Allgemein
Mastering AI
An urgent book on generative artificial intelligence exploring the risk and benefits looming in this seminal moment'Easily the best exploration to date on the perils and promise of AI." —ASHLEE VANCE author of When the Heavens Went on Sale'Mastering AI is a must-read. It's hard to put down'. —BETHANY McLEAN, coauthor of The Smartest Guys in the Room and The Big Fail'A timely and urgent exploration of AI's dizzying acceleration' —BRAD STONE, author of The Everything StoreThe debut of ChatGPT on November 30th was a watershed moment in the history of technology. We stand on the threshold of a new age — one where content of all kinds, even software itself, will be conjured, seemingly from thin air, with simple conversation.In a culture fraught with misinformation, Mastering AI pierces through the thicket of exaggerated claims, explaining how we arrived at this moment and mapping the likely long-term impacts on business, economics, culture and society this potent technology will have.This book will serve as a guide to those dangers — as well as highlighting the technology's transformative potential — and will pinpoint concrete steps that should be taken to regulate generative AI.Jeremy Kahn is a veteran technology and business journalist who has covered artificial intelligence for more than seven years, first at Bloomberg and then at Fortune.
Integrating Metaheuristics in Computer Vision for Real-World Optimization Problems
A COMPREHENSIVE BOOK PROVIDING HIGH-QUALITY RESEARCH ADDRESSING CHALLENGES IN THEORETICAL AND APPLICATION ASPECTS OF SOFT COMPUTING AND MACHINE LEARNING IN IMAGE PROCESSING AND COMPUTER VISION.Researchers are working to create new algorithms that combine the methods provided by CI approaches to solve the problems of image processing and computer vision such as image size, noise, illumination, and security. The 19 chapters in this book examine computational intelligence (CI) approaches as alternative solutions for automatic computer vision and image processing systems in a wide range of applications, using machine learning and soft computing. Applications highlighted in the book include:* diagnostic and therapeutic techniques for ischemic stroke, object detection, tracking face detection and recognition;* computational-based strategies for drug repositioning and improving performance with feature selection, extraction, and learning;* methods capable of retrieving photometric and geometric transformed images;* concepts of trading the cryptocurrency market based on smart price action strategies; comparative evaluation and prediction of exoplanets using machine learning methods; the risk of using failure rate with the help of MTTF and MTBF to calculate reliability; a detailed description of various techniques using edge detection algorithms;* machine learning in smart houses; the strengths and limitations of swarm intelligence and computation; how to use bidirectional LSTM for heart arrhythmia detection;* a comprehensive study of content-based image-retrieval techniques for feature extraction;* machine learning approaches to understanding angiogenesis;* handwritten image enhancement based on neutroscopic-fuzzy.AUDIENCEThe book has been designed for researchers, engineers, graduate, and post-graduate students wanting to learn more about the theoretical and application aspects of soft computing and machine learning in image processing and computer vision. SHUBHAM MAHAJAN, PHD, is an assistant professor in the School of Engineering at Ajeekya D Y Patil University, Pune, Maharashtra, India. He has eight Indian, one Australian, and one German patent to his credit in artificial intelligence and image processing. He has authored/co-authored more than 50 publications including peer-reviewed journals and conferences. His main research interests include image processing, video compression, image segmentation, fuzzy entropy, nature-inspired computing methods with applications in optimization, data mining, machine learning, robotics, and optical communication. KAPIL JOSHI, PHD, is an assistant professor in the Computer Science & Engineering Department, Uttaranchal Institute of Technology in Dehradun, India. His doctorate was on image quality enhancement using fusion techniques. He has 8 years of academic experience and has published patents, research papers, and two books. In 2021, he was awarded the ‘Best Young Researcher’ Award in Global Education and Corporate Leadership received by Life Way Tech India Pvt. Ltd. AMIT KANT PANDIT, PHD, is an associate professor in the School of Electronics & Communication Engineering Shri Mata Vaishno Devi University, India. He has authored/co-authored more than 60 publications including peer-reviewed journals and conferences. He has two Indian and one Australian patent to his credit in artificial intelligence and image processing. His main research interests are image processing, video compression, image segmentation, fuzzy entropy, and nature-inspired computing methods with applications in optimization. NITISH PATHAK, PHD, is an associate professor in the Department of Information Technology, Bhagwan Parshuram Institute of Technology, New Delhi, India. He has 17 years of engineering education experience and has published more than 80 journal articles, in peer-reviewed journals as well as book chapters, patents, and conference papers. His research areas include intelligent computing techniques, empirical software engineering, and artificial intelligence. Preface xv1 ADVANCEMENT IN DIAGNOSTIC AND THERAPEUTIC TECHNIQUES FOR ISCHEMIC STROKE 1Mukul Jain, Divya Patil, Shubham Gupta and Shubham Mahajan1.1 Introduction 21.2 Diagnostic Tools of Ischemic Stroke 41.3 Artificial Intelligence–Based Diagnostic Tools 71.4 Blood-Based Protein Biomarker for Stroke 81.5 Markers for Endothelial Damage 81.6 Markers of Brain Injury 91.7 Therapeutic Advances in Ischemic Stroke 91.8 Nanoparticles 111.9 Conclusion 132 OBJECT DETECTION AND TRACKING FACE DETECTION AND RECOGNITION 25Varsha K. Patil, Pawan Nawade, Rudra Nagarkar and Paresh Kadale2.1 Introduction 252.2 Motivation 302.3 The Basics of Computer Vision 312.4 Face Detection 342.5 Facial Expression 382.6 Object Detection 412.7 Face Detection and Identification in Practical Situations 442.8 Future Direction in Object Detection and Tracking 472.9 Conclusion 523 PRINTING ORGANS WITH 3D TECHNOLOGY 55Shaik Aminabee3.1 Introduction 553.2 Bioprinting in Three Dimensions (3D) 563.3 3D Printing Types 573.4 Applications for 3D Printing in Cells 603.5 New Developments 653.6 Progress in India 663.7 Limitation 673.8 A Future Point of View 673.9 Conclusion 684 COMPARATIVE EVALUATION OF MACHINE LEARNING ALGORITHMS FOR BANK FRAUD DETECTION 71Kiran Jot Singh, Divneet Singh Kapoor, Kunal Ranjan Singh, Chirag Kalucha, Gatik Alagh, Khushal Thakur and Anshul Sharma4.1 Introduction 714.2 Proposed Framework 734.3 Results 744.4 Concluding Remarks and Future Scope 775 AN OVERVIEW OF COMPUTATIONAL-BASED STRATEGIES FOR DRUG REPOSITIONING 81Shalu Verma, Nidhi Nainwal, Alka Singh, Gauree Kukreti and Kiran Dobhal5.1 Introduction 815.2 Drug Repositioning 825.3 Challenges and Opportunities for Drug Repurposing 935.4 Conclusion 946 IMPROVING PERFORMANCE WITH FEATURE SELECTION, EXTRACTION, AND LEARNING 99Varsha K. Patil, Vrinda Shinde, Ritika Singh and Vipul Singh6.1 Introduction 996.2 Feature Selection 1006.3 Feature Extraction 1106.4 Feature Learning 1156.5 Future Research and Development 1236.6 Future Scope 1246.7 Conclusion 1257 FUSION OF PHASE AND LOCAL FEATURES FOR CBIR 129Pooja Sharma7.1 Introduction 1297.2 Overview of the Proposed System 1327.3 Proposed Hybrid-Shape Descriptors 1327.4 Similarity Measurement 1377.5 Experimental Study and Performance Evaluation 1397.6 Conclusions 1478 TRADING BOT FOR CRYPTOCURRENCY MARKET BASED ON SMART PRICE ACTION STRATEGIES 151Divneet Singh Kapoor, Kiran Jot Singh, Anshoom Jain, Rhythm Chauhan, Khushal Thakur and Anshul Sharma8.1 Introduction 1518.2 Background 1548.3 Proposed Framework 1568.4 Results 1588.5 Conclusion and Future Scope 1619 COMPARATIVE EVALUATION AND PREDICTION OF EXOPLANETS USING MACHINE LEARNING METHODS 163Divneet Singh Kapoor, Kiran Jot Singh, Ashirvad Singh, Benarji Mulakala, Karan Singh, Prashant, Ramanjeet Singh and Shubham Mahajan9.1 Introduction 1649.2 Background 1679.3 Proposed Framework 1699.4 Results 1719.5 Conclusion and Future Scope 18210 THE RISK OF USING FAILURE RATE WITH THE HELP OF MTTF AND MTBF TO CALCULATE RELIABILITY 185Harpreet Kaur and Shiv Kumar Sharma10.1 Introduction 18510.2 Failure 18610.3 Conclusion 19111 A DETAILED DESCRIPTION ON VARIOUS TECHNIQUES OF EDGE DETECTION ALGORITHMS 193Pritha A. and G. Fathima11.1 Introduction 19311.2 Edge Detection Techniques 19411.3 Experimental Results 20311.4 Comparative Results 20311.5 Conclusion 20311.6 Future Work 20412 ADVANCEMENT OF ML IN SMART HOUSE 207Gokula Udhayan V., K. Mahaeshwari and N. Vinoth Kumar12.1 Objective 20712.2 Introduction 20712.3 Smart House System With IoT 20812.4 Future Scope 22312.5 Conclusion 22313 MULTI-ROBOT NAVIGATION: A BIOLOGICALLY INSPIRED FRAMEWORK 225Imran Mir and Faiza Gul13.1 Introduction 22513.2 Optimization Algorithms 22613.3 Algorithms and Self-Organization 23613.4 Future Research Directions 23813.5 Conclusion 23914 BIDIRECTIONAL LSTM FOR HEART ARRHYTHMIA DETECTION 243Nikhil M. Agrawal, H. D. Bhanu Cheitanya, Abhishek Kumar Rai and Shubham Mahajan14.1 Introduction 24314.2 About the Dataset 24514.3 Flow of the Model 24614.4 Results 24814.5 Conclusion 24815 STUDY ON CONTENT-BASED IMAGE RETRIEVAL 253Thanga Subha Devi M., R. Suji Pramila and Tibbie Pon Symon15.1 Introduction 25415.2 Related Works 25615.3 Extraction of Features 26115.4 User Interactions for CBIR System 26615.5 Conclusions 26916 MACHINE LEARNING AND ANGIOGENESIS IN CANCER 273Dharambir Kashyap, Riya Sharma, Neelam Goel and Vivek Kumar Garg16.1 Introduction 27316.2 History of Angiogenesis Discovery 27416.3 Overview of Angiogenesis 27416.4 Angiogenesis in Carcinogenesis 27516.5 Molecular Mechanisms of Angiogenesis Formation 27616.6 Angiogenesis as a Target in Cancer Therapy 27616.7 Machine Learning Approaches in Angiogenesis 27716.8 Conclusion 27817 HANDWRITTEN IMAGE ENHANCEMENT BASED ON NEUTROSCOPIC-FUZZY AND K-MEAN CLUSTERING 283Jaspreet Kaur, Divya Gupta, Simarjeet Kaur and Amrinder Singh17.1 Introduction 28417.2 Application of Image Processing 28617.3 Enhancement of Handwritten Document 28717.4 Clustering Techniques 28817.5 Performance Parameters 29017.6 Results and Discussion 29317.7 Conclusion 29518 A TEXTURE CLASSIFICATION SYSTEM BASED ON AN ADAPTIVE HISTOGRAM EQUALIZED SHEARLET TRANSFORM 299K. Gopalakrishnan, V. Karthikeyan and P.T. Vanathi18.1 Introduction 29918.2 Literature Survey 30318.3 Materials and Methods 30518.4 Proposed Methodology 30918.5 Result and Discussion 31118.6 Conclusion 32019 A THYROID NODULE DETECTION USING L1-NORM INCEPTION DEEP NEURAL NETWORK 323Saranya G.19.1 Introduction 32319.2 Related Work 32419.3 Methodology 32519.4 Results and Discussion 32919.5 Conclusion 336References 337Index 339
Machine Learning for Industrial Applications
THE MAIN GOAL OF THE BOOK IS TO PROVIDE A COMPREHENSIVE AND ACCESSIBLE GUIDE THAT EMPOWERS READERS TO UNDERSTAND, APPLY, AND LEVERAGE MACHINE LEARNING ALGORITHMS AND TECHNIQUES EFFECTIVELY IN REAL-WORLD SCENARIOS.Welcome to the exciting world of machine learning! In recent years, machine learning has rapidly transformed from a niche field within computer science to a fundamental technology shaping various aspects of our lives. Whether you realize it or not, machine learning algorithms are at work behind the scenes, powering recommendation systems, autonomous vehicles, virtual assistants, medical diagnostics, and much more. This book is designed to serve as your comprehensive guide to understanding the principles, algorithms, and applications of machine learning. Whether a student diving into this field for the first time, a seasoned professional looking to broaden your skillset, or an enthusiast eager to explore cutting-edge advancements, this book has something for you. The primary goal of Machine Learning for Industrial Applications is to demystify machine learning and make it accessible to a wide audience. It provides a solid foundation in the fundamental concepts of machine learning, covering both the theoretical underpinnings and practical applications. Whether you’re interested in supervised learning, unsupervised learning, reinforcement learning, or innovative techniques like deep learning, you’ll find comprehensive coverage here. Throughout the book, a hands-on approach is emphasized. As the best way to learn machine learning is by doing, the book includes numerous examples, exercises, and real-world case studies to reinforce your understanding and practical skills. AUDIENCEThe book will enjoy a wide readership as it will appeal to all researchers, students, and technology enthusiasts wanting a hands-on guide to the new advances in machine learning. KOLLA BHANU PRAKASH, PHD, is a professor and associate dean and R & D head for A.I. & Data Science Research Group at K L University, Vijayawada, Andhra Pradesh, India. He is also an adjunct professor at Taylors University, Malaysia. He has published 150+ research papers in international and national journals and conferences. He has authored two and edited 12 books as well as published 15 patents. His research interests include deep learning, data science, and quantum computing. He has received the ‘Best Researcher Award’ 4 times. Preface xix1 Overview of Machine Learning 12 Machine Learning Building Blocks 213 Multilayer Perceptron (in Neural Networks) 514 Kernel Machines 635 Linear and Rule-Based Models 736 Distance-Based Models 877 Model Ensembles 1038 Binary and Beyond Binary Classification 1179 Model Selection 12710 Support Vector Machines 14911 Clustering 17712 Reinforcement Learning 20513 Recommender Systems 22514 Advancements in Deep Learning 24515 Advanced Deep Learning Using Julia Programming 27716 Machine Learning for Industrial Applications 297Index 317
Blockchain, IoT, and AI Technologies for Supply Chain Management
Examine the synergistic possibilities of combining blockchain, IoT, and AI technologies in supply chain management. This book will address the difficulties and possibilities of integrating these technologies and offer helpful implementation advice.The current state of supply chain management involves several challenges, including lack of transparency, limited visibility into product movements, inefficient inventory management, and difficulty in tracking and tracing products. Blockchain, IoT, and AI can potentially address some of these challenges and improve supply chain management.To help illustrate this, case studies and actual instances of businesses implementing or experimenting with blockchain, IoT, and AI technology in their supply chains are included in the book. You’ll review helpful advice on implementation and highlight successful deployments, lessons learned, and the impact of these technologies on supply chain visibility, agility, sustainability, and customer experience. This book further elaborates the fundamental concepts of AI and ML algorithms and demonstrates how AI can process enormous volumes of supply chain data to produce actionable insights, improve inventory control, forecast demand, and increase forecasting precision.This collective work will serve as a comprehensive guide for supply chain professionals, researchers, and technology enthusiasts interested in understanding the potential of blockchain, IoT, and AI technologies in revolutionizing supply chain management practices.WHAT YOU WILL LEARN* Discuss the evolving landscape of technology, potential advancements, and how Blockchain, IoT, and AI can shape the future of supply chains* Gain Insight into upcoming developments and prepare for changing dynamics of the industry* Understand intricate details of blockchain, IoT, and AI Technologies in real-life scenariosWHO IS THIS BOOK FORIndustry Professionals working in the domain of supply chain management who would be interested in understanding how these technologies can enhance efficiency, transparency, and optimization in their supply chains.DR. VEENA GROVER is a Professor in Department of Management at Noida Institute of Engineering & Technology, India. Her interests include Micro Finance, Sustainability, Macro Economic Variables, and Innovation Strategy. She has published multiple articles in various journals and presented papers in various conferences. At present, she is guiding four research scholars and serves as an Editor of International Journal of Advanced Trends in Technology, Management & Applied Science.DR. BALAMURUGAN BALUSAMY is currently working as Associate Dean–Student Engagement in Shiv Nadar University, India. He has 15 years of experience in the field of computer science. His areas of interest are Internet of Things, Big data, Networking. He has published more than 100 papers and contributed multiple book chapters.PROF. SEIFEDINE KADRY focuses on Data Science, education using technology, system prognostics, stochastic systems, and applied mathematics. He is an ABET program evaluator for computing and ABET program evaluator for Engineering Tech. He is a Fellow of IET, Fellow of IETE, and Fellow of IACSIT. He is a distinguish speaker of IEEE Computer Society.DR. A. YOVAN FELIX has mentored students in the project areas of Big Data, Deep Learning, and Data Mining. He has published technical papers in national and international journals. He has over 17 years of experience and expertise in data analytics, smart prediction systems, and deep learning algorithms. He also coordinated in organizing several events at both national and international levels.Chapter 1: Supply Chain Management Strategy and Practices: Traditional Vs Advanced.- Chapter 2: Convergence of IoT, Artificial Intelligence and Blockchain Approaches for Applications in Supply Chain Management.- Chapter 3: Value Creation in Blockchain-Driven Supply Chain Financing Opportunities.- Chapter 4: Artificial Intelligence Applications for Demand Forecasting & Optimization.- Chapter 5: AI-Enabled Supply Chain Planning and Execution: A Pathway to Sustainability.- Chapter 6: Leveraging IOT In Supply Chain Sustainability: A Provenance Perspective.- Chapter 7: AI And Machine Learning in Supply Chain Optimization: Mapping the Territory.- Chapter 8: Blockchain and IoT Integration Based Transparency of Supply Chain Social Sustainability.- Chapter 9: Integration of Blockchain, IoT, And AI In Supply Chain Management: A New Paradigm for Supply Chain Integration and Collaboration.- Chapter 10: Challenges of Supply Chain Management Post COVID-19: Mitigation Strategies and Practical Lessons Learned.- Chapter 11: Supply Chain 4.0: Autonomous Vehicles and Delivery Robots in Supply Chain Management.- Chapter 12: Blockchain for the Future of Sustainable Supply Chain Management in Industry 4.0.- Chapter 13: Managing the Dynamics of New Technologies in The Global Supply Chain.- Chapter 14: Future Trends and Challenges in Supply Chain Technology.- Chapter 15: Real-World Applications of Generative AI for Data Augmentation.- Chapter 16: Case Studies and Best Practices in Supply Chain Management.
Practical GitLab Services
Learn all about GitLab administration, the open-source DevOps platform helping millions develop and deploy safe and secure software. This book__is designed to be your one-stop shop to get up and running with complete ease.Start with the basics like setting up a GitLab account and exploring user options before moving on to GitLab’s primary function as a source code management tool. From there, you’ll learn about one of the most unique features of GitLab: CI/CD configuration files. The next step on the journey is a discussion of how to organize code into projects and groups, along with defining access permissions using roles. You’ll also examine the various planning tools provided by GitLab.With the basic features out of the way, you’ll delve into more specialized services such as the built-in Docker image repository, the package registry, web page creation, and binary file storage. The book concludes with more advanced administrative topics such as working with GitLab’s REST and GraphQL APIs, setting up a proof-of-concept GitLab service using Amazon Web Services (AWS), and spinning up a production service that takes high availability and disaster recovery into account.With an abundance of information available for deploying secure software, selecting the right documentation can often be daunting. From planning to monitoring, _Practical GitLab Services_ eliminates the unknown in your DevOps lifecycle.WHAT YOU WILL LEARN* Use GitLab to manage source code files, track and plan issues, run builds and tests, and deploy software* See how administrators can support developers using GitLab* Set up your own standalone installation using AWSWHO THIS BOOK IS FORSoftware developers, potential GitLab administrators, supporting team members such as testers and project managers.JEFFREY PAINTER has spent the last 45 years in software development, working as a developer in various languages ranging from Fortran, C, C++, Java as well as Python and in a variety of roles from development to administration. The last seven years have been spent at Here Technologies as a system engineer first maintaining a farm of Jenkins servers for entire project teams and then prototyping and maintaining several self-managed GitLab servers.1. Only the Beginning.- 2. Just the Source.- 3. Working the Remote Life.- 4. Build, Test, Rinse and Repeat.- 5. Under One Condition.- 6. You Build It, You Keep It.- 7. Let's Get Organized.- 8. I Have an Issue with That.- 9. The Best Laid Plans.- 10. It's Nice to Share.- 11. There's an API for That.- 12. Well, Isn't That Special.- 13. I Can Do This on My Own.- 14. Things That Lurk in the Background.- 15. The Proof is in the Cloud.- 16. Working the Never-ending Queue.- 17. But Wait, There's More.- 18. It's an Admin's Life.- 19. Lights, Camera, Action.
Practical Cyber Intelligence
OVERVIEW OF THE LATEST TECHNIQUES AND PRACTICES USED IN DIGITAL FORENSICS AND HOW TO APPLY THEM TO THE INVESTIGATIVE PROCESSPractical Cyber Intelligence provides a thorough and practical introduction to the different tactics, techniques, and procedures that exist in the field of cyber investigation and cyber forensics to collect, preserve, and analyze digital evidence, enabling readers to understand the digital landscape and analyze legacy devices, current models, and models that may be created in the future. Readers will learn how to determine what evidence exists and how to find it on a device, as well as what story it tells about the activities on the device. Over 100 images and tables are included to aid in reader comprehension, and case studies are included at the end of the book to elucidate core concepts throughout the text. To get the most value from this book, readers should be familiar with how a computer operates (e.g., CPU, RAM, and disk), be comfortable interacting with both Windows and Linux operating systems as well as Bash and PowerShell commands and have a basic understanding of Python and how to execute Python scripts. Practical Cyber Intelligence includes detailed information on:* OSINT, the method of using a device’s information to find clues and link a digital avatar to a person, with information on search engines, profiling, and infrastructure mapping* Window forensics, covering the Windows registry, shell items, the event log and much more * Mobile forensics, understanding the difference between Android and iOS and where key evidence can be found on the device Focusing on methodology that is accessible to everyone without any special tools, Practical Cyber Intelligence is an essential introduction to the topic for all professionals looking to enter or advance in the field of cyber investigation, including cyber security practitioners and analysts and law enforcement agents who handle digital evidence. ADAM TILMAR JAKOBSEN works for the Danish National Police Agency’s special crime unit hunting down cyber criminals. Throughout his career he has worked on international cases with Europol and the FBI. Adam’s journey into cybersecurity and intelligence began in the Danish Army Intelligence, where he honed his skills in SIGINT, OSINT, HUMINT, and all-source intelligence. In this role, he executed a wide range of defense, intelligence, and attack missions. Transitioning to Bluewater Shipping, Adam initially served as a Solution Architect before pivoting towards information security, where he oversaw critical security operations. About the Author xviiiPreface xixAcknowledgments xxIntroduction xxi1 INTELLIGENCE ANALYSIS 11.1 Intelligence Life Cycle 11.2 Cyber Threat Intelligence Frameworks 101.3 Summary 132 DIGITAL FORENSICS 152.1 Device Collection 162.2 Preservation 172.3 Acquisition 182.4 Processing 192.5 Analysis 202.6 Documentation and Reporting 212.7 Summary 223 DISK FORENSICS 233.1 Acquisition 233.2 Preparation 253.3 Analysis 253.4 File and Data Carving 313.5 Summary 324 MEMORY FORENSICS 334.1 Acquisition 344.2 Analysis 354.3 Summary 385 SQLITE FORENSICS 395.1 Analyzing 405.2 Summary 436 WINDOWS FORENSICS 456.1 New Technology File System (NTFS) 456.2 Acquisition 516.3 Analysis 526.4 Evidence Location 606.5 Summary 937 MACOS FORENSICS 957.1 File System 957.2 Security 977.3 Acquisition 987.4 Analysis 1007.5 Evidence Location 1007.6 Summary 1048 LINUX FORENSICS 1058.1 File System 1058.2 Security 1078.3 Acquisition 1088.4 Analysis 1098.5 Evidence Location 1098.6 Summary 1159 IOS 1179.1 File System 1179.2 Security 1189.3 Applications 1199.4 Acquisition 1209.5 iCloud 1229.6 Analysis 1229.7 Evidence of Location 1249.8 Summary 13410 ANDROID 13710.1 File Systems 13710.2 Security 13710.3 Application 13810.4 Acquisition 13810.5 Analysis 14510.6 Evidence of Location 14611 NETWORK FORENSICS 15311.1 Acquisition 15311.2 Analysis 15811.3 Summary 16512 MALWARE ANALYSIS 16712.1 Acquiring Malware Samples 16812.2 Handling Malware Samples 16912.3 Analysis 17012.4 Summary 17413 OSINT 17713.1 Methodology 17813.2 Documentation 17913.3 Securing Yourself (OPSEC) 18013.4 Search Engines 18213.5 Profiling 18413.6 Hunt for Data 18913.7 Infrastructure Mapping 19413.8 Automation of OSINT Tasks 20813.9 Summary 20914 CASE STUDIES 21114.1 Case of “The Missing Author” 21114.2 The Insider Threat 21215 ENDING 21315.1 What’s the Next Step? 213Index 215
Cloud Security in der Praxis
Cloud-typische Sicherheitsthemen verständlich und praxisnah erklärt - Strategien und Lösungsansätze für alle gängigen Cloud-Plattformen, u.a. AWS, Azure und IBM Cloud - Deckt das breite Spektrum der Security-Themen ab - Gezieltes Einarbeiten durch den modularen Aufbau; mithilfe von Übungen können Sie Ihren Wissensstand überprüfen - Experten-Autor: IBM Distinguished Engineer mit zahlreichen Zertifizierungen und 25 Jahren Branchenerfahrung In diesem Praxisbuch erfahren Sie alles Wichtige über bewährte Sicherheitsmethoden für die gängigen Multivendor-Cloud-Umgebungen – unabhängig davon, ob Ihr Unternehmen alte On-Premises-Projekte in die Cloud verlagern oder eine Infrastruktur von Grund auf neu aufbauen möchte. Entwicklerinnen, IT-Architekten und Sicherheitsexpertinnen lernen Cloud-spezifische Techniken zur sicheren Nutzung beliebter Plattformen wie Amazon Web Services, Microsoft Azure und IBM Cloud kennen. Sie erfahren, wie Sie Data Asset Management, Identity and Access Management (IAM), Vulnerability Management, Netzwerksicherheit und Incident Response effektiv in Ihrer Cloud-Umgebung umsetzen. - Informieren Sie sich über neueste Herausforderungen und Bedrohungen im Bereich der Cloud-Sicherheit - Managen Sie Cloud-Anbieter, die Daten speichern und verarbeiten oder administrative Kontrolle bereitstellen - Lernen Sie, wie Sie grundlegende Prinzipien und Konzepte wie Least Privilege und Defense in Depth in der Cloud anwenden - Verstehen Sie die entscheidende Rolle von IAM in der Cloud - Machen Sie sich mit bewährten Praktiken vertraut, um häufig auftretende Sicherheitszwischenfälle zu erkennen, zu bewältigen und den gewünschten Zustand wiederherzustellen - Erfahren Sie, wie Sie mit verschiedensten Sicherheitslücken, insbesondere solchen, die in Multi-Cloud- und Hybrid-Cloudarchitekturen auftreten, umgehen - Überwachen Sie PAM (Privileged Access Management) in Cloud-Umgebungen
High Performance with Java
Building high performance into your applications is key to creating an optimal user experience, although it is not the only consideration for the performant nature of your apps. High performance applications can lead to cost-effective resource utilization, especially when scalability and cloud computing are involved. They can also provide highly reliable systems that are easier to maintain.High Performance with Java begins by helping you explore the Java Virtual Machine (JVM) and understand how to push it to its limits to further optimize your programs. You’ll take a hands-on approach to go through memory optimization strategies, input/output operations, concurrency, networking, as well as frameworks and libraries focused on performance. You’ll also learn key strategies and best practices by using industry-relevant examples to architect scalable and resource-efficient applications. The concluding chapters provide valuable insights on optimizing your Java code when interacting with databases and show you how to leverage artificial intelligence (AI) for high performance Java applications.By the end of this book, you’ll grasp the importance of developing high performance Java applications and gain practical experience in implementing key strategies to help ensure your Java applications perform optimally.
Introducing Microsoft Copilot for Managers
Embark on an exhilarating journey through the digital landscape with Microsoft Copilots, a suite of AI-powered tools that help you create, edit, and optimize content, code, and data across various Microsoft platforms. This book will be your indispensable guide to harnessing the power of generative AI within the Microsoft ecosystem, introducing you to various copilots and their impact on your business processes. The book will guide you as a manager to leverage Microsoft Copilot to improve your personal productivity, your team's productivity, and achieve your business goals with success.This book is organized into five parts. The first part introduces you to Microsoft Copilot and its features and benefits. In the second part, you will get an overview of the integration of Microsoft Copilot with M365 tools. The third part teaches you about the maker copilot in Power Platform services followed by the business expert copilot for Sales and Service for Business Applications such as Dynamics 365 and Salesforce. The book also introduces you to Copilot Studio to help you extend the copilots or build your own.By the end of this book, you will have a solid understanding of Microsoft Copilot and how to use copilots effectively and efficiently with various transformation platforms. You will also have a collection of tips, tricks, and best practices to help you get the most out of Microsoft Copilot.WHAT WILL YOU LEARN* Set up and activate Microsoft Copilot on various Microsoft platforms* Use Microsoft Copilot to generate and enhance content, code, and data with M365, Power Platform, and Business Applications tools* Understand tips, tricks, and best practices to get the most out of Microsoft Copilot* Build your own copilot using your own organization dataWHO THIS BOOK IS FORManagers, team leaders, and business practitioners who want to improve their and their team's productivity and creativity with Microsoft platformsMOHAMMAD ADEEL KHAN is a distinguished Senior Technical Specialist at Microsoft, renowned for his expertise in driving enterprise-grade digital transformations. His nearly two decades of experience encompass a deep understanding of Cloud Solutions, AI & ML, and data management solution architectures that have consistently delivered customer success and profitability. Adeel's global professional journey has taken him across Pakistan, UAE, Malaysia, and Singapore, enriching his perspective and enhancing his ability to navigate complex technological landscapes. Adeel's academic achievements are notable, with an MBA from Coventry University and an AI certification from MIT. His multilingual fluency in English, Urdu, and Arabic complements his global leadership role. As an author and speaker, Adeel has shared his thought leadership at various regional and global events, inspiring audiences with his insights into the future of technology. In his role at Microsoft Operations in Singapore, Adeel has been recognized as an AI-Copilot Champion and has achieved the remarkable feat, helping fortune 500 organizations adopt and transform future of work.Section: ChapterPart I- Part I: Chapter 1- Introduction.- Part II- Part II: Chapter 2- Microsoft Copilot in Word.- Part II: Chapter 3- Microsoft Copilot in Power Point.- Part II: Chapter 4- Microsoft Copilot in Excel .- Part II: Chapter 5- Microsoft Copilot in Communication and Collaboration.- Chapter 6: Microsoft Copilot Chat.- Part III- Part III: Chapter 7- Microsoft Copilot for Power Apps.- Part III: Chapter 8- Microsoft Copilot for Power Automate.- Part III: Chapter 9- Microsoft Copilot for Power Pages.- Part III: Chapter 10- Microsoft Copilot for Power BI.- Part IV-Part IV: Chapter 11 - Microsoft Copilot for Sales.- Part IV: Chapter 12- Microsoft Copilot For Sales with Salesforce.- Part IV: Chapter 13- Microsoft Copilot For Sales with Dynamics 365 Sales.- Part IV: Chapter 14- Microsoft Copilot for Service.- Part IV: Chapter 15 - Microsoft Copilot For Service with Cloud Solutions.- Part IV: Chapter 16 - Microsoft Copilot For Service with Dynamics 365 Customer Service.- Part V-Part V: Chapter 17 - Copilot Studio.- Chapter 18- Copilot , Generative AI and Future of work.- Annex - A: Annex – A.
Empowering the Public Sector with Generative AI
This is your guide book to Generative AI (GenAI) and its application in addressing real-world challenges within the public sector. The book addresses a range of topics from GenAI concepts and strategy to public sector use cases, architecture patterns, and implementation best practices. With a general background in technology and the public sector, you will be able to understand the concepts in this book.The book will help you develop a deeper understanding of GenAI and learn how GenAI differs from traditional AI. You will explore best practices such as prompt engineering, and fine-tuning, and architectural patterns such as Retrieval Augmented Generation (RAG). And you will discover specific nuances, considerations, and strategies for implementation in a public sector organization.You will understand how to apply these concepts in a public sector setting and address industry-specific challenges and problems by studying a variety of use cases included in the book in the areas of content generation, chatbots, summarization, and program management.WHAT YOU WILL LEARN* GenAI concepts and how GenAI differs from traditional AI/ML * Prompt engineering, fine-tuning, RAG, and customizing foundation models* Strategy, methodologies, and frameworks for the public sector* Public sector use cases in the areas of content generation, summarization, and chatbots, plus program management, analytics, business intelligence, and reporting* Architecture and design patterns * Implementation, operations, and maintenance of GenAI applicationsWHO THIS BOOK IS FORTechnology and business leaders in the public sector who are new to AI/ML and are keen on exploring and harnessing the potential of Generative AI in their respective organizations.SANJEEV PULAPAKA is Principal Solutions Architect at Amazon Web Services (AWS). He leads the development of AI/ML and Generative AI solutions for the US Federal Civilian team. Sanjeev has extensive experience in leading, architecting, and implementing high-impact technology solutions that address diverse business needs in multiple sectors (including commercial, federal, and state and local governments). He has published numerous blogs and white papers on AI/ML and is an active speaker and panelist at various industry conferences, including AWS Public Sector Summit and AWS re:Invent. Sanjeev has an undergraduate degree in engineering from the Indian Institute of Technology and an MBA degree from the University of Notre Dame.SRINATH GODAVARTHI has over 20 years of experience serving public sector customers and he held leadership positions with global technology and consulting companies ,including Amazon and Accenture. In his previous roles, Srinath led cloud strategy, architecture, and digital transformation efforts for a number of federal, state, and local agencies. Srinath specializes in AI/ML technologies and has published over a dozen white papers and blogs on various topics (including AI, ML, and Healthcare). He has been a speaker at various industry conferences, including the AWS Public Sector Summit, AWS re:Invent, and the American Public Human Services Association. He holds a master’s degree in computer science from Temple University and completed a Chief Technology Officer program from the University of California, Berkeley.SHERRY DING is an artificial intelligence and machine learning (AI/ML) technologist and evangelist with 20 years of experience in AI/ML research and applications. She currently works at Amazon Web Services as an AI/ML Specialist Solutions Architect, serving public sector customers on their AI/ML related business challenges, and guiding them to build highly reliable and scalable AI/ML applications on the cloud. Sherry holds a PhD in computer science from Korea University. She has authored more than 30 publications (including journal articles, book chapters, white papers, conference proceedings, and blogs) on different topics related to AI/ML. She is an active public speaker who has presented at various academia and industry conferences such as IEEE conferences, AWS re:Invent, and AWS Summits.Chapter 1: Introduction to Generative AI.- Chapter 2: Generative AI in the Public Sector.- Chapter 3: Gen AI Strategy: A Blueprint for Successful Adoption.- Chapter 4: Building a Generative AI Application.- Chapter 5: Content Generation.- Chapter 6: Chatbots and Enterprise Search.- Chapter 7: Summarization.- Chapter 8: Program Management, Business Intelligence, and Reporting.- Chapter 9: Implementation Considerations.- Chapter 10: Conclusion.- Appendix A.- Appendix B.- Appendix C.- Appendix D.- Appendix E.
Human Proxies in Cryptographic Networks
Human Proxies offer new directions to end-to-end encryption: End-A-to-End-Z encryption must be rethought when it turns out to be an End-B-to-End-Z encryption. And, Human Proxies raise questions that were neither answered by science, journalists nor the public. Regular Proxies on a network are forwarding Internet requests, e.g., to download a webpage. Also, in political and social settings a Proxy as an intermediate, deputy or representative with a similar function is given. Human Proxies now enable within the Encryption and Messenger Application Spot-On to choose a friend as a Human Proxy. The Spot-On program is a most modern and elaborated encryption suite available for several operation systems and provides many innovations in applied cryptography. It builds based on the Echo Protocol a cryptographic network, that is beyond Cryptographic Routing. With Human Proxies now a friend from the Messenger friends list sends out the chat message instead of the original sender. The construct of the "Inner Envelope" behind the Human Proxy function also creates new cryptographic challenges, provides plausible deniability to included nodes, and offers new perspectives in encryption, its analysis and decryption: As all messages in the network are encrypted, end-to-end encryption is new defined and gets with Human Proxies a potential second and plausible deniable start point. The essay in this book discusses some related aspects of Human Proxies and their referring's to encryption, networking, graph theory and comparable social and political processes of Proxies. This leads to a further general approach: Endpoints in Encryption are equipped by the application Spot-On with the vision of interoperability of endpoints in communications. | English & German language. Uni Nurf: Uni Nurf is author of the essay "Human Proxies in Cryptographic Networks - Establishing a new direction to end-to-end encryption with the introduction of the inner envelope in the echo protocol".
Automatisiertes Fahren 2024
Automatisiertes Fahren hilft Unfälle zu vermeiden. KI-unterstützte Roboterautos sind aber auch Grundlage für datengetriebene Geschäftsmodelle der OEMs. Konzepte zukünftiger Mobilitätslösungen müssen aus der Perspektive der Nutzer, der urbanen sowie der ländlichen Region und zielführender Geschäftsmodelle entwickelt werden, um erfolgreich zu sein. Im Fokus stehen dabei Verkehrssicherheit und Leistungsfähigkeit ebenso wie ökologische, ökonomische und soziale Nachhaltigkeit. Die internationale Konferenz „Automatisiertes Fahren“ widmet sich als Informations- und Kommunikationsplattform den zentralen Aspekten des Mobilitätswandels. Um die zentralen Herausforderungen künftiger ADAS-Systeme zu erfüllen, müssen Bereiche wie Sensorfusion, Rechnertechnik, KI oder V2X-Kommunikation optimiert werden, um die dafür notwendigen System-of-Systems-Architekturen entwickeln zu können. Die seit Jahren etablierte internationale ATZlive-Fachkonferenz "Automatisiertes Fahren" wird daher um die Themen DevOps, Tooling, Algorithmenentwicklung, Programmierung sowie SDW und E/E-Architektur erweitert. ADAS-Systeme werden fortlaufend weiterentwickelt, um Nutzerinnen und Nutzer nachhaltig zu unterstützen. Dabei ist es wichtig, sowohl die Verkehrssicherheit zu steigern als auch die Verfügbarkeit zu verbessern sowie die Akzeptanz der Systeme im Markt zu erreichen. Dafür müssen Bereiche wie Sensorfunktion, Umfeldmodellierung, Situationsprädiktion, Trajektorenplanung und Entscheidungsfindung auf der einen Seite und die Rechnertechnik und die V2X-Kommunikation auf der anderen Seite – unterstützt durch KI – optimiert werden, um die dafür notwendigen System-of-Systems-Architekturen entwickeln zu können. Die 9. Internationale ATZ-Tagung „Automatisiertes Fahren“ ist ein Forum für Entwicklungsmethodik, Technologiestacks und Security. Sie steht für Engineering AVF Level 2X und diskutiert Engineering und Technologien für das automatisierte Fahren ab Level 2+. Architekturen und Standardisierung.- Versicherungsthemen.- Manöverplanung.- Neue Fahrzeug- und Innenraumkonzepte.- Testverfahren und Absicherung.- Datengenerierung und Datensicherheit.- Verkehrsplanung und Geschäftsmodelle.- HMI und Fahrzeugmonitoring.
Learning Analytics und Künstliche Intelligenz in Studium und Lehre
In dem Sammelband werden die Ergebnisse aus dem Projekt „KI:edu.nrw - Didaktik, Ethik und Technik von Learning Analytics und KI in der Hochschulbildung“ im Zeitraum 2020-2023 vorgestellt. Ziel des Projekts war es, sowohl an der im Schwerpunkt geförderten Ruhr-Universität Bochum als auch an der partnerschaftlich verbundenen RWTH Aachen exemplarisch zu erarbeiten, wie Regeln, Konzepte, Prozesse und Technik für den Einsatz von Learning Analytics und KI in Studium und Lehre ausgestaltet werden können. Die Besonderheit: Alle lehrbezogenen Akteurinnen und Akteure wurden in einem umfassenden Ansatz einbezogen, um zu verstehen, wie Hochschulen sich als Gesamtorganisationen auf die kommenden Herausforderungen in diesem Bereich einstellen müssen. Der Band zeigt damit Wege in eine zukünftige Hochschulwelt, die nicht mehr in allzu weiter Ferne liegt.
Online Machine Learning
Dieses Buch beschreibt Theorie und Anwendungen aus dem Bereich des Online Maschine Learnings (OML), wobei der Fokus auf Verfahren des überwachten Lernens liegt. Es werden Verfahren zur Drifterkennung und -behandlung beschrieben. Verfahren zur nachträglichen Aktualisierung der Modelle sowie Methoden zur Modellbewertung werden dargestellt. Besondere Anforderungen aus der amtlichen Statistik (unbalancierte Daten, Interpretierbarkeit, etc.) werden berücksichtigt. Aktuelle und mögliche Anwendungen werden aufgelistet. Ein Überblick über die verfügbaren Software-Tools wird gegeben. Anhand von zwei Studien (“simulierten Anwendungen”) werden Vor- und Nachteile des OML-Einsatz in der Praxis experimentell analysiert.PROF. DR. THOMAS BARTZ-BEIELSTEIN ist ein Experte für KI mit über 30 Jahren Erfahrung. Als Professor für Angewandte Mathematik an der TH Köln und Leiter des Instituts für Data Science, Engineering und Analytics (IDE+A) hat er sich auf die Forschung in den Bereichen KI, maschinelles Lernen, Simulation und Optimierung spezialisiert. Seine Arbeit umfasst eine Vielzahl von Themen aus der angewandten Mathematik und Statistik, Versuchsplanung, simulationsbasierter Optimierung und Anwendungen in Bereichen wie Wasserwirtschaft, Aufzugssteuerung und Maschinenbau.EVA BARTZ ist auf KI und Datenschutz spezialisierte Juristin. Seit 2014 führt sie die angesehene Unternehmensberatung Bartz & Bartz GmbH. Diese bietet KI-basierte Lösungen für die Praxis in industriellen Anwendungen an.Die herausragende Arbeit der Unternehmensberatung führte zur Erstellung einer Expertise für das Statistische Bundesamt, aus der schließlich dieses wegweisende Buch entstand.Einleitung: Theorie und Anwendungen von Online Machine Learning.-Supervised Learning: Klassifikation und Regression.- Drifterkennung und -behandlung.- Initiale Auswahl und nachträgliche Aktualisierung von OML-Modellen.- Evaluation, Performance-Messung.- Besondere Anforderungen.- Anwendungen.- Software.- Simulierte Anwendungen.- Zusammenfassung und Ausblick.
Taming Your Dragon
Technical debt is an often-overlooked problem that the software industry needs to take more seriously. All organizations are impacted by it, most wish that they had less of it, but need help in understanding the nature of the beast. This book aims to clear up any misconceptions and show you how to implement a sound technical debt management program to suit your company’s needs.You’ll learn the greatest challenge in solving the technical debt dilemma is not to find solutions to it, but rather to find solutions to the human and organizational issues that lead to that debt. For example, convincing senior stakeholders of the importance of addressing technical debt, getting stakeholders to acknowledge how their actions lead to unintentional debt, and enabling teams to prioritize technical debt over short-term goals.Therefore, this book is divided into three parts: defining technical debt, understanding technical debt, and tackling technical debt. It begins by explaining why technical debt should not be considered a technical problem, but rather a problem of how trade-off decisions are made. You’ll then examine how making decisions using the affect heuristic, more commonly known as a “gut feeling,” can lead to unnecessary technical debt, followed by some techniques for combating your vulnerability to this trap.Reducing your organization’s level of technical debt is not easy. _Taming Your Dragon_ will show you how to implement a technical debt management program.WHAT YOU WILL LEARN* Review a new paradigm based on technical debt being a combination of trade-off problems and system problems* Understand the many ways that technical debt adversely affects an organization’s ability to deliver IT change* Create an effective process for addressing technical debt* See why analogies are importantWHO THIS BOOK IS FORSoftware teams supporting DevOps, managers, and other business stakeholderslooking to implement a technical debt management program.Andrew Richard Brown has worked in the software industry since 1999. He started as an SAP programmer fixing Y2K bugs, although he admits that he sometimes inadvertently replaced them with Y-2050 bugs. Later, he realized that the biggest problems in software development were not technical but human. What’s more, nobody had yet figured out what to do about them! Since then, he has helped teams improve their performance through understanding and addressing these problems.Andrew also coaches organizations on software development, quality engineering, and addressing issues driven by human factors. He is particularly active in addressing long-standing issues, like technical debt, risk in complex systems, and project underestimation. He investigates how software development problems are driven by cognitive biases, plus how to address them using behavioral science techniques.His research has led to new and counterintuitive insights into the true causes of software development problems, as well as fresh approaches to solving them. He is a regular speaker at international software conferences and has a growing YouTube channel dedicated to understanding these problems.Part 1: Exploring Technical Debt.- Chapter 1 What is technical debt?.- Chapter 2: Why you need to address technical debt.- Chapter 3: Why has technical debt proved so resistant to solutions?.- Part 2: Understanding the Technical Debt Problem.- Chapter 4: The broken analogy.- Chapter 5: Technical debt as a trade-off problem.- Chapter 6: Technical debt as a systems problem.- Chapter 7: Technical debt as an economics problem.- Chapter 8: Technical debt as a wicked problem.- Chapter 9: Common technical debt anti-patterns.- Part 3: Tackling Technical Debt.- Chapter 10: Convincing everyone.- Chapter 11: Modelling technical debt with system modelling tools.- Chapter 12: A program to address technical debt.- Chapter 13: Preliminary information gathering.- Chapter 14: Workshops for problem understanding.- Chapter 15: Additional information gathering.- Chapter 16: Workshops for solution development.- Chapter 17: Pilot solutions.- Chapter 18: Rollout and stabilization.- Appendix.
Mastering REST APIs
Embark on a transformative journey into the nuances of API design and implementation. This comprehensive guide will equip you with the prowess to craft APIs that exemplify excellence, optimize performance, fortify security, and elevate user experience.From grasping the core tenets of REST architecture to navigating diverse frameworks like Node.js with Express, Ruby on Rails, Django, Laravel with PHP, ASP.NET Core with C#, and Spring Boot with Java, this compendium empowers you to create APIs that set new industry benchmarks. In-depth tutorials will empower you to master data serialization, robust authentication protocols, and impervious security measures. This book also delves into the more advanced topics encompassing API governance, meticulous versioning strategies, cross-origin resource sharing (CORS) considerations, real-time capabilities, and microservices communication intricacies.You'll gain insights into vigilant monitoring, astute analytics, and optimization techniques that truly differentiate your APIs. Moreover, this book navigates the ever-evolving legal and privacy landscape confidently, ensuring compliance and upholding user trust, and provides the expertise needed to craft more efficient APIs that stand at the forefront of modern digital innovation.Presenting real-world case studies, comprehensive explanations, and practical illustrations, _Mastering REST APIs_ is your compass to navigate the complex world of web development.WHAT YOU'LL LEARN* REST architectures and how it shapes modern API development.* Effectively develop and build APIs using a diverse set of web development frameworks* Dive into advanced topics such as API governance, real-time features, microservices communication.* Review real-world case studies and hands-on examples, helping you to actively design, implement and optimize APIs.WHO THIS BOOK IS FORExperienced web developers, software engineers, and tech enthusiasts who are looking to supercharge their API development knowledge and take it to the next levelSIVA SELVARAJ work focuses on modern technologies and industry best practices. These topics include frontend development techniques using HTML5, CSS3, and JavaScript frameworks; implementing responsive web design and optimizing user experience across devices; building dynamic web applications with server-side languages such as PHP, WordPress, and Laravel; and Database management and integration using SQL and MySQL databases He loves to share his extensive knowledge and experience to empower readers to tackle complex challenges and create highly functional and visually appealing websites.1. Introduction to REST APIs.- 2. Building REST APIs with Node.js and Express.- 3. Building REST APIs with Ruby on Rails.- 4. Building REST APIs with Django.- 5. Building REST APIs with Laravel.- 6. Building REST APIs with ASP.NET Core.- 7. Building REST APIs with Spring Boot.- 8. Building REST APIs with Serverless Cloud Platforms.- 9. Advanced Topics and Case Studies.- 10. Advanced API Design Patterns and Future Trends.
Mastering GitHub Enterprise Management and Administration
This book is a comprehensive guide to GitHub Enterprise Cloud and provides a detailed overview of how to set up, manage, administer, and configure GitHub for organizations. In addition to this, you will also learn identity management and the CI/CD pipeline.The book starts with a thorough introduction to GitHub administration and its benefits. You will then learn how to set up and manage a GitHub Enterprise account and organization, guiding administrators through each step. Next, you will go through GitHub Repository Secure Management and Best Practices along with an understanding of how to manage access to GitHub using SAML SSO. GitHub enterprise support strategies and their usage and adoption are discussed next in detail. Moving ahead, you will learn about GitHub Action and Packages followed by GitHub Copilot management. How to automate repetitive tasks and workflows using GitHub Actions and enhancing productivity is discussed in detail with the help of case studies. Towards the end, you will demonstrate securing the software development lifecycle through advanced security and use GitHub Actions for automating business processes.After reading this book, you will be able to leverage the full potential of GitHub Enterprise Cloud for your software development needs.WHAT WILL YOU LEARN* How to set up and configure GitHub Enterprise for optimal collaboration, security, and scalability in an enterprise environment.* Best practices for managing organizations, repositories, and user access permissions effectively to foster efficient teamwork and code collaboration.* Strategies to implement robust CI/CD pipelines using GitHub Actions, automating build, testing, and deployment processes for faster and more reliable software delivery.* Proven techniques for ensuring top-notch security and compliance, including authentication methods, access controls, and vulnerability scanning, to protect code repositories and sensitive data.WHO IS THIS BOOK FORSoftware Development teams, DevOps engineers, and IT professionals who are looking to use GitHub Enterprise Cloud for code collaboration, management, and deployment.BALU ILAG is a Microsoft Certified Trainer (MCT), Microsoft 365 Certified Teams Administrator Associate, and Microsoft Certified Solutions Expert (MCSE) for communication and productivity. He has written several blog posts on unified communication and collaboration technologies including subjects ranging from a how-to guide to best practices and troubleshooting.He is currently working as an Office 365 and collaboration specialist at Juniper networks. Balu has over 13 years' experience in messaging, telecom and unified communications and collaboration and is focused on Microsoft Teams and Microsoft Office 365 collaboration. His role is a combination of product administration, product development, and strategic guidance for enterprise customers.Chapter 1: Introduction to GitHub Administration.- Chapter 2: GitHub Enterprise Account and Organization Setup and Administration.- Chapter 3: GitHub Repository Secure Management and Best Practices.- Chapter 4: GitHub Identity Access Management (SAML SSO and Enterprise Managed User) with User Onboarding and Offboarding.- Chapter 5: GitHub Enterprise Support and Adoption.- Chapter 6: GitHub Usage and Adoption.- Chapter 7: GitHub Action and GitHub Packages Management.- Chapter 8: GitHub Copilot Management.- Chapter 9: GitHub Monitoring and Reporting.- Chapter 10: Automate Development Tasks and Workflows with GitHub Actions.- Chapter 11: Secure Software Development Lifecycle through GitHub Advanced Security.- Chapter 12: Use GitHub Actions for Automating Business Processes.
CompTIA DataX Study Guide
DEMONSTRATE YOUR DATA SCIENCE SKILLS BY EARNING THE BRAND-NEW COMPTIA DATAX CREDENTIALIn CompTIA DataX Study Guide: Exam DY0-001, data scientist and analytics professor, Fred Nwanganga, delivers a practical, hands-on guide to establishing your credentials as a data science practitioner and succeeding on the CompTIA DataX certification exam. In this book, you'll explore all the domains covered by the new credential, which include key concepts in mathematics and statistics; techniques for modeling, analysis and evaluating outcomes; foundations of machine learning; data science operations and processes; and specialized applications of data science. This up-to-date Study Guide walks you through the new, advanced-level data science certification offered by CompTIA and includes hundreds of practice questions and electronic flashcards that help you to retain and remember the knowledge you need to succeed on the exam and at your next (or current) professional data science role. You'll find:* Chapter review questions that validate and measure your readiness for the challenging certification exam* Complimentary access to the intuitive Sybex online learning environment, complete with practice questions and a glossary of frequently used industry terminology* Material you need to learn and shore up job-critical skills, like data processing and cleaning, machine learning model-selection, and foundational math and modeling conceptsPerfect for aspiring and current data science professionals, CompTIA DataX Study Guide is a must-have resource for anyone preparing for the DataX certification exam (DY0-001) and seeking a better, more reliable, and faster way to succeed on the test. ABOUT THE AUTHORFRED NWANGANGA is a technology professional and professor in the IT, Analytics, and Operations Department within the University of Notre Dame – Mendoza College of Business. He teaches undergraduate and graduate courses in Python for Data Analytics, Machine Learning, and Unstructured Data Analytics. He has over 20 years of experience in technology management and analytics. He is the author of several LinkedIn Learning machine learning courses and the founder of the Early Bridges to Data Science Program in the Notre Dame Lucy Family Institute for Data & Society. Introduction xxiiiChapter 1 What Is Data Science? 1Chapter 2 Mathematics and Statistical Methods 25Chapter 3 Data Collection and Storage 63Chapter 4 Data Exploration and Analysis 97Chapter 5 Data Processing and Preparation 131Chapter 6 Modeling and Evaluation 167Chapter 7 Model Validation and Deployment 195Chapter 8 Unsupervised Machine Learning 225Chapter 9 Supervised Machine Learning 249Chapter 10 Neural Networks and Deep Learning 271Chapter 11 Natural Language Processing 293Chapter 12 Specialized Applications of Data Science 315APPENDIX ANSWERS TO REVIEW QUESTIONS 337Chapter 1: What Is Data Science? 338Chapter 2: Mathematics and Statistical Methods 339Chapter 3: Data Collection and Storage 341Chapter 4: Data Exploration and Analysis 343Chapter 5: Data Processing and Preparation 345Chapter 6: Modeling and Evaluation 346Chapter 7: Model Validation and Deployment 347Chapter 8: Unsupervised Machine Learning 349Chapter 9: Supervised Machine Learning 350Chapter 10: Neural Networks and Deep Learning 352Chapter 11: Natural Language Processing 353Chapter 12: Specialized Applications of Data Science 355Index 357
Next Generation Digital: Digitalisierung & KI strategisch einsetzen
Information, Anfragen, Daten, Kommunikation, Krisen werden rasch weiter zunehmen. Bei stark steigenden Anforderungen und gleichzeitigem Arbeitskräftemangel reicht es nicht, wenn wir jedes Jahr einfach nur schneller arbeiten. Wir müssen anders arbeiten.Zum InhaltEin Buch für Executives und IT-Professionals, die Digitalisierung und KI strategisch einsetzen wollen.Übersicht der für digitale Tools und KI relevanten Compliance, mit der wiederum digitale Tools und KI helfen können: NIS 2, EU AI Act, Digital Services Act, Product Liability Directive u.v.m.Scouting einer Auswahl der für betrieblichen Einsatz relevantesten Technologien und Bewertung von Nutzen und Einsatzmöglichkeiten.Strategie, wie sie sein soll, legt fest, WIE wir gewinnen werden. Das Buch führt von der systematischen Bedarfsfeststellung zur Toolwahl.Best Practice Cases runden das Werk ab.Die Abkehr von der Beliebigkeit.Die für ihre konsequent systematischen Konzepte und Strategien be-kannte Autorin wurde bereits als Top CIO des Jahres ausgezeichnet und ist in einer Reihe von nationalen und internationalen Digitalisierungs- und KI-Beiräten im Einsatz. Isabella Mader lehrt seit 15 Jahren IT-Strategie. Sie legt mit diesem Werk ein praktisches Arbeitsbuch vor, das entlang aktueller Herausforderungen zu einer rasch umsetzbaren Strategie führt.
Master Vue.js in 6 Days
Prepare for an exciting journey into the world of Vue.js. Organized into six days of learning Vue.js, this book will guide you through the key concepts needed to become a proficient developer with this versatile framework.Backed by clear explanations, concrete examples, hands-on exercises, and development tips, you’ll examine the main ingredients needed to build web user interfaces. From creating components to handling events, delving into HTTP requests, and custom directives, each day promises a new skill and practical knowledge that you can immediately apply to your projects.Whether it's for creating professional web applications or simply expanding your horizons in web development, this book will equip you with the necessary skills to excel in with Vue.js. So, dive into this adventure and become a Vue.js master in just six days!WHAT YOU’LL LEARN* Understand key Vue.js principles and concepts. * Create Reactive user interfaces.* Acquire a comprehensive understanding of the Vue.js framework.WHO THIS BOOK IS FORWeb Developers, programmers, students, and teachers who are looking to learn or brush up on Vue.jsERIC SARRION is a trainer, web developer, and an independent consultant. He has been involved in all kinds of IT projects for over 30 years. He is also a long-time author of web development technologies and is renowned for the clarity of his explanations and examples. He resides in Paris, France. Some of his recent publications include _Master React in 5 Days_ (Apress), _ChatGPT for Beginners_ (Apress), and _JavaScript from Frontend to Backend _(Packt)Chapter 1. Day 1: Mastering Components in Vue.js.- Chapter 2. Day 2: Mastering Directives in Vue.js.- Chapter 3. Day 3: Mastering Events in Vue.js.- Chapter 4. Day 4: Mastering HTTP Requests in Vue.js.- Chapter 5. Day 5: Mastering the Creation of Directives in Vue.js.- Chapter 6. Day 6: Mastering the Creation of Composables in Vue.js.- Chapter 7. JavaScript Reminders.- Chapter 8. Book Summary.
Privacy in the Age of Innovation
This book will help you comprehend the impact of artificial intelligence (AI) on information security, data privacy, and data security.The book starts by explaining the basics and setting the goals for a complete understanding of how AI, Information Security, Data Privacy, and Data Security all connect. Then, it gives you important information about the basics of AI, machine learning, and deep learning in simple terms. It also talks about the ethics of using AI in privacy and security, making sure you understand the power and responsibility that come with AI. Next, it takes you through the complex world of information security and data privacy. It covers everything from the current state of security to how AI can detect threats and protect privacy. Additionally, it delves into ethical considerations to ensure the responsible use of AI in managing data privacy. Later chapters discuss strategies and future trends in using AI for data security, finding the right balance between security and privacy, and giving useful advice for organizations.In the end, this book examines the current landscape and foresees the future, underscoring the vital importance of maintaining a balance between innovation and privacy in AI-powered security.What you will learn:* How AI is being used to detect and prevent cyberattacks in real-time* What are the AI-powered techniques for anonymizing and de-identifying data,* What are the latest advancements in AI-powered privacy-enhancing technologies (PETs)* How to find the right balance between security and privacyWho this book is for:Information security professionals, data scientists, and software developers seeking to gain an understanding of the latest trends and techniques in AI for information securityRANADEEP REDDY PALLE has over 12 years of experience and specializes in the development of distributed and scalable Microservices. His proficiency extends to deploying these Microservices on major cloud platforms like AWS and Azure, always prioritizing strict adherence to privacy and cybersecurity standards. Ranadeep has contributed extensively to journals, particularly in critical domains such as machine learning, AI, Cloud Computing, and data analytics. Holding diverse certifications in both Amazon Web Services (AWS) and Microsoft Azure, he currently serves as a Senior Software Engineer at Zoom in Austin, TX. In this role, he leads a team in implementing cutting-edge solutions and plays a crucial part in the design and development of Microservices for Consent Management, ensuring compliance with global privacy regulations. Ranadeep holds a Master's degree in Computer Science from the University of Houston, Texas.KRISHNA CHAITANYA RAO KATHALA is a prominent researcher in the field of Data Science, Analytics, Machine Learning, and AI, a Ph.D Candidate at the University of Massachusetts Amherst. With over 8 years of specialized experience in AI, Krishna's expertise covers a wide range of topics within Artificial Intelligence, including Generative AI, Ethics, Bias, Fairness, and Safe/Secure AI. He is a prolific scholar, having co-authored 2 books and secured more than 5 international patents. Additionally, Krishna has authored over 8 research papers published in prestigious journals. His influence in the academic and professional realms is widespread, often serving as a judge at more than 10 national and international events, including research symposiums and hackathons. Krishna also contributes actively to the academic community through roles on editorial boards, reviews, and program committees at various conferences. Krishna's merit in the field has led to invitations to speak at distinguished international forums such as the United Nations, the Ministry of Foreign Affairs Ukraine, UNESCO, UNDP, United Nations Women, the Office of the United Nations High Commissioner for Human Rights, and the Talent AI Foundation. His research excellence has been recognized with numerous significant awards and scholarships, highlighting his impactful contributions to AI and technology. He currently holds a leadership position as a Co-Chair at the Northeastern Educational Research Association, Inc., based in Boston, Massachusetts.Krishna is also an active member of the International Society for Technology in Education (ISTE) and the International Association of Engineers - Hong Kong. Beyond his research and professional activities, Krishna is deeply committed to mentoring, particularly focused on supporting first-generation, under-represented, and marginalized students in STEM fields. His dedication to fostering inclusivity and diversity within the tech community underscores his commitment to using his expertise to make a positive societal impact. Krishna holds a Masters degree in Data Science from University of Massachusetts Amherst.1. INTRODUCTION.- 2. UNDERSTANDING AI AND ETHICS.- 3. INFORMATION SECURITY AND DATA PRIVACY LANDSCAPE.- 4. AI FOR THREAT DETECTION AND PREVENTION.- 5. PRIVACY-PRESERVING AI TECHNIQUES.- 6. DATA PROTECTION AND COMPLIANCE.- 7. SECURING AI MODELS.- 8. CASE STUDIES.- 9. AI IN DATA PRIVACY AND ETHICS.- 10. AI AND DATA SECURITY.- 11. BALANCE BETWEEN SECURITY AND PRIVACY.- 12. BEST PRACTICES AND RECOMMENDATIONS.- 13. FUTURE TRENDS AND CHALLENGES.
Generative Artificial Intelligence
This book explains the field of Generative Artificial Intelligence (AI), focusing on its potential and applications, and aims to provide you with an understanding of the underlying principles, techniques, and practical use cases of Generative AI models.The book begins with an introduction to the foundations of Generative AI, including an overview of the field, its evolution, and its significance in today’s AI landscape. It focuses on generative visual models, exploring the exciting field of transforming text into images and videos. A chapter covering text-to-video generation provides insights into synthesizing videos from textual descriptions, opening up new possibilities for creative content generation. A chapter covers generative audio models and prompt-to-audio synthesis using Text-to-Speech (TTS) techniques. Then the book switch gears to dive into generative text models, exploring the concepts of Large Language Models (LLMs), natural language generation (NLG), fine-tuning, prompt tuning, and reinforcement learning. The book explores techniques for fixing LLMs and making them grounded and indestructible, along with practical applications in enterprise-grade applications such as question answering, summarization, and knowledge-based generation.By the end of this book, you will understand Generative text, and audio and visual models, and have the knowledge and tools necessary to harness the creative and transformative capabilities of Generative AI.WHAT YOU WILL LEARN* What is Generative Artificial Intelligence?* What are text-to-image synthesis techniques and conditional image generation?* What is prompt-to-audio synthesis using Text-to-Speech (TTS) techniques?* What are text-to-video models and how do you tune them?* What are large language models, and how do you tune them?WHO THIS BOOK IS FORThose with intermediate to advanced technical knowledge in artificial intelligence and machine learningSHIVAM SOLANKI is an accomplished Senior Advisory Data Scientist leading the AI team for a worldwide partner ecosystem to solve challenging problems using Artificial Intelligence (AI). Shivam holds a master’s degree from Texas A&M University with major coursework in Applied Statistics. Throughout his career, he has delved into various AI fields, including Machine Learning, Deep Learning, and Natural Language Processing (NLP). His expertise extends to Generative AI, where his practical experience and in-depth knowledge empower him to navigate its intricacies. As a researcher in Artificial Intelligence, Shivam has filed two patents for Machine Learning and Natural Language Processing (NLP), co-authored a book on Deep Learning, and published a paper in Generative AI.DRUPAD KHUBLANI is a skilled Senior Data Scientist and part of the revenue management team in a real estate company. His leadership in partnering with teams across marketing, call center operations, product management, customer experience, and operations has cultivated a wealth of experience, empowering him to extract actionable insights and co-create innovative solutions Drupad completed his graduate and postgraduate studies from the Indian Institute of Technology (Indian School of Mines) and Texas A&M University. Collaborating with Dr. Jean-Francois Chamberland on the development of technology to identify obstacles and gauge distances using only a monocular camera highlights Drupad's inventive approach and dedication to real-world applications, alongside his accomplishments in both the commercial and academic arenas.Chapter 1: Introduction to Generative AI.- Chapter 2: Text-to-Image Generation.- Chapter 3: From Script to Screen: Unveiling Text-to-Video Generation .- Chapter 4: Bridging Text and Audio in Generative AI.- Chapter 5: Introduction to Language Models (LLMs).- Chapter 6: Generative LLMs.- Chapter 7: Advanced Techniques for LLMs.- Chapter 8: Building Demo Applications using LLMs.- Chapter 9: Enterprise-Grade Apps using LLMs.
Digital Presences of Organizations
Organizations communicate in complex and various ways, and the context is mainly characterized by the pervasiveness of the digital ecosystem, including the Web, social networks and the Internet of data. However, its information delivery cannot overlook the requirements of multicultural communications at a variety of levels.Digital Presences of Organizations highlights the communication roadblocks faced by organizations as they emerge, arising not only from issues encountered on their own websites, but also as they construct online narratives. This multi-faceted and multi-strategy digital presence of organizations is addressed via three main thematic axes.The first focuses on differentiated strategies (content, services, interaction) that can be observed depending on the types of organizations and their users. The second examines the cultural dimension of websites, ranging from the local to the global. Finally, the third focuses on the role of narration in organizations' online communication strategies.NATHALIE PINÈDE is Professor of Information and Communication Sciences at Bordeaux Montaigne University, France.LUC MASSOU is Professor of Information and Communication Sciences at the University of Lorraine, France.PATRICK MPONDO-DICKA is a lecturer in Information and Communication Sciences at the University of Toulouse – Jean-Jaurès, France.Foreword xiiiPeter STOCKINGERIntroduction xviiNathalie PINÈDE, Luc MASSOU and Patrick MPONDO-DICKAPART 1. WEBSITES AND ORGANIZATIONAL STRATEGIES 1CHAPTER 1. WEBSITES AND THE AGENCY OF CIRCULATING ENTITIES 3Mariannig LE BÉCHEC1.1. Introduction 31.2. From website analysis to website network analysis 41.3. The concept of digital territories of brands 71.4. Conclusion 161.5. References 16CHAPTER 2. DANONE'S "DID YOU KNOW?": NARRATIVE STRATEGY AND IDENTITY DIALOGUE 21Stela RAYTCHEVA, Thierry CÔME and Gilles ROUET2.1. Introduction 212.2. Culture, strategy and narratives 232.3. Danone: storytelling of a culture 292.4. Danone's history and the use of the "Did you know?" insets on Facebook 412.5. A coherent communication strategy 452.6. Conclusion 472.7. References 49CHAPTER 3. WEBSITE AND MEDIA ETHOS: A CASE STUDY OF PHOTOGRAPHIC EQUIPMENT MANUFACTURERS 51Marion ROLLANDIN3.1. Introduction 513.2. The communication situation induced by a photographic equipment manufacturer's website 533.3. Initiating the photographic equipment manufacturer's media ethos 593.4. Media ethos and discursive strategy 633.5. Media ethos and audience segmentation 733.6. Conclusion 803.7. References 82CHAPTER 4. ANALYSES OF DIGITAL COMMUNICATION STRATEGIES FOR FAMILY CAREGIVERS 83Sébastien ROUQUETTE and Christelle CHAUZAL-LARGUIER4.1. Introduction 834.2. Methodology 854.3. Analytical corpus 874.4. The central position of websites in digital communication strategies 904.5. Websites: advantages for associative actors 944.6 Conclusion 1054.7. Appendix 1074.8. References 109CHAPTER 5. ASSOCIATIONS' ONLINE COMMUNICATION AND DISCURSIVE STRATEGIES: A CASE STUDY. 111Marcy Delsione OVOUNDAGA5.1. Introduction 1115.2. Theoretical framework 1135.3. Methodological approach 1145.4. Digital social media at the heart of organizations' new communication strategy 1185.5. Online discursive strategies at the heart of associations' social marketing 1225.6. Conclusion 1355.7. References 136PART 2. WEBSITES AND CULTURAL DYNAMICS 139CHAPTER 6. WEBSITE LOCALIZATION AND THE CULTURAL DIMENSION: PROFESSIONAL SKILLS 141Alexander FRAME and Will NOONAN6.1. Introduction 1416.2. Field-testing cultural localization: from words to action 1436.3. From (intercultural) communication to localization services 1516.4. Attempts and experiments for a complex, non-essentialist approach to cultural localization 1556.5. Conclusion 1636.6. References 165CHAPTER 7. REPRESENTATIVITY OF INDIGENOUS MINORITIES AND CULTURAL IDENTITY ON THE WEB 171Cécile-Marie MARTIN7.1. Introduction 1717.2. "Indigenous minorities", a terminology to designate without discriminating 1727.3. Web access routes for indigenous minorities 1787.4. Access strategies, from consultation to contribution 1867.5. Conclusion 1937.6. References 193CHAPTER 8. CULTURAL AND POLITICAL ANCHORS OF ENVIRONMENTAL COMMUNICATION ON THE WEB 199Sandra MELLOT, Anh Ngoc HOANG, Magali PRODHOMME and Anaïs THEVIOT8.1. Introduction 1998.2. Methodological approach: analysis of the ecological ethos in a digital regime 2028.3. Ethos of action (Greenpeace) 2088.4. Ethos of the will (WWF) 2118.5. Ethos of justice (L'Affaire du Siècle) 2148.6. Ethos of belief 2188.7. Structuring an ecological homonoia on the Web: emergency, praise and blame 2238.8. Conclusion 2278.9. References 228CHAPTER 9. COVID-19 AND DIGITAL FUNDRAISING: ACTORS, STRATEGIES AND PERSPECTIVES 231Géraud AHOUANDJINOU, Ornheilia ZOUNON, Agnès BADOU and Ismène KPÉDJO9.1. Introduction 2319.2. Theoretical and methodological framework 2339.3. Results and discussion 2469.4. Conclusion 2579.5. References 258Part 3. Communication of Organizations and Online Narrative 261CHAPTER 10. COMMUNICATING THROUGH NARRATIVE: ORGANIZATIONS FACING THE CHALLENGE OF THEIR COLLECTIVE DIMENSION? 263Julien FALGAS10.1. Introduction 26310.2. Defining the act of narrating by the storytelling, narration and story triad 26410.3. Application to the Web page analysis: the analysis framework of the manufacturing of representations 26910.4. From the manufacturing of the narration to a critique of the narrative communication of organizations on digital social networking sites 28010.5. Conclusion 28310.6. References 285CHAPTER 11. TRANSMEDIA AND ONLINE STORYTELLING: FROM EPHEMERAL UNIVERSES TO ARCHIVES 289Mélanie BOURDAA11.1. Introduction 28911.2. New term, old creations: a quick historical overview 29111.3. Evolutionary transmedia websites: a progression of and in storytelling 29311.4. Apps and social media: an engaging transmedia strategy 29911.5. Fans' archives: preserving ephemeral devices 30311.6. Conclusion 30511.7. References 306CHAPTER 12. AUGMENTED STORYTELLING AND NETFLIX SERIES PROMOTION STRATEGY 309Frédéric AUBRUN and Thomas BIHAY12.1. Introduction 30912.2. Augmented storytelling from explicit, implicit and zero textures 31212.3. Unadvertization of promotional discourse of series 31612.4. Conclusion 32212.5. References 325List of Authors 327Index 331
Game Development with Unreal Engine 5 Volume 1
Dive into the heart of game development with Unreal Engine 5 (UE5), the latest revolution in creating immersive and visually stunning game worlds. Crafted to encourage your imaginative and inventive skills, Volume 1 of this two-part guide stands as a crucial tool in your journey towards developing incredible video games with UE5 and serves as a transition into the programming dimensions of game creation with C++ featured in Volume 2.Blending artistic mastery with technical prowess, you’ll journey from the basics of UE5’s environment to creating expansive landscapes with procedural content generation and combining materials for lifelike terrains. Discover the power of Quixel Bridge and Megascans to bring realistic textures and models into your projects, and master Nanite for rendering complex scenes with cinematic fidelity.You’ll also learn to create dynamic lighting and shadow effects with Lumen, enrich your game’s atmosphere with sophisticated particle systems using Niagara. Then integrate characters and adversaries into our worlds, making them come alive with interactive elements. From designing large open landscapes to implementing advanced visual effects, _Game Development with UE 5, Volume 1 _is your gateway to elevating the visual appeal and interactive experience of your game.WHAT YOU WILL LEARN* Sculpt vast, open worlds with UE5's advanced landscape tools and Heightmaps.* Construct highly detailed environments with Nanite, achieving unparalleled visual quality without sacrificing performance.* Introduce dynamic global illumination with Lumen, crafting stunning lighting and shadow effects that respond to changes in the game world in real-time.* Implement Real-Time Virtual Textures to significantly enhance texture streaming efficiency in large-scale environments.* Use Procedural Content Graph to populate your game worlds with dynamic, lifelike vegetation that adds depth and realism to your landscapes.* Explore Niagara's powerful visual effects system to create complex and captivating effects that elevate the aesthetic appeal of your game.WHO THIS BOOK IS FORGame developers who want to learn how to use Unreal Engine 5 would benefit from this book.Dr. Tiow Wee Tan is an Associate Professor at Department of Game Department, Inland Norway University of Applied Science (INN), Norway. He is also serves as the Course Co-ordinator for the Augmented and Virtual Reality Add-On Program at the Game School.Tiow Wee's interests revolve around the development of Extended Reality (XR) for cross-disciplinary enterprise application. He was actively participated in projects on Neural Networks and Artificial Intelligent (AI) for gaming. Some of his works focus on the utilization of AR & VR technology within games engine; the creation of hybrid version of AR and VR research application for healthcare, art, and tourism; and the exploration of cognitive aspects in human-computer interaction environments, integrated into neural network systems.Chapter 1. Getting Started with Unreal Engine 5.- Chapter 2. From Heightmap to Large Open World Landscape.- Chapter 3.- Auto-Blend Landscape Materials.- Chapter 4. Revitalizing Visuals: Asset Import and Procedural Creation.- Chapter 5. Enhancing Visual Realism with Realtime Virtual Textures and Material Blending.- Chapter 6. Mastering Lumen Global Illumination in Unreal Engine 5.- Chapter 7. Harnessing the Power of Niagara: Practical Examples in Unreal Engine 5.