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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
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.
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.
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.
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.
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.
Penetrationstests erfolgreich umsetzen
Dieses Buch ist ein Praxisleitfaden für Verantwortliche in Unternehmen, die Pentests erfolgreich umsetzen wollen. Dabei werden aktuelle regulatorische Anforderungen und Herausforderungen ebenso beleuchtet wie die unterstützende Wirkung der KI.Professionelle Dienstleister decken durch Pentests Schwachstellen in Komponenten auf, damit Betroffene diese proaktiv beheben können. Dabei werden Vorgehen und Methoden echter Angreifer angewendet.Die Autoren geben praxisnahe Tipps zum Vorgehen, beginnend bei der Planung erster Pentests bis zur Nachbereitung. Es wird in sämtlichen Phasen aufgezeigt, wie für alle Seiten ein optimaler Nutzen aus Pentest-Projekten gezogen wird, bei gleichzeitig rechtlich sicheren Rahmenbedingungen.NINA WAGNER hat nach ihrem Mathe-Studium die IT-Sicherheitsbranche fasziniert, besonders das proaktive Aufdecken von Schwachstellen. Vor der Gründung ihrer eigenen Firma, der MindBytes GmbH, hat sie bereits mehrere Jahre als Pentesterin und Red Teamerin gearbeitet.HORST SPEICHERT ist Partner der Kanzlei esb Rechtsanwälte und seit mehr als 25 Jahren als Rechtsanwalt spezialisiert auf IT-Recht, Datenschutz und Informationssicherheit.DR. STEPHEN FEDTKE ist Wirtschaftsingenieur der Elektrotechnik (TH Darmstadt, Regelungstechnik), Autor und Herausgeber im Springer Verlag, und CTO des Sicherheits- und Compliance-Lösungsanbieters Enterprise-IT-Security.com.BERNHARD C. WITT berät seit 1998 zu Informationssicherheit und ist als Principal on Cybersecurity and Critical Entities Protection bei der SITS Deutschland GmbH beschäftigt. Er ist ein ausgewiesener Experte zur neuen Regulierung zur Cybersicherheit und hat zahlreiche Prüfungen kritischer Infrastrukturen nach § 8a Abs. 3 BSIG durchgeführt oder begleitet.Einleitung.- Testgegenstände.- Anbieterauswahl.- Ablauf eines Pentests.- Pentests rechtssicher umsetzen.- Woher kommen Pflichten für Pentests.- Erste Pentests umsetzen.- Pentests und künstliche Intelligenz.- Anhang.
Metaversum
Die Entwicklung des Internets, insbesondere des WWW, stößt aktuell an ihre Grenzen – sowohl technisch als auch sozio-kulturell und ökonomisch. Als Lösung wird ein neues Internet versprochen, das die Grenzen der realen und der virtuellen Welt überwinden und Realität und Digitalität verschmelzen soll – das Metaversum. Technische, semantische und organisatorische Details greifen hierzu eng ineinander. Was aber bedeutet dies bei genauerer Betrachtung? Welche technisch-technologischen Herausforderungen müssen bewältigt werden, um ein solches Verschmelzen zu erreichen? Welche ökonomischen Möglichkeiten eröffnen sich– und welche verbieten sich möglicherweise? Wie kann erreicht werden, dass ein offenes und für jeden benutzbares Metaversum entsteht? Und wie kann vermieden werden, dass auch in diesem neuen Metaversum wenige große Anbieter ihre proprietären Ideen durchsetzen? Für diese Fragen soll dieses Buch Antworten aufzeigen. In der vorliegenden Auflage wurden zudem aktuelle Trends sowie der Beitrag der künstlichen Intelligenz zum Metaversum ergänzt.DR. PETER HOFFMANN, einerseits Hochschullehrer für Wirtschaftsinformatik, andererseits Medieninformatiker mit Herz und Seele, beschäftigt sich seit mittlerweile mehr als 20 Jahren mit den Fragen danach, was „digitale Medien“ und „virtuelle Welten“ eigentlich sind und wie der Benutzer mit ihnen interagieren kann.Metaversum?.- Woher … wohin … oder: was überhaupt.- Das Verschmelzen von Welten und …versen.- Eine andere Dimension: Ökonomisches Verschmelzen.- Was nicht fehlen darf: Kritik.- Die wirkliche Vision.- Jetzt ist die Zeit zum Bauen!.- Nachtrag 1 - Weil es so aktuell ist: Künstliche Intelligenz im Metaversum?.
Getting Started with .NET Aspire
Learn to master the brand-new .NET Aspire stack to simplify the creation of cloud-native and distributed applications. You will learn how .NET Aspire combines all the necessary tools, templates, and packages to minimize friction for applications that draw on a broad array of servers.Experienced software engineer Dave Rael explains how to leverage .NET Aspire. He begins by describing the motivations for .NET Aspire and how it improves upon current approaches for distributed applications. Then, he shows you how to use .NET Aspire and its associated tools and libraries in your projects, whether your project is completely from scratch or builds upon a previously existing solution.WHAT YOU WILL LEARN:* Gain a solid understanding of the .NET Aspire stack* Create rich and dynamic distributed apps using .NET Aspire* Test, deploy, and observe your cloud-native app* Leverage built-in tools to use unit testing and integration testing with your projectsWHO THIS BOOK IS FOR:This book is for both students and .NET developers who want to build cloud-native, distributed applications using the .NET Framework. A working knowledge of C# is recommended to follow the examples used in the book.DAVE RAEL is a father, husband, and seasoned software professional. He has worked as a software developer, analyst, tester, engineer, and architect in numerous verticals and industries over the course of more than 25 years. In 1999, he started in professional software development for a large telecom company working with C++, Visual Basic, .NET, and C#. He created and published the popular podcast _Developer On Fire_ from 2015-2019, in which he interviewed software professionals to gather stories from the world of software. The project of raising excellent offspring is his most important and most successful project to date.Chapter 1: Introducing .NET Aspire.- Chapter 2: Getting Started with .NET Aspire.- Chapter 3: .NET Aspire Project Types and Templates.- Chapter 4: System Architecture Considerations.- Chapter 5: Testing Your Systems.- Chapter 6: .NET Aspire Integrations.- Chapter 7: Deploying Your Aspire-Based System.- Chapter 8: System Observability with .NET Aspire.- Chapter 9: Greenfield: Implementing New Systems with .NET Aspire.- Chapter 10: Brownfield: Using .NET Aspire with Existing Systems.- Chapter 11: Wrapping Up.
Designing Websites with Publii and GitHub Pages
Does getting online seem overwhelmingly difficult? Are you paying too much for your hosting solution? Have you always wanted to have a blog but don’t know where to start? Do you settle for a Facebook page for your business website but know you need more? The solution to these problems is choosing the right tools. This book will guide you through the process of setting up a Publii-based publishing platform and hosting your site for free on GitHub.Publii is a free, open source, desktop application that runs on Windows, Mac, and Linux and makes building the website or blog you dream of is a simple process. This book walks you through the process of installing and using Publii, setting up accounts on GitHub and hosting a static blog or website there. You will gain background insights on here to get no-cost imagery for website, how to leverage AI to generate ideas, outlines, and images. You’ll also review search engine optimization (SEO) best practices to ensure your site is searchable._Designing Websites with Publii and GitHub Pages_ is your roadmap to creating a website and understanding how the publishing workflow works.WHAT YOU WILL LEARN* Use text editors such as WYSIWYG, Block, and Markdown* Make a page from a post.* Work on advanced processes such as installing themes and plugins* Manage and back up your data* Explore GDRP and cooking banner considerationsWHO THIS BOOK IS FORThose with limited or no programming or compute skills who want to learn how to set up a website.BRAD MOORE is a technical writer and blogger based in Kentucky, USA. who has been involved in web development for 20 years. He has helped clients host sites with WordPress, Grav and Publii since 2023. Brad enjoys programming, electronics, microprocessors, and model trains. Brad is married and has three children.PART I.- 1: Introduction.- 2: Getting Started.- 3: Getting Publii Running.- 4: Getting Ready for Content.- 5: Adding Content.- 6: Page Building in Publii.- 7: Creating a GitHub Page.- 8: Configure Publii for Sync.- PART II.- 9: Backups and Sites.- 10: Themes.- 11: Single Page Sites.- 12: Gallery & Contacts.- 13: Internet Real Estate.- PART III.- 14: Plugins and Cookies.- 15: CSS Tricks.
Cybersecurity Threats and Attacks in the Gaming Industry
Learn about the most common and known threats and attacks in the gaming industry. Cybersecurity is a critical concern in the gaming industry due to the significant financial investments, personal data, and intellectual property at stake. Game developers, publishers, and players all have a vested interest in maintaining a secure gaming environment.This pocketbook is about why cybersecurity in the gaming industry is essential to protect player data, maintain a secure gaming environment, and safeguard intellectual property. Both players and game developers need to remain vigilant, educate themselves about potential threats, and employ best practices to ensure a safe and enjoyable gaming experience. We will describe the most common type of targeted games facing cybersecurity attacks as well as some of the most common types of cyber threats faced by the gaming industry such as malware, distributed denial of service (DDoS) attacks, data breaches, etc.WHAT YOU WILL LEARN* Describes the importance cybersecurity in the gaming industry* Explains key aspects of cybersecurity in the gaming* Describes the common types of cyber threats faced by the gaming industryWHO IS THIS BOOK FORThe book assumes you have strong gaming development and security knowledge. The book will be written mainly for developers who want to learn how to choose the right tools, what are the best practice, the threats, and vulnerabilitiesMASSIMO NARDONE has more than 27 years of experience in information and cybersecurity for IT/OT/IoT/IIoT, web/mobile development, cloud, and IT architecture. His true IT passions are security and Android. He has been programming and teaching how to program with Android, Perl, PHP, Java, VB, Python, C/C++, and MySQL for more than 27 years. He holds an M.Sc. degree in computing science from the University of Salerno, Italy. Throughout his working career, he has held various positions starting as programming developer, then security teacher, PCI QSA, Auditor, Assessor, Lead IT/OT/SCADA/SCADA/Cloud Architect, CISO, BISO, Executive, Program Director, OT/IoT/IIoT Security Competence Leader, etc.In his last working engagement, he worked as a seasoned Cyber and Information Security Executive, CISO and OT, IoT and IIoT Security competence Leader helping many clients to develop and implement Cyber, Information, OT, IoT Security activities.His technical skills include Security, OT/IoT/IIoT, Android, Cloud, Java, MySQL, Drupal, Cobol, Perl, web and mobile development, MongoDB, D3, Joomla!, Couchbase, C/C++, WebGL, Python, Pro Rails, Django CMS, Jekyll, and Scratch. He has served as a visiting lecturer and supervisor for exercises at the Networking Laboratory of the Helsinki University of Technology (Aalto University).He stays current to industry and security trends, attending events, being part of a board such as the ISACA Finland Chapter Board, ISF, Nordic CISO Forum, Android Global Forum, etc.He holds four international patents (PKI, SIP, SAML, and Proxy areas). He currently works as a Cyber Security Freelancer for IT/OT and IoT. He has reviewed more than 55 IT books for different publishers and has coauthored _Pro Spring Security_ (Apress, 2023) _Pro JPA 2 in Java EE 8_ (Apress, 2018), _Beginning EJB in Java EE 8_ (Apress, 2018), and _Pro Android Games_ (Apress, 2015).Chapter 1: Introduction of Cybersecurity in the Gaming Industry.- Chapter 2: Key aspects of Cybersecurity in Gaming Industry.- Chapter 3: Games Target of Cybersecurity Attacks.- Chapter 4: Cybersecurity Threats & Attacks in Gaming Industry.