practical understanding of the challenges and considerations in managing Power Platform projects within a business context.The book concludes with strategies for continuous learning and resources for professional development, including practice questions to assess knowledge and readiness for the PL-600 exam. After reading the book, you will be ready to take the exam and become a successful Power Platform Solution Architect.WHAT YOU WILL LEARN* Understand the Solution Architect's role, responsibilities, and strategic approaches to successfully navigate projects* Master the basics of Power Platform Solution Architecture* Understand governance, security, and integration concepts in real-world scenarios* Design and deploy effective business solutions using Power Platform components* Gain the skills necessary to prep for the PL-600 certification examWHO THIS BOOK IS FORProfessionals pursuing Microsoft PL-600 Solution Architect certification and IT consultants and developers transitioning to solution architect rolesLOGANATHAN K is a seasoned Microsoft Certified Trainer (MCT) and Functional Consultant with extensive experience in Power Platform, Dynamics 365, and business process automation. Currently working as a Functional Consultant in a Microsoft Partner company, he is passionate about helping organizations drive digital transformation through the Power Platform and Microsoft Business Applications.As the author of the popular blog LK Techs (lktechs.com), he shares knowledge of Microsoft technologies, certification paths, and real-world use cases to help individuals build careers in IT. He holds several advanced certifications, including those in Microsoft Business Central and the Power Platform, and regularly conducts training sessions for students, professionals, and educators.Chapter 1: Getting Started with the PL-600 Exam: Overview and Essentials.- Chapter 2: Building a Successful Solution Architect Framework: Key Stages and Skills.- Chapter 3: Governance, Architecture, and Core Components in Power Platform and Dynamics 365.- Chapter 4: Leveraging Microsoft Copilot, RPA, and Securing Data Models in Power Platform Solutions.- Chapter 5: Implementing Analytics, AI, and ALM Strategies for Power Platform Success.- Chapter 6: Evaluating Your Expertise Through Real-World Scenarios.
Emerging Smart Agricultural Practices Using Artificial Intelligence
BRING THE LATEST TECHNOLOGY TO BEAR IN THE FIGHT FOR SUSTAINABLE AGRICULTURE WITH THIS TIMELY VOLUMEArtificial intelligence (AI) has the potential to revolutionize virtually every area of research and scientific practice, including agriculture. With AI solutions emerging to drive higher yields, produce increased resource efficiency, and foster sustainability, there is an urgent need for a volume outlining this progress and charting its future course. Emerging Smart Agricultural Practices Using Artificial Intelligence meets this need with a deep dive into the rapidly developing intersection of agriculture and artificial intelligence. Taking an interdisciplinary approach which applies data science, computer science, and engineering techniques, the book provides cutting-edge insights on the latest advancements in AI-driven agricultural practices. The result is an absolutely critical tool in the ongoing fight to develop sustainable world agriculture. In addition, this book provides:* Case studies and real-world applications of new techniques throughout* Detailed discussion of agricultural applications for AI-driven technologies such as machine learning, computer vision, and data analytics * A regional approach showcasing international best practices and addressing the varying needs of farmers worldwideEmerging Smart Agricultural Practices Using Artificial Intelligence is ideal for agricultural professionals and scientists, as well as data scientists, technologists, and agricultural policymakers. ASHISH KUMAR, PHD, is an Associate Professor with Bennett University, Greater Noida, U.P. India. He has published widely on subjects including object tracking, image processing, artificial intelligence, and medical imaging analysis, and is a member of the IEEE. JAI PRAKASH VERMA, PHD, is an Associate Professor in the Department of Computer Science and Engineering, Nirma University, Ahmedabad, India. He offers customized training on big data analytics to the Indian Navy, SAC-ISRO scientists in Ahmedabad, and other experts from industry and academia. RACHNA JAIN, PHD, is an Associate Professor in the Department of Information Technology Bhagwan Parshuram Institute of Technology. She has 18+ years of academic/research experience with more than 100+ publications in various international conferences and international journals (Scopus/ISI/SCI) of high repute.
AWS Certified Machine Learning Engineer Study Guide
PREPARE FOR THE AWS MACHINE LEARNING ENGINEER EXAM SMARTER AND FASTER AND GET JOB-READY WITH THIS EFFICIENT AND AUTHORITATIVE RESOURCEIn AWS Certified Machine Learning Engineer Study Guide: Associate (MLA-C01) Exam, veteran AWS Practice Director at Trace3—a leading IT consultancy offering AI, data, cloud and cybersecurity solutions for clients across industries—Dario Cabianca delivers a practical and up-to-date roadmap to preparing for the MLA-C01 exam. You'll learn the skills you need to succeed on the exam as well as those you need to hit the ground running at your first AI-related tech job.You'll learn how to prepare data for machine learning models on Amazon Web Services, build, train, refine models, evaluate model performance, deploy and secure your machine learning applications against bad actors.INSIDE THE BOOK:* Complimentary access to the Sybex online test bank, which includes an assessment test, chapter review questions, practice exam, flashcards, and a searchable key term glossary* Strategies for selecting and justifying an appropriate machine learning approach for specific business problems and identifying the most efficient AWS solutions for those problems* Practical techniques you can implement immediately in an artificial intelligence and machine learning (AI/ML) development or data science rolePerfect for everyone preparing for the AWS Certified Machine Learning Engineer -- Associate exam, AWS Certified Machine Learning Engineer Study Guide is also an invaluable resource for those preparing for their first role in AI or data science, as well as junior-level practicing professionals seeking to review the fundamentals with a convenient desk reference.ABOUT THE AUTHORDARIO CABIANCA is the AWS Practice Director at Trace3—a leading IT consultancy and AWS Advanced Consulting Partner—offering AI, data, cloud and cybersecurity solutions. He is the author of Google Cloud Platform (GCP) Professional Cloud Security Engineer Certification Companion and Google Cloud Platform (GCP) Professional Cloud Network Engineer Certification Companion. Dario has collaborated with leading global consulting firms and enterprises for over 20 years, delivering impactful solutions in enterprise architecture, cloud computing, cybersecurity, and artificial intelligence. ContentsChapter 1Introduction to Machine Learning1Understanding Artificial Intelligence2Data, Information, Knowledge3Data3Information4Knowledge5Understanding Machine Learning6ML Lifecycle6Define ML Problem6Collect Data8Process Data8Choose Algorithm8Train Model9Evaluate Model9Deploy Model9Derive Inference11Monitor Model11ML Concepts11Features11Target Variable12Optimization Problem12Objective Function13ML Algorithms vs. ML Models13Differences Between ML and AI14Understanding Deep Learning16Introduction to Neural Networks16Structure of a Neural Network16Neuron16Input Layer18Hidden Layers18Output Layer18How Neural Networks Work18Neural Networks Types19Artificial Neural Networks20Deep Neural Networks20Convolutional Neural Networks20Recurrent Neural Networks20Differences Between DL and ML21Case Studies21Case Study 1: Mobileye’s Autonomous Driving Technology21Case Study 2: Leidos’ Healthcare ML Applications21Summary22Exam Essentials23Review Questions24Chapter 2Data Ingestion and Storage27Introducing Ingestion and Storage28Ingesting and Storing Data28Data Formats and Ingestion Techniques31Choosing AWS Ingestion Services34Amazon Data Firehose35Amazon Kinesis Data Streams35Amazon Managed Streaming for Apache Kafka (MSK)36Amazon Managed Service for Apache Flink38AWS DataSync39AWS Glue40Choosing AWS Storage Services41Amazon Simple Storage Service (S3)42Amazon Elastic File System (EFS)45Amazon FSx for Lustre47Amazon FSx for NetApp ONTAP49Amazon FSx for Windows File Server50Amazon FSx for OpenZFS51Amazon Elastic Block Storage (EBS)51Amazon Relational Database Service (RDS)52Amazon DynamoDB52Troubleshooting53Summary54Exam Essentials55Review Questions57Chapter 4Model Selection61Understanding AWS AI Services63Vision64Amazon Rekognition64Amazon Textract65Speech66Amazon Polly66Amazon Transcribe67Language67Amazon Translate67Amazon Comprehend68Chatbot69Amazon Lex69Recommendation70Amazon Personalize70Generative AI71Amazon Bedrock71Developing Models with Amazon SageMaker Built-in Algorithms81Supervised ML Algorithms81General Regression and Classification Algorithms83Recommendation102Forecasting104Unsupervised ML Algorithms105Clustering105Dimensionality Reduction113Topic Modeling119Anomaly Detection121Textual Analysis123BlazingText124Sequence-to-Sequence126Image Processing127Image Classification127Object Detection128Semantic Segmentation130Criteria for Model Selection131Summary132Exam Essentials133Review Questions136Chapter 5Model Training and Evaluation141Training143Local Training144Remote Training145Distributed Training146Monitoring Training Jobs147Debugging Training Jobs148Hyperparameter Tuning149Model Parameter and Hyperparameter151Exploring the Hyperparameter Space with Amazon SageMaker AI Automatic Model Tuning152Evaluation Metrics154Classification Problem Metrics154Regression Problem Metrics160Hyperparameter Tuning Techniques164Manual Search164Grid Search165Random Search165Bayesian Search165Multi-algorithm Optimization166Managing Bias and Variance Trade-Off166Addressing Overfitting and Underfitting168Underfitting168Overfitting170Regularization170Advanced Techniques173Model Performance Evaluation173Performance Evaluation Methods173K-Fold Cross-Validation174Random Train-Test Split175Holdout Set176Bootstrap176Evaluating Foundation Models177Automatic Evaluations177Human Evaluations177LLM-as-a-Judge177Programmatic Evaluations177Knowledge Base Evaluations177Deep Dive Model Tuning Example177Summary185Exam Essentials187Review Questions190Chapter 6Model Deployment and Orchestration193AWS Model Deployment Services194Deploying AI Services195Amazon Rekognition196Amazon Textract197Amazon Polly197Amazon Transcribe198Amazon Comprehend198Amazon Lex199Amazon Personalize199Amazon Bedrock200Deploying Your Model201Infrastructure Selection Considerations202Managed Model Deployments203Unmanaged Model Deployments211Optimizing ML Models for Edge Devices216Advanced Model Deployment Techniques218Autoscaling Endpoints218Deployment and Testing Strategies221Blue/Green Deployment221Orchestrating ML Workflows227Introducing Amazon SageMaker Pipelines228Code Repository and Version Control228Introducing Amazon SageMaker Model Registry229CI/CD230MLOps Orchestration230AWS Step Functions231Amazon Managed Workflows for Apache Airflow232Choosing an Orchestration Tool232Automating Model Building and Deployment233Define the Workflow Steps234Create and Configure Pipeline Steps234Define the Pipeline237Set Up Triggers and Schedules237Execute the Pipeline238Key Considerations238Deep-Dive Model Deployment Example238Summary247Exam Essentials248Review Questions250Chapter 7Model Monitoring and Cost Optimization253Monitoring Model Inference255Drifts in Models256Techniques to Monitor Data Quality and Model Performance257Monitoring Workflow259Design Principles for Monitoring261Operational Excellence Pillar261Security Pillar262Reliability Pillar263Performance Efficiency Pillar264Cost Optimization Pillar266Sustainability Pillar269Monitoring Infrastructure and Cost270Monitoring and Observability Services271Amazon CloudWatch Logs Insights272Amazon EventBridge273AWS CloudTrail274AWS X-Ray274Amazon GuardDuty275Amazon Inspector276AWS Security Hub277Cost Tracking and Optimization Services278AWS Cost Explorer278AWS Cost and Usage Reports279AWS Trusted Advisor280AWS Budgets280Pricing Models281Summary283Exam Essentials284Review Questions286Chapter 8Model Security289Security Design Principles290Implement a Strong Identity Foundation290Apply Security at all Layers291Enable Traceability292Protect Your Data (At-Rest, In-Use, and In-Transit)293Automate Security Processes294Prepare for Security Events295Securing AWS Services295Securing Identities with IAM296Identities296Access Policies302Securing Infrastructure and Data305Network Isolation with VPC305Private Connectivity306Data Protection306Monitoring and Auditing307Ensuring Compliance307Summary308Exam Essentials309Review Questions311
Preventing Bluetooth and Wireless Attacks in IoMT Healthcare Systems
A TIMELY TECHNICAL GUIDE TO SECURING NETWORK-CONNECTED MEDICAL DEVICESIn Preventing Bluetooth and Wireless Attacks in IoMT Healthcare Systems, Principal Security Architect for Connection, John Chirillo, delivers a robust and up-to-date discussion of securing network-connected medical devices. The author walks you through available attack vectors, detection and prevention strategies, probable future trends, emerging threats, and legal, regulatory, and ethical considerations that will frequently arise for practitioners working in the area. Following an introduction to the field of Internet of Medical Things devices and their recent evolution, the book provides a detailed and technical series of discussions—including common real-world scenarios, examples, and case studies—on how to prevent both common and unusual attacks against these devices. INSIDE THE BOOK:* Techniques for using recently created tools, including new encryption methods and artificial intelligence, to safeguard healthcare technology* Explorations of how the rise of quantum computing, 5G, and other new or emerging technology might impact medical device security* Examinations of sophisticated techniques used by bad actors to exploit vulnerabilities on Bluetooth and other wireless networksPerfect for cybersecurity professionals, IT specialists in healthcare environments, and IT, cybersecurity, or medical researchers with an interest in protecting sensitive personal data and critical medical infrastructure, Preventing Bluetooth and Wireless Attacks in IoMT Healthcare Systems is a timely and comprehensive guide to securing medical devices. JOHN CHIRILLO is an accomplished, published programmer and author with decades of hands-on experience. He’s a leading expert on medical device security who speaks regularly on regulatory compliance, risk assessment and mitigation, and incident management. Preface xxviiForeword xxixPART I FOUNDATION 1CHAPTER 1 INTRODUCTION TO IOMT IN HEALTHCARE 3What Is IoMT in Healthcare? 4Impact of IoMT on Healthcare 5How IoMT Works in Healthcare and Its Applications 16Challenges and Considerations in IoMT Adoption 17Best Practices for IoMT Security 18Future Trends in IoMT 20Key Takeaways of IoMT in Healthcare 22CHAPTER 2 THE EVOLVING LANDSCAPE OF WIRELESS TECHNOLOGIES IN MEDICAL DEVICES 23Overview of Wireless Technologies in Medical Devices 24Benefits of Wireless Technologies in Medical Devices 29Introduction to Risks in the Applications ofWireless Integration Challenges and Considerations 38Emerging Wireless Trends and Future Directions 40Regulatory Landscape for Wireless Medical Devices 41Best Practices for Wireless Technology Implementation 43Key Takeaways of Wireless Technologies in Healthcare 44CHAPTER 3 INTRODUCTION TO BLUETOOTH AND WI-FI IN HEALTHCARE 46Bluetooth Communication in Healthcare 47Wi-Fi Communication in Healthcare 52Overview of Bluetooth and Wi-Fi Security Risks 58Key Takeaways of Bluetooth and Wi-Fi 64PART II ATTACK VECTORS 65CHAPTER 4 BLUETOOTH VULNERABILITIES, TOOLS, AND MITIGATION PLANNING 67Introduction to Bluetooth Security 68Common Bluetooth Vulnerabilities 71Bluetooth Hacking Tools 82Mitigating Bluetooth Vulnerabilities 101Key Takeaways of Bluetooth Vulnerabilities and Exploits 103CHAPTER 5 WI-FI AND OTHER WIRELESS PROTOCOL VULNERABILITIES 104INTRODUCTION TO WI-FI SECURITY 105Building a Resilient Network Architecture with Segmentation 107Strong Authentication and Access Control 108Wi-Fi 6/6E Security Solutions 110Common Wi-Fi Vulnerabilities with Examples and Case Studies 111Wi-Fi Hacking Tools 120Bettercap 122coWPAtty 125Fern Wi-Fi Cracker 128Hashcat 131Wifite 134Kismet 138Reaver 141Storm 145WiFi Pineapple 146WiFi-Pumpkin 149Wifiphisher 151Wireshark 153Modern Wireless Operational Guide for Healthcare Compliance 156Key Takeaways of Wi-Fi Vulnerabilities and Exploits 159CHAPTER 6 MAN-IN-THE-MIDDLE ATTACKS ON MEDICAL DEVICES 161Understanding Medical Device Man-in-the-Middle Attacks 162Exploits and Other Potential Impacts of MITM Attacks on Medical Devices 167Challenges in Securing Medical Devices 168Mitigation Strategies for Healthcare Organizations 169Implement Robust Device Authentication 171Deploy Network Segmentation and Isolation 174Ensure Regular Updates and Patching 176Deploy Advanced Monitoring and Intrusion Detection 179Conduct Training and Awareness Programs 182Collaborate with Vendors to Enhance Device Security 186Key Benefits of a Comprehensive Mitigation Strategy 190Key Takeaways of Man-in-the-Middle Attacks on Medical Devices 194CHAPTER 7 REPLAY AND SPOOFING ATTACKS IN IOMT 196Understanding Replay Attacks in IoMT 197How Replay Attacks Work in IoMT Systems 197Implications of Replay Attacks in Healthcare 198Use Case of a Replay Attack on an Infusion Pump 199Other Examples of Replay Attacks in IoMT 200Strategies for Mitigation of Replay Attacks 200What Is a Spoofing Attack in IoMT? 202Mitigation Strategies for Spoofing Attacks in IoMT 205Key Takeaways of Replay and Spoofing Attacks in IoMT 206CHAPTER 8 DENIAL OF SERVICE IN WIRELESS MEDICAL NETWORKS 208Understanding DoS Attacks 208Common Types of DoS Attacks, Targets, and Device Impact 209Impact of DoS Attacks on Healthcare Operations 213Common Vulnerabilities That Enable DoS Attacks in Wireless Medical Networks 214Mitigation Strategies for Denial of Service Attacks 217Key Takeaways from DoS in Wireless Medical Networks 224PART III CASE STUDIES AND REAL-WORLD SCENARIOS 227CHAPTER 9 PACEMAKER HACKING 229Understanding Pacemaker Technology and Its Risks and Limitations 230How Does the Heart Normally Function? 230What Is a Pacemaker? 230Understanding Vulnerabilities in Pacemakers in Today’s Connected World 233Real-World Case Studies and Impact 235Strategies and Technologies to Mitigate Pacemaker Cybersecurity Risks 242More on Consequences of Pacemaker Hacking 244Key Takeaways from Pacemaker Hacking 245CHAPTER 10 INSULIN PUMP VULNERABILITIES AND EXPLOITS 247Understanding Insulin Pumps and Their Vulnerabilities 249Implications and Real-World Scenarios of Insulin Pump Exploits 258Education and Training for Patients and Healthcare Providers 261Key Takeaways from Insulin Pump Vulnerabilities and Exploits 261CHAPTER 11 ATTACK VECTOR TRENDS AND HOSPITAL NETWORK BREACHES WITH IOMT DEVICES 263Understanding the IoMT Risk Landscape 264Attack Vector Trends and Landscape 268Malware Analysis for Digital Forensics Investigations 272Key Takeaways from Hospital Network Breaches with IoMT Devices 280CHAPTER 12 WEARABLE MEDICAL DEVICE SECURITY CHALLENGES 282The Rise of Wearable Medical Devices 282Security Challenges of Wearable Medical Devices 283New Trends and Threats in Wearable Device Security 289Proactive Measures for Mitigating Wearable Device Threats 290How AI Can Help 291Key Takeaways from Security Challenges of Wearable Medical Devices 294PART IV DETECTION AND PREVENTION 295CHAPTER 13 INTRUSION DETECTION AND PREVENTION FOR IOMT NETWORKS 297Introduction to Intrusion Detection and PreventionSystems for IoMT 297Understanding IoMT Ecosystems 299What Is Intrusion Detection and Prevention in IoMT Environments? 299Case Study: Implementing IDPS in a Healthcare Environment 302IDPS Solutions 304Best Practices for IoMT IDPS Deployment 331Modern Innovations in IoMT IDS 333Emerging Trends in IoMT IDS 336Key Takeaways from IDPS for IoMT Networks 336CHAPTER 14 MACHINE LEARNING APPROACHES TO WIRELESS ATTACK DETECTION 338Introduction to Machine Learning for WirelessMachine Learning Feature Engineering for Wireless Attack Detection 342Types of Machine Learning Techniques 344Machine Learning Applications in Healthcare and IoMT 350Challenges in Applying ML to Wireless Security in IoMT 352Future Directions of Machine Learning for Attack Detection in Healthcare 356Machine Learning Case Studies in Healthcare 362Key Takeaways from Machine Learning Approaches to Wireless Attack Detection 364CHAPTER 15 SECURE COMMUNICATION PROTOCOLS FOR MEDICAL DEVICES 366Importance of Secure Communication in Medical Devices 366Key Security Requirements for Medical Device Communication 368Secure Communication Protocols for Medical Devices 371Encryption Algorithms and Key Management 373Secure Device Pairing and Onboarding 377Out-of-Band Authentication Methods 377Regulatory Compliance and Standards 379Challenges in Implementing Secure Communication Protocols 381Best Practices for Secure Medical Device Communication 383Emerging Technologies and Future Trends 384Secure Communication Strategies 386Ethical Considerations 387Key Takeaways from Secure Communication Protocols for Medical Devices 389CHAPTER 16 BEST PRACTICES FOR IOMT DEVICE SECURITY 391Endpoint Security Best Practices 392Network Security Best Practices 393Perimeter Security Best Practices 394Cloud Security Best Practices 395Network Segmentation 396Strong Authentication and Access Controls 397Regular Updates and Patching 401AI-Powered Monitoring and Analytics 403Zero Trust Security Model 405Encryption and Data Protection 407Asset Inventory and Management 409Vendor Management and Third-Party Risk Assessment 411Compliance with Regulatory Standards 414Continuous Monitoring and Incident Response 417Employee Training and Awareness 420Secure Device Onboarding and Decommissioning 422Physical Security Measures 425Backup and Recovery 428Secure Communication Protocols 430Data Minimization and Retention Policies 433Cybersecurity Insurance 435Regular Security Audits 436Key Takeaways of Best Practices for IoMT Device Security 438PART V FUTURE TRENDS AND EMERGING THREATS 441CHAPTER 17 5G AND BEYOND AND IMPLICATIONS FOR IOMT SECURITY 443Introduction to 5G and Beyond Technologies 443Impact of 5G on IoMT 445Security Implications for IoMT 447Regulatory Considerations 450Future Research Directions 455Industry Collaboration and Knowledge Sharing 456Key Takeaways of 5G and Beyond and Implications for IoMT Security 458CHAPTER 18 QUANTUM COMPUTING IN MEDICAL DEVICE SECURITY 459Fundamentals of Quantum Computing 459Potential Applications in Medical Device Security 461Challenges Posed by Quantum Computing 462Quantum Attack on IoMT Firmware 463Quantum-Resistant Cryptography for Medical Devices 466Quantum Sensing and Metrology in Medical Devices 467Quantum-Safe Network Protocols for Medical Devices 468Regulatory and Standardization Efforts 469Ethical and Privacy Considerations 470Future Research Directions 472Preparing the Healthcare Industry for the Quantum Era 473Key Takeaways from Quantum Computing in Medical Device Security 475CHAPTER 19 AI-DRIVEN ATTACKS AND DEFENSES IN HEALTHCARE 476Types of AI-Driven Attacks in Healthcare 476Impact of AI-Driven Attacks on Healthcare 478AI-Driven Defenses in Healthcare 480Challenges in Implementing AI-Driven Defenses 484Future Trends in AI-Driven Healthcare Cybersecurity 486Best Practices for Healthcare Organizations 488Key Takeaways from AI-Driven Attacks and Defenses in Healthcare 489PART VI LEGAL AND ETHICAL CONSIDERATIONS 491CHAPTER 20 REGULATORY FRAMEWORKS FOR IOMT SECURITY 493Key Regulatory Bodies and Frameworks 493Legal Considerations 495Ethical Considerations 498Challenges in Regulatory Framework Development 500Best Practices for Regulatory Compliance 502Future Trends in IoMT Security Regulation 504Examples of Benefits from Regulation Implementation 505Recommendations for Stakeholders 507Key Takeaways from Regulatory Frameworks for IoMT Security 509CHAPTER 21 GUIDELINES FOR ETHICAL HACKING IN HEALTHCARE 510Importance of Ethical Hacking in Healthcare 510Scope of Ethical Hacking in Healthcare 512Legal and Regulatory Considerations 513Ethical Boundaries and Guidelines 515Best Practices for Ethical Hacking in Healthcare 516Challenges in Healthcare Ethical Hacking 519Emerging Trends and Future Considerations 520Training and Certification for Healthcare Ethical Hackers 521Case Studies 523Key Takeaways from Ethical Hacking in Healthcare 524Conclusion 525Index 527
Navigating Misinformation
Informed navigation of misinformation on social media constitutes a major challenge. The field of Human-Computer Interaction (HCI) suggests digital misinformation interventions as user-centered countermeasures. This book clusters (1) existing misinformation interventions within a taxonomy encompassing designs, interaction types, and timings. The book demonstrates that current research mostly addresses higher-educated participants, and targets Twitter/X and Facebook. It highlights trends toward comprehensible interventions in contrast to top-down approaches. The findings informed (2) the design, implementation, and evaluation of simulated apps for TikTok, voice messages, and Twitter/X as indicator-based interventions. Therefore, (3) the book identified misinformation indicators for various modalities that were perceived as comprehensible.The book empirically demonstrates that (4) indicator-based interventions are positively received due to their transparency. However, they also come with challenges, such as users' blind trust and lack of realistic assessments of biases. This research outlines chances and implications for future research.
Python für Kinder
Python für Kinder – Spielend leicht programmieren lernen Dein Kind liebt Computer und hat Spaß daran, Dinge auszuprobieren? Es fragt sich, wie Spiele oder Apps eigentlich funktionieren, und möchte selbst kreativ werden? Dann ist das Buch "Python für Kinder" genau das Richtige! Florian Dalwigk, ein erfolgreicher YouTuber mit über 100.000 Abonnenten, bringt mit diesem Buch die Welt der Programmierung auf spielerische Weise direkt zu euch nach Hause. Dieses Buch bietet einen leichten Einstieg in die Welt der Python-Programmierung, selbst für absolute Anfänger. Florian erklärt Schritt für Schritt, wie dein Kind spannende Projekte umsetzen kann – von Spielen bis hin zu kreativen Übungen, die nicht nur Spaß machen, sondern auch die Grundlagen der Informatik vermitteln. Das erwartet dein Kind in diesem Buch: - Einfacher Einstieg: Dank klarer Erklärungen und leicht verständlicher Beispiele kann dein Kind ohne Vorkenntnisse loslegen. - Python kinderleicht installieren: Ob auf Mac, Windows oder online – dein Kind lernt, wie Python eingerichtet wird, um sofort mit den Projekten zu starten. - Bewegte Schildkröten: Mit Python können Schildkröten auf dem Bildschirm laufen und zeichnen – ein kreativer Weg, die Grundlagen der Programmierung zu verstehen. - Spiele programmieren: Mit spaßigen Projekten wie eigenen Spielen lernt dein Kind spielerisch wichtige Konzepte wie Schleifen und Bedingungen. - Grundlagen der Informatik: Was sind Algorithmen, wie funktioniert ein Computer, und warum sind Programme so wichtig? Dein Kind wird es bald wissen! Perfekt für Eltern und Kinder: - Gemeinsames Lernen: Auch Eltern ohne Vorkenntnisse können zusammen mit ihren Kindern die Projekte ausprobieren und so wertvolle Zeit gemeinsam verbringen. - Einfach loslegen: Mit leicht verständlichen Anleitungen und spannenden Aufgaben können Kinder sofort starten – ohne lange Vorbereitung. Florian Dalwigk – Der perfekte Begleiter ins Programmieren Mit seinem Bestseller "Python für Einsteiger" hat Florian Dalwigk bereits bewiesen, dass er komplexe Themen anschaulich und für alle verständlich machen kann. Jetzt bringt er dieses Wissen in "Python für Kinder" kindgerecht auf den Punkt. Werde Teil der digitalen Zukunft! Warum warten? Mit "Python für Kinder" kann dein Kind schon heute anfangen, die Welt der Technik spielerisch zu entdecken. Bestell jetzt das Buch und erlebe, wie viel Spaß Programmieren machen kann!
Konstruierte Wahrheiten
In einer Welt, in der immer mehr Fake News verbreitet werden, wird es zunehmend schwieriger, Wahrheit und Lüge, Wissen und Meinung auseinanderzuhalten. Desinformationskampagnen werden nicht nur als ein politisches Problem wahrgenommen, vielmehr geht es in der Fake-News-Debatte auch um fundamentale philosophische Fragen: Was ist Wahrheit? Wie können wir sie erkennen? Gibt es so etwas wie objektive Fakten oder ist alles sozial konstruiert? Dieses Buch erklärt, wie Echokammern und alternative Weltbilder entstehen, es macht das postfaktische Denken für die gegenwärtige Wahrheitskrise verantwortlich und zeigt, wie wir einem drohenden Wahrheitsrelativismus entgehen können.THOMAS ZOGLAUER (Dr. phil. habil.) lehrt Philosophie an der Brandenburgischen Technischen Universität Cottbus-Senftenberg und an der Graduierten-Akademie der Universität Stuttgart und ist Autor zahlreicher Bücher zur Technikphilosophie und angewandten Ethik.Filterblasen und Echokammern.- Verschwörungstheorien.- Fake News.- Epistemologie des Postfaktischen.- Wahrheitstheorien.- Information und Wissen.
Edge Computing
UNDERSTAND THE COMPUTING TECHNOLOGY THAT WILL POWER A CONNECTED FUTUREThe explosive growth of the Internet of Things (IoT) in recent years has revolutionized virtually every area of technology. It has also driven a drastically increased demand for computing power, as traditional cloud computing proved insufficient in terms of bandwidth, latency, and privacy. Edge computing, in which data is processed at the edge of the network, closer to where it’s generated, has emerged as an alternative which meets the new data needs of an increasingly connected world. Edge Computing offers a thorough but accessible overview of this cutting-edge technology. Beginning with the fundamentals of edge computing, including its history, key characteristics, and use cases, it describes the architecture and infrastructure of edge computing and the hardware that enables it. The book also explores edge intelligence, where artificial intelligence is integrated into edge computing to enable smaller, faster, and more autonomous decision-making. The result is an essential tool for any researcher looking to understand this increasingly ubiquitous method for processing data. Edge Computing readers will also find:* Real-world applications and case studies drawn from industries including healthcare and urban development* Detailed discussion of topics including latency, security, privacy, and scalability* A concluding summary of key findings and a look forward at an evolving computing landscapeEdge Computing is ideal for students, professionals, and enthusiasts looking to understand one of technology’s most exciting new paradigms. LANYU XU, PHD, is Assistant Professor in the Department of Computer Science and Engineering, Oakland University, Michigan, where she leads the Edge Intelligence System Laboratory. Her research intersects edge computing and deep learning, emphasizing the development of efficient edge intelligence systems. Her work explores optimization frameworks, intelligent systems, and AI applications to address challenges in efficiency and real-world applicability of edge systems across various domains. WEISONG SHI, PHD, is an Alumni Distinguished Professor and Chair of the Department of Computer and Information Sciences at the University of Delaware, where he leads the Connected and Autonomous Research Laboratory. He is an internationally renowned expert in edge computing, autonomous driving, and connected health. His pioneer paper, “Edge Computing: Vision and Challenges,” has been cited more than 8000 times in eight years. He is an IEEE Fellow.
Protecting and Mitigating Against Cyber Threats
THE BOOK PROVIDES INVALUABLE INSIGHTS INTO THE TRANSFORMATIVE ROLE OF AI AND ML IN SECURITY, OFFERING ESSENTIAL STRATEGIES AND REAL-WORLD APPLICATIONS TO EFFECTIVELY NAVIGATE THE COMPLEX LANDSCAPE OF TODAY’S CYBER THREATS.Protecting and Mitigating Against Cyber Threats delves into the dynamic junction of artificial intelligence (AI) and machine learning (ML) within the domain of security solicitations. Through an exploration of the revolutionary possibilities of AI and ML technologies, this book seeks to disentangle the intricacies of today’s security concerns. There is a fundamental shift in the security soliciting landscape, driven by the extraordinary expansion of data and the constant evolution of cyber threat complexity. This shift calls for a novel strategy, and AI and ML show great promise for strengthening digital defenses. This volume offers a thorough examination, breaking down the concepts and real-world uses of this cutting-edge technology by integrating knowledge from cybersecurity, computer science, and related topics. It bridges the gap between theory and application by looking at real-world case studies and providing useful examples. Protecting and Mitigating Against Cyber Threats provides a roadmap for navigating the changing threat landscape by explaining the current state of AI and ML in security solicitations and projecting forthcoming developments, bringing readers through the unexplored realms of AI and ML applications in protecting digital ecosystems, as the need for efficient security solutions grows. It is a pertinent addition to the multi-disciplinary discussion influencing cybersecurity and digital resilience in the future. Readers will find in this book:* Provides comprehensive coverage on various aspects of security solicitations, ranging from theoretical foundations to practical applications;* Includes real-world case studies and examples to illustrate how AI and machine learning technologies are currently utilized in security solicitations;* Explores and discusses emerging trends at the intersection of AI, machine learning, and security solicitations, including topics like threat detection, fraud prevention, risk analysis, and more;* Highlights the growing importance of AI and machine learning in security contexts and discusses the demand for knowledge in this area.AUDIENCECybersecurity professionals, researchers, academics, industry professionals, technology enthusiasts, policymakers, and strategists interested in the dynamic intersection of artificial intelligence (AI), machine learning (ML), and cybersecurity. SACHI NANDAN MOHANTY, PHD is an associate professor at the School of Computer Science and Engineering, VIT-AP University, Amaravati, Andhra Pradesh, India, He has published 60 articles in journals of international repute, edited 24 books, and serves as an editor for several international journals. His research interests include data mining, big data analysis, cognitive science, fuzzy decision making, brain-computer interface, cognition, and computational intelligence. SUNEETA SATPATHY, PHD is an associate professor in the Center for Artificial Intelligence and Machine Learning at Siksha O. Anusandhan University, India. She has published several papers in international journals and conferences of repute and edited numerous books. Her research interests include computer forensics, cyber security, data fusion, data mining, big data analysis, and decision mining. MING YANG, PHD is a professor in the College of Computing and Software Engineering at Kennesaw State University, Georgia, USA and serves as a consultant for many companies. He has published over 70 peer-reviewed conference and journal papers and book chapters in addition to serving as an editor for several journals. His research interests include image processing, multimedia communication, computer vision, and machine learning. D. KHASIM VALI, PHD is an assistant professor in the School of Computer Science and Engineering, the Vellore Institute of Technology, Andhra Pradesh University, India, with over 18 years of teaching experience. He has 21 international publications to his credit and is a life member of ISTE and IETE. His research interests include artificial intelligence, machine learning, and deep learning.
Artificial Intelligence in Neurological Disorders
THE BOOK GIVES INVALUABLE INSIGHTS INTO HOW ARTIFICIAL INTELLIGENCE IS REVOLUTIONIZING THE MANAGEMENT AND TREATMENT OF NEUROLOGICAL DISORDERS, EMPOWERING YOU TO STAY AHEAD IN THE RAPIDLY EVOLVING LANDSCAPE OF HEALTHCARE.Embark on a groundbreaking exploration of the intersection between cutting-edge technology and the intricate complexities of neurological disorders. Artificial Intelligence in Neurological Disorders: Management, Diagnosis and Treatment comprehensively introduces how artificial intelligence is becoming a vital ally in neurology, offering unprecedented advancements in management, diagnosis, and treatment. As the digital age converges with medical expertise, this book unveils a comprehensive roadmap for leveraging artificial intelligence to revolutionize neurological healthcare. Delve into the core principles that underpin AI applications in the field by exploring intricate algorithms that enhance the precision of diagnosis and how machine learning not only refines the understanding of neurological disorders but also paves the way for personalized treatment strategies tailored to individual patient needs. With compelling case studies and real-world examples, the realms of neuroscience and artificial intelligence converge, illustrating the symbiotic relationship that holds the promise of transforming patient care. Readers of this book will find it:* Provides future perspectives on advancing artificial intelligence applications in neurological disorders;* Focuses on the role of AI in diagnostics, delving into how advanced algorithms and machine learning techniques contribute to more accurate and timely diagnosis of neurological disorders;* Emphasizes practical integration of AI tools into clinical practice, offering insights into how healthcare professionals can leverage AI technology for more effective patient care;* Recognizes the interdisciplinary nature of neurology and AI, bridging the gap between these fields, making it accessible to healthcare professionals, researchers, and technologists;* Addresses the ethical implications of AI in healthcare, exploring issues such as data privacy, bias, and the responsible deployment of AI technologies in the neurological domain.AUDIENCEResearchers, scientists, industrialists, faculty members, healthcare professionals, hospital management, biomedical industrialists, engineers, and IT professionals interested in studying the intersection of AI and neurology. RISHABHA MALVIYA, PHD is an associate professor in the Department of Pharmacy in the School of Medical and Allied Services at Galgotias University with over 13 years of research experience. He has authored 57 books, 58 chapters, and over 150 research papers for national and international journals of repute, as well as 51 patents. His areas of interest include formulation optimization, nanoformulation, targeted drug delivery, localized drug delivery, and characterization of natural polymers as pharmaceutical excipients. SURAJ KUMAR is an assistant professor in the School of Medical and Allied Sciences at Galgotias University. He has published over ten papers in international journals and five book chapters. His research interests include sustainable polymeric fibers, nanoparticles, and controlled drug delivery. ADITYA SUSHIL SOLANKE, PHD is a Senior Resident in Neurosurgery at Byramjee Jeejeebhoy Government Medical College and Sassoon Hospital, India. He completed his Bachelor of Medicine, Bachelor of Surgery, and Masters in General Surgery from the Government Medical College in Nagpur. PRIYANSHI GOYAL, M.PHARM is an assistant professor in the School of Pharmacy at Mangalayatan University. She has authored seven review articles and two books and attended 14 national and international conferences and webinars. Her area of interest is treatment strategies for neurological disorders. KAPIL CHAUHAN, PHD is an emergency physician at Max Hospital in Dehradun, India. He completed his Bachelor of Medicine and Bachelor of Surgery from Teerthanker Mahavir Medical College and Masters in Emergency Medicine from Max Hospital.
Mathematics for Digital Science 3
Over the past century, advancements in computer science have consistently resulted from extensive mathematical work. Even today, innovations in the digital domain continue to be grounded in a strong mathematical foundation. To succeed in this profession, both today's students and tomorrow’s computer engineers need a solid mathematical background.The goal of this book series is to offer a solid foundation of the knowledge essential to working in the digital sector. Across three volumes, it explores fundamental principles, digital information, data analysis, and optimization. Whether the reader is pursuing initial training or looking to deepen their expertise, the Mathematics for Digital Science series revisits familiar concepts, helping them refresh and expand their knowledge while also introducing equally essential, newer topics.GÉRARD-MICHEL COCHARD is Professor Emeritus at Université de Picardie Jules Verne, France, where he has held various senior positions. He has also served at the French Ministry of Education and the CNAM (Conservatoire National des Arts et Métiers). His research is conducted at the Eco-PRocédés, Optimisation et Aide à la Décision (EPROAD) laboratory, France.MHAND HIFI is Professor of Computer Science at Université de Picardie Jules Verne, France, where he heads the EPROAD UR 4669 laboratory and manages the ROD team. As an expert in operations research and NP-hard problem-solving, he actively contributes to numerous international conferences and journals in the field.
The AI Act Handbook
Compliant Usage of Artificial Intelligence in the Private and Public Sectors- Detailed overview of the AI Act- Impact of the AI Act on various areas (including fi nance, employment law, advertising and administration)- Related areas of law (data protection, IP and IT law)- Practical overview of AI governance, risk and compliance in companies- Information on standards, norms and certificationsBy experts for practitioners – with this handbook, you can prepare yourself for the requirements of the European AI Act in a practical and compliant manner. Get comprehensive information on the effects on the various application fields of artificial intelligence in the private and public sectors. After a brief introduction to the history and technology of AI, you will receive a detailed subsumption of the content of the AI Act based on the various risk categories. Subsequently, areas of law closely related to the use of AI, in particular data protection, IP and IT law, will be dealt with in detail. By providing case studies, the book shares insights about the impact of the AI Act on various areas such as autonomous driving, work, critical infrastructure, medicine, insurance, etc. The correlation with the areas of law relevant to these areas will also be considered. A practical overview of the topic of AI governance, risk and compliance (GRC) in companies, tips on the application of guidelines and governance frameworks, implementation ideas for trustworthy AI as well as standards, norms and certifications complement the book.The TEAM OF AUTHORS consists of lawyers specializing in IT and data protection law and the use of AI. It includes, among others, one of Austria's representative in the AI Act negotiations at EU Council level and the founder of the Austrian association Women in AI.FROM THE CONTENTS- What Is AI and How Do Data Science and Data Analytics Differ?- Geopolitics of Artificial Intelligence- AI Act: Rights and Obligations- Data Protection- Intellectual Property- AI and IT Contract Law- Private Sector- Public Sector- Ethics- Governance in the Company
The AI Act Handbook
THE AI ACT HANDBOOK // - Detailed overview of the AI Act - Impact of the AI Act on various areas (including fi nance, employment law, advertising and administration) - Related areas of law (data protection, IP and IT law) - Practical overview of AI governance, risk and compliance in companies - Information on standards, norms and certifications By experts for practitioners – with this handbook, you can prepare yourself for the requirements of the European AI Act in a practical and compliant manner. Get comprehensive information on the effects on the various application fields of artificial intelligence in the private and public sectors. After a brief introduction to the history and technology of AI, you will receive a detailed subsumption of the content of the AI Act based on the various risk categories. Subsequently, areas of law closely related to the use of AI, in particular data protection, IP and IT law, will be dealt with in detail. By providing case studies, the book shares insights about the impact of the AI Act on various areas such as autonomous driving, work, critical infrastructure, medicine, insurance, etc. The correlation with the areas of law relevant to these areas will also be considered. A practical overview of the topic of AI governance, risk and compliance (GRC) in companies, tips on the application of guidelines and governance frameworks, implementation ideas for trustworthy AI as well as standards, norms and certifications complement the book. The TEAM OF AUTHORS consists of lawyers specializing in IT and data protection law and the use of AI. It includes, among others, one of Austria's representative in the AI Act negotiations at EU Council level and the founder of the Austrian association Women in AI. FROM THE CONTENTS // - What Is AI and How Do Data Science and Data Analytics Differ? - Geopolitics of Artificial Intelligence - AI Act: Rights and Obligations - Data Protection - Intellectual Property - AI and IT Contract Law - Private Sector - Public Sector - Ethics - Governance in the Company
Mobile Systeme
Konzeption, Entwicklung und Betrieb mobiler Systeme. In Erstauflage aus dem Juni 2025.- Erklärt, wie mobile Systeme von Anfang bis Ende entwickelt und genutzt werden.- Vermittelt fundiert die Grundlagen und bietet praktische Einblicke für Studium und Beruf.- Zeigt Strategien und bewährte Methoden, um erfolgreiche und nachhaltige mobile Systeme zu entwickeln.- Stellt neue Entwicklungen, Trends und Technologien vor, die die mobile Welt in Zukunft verändern werden.„Mobile Systeme – Konzeption, Entwicklung und Betrieb“ ist ein umfassendes Grundlagenwerk, das fundiertes Wissen über mobile Technologien, deren Entwicklung und praktischen Einsatz vermittelt. Es erklärt die technischen Grundlagen ebenso wie fortgeschrittene Anwendungsbereiche und deckt den gesamten Lebenszyklus mobiler Systeme ab. Dabei geht es um Themen wie User Experience Design, Entwicklungsstrategien, Application Management, Green IT, XR-Technologien, Mobile Security und Zukunftsthemen wie das Mobile Metaverse. Das Ziel ist es, Studierende der Informatik, Wirtschaftsinformatik und Medieninformatik sowie IT-Manager:innen mit den Besonderheiten, Chancen und Herausforderungen mobiler Ökosysteme vertraut zu machen. Sie sollen lernen, wie man mobile Technologien gezielt und nachhaltig einsetzt. Das Buch bereitet sie auf die Umsetzung innovativer mobiler Projekte in verschiedenen Branchen vor.AUS DEM INHALT- Mobile Systeme: Komponenten und Basistechnologien- Mobile Geräte: Klassen, Technik und Infrastruktur- Mobile Entwicklungsframeworks: Nativ, Cross-Plattform, Hybrid- Mobile User Experience (UX)- Mobile Application Life Cycle Management (ALM), Mobile Application Management (MAM)- Mobile Security: Risiken und Prävention- Mobile KI- Mobile Business: Geschäftsmodelle und globaler Markt- Mobile XR und Mobile Metaverse- Green IT und Green Coding- Technikfolgenabschätzung und soziokulturelle Implikationen
Samba 4 (3. Auflage)
Das Handbuch für Administratoren in 3. Auflage aus Juli 2025.- Ein Buch für alle, die Samba 4 in ihrem Netzwerk einsetzen wollen – sei es als Active Directory Domaincontroller, als Fileserver oder als Cluster.- Es begleitet von Anfang bis Ende den Aufbau einer kompletten Samba-4-Umgebung, aber für bestimmte Dienste erhalten Sie auch Informationen in einzelnen Kapiteln.- In einem neuen Kapitel wird besonders auf das Thema Sicherheit eingegangen. Hier werden die Möglichkeiten des Function Level 2016 besprochen.Dieses Buch gibt Ihnen eine umfangreiche Anleitung für die Einrichtung und den Betrieb einer Samba-4-Umgebung. Ein Schwerpunkt liegt auf der Verwendung von Samba 4 als Active Directory-Domaincontroller.Dabei werden alle Schritte zu deren Verwaltung beschrieben bis hin zur Behebung eines Ausfalls von Domaincontrollern.Ein weiterer Schwerpunkt ist die Verwaltung von Fileservern in einer Netzwerkumgebung, sei es als einzelner Server oder als Cluster. Bei der Einrichtung des Clusters wird dabei komplett auf Open-Source-Software gesetzt. Auch die Einbindung von Clients – von Windows, Linux und macOS – kommt nicht zu kurz.Die Einrichtung von zwei DHCP-Servern für die ausfallsichere DDNS-Umgebung wird mit allen Schritten und Skripten beschrieben. CTDB wird um die Funktion NFS-Server hochverfügbar bereitstellen erweitert. Gerade als Linux-Administrator ist man es gewohnt, alles möglichst über Skripte auf der Kommandozeile durchführen zu können. Deshalb gibt es zu diesem Bereich ein eigenes Kapitel.Auch wird in dieser Auflage das Thema Sicherheit genauer beleuchtet. Dabei geht es um neue Techniken und die Möglichkeiten, die sich daraus ergeben.AUS DEM INHALT- Installation von Domaincontrollern und Fileservern- Einrichten und Testen von Domaincontrollern- Benutzerverwaltung- Grundlagen zu Gruppenrichtlinien- Einrichtung servergespeicherter Profi le und Ordnerumleitung via GPOs- Einrichtung von RODC (Read Only Domain Controller)- Ausfallsichere DDNS-Infrastruktur- Fileserver in der Domäne- Freigaben einrichten und verwalten- Einrichtung des Virusfilters- Clients in der Domäne- Cluster mit CTDB und GlusterFS- Schemaerweiterung- Einrichten von Vertrauensstellungen- Sicherheit- Hilfe zur Fehlersuche- CTDB und NFS als Cluster
Human Capital Analytics
THE BOOK EQUIPS READERS WITH ESSENTIAL INSIGHTS AND STRATEGIES FOR LEVERAGING CUTTING-EDGE TECHNOLOGY AND HUMAN CAPITAL ANALYTICS, ENSURING ORGANIZATIONS THRIVE IN THE ERA OF HUMAN-ROBOT COLLABORATION AND SUSTAINABLE WORKFORCE DEVELOPMENT.Human Capital Analytics: Exploring the HR Spectrum in Industry 5.0 provides a comprehensive investigation into the ever-changing junction of human capital and cutting-edge technology in the context of the Fifth Industrial Revolution. This volume emphasizes the revolutionary role that human capital analytics plays in changing workforce management, talent development, and HR strategies. This position is particularly relevant as organizations transition into Industry 5.0, where human-robot collaboration is the norm. The purpose of this book is to provide a forward-looking perspective on how data-driven human resource strategies will become vital for boosting worker potential and driving organizational success. This is accomplished by integrating developing technologies such as artificial intelligence, machine learning, and robots. Readers will find that this book:* Explores the transformative role of human-robot collaboration, emerging technologies, and strategic HR planning in the context of the Fifth Industrial Revolution;* Provides a comprehensive overview of how predictive analytics and human capital analytics can enhance workforce management, employee engagement, and performance measurement;* Focuses on how HR 5.0 contributes to advancing the United Nations Sustainable Development Goals, driving both social and business impact;* Includes empirical studies, case studies, and real-world examples of implementing Industry 5.0 in organizations;* Provides actionable strategies for HR professionals to navigate the digital transformation of human resource management, incorporating AI, robotics, and data-driven approaches.AUDIENCEHuman resource developers, analysts, professionals, business executives, data scientists, consultants, professors, academics, and students exploring ways to leverage technology for Industry 5.0. DEEPA GUPTA, PHD is a distinguished academician with over 24 years of experience in management studies, currently serving as Dean at GL Bajaj Institute of Management. Her expertise extends to organizational development, corporate relations, and international collaboration. MUKUL GUPTA, PHD is a professor at GL Bajaj Institute of Management with over 25 years of experience in teaching and the corporate sector. His research and expertise in consumer behavior are invaluable for understanding the human-centric aspects of Human Capital Analytics, offering insights into user behavior, adoption, and interaction with AI-driven systems and services. PAWAN BUDHWAR, PHD is a professor of International Human Resource Management and the Associate Deputy Vice Chancellor International at Aston Business School. His research interests include personnel and human resource management, organizational performance, and artificial intelligence. JIM WESTERMAN, PHD is a professor in the Department of Management at Appalachian State University, Boone, North Carolina, USA. His areas of expertise include human resource management, organizational behavior, leadership, sustainable business, and business ethics. RAJESH KUMAR DHANARAJ, PHD is a professor at Symbiosis International University. His research in areas such as machine learning, cyber-physical systems, and wireless sensor networks is directly relevant to the core technologies underpinning computational intelligence in HR. BALAMURUGAN BALUSAMY, PHD is an Associate Dean of Students at Shiv Nadar University with 12 years of teaching experience. He has published over 200 papers and over 80 books in collaboration with professors worldwide. His research interests include engineering education, blockchain, and data sciences.
Blockchain Technology for the Engineering and Service Sectors
BLOCKCHAIN TECHNOLOGY FOR THE ENGINEERING AND SERVICE SECTORS IS ESSENTIAL FOR ANYONE LOOKING TO UNDERSTAND HOW TO HARNESS BLOCKCHAIN TECHNOLOGY, DRIVING INNOVATION AND EFFICIENCY ACROSS VARIOUS SECTORSBlockchain technology stands as one of the most transformative innovations of the 21st century, significantly impacting sectors including finance, manufacturing, and the service industry. Despite its relatively recent emergence, blockchain has the potential to revolutionize a wide array of industries, including tourism, agriculture, healthcare, and automobiles. With the growing interest in decentralized finance, governments and businesses are increasingly investing in research and development to enhance blockchain’s capabilities. As the technology continues to evolve, we can expect even more ground-breaking advancements in the near future. Blockchain Technology for the Engineering and Service Sectors is designed to provide a comprehensive exploration of blockchain technology, divided into two key areas of study. The first section delves into the history and technical evolution of blockchain, tracing its development from the inception of Bitcoin to its integration with other advanced technologies like the Internet of Things. The second section focuses on the frameworks and applications of blockchain, examining its use across various industries, including supply chain management, tourism, banking, healthcare, and automation. Additionally, the book addresses current challenges, emerging trends, and the future potential of blockchain technology. Through a detailed and structured presentation of these topics, readers will gain a deep understanding and expertise in the field of blockchain technology. AUDIENCEResearchers, engineers, and industry professionals working in research and development to explore the possibilities of blockchain.
Artificial Intelligence and Machine Learning for Industry 4.0
THIS BOOK IS ESSENTIAL FOR ANY LEADER SEEKING TO UNDERSTAND HOW TO LEVERAGE INTELLIGENT AUTOMATION AND PREDICTIVE MAINTENANCE TO DRIVE INNOVATION, ENHANCE PRODUCTIVITY, AND MINIMIZE DOWNTIME IN THEIR MANUFACTURING PROCESSES.Intelligent automation is widely considered to have the greatest potential for Industry 4.0 innovations for corporations. Industrial machinery is increasingly being upgraded to intelligent machines that can perceive, act, evolve, and interact in an industrial environment. The innovative technologies featured in this machinery include the Internet of Things, cyber-physical systems, and artificial intelligence. Artificial intelligence enables computer systems to learn from experience, adapt to new input data, and perform intelligent tasks. The significance of AI is not found in its computational models, but in how humans can use them. Consistently observing equipment to keep it from malfunctioning is the procedure of predictive maintenance. Predictive maintenance includes a periodic maintenance schedule and anticipates equipment failure rather than responding to equipment problems. Currently, the industry is struggling to adopt a viable and trustworthy predictive maintenance plan for machinery. The goal of predictive maintenance is to reduce the amount of unanticipated downtime that a machine experiences due to a failure in a highly automated manufacturing line. In recent years, manufacturing across the globe has increasingly embraced the Industry 4.0 concept. Greater solutions than those offered by conventional maintenance are promised by machine learning, revealing precisely how AI and machine learning-based models are growing more prevalent in numerous industries for intelligent performance and greater productivity. This book emphasizes technological developments that could have great influence on an industrial revolution and introduces the fundamental technologies responsible for directing the development of innovative firms. Decision-making requires a vast intake of data and customization in the manufacturing process, which managers and machines both deal with on a regular basis. One of the biggest issues in this field is the capacity to foresee when maintenance of assets is necessary. Leaders in the sector will have to make careful decisions about how, when, and where to employ these technologies. Artificial Intelligence and Machine Learning for Industry 4.0offers contemporary technological advancements in AI and machine learning from an Industry 4.0 perspective, looking at their prospects, obstacles, and potential applications. M. THIRUNAVUKKARASAN, PHD is an assistant professor in the School of Computer Science and Engineering at the Vellore Institute of Technology with over 15 years of research and teaching experience. He has published papers in several international conferences and journals and given keynote speeches at many international conferences. His research interests include Internet of Things (IoT), wireless sensor networks, wireless communication, cloud computing, artificial intelligence, and machine learning. S.A. SAHAAYA ARUL MARY, PHD is a professor in the School of Computer Science and Engineering, Vellore Institute of Technology with over 29 years of teaching and over 15 years of research experience. She has over 70 publications in various reputed journals and conferences and reviewed over 35 papers in addition to mentoring aspiring PhD students. Her research includes software engineering, data mining, machine learning, and artificial intelligence. SATHIYARAJ R., PHD is an assistant professor in the Department of Computer Science and Engineering at Gandhi Institute of Technology and Management University in Bangalore, India. He has contributed to two books, served as lead editor for an additional two books, and published five patents and over 20 articles in various international journals and conferences. His research interests include machine learning, big data analytics, and intelligent systems. G.S. PRADEEP GHANTASALA, PHD is a professor in the Department of Computer Science and Engineering, at Alliance University with over 16 years of academic experience. He has contributed to internationally published books, chapters, patents, and numerous papers in journals and conferences. He also serves as an editor and reviewer for several journals. His research interests include machine learning, deep learning, healthcare applications, and software engineering applications. MUDASSIR KHAN, PHD is an assistant professor in the Department of Computer Science at King Khalid University with over ten years of teaching experience. He has published over 25 papers in international journals and conferences and one patent. He is a member of various technical and professional societies including the Institute for Electrical and Electronics Engineers and Computer Science Teachers Association. His research interests include big data, deep learning, machine learning, eLearning, fuzzy logic, image processing, and cyber security. Preface xiii1 Industry 4.0 and the AI/ML Era: Revolutionizing Manufacturing 1Balusamy Nachiappan, C. Viji, N. Rajkumar, A. Mohanraj, N. Karthikeyan, Judeson Antony Kovilpillai J. and Pellakuri Vidyullatha2 Business Intelligence and Big Data Analytics for Industry 4.0 29N. Rajkumar, C. Viji, Balusamy Nachiappan, A. Mohanraj, N. Karthikeyan, Judeson Antony Kovilpillai J. and Sathiyaraj. R3 "AI-Powered Mental Health Innovations": Handling the Effects of Industry 4.0 on Health 55U Ananthanagu and Pooja Agarwal4 AI ML Empowered Smart Buildings and Factories 87Akey Sungheetha, Rajesh Sharma R., R. Chinnaiyan and G. S. Pradeep Ghantasala5 Applications of Artificial Intelligence and Machine Learning in Industry 4.0 107Tina Babu, Rekha R. Nair and Kishore S.6 Application of Machine Learning in Moisture Content Prediction of Coffee Drying Process 145Tuan M. Le, Thuy T. Tran, Hieu M. Tran and Son V.T. Dao7 Survivable AI for Defense Strategies in Industry 4.0 169Anuradha Reddy, G. S. Pradeep Ghantasala, Ochin Sharma, Mamatha Kurra, Kumar Dilip and Pellakuri Vidyullatha8 Industry 4.0 Based Turbofan Performance Prediction 197M. Sai Narayan, Prajakta P. Nandanwar, Annabathini Lokesh, Bathula Lakshmi Narayana, Varun Revadigar, Judeson Antony Kovilpillai J., Neelapala Anil Kumar and D.M. Deepak Raj9 Industrial Predictive Maintenance for Sustainable Manufacturing 223Mohammed Rihan, Ethiswar Muchherla, Shwejit Shri, Kushagra Jasoria, Judeson Antony Kovilpillai J. and G. S. Pradeep Ghantasala10 Enhanced Security Framework with Blockchain for Industry 4.0 Cyber-Physical Systems, Exploring IoT Integration Challenges and Applications 247P. Vijayalakshmi, B. Selvalakshmi, K. Subashini, Sudhakar G., Kavin Francis Xavier and Pradeepa K.11 Integrating Artificial Intelligence and@Machine Learning for Enhanced Cyber Security in Industry 4.0: Designing a Smart Factory with IoT and CPS 267Kavin Francis Xavier, Subashini K., Vijayalakshmi P., Selvalakshmi B., Sudhakar G. and Pradeepa K.12 Application of AI and ML in Industry 4.0 287V. Vinaya Kumari, G. S. Pradeep Ghantasala, S. A. Sahaaya Arul Mary, M. Thirunavukkarasan and Sathiyaraj. RReferences 303About the Editors 307Index 309
Frictionless Data
YOU’VE HEARD THE PROMISES OF DATA: IF YOU JUST UNLOCK THE HIDDEN INSIGHTS, YOU CAN WIN AN UNFAIR GAME. BUT FOR PEOPLE AT MOST COMPANIES, FRICTION PREVENTS DATA FROM FLOWING EFFORTLESSLY INTO DECISIONS. Technology alone won’t make the connection for you. Neither will finding more data; you’ve already got plenty. To connect data with decisions, you’ll need to reverse the way data flows through all your systems and decisions.If you’re a business decision-maker – a CEO, CIO, or CxO – you’ll see the connection between a data strategy and the thousands of decisions people in your company make every day. If you’re a data worker, you’ll see how your work changes the direction of a company. And if you’re an analyst – someone who bridges the gap between top-level decision makers and what’s really happening in the business – you’ll find a new vision of how to use data to transform your job and your company.Instead of new technology offering tired promises to make your job easier, you’ll find management solutions for better, faster decisions. Unified data flowing through your company, to everyone at the same time, improving business decisions through alignment and visibility, trust and scale.That’s Frictionless Decision Data.
Integrating Neurocomputing with Artificial Intelligence
INTEGRATING NEUROCOMPUTING WITH ARTIFICIAL INTELLIGENCE PROVIDES UNPARALLELED INSIGHTS INTO THE CUTTING-EDGE CONVERGENCE OF NEUROSCIENCE AND COMPUTING, ENRICHED WITH REAL-WORLD CASE STUDIES AND EXPERT ANALYSES THAT HARNESS THE TRANSFORMATIVE POTENTIAL OF NEUROCOMPUTING IN VARIOUS DISCIPLINES.Integrating Neurocomputing with Artificial Intelligence is a comprehensive volume that delves into the forefront of the neurocomputing landscape, offering a rich tapestry of insights and cutting-edge innovations. This volume unfolds as a carefully curated collection of research, showcasing multidimensional perspectives on the intersection of neuroscience and computing. Readers can expect a deep exploration of fundamental theories, methodologies, and breakthrough applications that span the spectrum of neurocomputing. Throughout the book, readers will find a wealth of case studies and real-world examples that exemplify how neurocomputing is being harnessed to address complex challenges across different disciplines. Experts and researchers in the field contribute their expertise, presenting in-depth analyses, empirical findings, and forward-looking projections. Integrating Neurocomputing with Artificial Intelligence serves as a gateway to this fascinating domain, offering a comprehensive exploration of neurocomputing’s foundations, contemporary developments, ethical considerations, and future trajectories. It embodies a collective endeavor to drive progress and unlock the potential of neurocomputing, setting the stage for a future where artificial intelligence is not merely artificial, but profoundly inspired by the elegance and efficiency of the human brain. ABHISHEK KUMAR, PHD is a professor and Assistant Director in the Computer Science and Engineering Department at Chandigarh University, Punjab with over 13 years of teaching experience. He has published over 170 peer-reviewed papers, seven books, and one patent and edited over 50 volumes. His research interests include artificial intelligence, renewable energy systems, image processing, and data mining. PRAMOD SINGH RATHORE is an assistant professor in the Department of Computer and Communication Engineering at Manipal University with over 11 years of teaching experience. He has published over 55 papers in reputable national and international journals, books, and conferences. His research interests include NS2, computer networks, mining, and database management systems. SACHIN AHUJA, PHD is the Executive Director of Engineering at Chandigarh University with extensive research and academic experience. He has served in key academic positions at various reputed higher education institutes, guiding several master’s and doctoral scholars in areas including artificial intelligence, machine learning, and data mining. UMESH KUMAR LILHORE, PHD is affiliated with Galgotias University where he actively engages in academic leadership, research, and mentoring. He has published over 100 scholarly articles and is a senior member of the Institue for Electrical and Electronics Engineers. His areas of expertise include artificial intelligence, machine learning, Internet of Things (IoT), cloud computing, and cybersecurity.
PHP, MySQL, & JavaScript All-In-One For Dummies
LEARN THE ESSENTIALS OF CREATING WEB APPS WITH SOME OF THE MOST POPULAR PROGRAMMING LANGUAGESPHP, MySQL, & JavaScript All-in-One For Dummies bundles the essentials of coding in some of the most in-demand web development languages. You'll learn to create your own data-driven web applications and interactive web content. The three powerful languages covered in this book form the backbone of top online apps like Wikipedia and Etsy. Paired with the basics of HTML and CSS—also covered in this All-in-One Dummies guide—you can make dynamic websites with a variety of elements. This book makes it easy to get started. You'll also find coverage of advanced skills, as well as resources you'll appreciate when you're ready to level up.* Get beginner-friendly instructions and clear explanations of how to program websites in common languages* Understand the basics of object-oriented programming, interacting with databases, and connecting front- and back-end code* Learn how to work according to popular DevOps principles, including containers and microservices* Troubleshoot problems in your code and avoid common web development mistakesThis All-in-One is a great value for new programmers looking to pick up web development skills, as well as those with more experience who want to expand to building web apps. RICHARD BLUM is a highly experienced programmer and systems administrator. He is also author of the most recent editions of Linux For Dummies and Linux All-in-One For Dummies.
Swift - Das umfassende Handbuch (Auflg. 5)
Mit Swift und SwiftUI erstellen Sie professionelle und moderne Apps für macOS und iOS. Wie das geht, zeigt Ihnen Michael Kofler in diesem vollständig neu konzipierten Swift-Handbuch. Von den ersten Zeilen in Xcode über das Design Ihrer neuen App mit SwiftUI bis zur Veröffentlichung im App-Store lernen Sie alle Schritte der Anwendungsentwicklung kennen und machen sich mit den neuen Features von Swift 6 vertraut. Ideal für das Selbststudium und den Unterricht.Solides FundamentVon der einfachen for-Schleife bis zum Einsatz von Closures: Dieses Buch gibt einen Überblick über alle wesentlichen Sprachelemente von Swift 6 und erläutert ihren Einsatz. Programmiertechniken zeigen den Einsatz der Swift-Konzepte in der Praxis: JSON-Dateien verarbeiten, Dateien aus dem Internet herunterladen, REST-APIs anwenden, Code asynchron ausführen und vieles mehr.Modernes GUI-DesignDie deklarative Bibliothek SwiftUI macht die Gestaltung moderner Apps zwar nicht zum Kinderspiel, aber einfacher als je zuvor! Lernen Sie, wie Sie Ihre Apps aus Views zusammensetzen, diese optisch ansprechend gestalten, Listen darstellen und zwischen verschiedenen Ansichten navigieren.Daten eingeben, darstellen und speichernDer Datenfluss von der Oberfläche über Ihre eigenen Klassen bis hin zur persistenten Speicherung mit SwiftData oder in der iCloud ist die größte Herausforderung bei der Entwicklung neuer Apps. Umfangreiche, praxisnahe Beispiel-Apps zeigen die Anwendung moderner Coding-Techniken.Aus dem Inhalt: Crashkurs Xcode Schleifen, Funktionen und Closures Strukturen, Klassen und Protokolle Views anwenden und selbst programmieren App-Design und Animation Data Binding, SwiftData und iCloud Internationalisierung und App StoreLeseprobe (PDF-Link)
Abschlüsse in SAP S/4HANA
Nutzen Sie die Stellschrauben für präzise Abschlüsse in SAP S/4HANA! Finanzteams, Projektteams, SAP-Beratung und IT-Management erhalten in diesem Buch fundiertes Wissen für die zuverlässige Durchführung von Periodenabschlüssen. Das Autorenteam beantwortet sowohl technische als auch organisatorische Fragen und gibt anhand von Screenshots und Beispielen einen Einblick in die aktuellen SAP-Funktionen. Von der Anlagenbuchhaltung über die Hauptbuchhaltung bis hin zum Controlling erhalten Sie praxisorientierte Empfehlungen für effiziente Closing-Prozesse. Darüber hinaus erfahren Sie, wie Sie SAP Advanced Financial Closing zur Optimierung einsetzen können. Aus dem Inhalt: Organisationsobjekte und StammdatenAnlagenbuchhaltungDebitorenbuchhaltungKreditorenbuchhaltungHauptbuchhaltungGemeinkostenrechnungProduktkostenrechnungMargenanalyseOptimierung der Abschlussarbeiten Vorwort ... 15 Einleitung ... 19 TEIL I. Grundlagen ... 25 1. Grundlagen der Finanzabschlüsse ... 27 1.1 ... Einführung in SAP S/4HANA Finance ... 27 1.2 ... Einführung in SAP Fiori ... 31 1.3 ... Stichtagsbetrachtung ... 40 1.4 ... Parallele Rechnungslegung mit parallelen Ledgern ... 44 1.5 ... Zusammenfassung und Empfehlungen ... 46 2. Organisationsobjekte für den Abschluss ... 49 2.1 ... Mandant/System ... 50 2.2 ... Ledger ... 53 2.3 ... Rechnungslegungsvorschrift ... 56 2.4 ... Kostenrechnungskreis ... 58 2.5 ... Buchungskreis/Gesellschaft ... 62 2.6 ... Werk ... 67 2.7 ... Kontenplan ... 68 2.8 ... Zusammenfassung und Empfehlungen ... 72 3. Stammdaten für den Abschluss ... 75 3.1 ... Sachkonten/Konzernkontonummer ... 75 3.2 ... Globale Hierarchien verwalten ... 80 3.3 ... Profitcenter und Segment ... 86 3.4 ... Geschäftspartner und Partnergesellschaft ... 91 3.5 ... Zusammenfassung und Empfehlungen ... 95 TEIL II. Periodenabschluss im Finanzwesen ... 97 4. Abschluss in der Anlagenbuchhaltung ... 99 4.1 ... Customizing der Anlagenbuchhaltung ... 99 4.2 ... Abrechnung von Anlagen im Bau (AiB) ... 101 4.3 ... Anlageninventur ... 113 4.4 ... Abschreibungslauf ... 116 4.5 ... Abschreibungen neu rechnen ... 130 4.6 ... Berichtswesen ... 131 4.7 ... Jahreswechsel und Jahresabschluss ... 138 4.8 ... Zusammenfassung und Empfehlungen ... 143 5. Abschluss in der Debitorenbuchhaltung ... 145 5.1 ... Allgemein ... 145 5.2 ... Analyse der offenen Posten ... 147 5.3 ... Mahnen ... 149 5.4 ... Saldenbestätigung ... 156 5.5 ... Verzinsung ... 164 5.6 ... Dauerbuchungen ... 169 5.7 ... Zusammenfassung und Empfehlungen ... 171 6. Abschluss in der Kreditorenbuchhaltung ... 173 6.1 ... Analytische Funktionen ... 174 6.2 ... Saldenbestätigung ... 178 6.3 ... Verzinsung ... 178 6.4 ... Dauerbuchung ... 183 6.5 ... Zahllauf ... 183 6.6 ... Meldung gemäß Außenwirtschaftsverordnung Z5a ... 190 6.7 ... Zusammenfassung und Empfehlungen ... 194 7. Abschluss in der Hauptbuchhaltung ... 197 7.1 ... Periodensteuerung ... 198 7.2 ... Maschinelle Pflege des WE/RE-Verrechnungskontos ... 205 7.3 ... Erweiterte Bewertung in der Finanzbuchhaltung ... 207 7.4 ... Saldovortrag im Hauptbuch ... 224 7.5 ... Dauerbuchungen im Hauptbuch ... 231 7.6 ... SAP S/4HANA Accrual Management ... 235 7.7 ... Zusammenfassende Meldung ... 246 7.8 ... Meldung gemäß Außenwirtschaftsverordnung Z4 ... 249 7.9 ... Saldenbestätigungen im Hauptbuch ... 255 7.10 ... Saldenvalidierung (Balance Validation) ... 256 7.11 ... Zusammenfassung und Empfehlungen ... 262 8. Andere Abschlussschritte im Finanzwesen ... 265 8.1 ... SAP Document and Reporting Compliance ... 265 8.2 ... Finanzdatenkonsistenzanalyse ... 278 8.3 ... Spiegeldarstellung ... 283 8.4 ... Abstimmung der Materialwirtschaft mit dem Hauptbuch ... 294 8.5 ... Audit Journal ... 296 8.6 ... Zusammenfassung und Empfehlungen ... 298 9. Vorbereitungen für den Konzernabschluss ... 301 9.1 ... Meldedaten ... 301 9.2 ... Intercompany-Buchungen ... 310 9.3 ... Intercompany-Abstimmung (Intercompany Matching and Reconciliation) ... 316 9.4 ... Vorbereitungs-Ledger in SAP S/4HANA ... 324 9.5 ... Zusammenfassung und Empfehlungen ... 329 TEIL III. Periodenabschluss im Controlling ... 331 10. Abschluss in der Gemeinkostenrechnung ... 333 10.1 ... Kontierung von Objekten in der Gemeinkostenrechnung ... 334 10.2 ... Manuelle Istbuchungen ... 335 10.3 ... Universelle Verrechnung ... 351 10.4 ... Periodische Umbuchung ... 391 10.5 ... Abgrenzung ... 405 10.6 ... Periodenabschluss von Gemeinkostenaufträgen ... 415 10.7 ... Zusammenfassung und Empfehlungen ... 445 11. Abschluss in der Produktkostenrechnung ... 447 11.1 ... Einführung in die Kostenträgerrechnung ... 447 11.2 ... Kostenrechnungsrelevante Einstellungen für Fertigungsaufträge ... 449 11.3 ... Materialkalkulation überprüfen ... 452 11.4 ... Zuschlagsberechnung für Materialeinzelkosten und teilrückgemeldete Fertigungseinzelkosten ... 457 11.5 ... Ermittlung der Ware in Arbeit für den freigegebenen Fertigungsauftrag ... 464 11.6 ... Abrechnung der Ware in Arbeit ... 470 11.7 ... Zuschlagsberechnung für den vollständig rückgemeldeten Fertigungsauftrag ... 475 11.8 ... Ermittlung der Ware in Arbeit für den gelieferten Fertigungsauftrag ... 477 11.9 ... Abweichungsermittlung für den gelieferten Fertigungsauftrag ... 478 11.10 ... Abrechnung der Istkosten und der Abweichungen ... 484 11.11 ... Zusammenfassung und Empfehlungen ... 490 12. Abschluss in der Margenanalyse ... 493 12.1 ... Einführung in die Margenanalyse ... 493 12.2 ... Werteflüsse in der Margenanalyse ... 494 12.3 ... Kostenstellenverteilung an die Margenanalyse ... 496 12.4 ... Top-down-Verteilung ... 513 12.5 ... Abrechnung von Controlling-Objekten an die Margenanalyse ... 534 12.6 ... Zusammenfassung und Empfehlungen ... 545 TEIL IV. Koordination des Abschlusses ... 547 13. SAP Advanced Financial Closing ... 549 13.1 ... Grundlagen ... 549 13.2 ... Inhaltliche und technische Vorbereitungen ... 552 13.3 ... Abschlussvorlage anlegen ... 556 13.4 ... Abschlussvorlage pflegen ... 573 13.5 ... Abschlussvorlage freigeben und bearbeiten ... 581 13.6 ... Abschluss überwachen ... 588 13.7 ... Zusammenfassung und Empfehlungen ... 594 Anhang ... 597 A ... SAP-Fiori-Apps und Transaktionen ... 597 B ... Wichtige SAP-Hinweise ... 605 C ... Weiterführende Informationsquellen ... 609 Das Autorenteam ... 615 Index ... 617