Computer und IT
CompTIA A+ (7. Auflage)
Alle Inhalte der A+-Prüfungen für PC-Techniker ausführlich erläutert mit praktischen Übungsfragen und ExamenstippsPraxiswissen für Systemadministration und Wartung von Hardware, Betriebssystemen und Netzwerken sowie Sicherheit und SupportHandbuch und Nachschlagewerk für Berufseinstieg und Arbeitsalltag Die CompTIA A+-Zertifizierung richtet sich an alle, die in einem technischen Unternehmen mit regelmäßigem Kundenkontakt arbeiten oder zukünftig arbeiten möchten, egal, ob sie Supporter, Betriebstechniker, Kundendiensttechniker oder PC-Techniker sind. Anschaulich und übersichtlich führt Sie Markus Kammermann in diesem Buch in die Bereiche Hardware, Netzwerk, ICT-Support, Betriebssysteme und Sicherheit ein. Zudem bereitet er Sie mit ausführlichen Informationen und Beispielfragen zu den CompTIA A+-Prüfungen optimal auf die Anforderungen einer Zertifizierung vor. Dieses Buch behandelt sowohl die in der Prüfung 220-1201 als auch die in der Prüfung 220-1202 abgehandelten Wissensgebiete.In der Prüfung 220-1201 geht es um: Mobile GeräteNetzwerkeHardwareVirtualisierung und Cloud ComputingFehlerbehebung bei Hardware und Netzwerken In der Prüfung 220-1202 geht es um: Unterschiedliche BetriebssystemeSicherheitSoftware-FehlerbehebungOperative Arbeitsabläufe Die genannten Themenbereiche werden ausführlich vermittelt, damit Sie das für die Zertifizierung notwendige Wissen erhalten und ein praxistaugliches Verständnis für die Thematik entwickeln. Mit diesem verständlich geschriebenen und praxisnahen Buch werden Sie nicht nur die A+-Zertifizierung erfolgreich meistern, sondern ebenso ausgezeichnet auf Ihre Tätigkeit als PC-Techniker vorbereitet sein.Aus dem Inhalt: Vom Bit zum Personal ComputerEinblick in die SystemarchitekturSystembusse und BussystemeAktuelle SchnittstellenInterne und externe GeräteEin- und AusgabegeräteDruckersysteme und -methodenOrganisatorische Grundlagen für den SupportOperative Prozesse im Umfeld des SupportsBevor Sie loslegen – konkrete SupportvorbereitungHardware auf- und umrüstenMobile Systeme unterhaltenVirtualisierung und Cloud ComputingKommunikation im SupportDer Einsatz von NetzwerkprotokollenHardware und Aufbau eines NetzwerksNetzwerke konfigurierenNetzwerkunterhalt und FehlersucheInstallation und Konfiguration von Windows-SystemenManagement von Windows 10 und Windows 11Windows unterhalten und Fehler behebenInstallation und Konfiguration von Linux-DesktopsystemenAufbau und Konfiguration von MacOSDie Welt ist böse – lernen Sie, sich zu schützenSicherheitsmaßnahmen realisierenSysteme und Netzwerke schützenDatenschutz und DatensicherungDie neue Welt der KIDie CompTIA A+-PrüfungenBeispielfragen und -antworten Markus Kammermann ist seit mehr als fünfundzwanzig Jahren in der Systemtechnik tätig und fast ebenso lange als Ausbilder und Autor. Dies ist bereits die sechste Auflage seines Buches, in dem er sich mit dem Innenleben von Hardware, Betriebssystemen und Netzwerken beschäftigt.
Quantum Computing and Machine Learning for 6G
Secure your expertise in the next frontier of wireless technology with this essential book, which provides a deep dive into the integration of machine learning and quantum computing to build the necessary infrastructure for 6G communication networks. Despite the potential benefits of 6G, the technology to enable its realization is not yet available. As a result, the development of technology to solve these challenges must be met before we can start working towards 6G. The primary applications of machine learning within 6G are to create necessary infrastructure advantages as the technology matures. Additionally, 6G communication networks use quantum computing to detect, mitigate, and prevent security vulnerabilities. By integrating machine learning and quantum computing into 5G and 6G technology, intelligent base stations will be able to make decisions for themselves, and mobile devices will be able to create dynamically adaptable clusters based on learned data. This book highlights the role of real-time network learning and the integration of quantum computing, machine learning, and quantum machine learning to enhance service quality. It provides a deep dive into the interplay of these technologies within 6G networks, starting from 5G fundamentals. The book elaborates on how these advanced technologies will underpin 6G’s architecture to meet comprehensive service demands, including those for smart city applications requiring extensive coverage, ultra-low latency, and reliable connectivity. The book details how the synergy between quantum computing, machine learning, and 6G technologies will transform communications, revolutionize markets, and enable groundbreaking applications globally. Readers will find the volume: Explores real-world scenarios for illustrating the integration of quantum computing and machine learning in 6G;Covers an extensive range of applications to illustrate the full picture of 6G that implements machine learning and quantum computing approaches;Offers expert insights through a comprehensive collection of literature reviews and research articles;Introduces the interdisciplinary innovations and potential of 6G across multiple industries. Audience Scientists, industry professionals, researchers, academicians, instructors, and students working in quantum computing and machine learning, especially in the context of advanced wireless communication technology. Pallavi Sapkale, PhD is an Assistant Professor, Ramrao Adik Institute of Technology, D.Y. Patil University, Navi Mumbai, Maharashtra, India, with more than 17 years of experience. She has published four books, more than 25 research articles in various international journals and conferences, four international patents, and 12 Indian patents. Her research focuses on quantum computing, machine learning, wireless communication, 5G mobility management, and next-generation networks like 6G. Shilpa Mehta, PhD is a Teaching Assistant at the Auckland University of Technology, New Zealand, with more than five years of teaching experience. She has worked on various interdisciplinary research projects and edited several internationally published books. Her research interests include radio frequency integrated circuits, RF front ends, optimization, Internet of Things, wireless communication, artificial intelligence, healthcare, radars, and smart cities. S. Balamurugan, PhD is the Director of Albert Einstein Engineering and Research Labs, Coimbatore, Tamilnadu, India. He has published more than 60 books, 300 articles in national and international journals and conferences, and 200 patents. He is also the Vice-Chairman of Renewable Energy Society of India (RESI). He also serves as a research consultant for many companies, startups, and micro-, small, and medium enterprises.
AI for Cybersecurity
Informative reference on the state of the art in cybersecurity and how to achieve a more secure cyberspace AI for Cybersecurity presents the state of the art and practice in AI for cybersecurity with a focus on four interrelated defensive capabilities of deter, protect, detect, and respond. The book examines the fundamentals of AI for cybersecurity as a multidisciplinary subject, describes how to design, build, and operate AI technologies and strategies to achieve a more secure cyberspace, and provides why-what-how of each AI technique-cybersecurity task pair to enable researchers and practitioners to make contributions to the field of AI for cybersecurity. This book is aligned with the National Science and Technology Council’s (NSTC) 2023 Federal Cybersecurity Research and Development Strategic Plan (RDSP) and President Biden’s Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence. Learning objectives and 200 illustrations are included throughout the text. Written by a team of highly qualified experts in the field, AI for Cybersecurity discusses topics including: Robustness and risks of the methods covered, including adversarial ML threats in model training, deployment, and reusePrivacy risks including model inversion, membership inference, attribute inference, re-identification, and deanonymizationForensic and formal methods for analyzing, auditing, and verifying security- and privacy-related aspects of AI componentsUse of generative AI systems for improving security and the risks of generative AI systems to securityTransparency and interpretability/explainability of models and algorithms and associated issues of fairness and bias AI for Cybersecurity is an excellent reference for practitioners in AI for cybersecurity related industries such as commerce, education, energy, financial services, healthcare, manufacturing, and defense. Fourth year undergraduates and postgraduates in computer science and related programs of study will also find it valuable. Houbing Herbert Song is Professor at the Department of Information Systems, University of Maryland, Baltimore County (UMBC). Elisa Bertino is Samuel D. Conte Distinguished Professor at the Department of Computer Science, Purdue University. Alvaro Velasquez is a program manager in the Innovation Information Office (I2O) of the Defense Advanced Research Projects Agency (DARPA) and an assistant professor at the University of Colorado Boulder. Huihui Helen Wang is a teaching professor and director of computing programs in the Khoury College of Computer Sciences at Northeastern University, based in Arlington. Yan Shoshitaishvili is an Associate Professor at Arizona State University. Sumit Kumar Jha is Eminent Scholar Chaired Professor of Computer Science at Florida International University (FIU).
AI Trust, Risk, and Security Management
For industry practitioners, academic researchers, and governance professionals alike, this book offers both clarity and depth in one of the most important domains of modern technology. As AI matures, trust and risk management will define its success—and this book lays the groundwork for achieving that vision. As AI continues to permeate sectors ranging from healthcare to finance, ensuring that these systems are not only powerful but also accountable, transparent, and secure, is more critical than ever. This book offers a vital exploration into the intersection of trustworthiness, risk mitigation, and security governance in artificial intelligence systems, serving as a definitive guide for professionals, researchers, and policymakers striving to build, deploy, and manage AI responsibly in high-stakes environments. Using a comprehensive approach, it explores how to integrate technical safeguards, organizational practices, and regulatory alignment to manage the unique risks posed by AI, including algorithmic bias, data misuse, adversarial attacks, and opaque decision-making. The result is a strategic approach that not only identifies vulnerabilities, but also promotes resilient, auditable, and trustworthy AI ecosystems. At its core, AI TRiSM is a forward-looking concept that embraces the realities of AI in production environments. The framework moves beyond traditional static models of governance to propose dynamic, adaptive controls that evolve alongside AI systems. Through real-world case studies, the book outlines how tools like model cards, bias audits, and zero-trust architectures can be embedded into the AI development lifecycle. Readers will find the volume: Introduces concepts to stay ahead of regulations and build trustworthy AI systems that customers and stakeholders can rely on;Addresses security threats, bias, and compliance gaps to avoid costly AI failures;Explores proven frameworks and best practices to deploy AI responsibly and strategies to outperform;Provides comprehensive guidance through real-world case studies and contributions from industry and academia. Audience AI and machine learning engineers, data scientists, cybersecurity and risk management specialists, academics, researchers, and policymakers specializing in AI ethics, security, and risk management. R. Karthick Manoj, PhD is an Assistant Professor at the Academy of Maritime Education and Training Tamil Nadu, India, with more than 14 years of experience. His scholarly contributions include six national and twelve international journal articles, four patents, three books, ten book chapters, and more than fifteen conference presentations. S. Senthilnathan, PhD is an Assistant Professor in the Department of Electronics and Communication Engineering in the School of Engineering and Technology at Christ University, Bangalore, India. His research interests include quantum dot cellular automata and quantum computing. S. Arunmozhi Selvi, PhD is a Professor in the Holy Cross Engineering College, Anna University, Tamil Nadu, India with more than 15 years of research and teaching experience. She has published 30 articles in international journals and conference proceedings and written many book chapters. T. Ananth Kumar, PhD is an Associate Professor in the Department of and Computer Science and Engineering, IFET College of Engineering, Tamil Nadu, India. He has authored one book, edited six books and several book chapters, and presented papers in various national and international journals and conferences. S. Balamurugan, PhD is the Director of Research at iRCS, an Indian Technological Research and Consulting, Coimbatore India. He has published 100 books, 300 papers in international journals and conferences, and 300 patents. With 20 years of experience researching various cutting-edge technologies, he provides expert guidance in technology forecasting and decision making for leading companies and startups.
Einstieg in C# mit Visual Studio 2026 (8. Auflg.)
Sie möchten das Programmieren mit C# lernen? Dann führt Sie dieses Buch schnell und sicher zum Ziel. Anhand anschaulicher und leicht nachvollziehbarer Beispiele werden alle wichtigen Themen erläutert: Grundlagen zu Variablen, Operatoren, Schleifen und Co., objektorientierte Programmierung, Fehlerbehandlung, Erstellen von Datenbankanwendungen. Auch in die Entwicklung von GUIs mit der Windows Presentation Foundation werden Sie eingeführt. Ausführliche Schritt-für-Schritt-Anleitungen und regelmäßige Zusammenfassungen sichern Ihren Lernerfolg. Die praktische Umsetzung können Sie mit zahlreichen Übungsaufgaben trainieren. Aus dem Inhalt: C#-SprachgrundlagenEinführung in die Windows-ProgrammierungObjektorientierte ProgrammierungWichtige KlassenFehlerbehandlungDatenbank-AnwendungenZeichnen mit GDI+Einführung in Windows Presentation FoundationVerteilung von Programmen
iPhone für Senioren
Lernen Sie, Ihr iPhone von Anfang an sicher in Betrieb zu nehmen und seine Apps richtig zu nutzen – alles wird ganz einfach Schritt für Schritt erklärt und an extra großen Bildausschnitten gezeigt. Die erfahrenen Autoren helfen Ihnen von Anfang an über alle nur denkbaren Stolpersteine hinweg, halten so manchen nützlichen Rat für den iPhone-Alltag für Sie bereit und trainieren auch Ihre Fingerfertigkeit auf dem Touchdisplay und der virtuellen Tastatur. So wird Ihr iPhone bald zu einem vertrauten und unentbehrlichen Begleiter. Aus dem Inhalt: Neu oder gebraucht – welches iPhone passt zu mir?Mobilfunkanbieter, Tarife und Roaming im AuslandDas iPhone einrichten: WLAN, Fingerabdruck und GesichtserkennungDie Knöpfe und Schalter am iPhoneKlicken, Drücken, Tippen, Wischen auf dem berührungsempfindlichen BildschirmAlle Apps richtig bedienenSprachanrufe und VideotelefonateTextnachrichten, WhatsApp und E-MailsFotos, Videos und MusikEinstellungen rund um die SicherheitDaten in der iCloud sichernPraktisches Zubehör anschließenWenn nichts mehr geht: Fehler selbst beheben
RP2040 Assembly Language Programming
Learn to program the Raspberry Pi Pico’s dual ARM Cortex M0+ CPUs in Assembly Language. The Pico contains a customer System on a Chip (SoC) called the RP2040, making it the Foundation’s first entry into the low-cost microcontroller market. The RP2040 contains a wealth of coprocessors for performing arithmetic as well as performing specialized I/O functionality. This book will show you how these CPUs work from a low level, easy-to-learn perspective. There are eight new Programmable I/O (PIO) coprocessors that have their own specialized Assembly Language supporting a wide variety of interface protocols. You'll explore these protocols and write programs or functions in Assembly Language and interface to all the various bundled hardware interfaces. Then go beyond working on your own board and projects to contribute to the official RP2040 SDK. Finally, you'll take your DIY hardware projects to the next level of performance and functionality with more advanced programming skills. For this New Edition The new edition of the book would now incorporate all new features: the new Raspberry Pi Pico 2 with the RP2350 CPU that includes floating point and other advanced instructions. Further, the Raspberry Pico SDK has been updated quite a bit including Visual Studio Code support. What You'll Learn Read and understand the Assembly Language code that is part of the Pico’s SDKIntegrate Assembly Language and C code together into one programInterface to available options for DIY electronics and IoT projects Who This Book Is For Makers who have already worked with microcontrollers, such as the Arduino or Pico, programming in C or Python. Those interested in going deeper and learning how these devices work at a lower level, by learning Assembly Language.
Autodesk Revit 2026
Architekturkonstruktionen vom Grundriss bis zum 3D-Modell und PlotDie wichtigsten Konstruktions- und Bearbeitungsbefehle mit zahlreichen BeispielenPraxisnahe Beispielkonstruktion: Einfamilienhaus vom Keller bis zum Dach Fundierte und praxisnahe Einführung Dieses Grundlagen- und Lehrbuch zeigt Ihnen die typischen Befehle der Architektursoftware Revit 2026 anhand einer vollständigen Beispielkonstruktion sowie kleiner Demonstrationsbeispiele. Der Autor richtet sich insbesondere an Revit-Neulinge, die einen fundierten, praxisnahen Einstieg suchen. Sie können sofort beginnen und in Kürze Ihre ersten Grundrisse und Häuser erstellen. Für jedes Kapitel finden Sie Testfragen mit dazugehörigen Lösungen. Zahlreiche Praxisbeispiele Die wichtigsten Vorgehensweisen bei der Konstruktion werden sowohl mit einem vollständigen Projektbeispiel als auch anhand vieler Detailbeispiele erklärt und geübt. Bei Revit ist es besonders wichtig, die verschiedenen Befehlsoptionen und Bedienelemente über Beispiele kennenzulernen, weil dabei stets die Element-Eigenschaften und Typvorgaben sowie die Einstellungen der Optionsleiste und der Eingabeaufforderungen beachtet werden müssen. Alle wichtigen Konstruktionsmethoden Neben der traditionellen Konstruktionsweise für einzelne Stockwerke mit Wänden, Türen, Fenstern, Geschossdecken, Treppen und Dächern wird auch das konzeptionelle Design vorgestellt, bei dem als Basis die Gebäudeform als Volumenkörper entworfen wird. Schließlich wird die Erstellung eigener Architekturkomponenten mithilfe des Familieneditors demonstriert. Aus dem Inhalt: Installation und BenutzeroberflächeElemente in andere Geschosse kopierenBearbeitungsfunktionen zum Ändern und AnpassenBemaßung und Beschriftung im Grundriss und im SchnittAusrichtung des Projekts: Gelände, Himmelsrichtung, HöheAußen-, Innen-, Detail- und SchnittansichtenStützen, Träger, Streben sowie Einführung in den StahlbauVerschiedene DachformenFotorealistische Darstellungen mit RendernAuswertungen mit Raumstempeln und ElementlistenWege über Routen-Analyse bestimmenAusgabe mehrerer Pläne und Ansichten als PDFAlternatives konzeptionelles DesignEinführung in den FamilieneditorBIM-Austausch von und zu Inventor Zum Download: Vollständig dokumentiertes Beispielprojekt: Einfamilienhaus Detlef Ridder gibt Schulungen zu AutoCAD, Inventor, Revit und Archicad sowie CNC und hat bereits zahlreiche Bücher zu diesen Themen veröffentlicht.
Quantum Computing and Machine Learning for 6G
Secure your expertise in the next frontier of wireless technology with this essential book, which provides a deep dive into the integration of machine learning and quantum computing to build the necessary infrastructure for 6G communication networks. Despite the potential benefits of 6G, the technology to enable its realization is not yet available. As a result, the development of technology to solve these challenges must be met before we can start working towards 6G. The primary applications of machine learning within 6G are to create necessary infrastructure advantages as the technology matures. Additionally, 6G communication networks use quantum computing to detect, mitigate, and prevent security vulnerabilities. By integrating machine learning and quantum computing into 5G and 6G technology, intelligent base stations will be able to make decisions for themselves, and mobile devices will be able to create dynamically adaptable clusters based on learned data. This book highlights the role of real-time network learning and the integration of quantum computing, machine learning, and quantum machine learning to enhance service quality. It provides a deep dive into the interplay of these technologies within 6G networks, starting from 5G fundamentals. The book elaborates on how these advanced technologies will underpin 6G’s architecture to meet comprehensive service demands, including those for smart city applications requiring extensive coverage, ultra-low latency, and reliable connectivity. The book details how the synergy between quantum computing, machine learning, and 6G technologies will transform communications, revolutionize markets, and enable groundbreaking applications globally. Readers will find the volume: Explores real-world scenarios for illustrating the integration of quantum computing and machine learning in 6G;Covers an extensive range of applications to illustrate the full picture of 6G that implements machine learning and quantum computing approaches;Offers expert insights through a comprehensive collection of literature reviews and research articles;Introduces the interdisciplinary innovations and potential of 6G across multiple industries. Audience Scientists, industry professionals, researchers, academicians, instructors, and students working in quantum computing and machine learning, especially in the context of advanced wireless communication technology. Pallavi Sapkale, PhD is an Assistant Professor, Ramrao Adik Institute of Technology, D.Y. Patil University, Navi Mumbai, Maharashtra, India, with more than 17 years of experience. She has published four books, more than 25 research articles in various international journals and conferences, four international patents, and 12 Indian patents. Her research focuses on quantum computing, machine learning, wireless communication, 5G mobility management, and next-generation networks like 6G. Shilpa Mehta, PhD is a Teaching Assistant at the Auckland University of Technology, New Zealand, with more than five years of teaching experience. She has worked on various interdisciplinary research projects and edited several internationally published books. Her research interests include radio frequency integrated circuits, RF front ends, optimization, Internet of Things, wireless communication, artificial intelligence, healthcare, radars, and smart cities. S. Balamurugan, PhD is the Director of Albert Einstein Engineering and Research Labs, Coimbatore, Tamilnadu, India. He has published more than 60 books, 300 articles in national and international journals and conferences, and 200 patents. He is also the Vice-Chairman of Renewable Energy Society of India (RESI). He also serves as a research consultant for many companies, startups, and micro-, small, and medium enterprises.
Generative Artificial Intelligence for Next-Generation Security Paradigms
Fortify your digital defenses with this essential book, which provides a roadmap for moving beyond the limitations of traditional encryption by leveraging generative AI algorithms to proactively anticipate, detect, and mitigate the next generation of cyber threats in real-time. In recent years, encryption has shown limitations as the sole safeguard against cyber threats in an increasingly interconnected world. While encryption remains a crucial component of cybersecurity, it is no longer sufficient to combat the evolving tactics of malicious actors. This book advocates for a paradigm shift towards leveraging generative AI algorithms to anticipate, detect, and mitigate emerging threats in real-time. Through detailed case studies and practical examples, the book illustrates how these AI-driven approaches can augment traditional security measures, providing organizations with a proactive defense against cyberattacks. It explores the connections between artificial intelligence and cybersecurity, exploring how generative AI technologies can revolutionize security paradigms beyond traditional encryption methods. Authored by leading experts in both AI and cybersecurity, the book presents a comprehensive examination of the challenges facing modern digital security and proposes innovative solutions grounded in generative AI. By combining theoretical frameworks with actionable insights, this book serves as a roadmap for organizations looking to fortify their defenses in an era of unprecedented cyber threats, making it an essential resource for anyone invested in the evolving landscape of cybersecurity and AI. Fortify your digital defenses with this essential book, which provides a roadmap for moving beyond the limitations of traditional encryption by leveraging generative AI algorithms to proactively anticipate, detect, and mitigate the next generation of cyber threats in real-time. In recent years, encryption has shown limitations as the sole safeguard against cyber threats in an increasingly interconnected world. While encryption remains a crucial component of cybersecurity, it is no longer sufficient to combat the evolving tactics of malicious actors. This book advocates for a paradigm shift towards leveraging generative AI algorithms to anticipate, detect, and mitigate emerging threats in real-time. Through detailed case studies and practical examples, the book illustrates how these AI-driven approaches can augment traditional security measures, providing organizations with a proactive defense against cyberattacks. It explores the connections between artificial intelligence and cybersecurity, exploring how generative AI technologies can revolutionize security paradigms beyond traditional encryption methods. Authored by leading experts in both AI and cybersecurity, the book presents a comprehensive examination of the challenges facing modern digital security and proposes innovative solutions grounded in generative AI. By combining theoretical frameworks with actionable insights, this book serves as a roadmap for organizations looking to fortify their defenses in an era of unprecedented cyber threats, making it an essential resource for anyone invested in the evolving landscape of cybersecurity and AI. Santosh Kumar Srivastava, PhD is an Associate Professor in the Department of Applied Computational Science and Engineering at the GL Bajaj Institute of Technology and Management with more than 21 years of experience. He has published more than 15 papers in reputed national and international journals and conferences and five patents. He is a distinguished researcher in the areas of computer networking, wireless technology, network security, and cloud computing. Durgesh Srivastava, PhD is an Associate Professor in the Chitkara University Institute of Engineering and Technology at Chitkara University with more than 14 years of academic and research experience. He has published more than 30 papers in reputed national and international journals and conferences, as well as several books and patents. His research interests include machine learning, soft computing, pattern recognition, and software engineering, modeling, and design. Manoj Kumar Mahto, PhD is an Assistant Professor at BRCM College of Engineering and Technology. Bahal, Haryana, India. He has published more than 15 journal articles, ten book chapters, and three patents. His research interests encompass AI and machine learning, image processing, and natural language processing. Ben Othman Soufiane, PhD works in the Programming and Information Center Research Laboratory associated with the Higher Institute of Informatics and Techniques of Communication. He has published more than 70 papers in reputed international journals, conferences, and book chapters. His research focuses on the Internet of Medical Things, wireless body sensor networks, wireless networks, artificial intelligence, machine learning, and big data. Praveen Kantha, PhD is an Associate Professor in the School of Engineering and Technology at Chitkara University. He is the author of 20 research papers published in national and international journals and conferences, several book chapters, and two patents. His research interests include machine learning, intrusion detection, big data analytics, and autonomous and connected vehicles.
Context-based Modeling of Activity in Real-World Projects
Context-based Modeling of Activity in Real-World Projects presents a synthesis of 25 years of research on modeling and using context in real-world applications in a very large spectrum of domains, which allows us to illustrate the keystone aspects of context from an initial operational definition; this opens up a four-level framework under conceptual, operational, implementation and environment aspects of activity modeling. The result is the Contextual-Graphs (CxG) formalism, thanks to strong connections between context and an actor’s focus of attention, leading to a uniform representation of knowledge, reasoning and context for actor and group activity. The results of this research constitute the building blocks for designing future types of AI systems, namely the context-based intelligent assistant systems. This book presents the proceduralized context as a new definition of context, that is a real-time definition, which is then applied to context modeling for actor or group activity – before finally elaborating the two versions of the CxG formalism including uses in different modeling. Patrick Brézillon works in artificial intelligence. His research includes a four-level scientific approach leading to contextual-graph formalism, a real-time definition of context. His objective is the design of context-based intelligent assistant systems.
Adversarial Machine Learning
Enables readers to understand the full lifecycle of adversarial machine learning (AML) and how AI models can be compromised Adversarial Machine Learning is a definitive guide to one of the most urgent challenges in artificial intelligence today: how to secure machine learning systems against adversarial threats. This book explores the full lifecycle of adversarial machine learning (AML), providing a structured, real-world understanding of how AI models can be compromised—and what can be done about it. The book walks readers through the different phases of the machine learning pipeline, showing how attacks emerge during training, deployment, and inference. It breaks down adversarial threats into clear categories based on attacker goals—whether to disrupt system availability, tamper with outputs, or leak private information. With clarity and technical rigor, it dissects the tools, knowledge, and access attackers need to exploit AI systems. In addition to diagnosing threats, the book provides a robust overview of defense strategies—from adversarial training and certified defenses to privacy-preserving machine learning and risk-aware system design. Each defense is discussed alongside its limitations, trade-offs, and real-world applicability. Readers will gain a comprehensive view of today?s most dangerous attack methods including: Evasion attacks that manipulate inputs to deceive AI predictions Poisoning attacks that corrupt training data or model updates Backdoor and trojan attacks that embed malicious triggersPrivacy attacks that reveal sensitive data through model interaction and prompt injectionGenerative AI attacks that exploit the new wave of large language models Blending technical depth with practical insight, Adversarial Machine Learning equips developers, security engineers, and AI decision-makers with the knowledge they need to understand the adversarial landscape and defend their systems with confidence. Enables readers to understand the full lifecycle of adversarial machine learning (AML) and how AI models can be compromised Adversarial Machine Learning is a definitive guide to one of the most urgent challenges in artificial intelligence today: how to secure machine learning systems against adversarial threats. This book explores the full lifecycle of adversarial machine learning (AML), providing a structured, real-world understanding of how AI models can be compromised—and what can be done about it. The book walks readers through the different phases of the machine learning pipeline, showing how attacks emerge during training, deployment, and inference. It breaks down adversarial threats into clear categories based on attacker goals—whether to disrupt system availability, tamper with outputs, or leak private information. With clarity and technical rigor, it dissects the tools, knowledge, and access attackers need to exploit AI systems. In addition to diagnosing threats, the book provides a robust overview of defense strategies—from adversarial training and certified defenses to privacy-preserving machine learning and risk-aware system design. Each defense is discussed alongside its limitations, trade-offs, and real-world applicability. Readers will gain a comprehensive view of today???s most dangerous attack methods including: Evasion attacks that manipulate inputs to deceive AI predictions Poisoning attacks that corrupt training data or model updates Backdoor and trojan attacks that embed malicious triggersPrivacy attacks that reveal sensitive data through model interaction and prompt injectionGenerative AI attacks that exploit the new wave of large language models Blending technical depth with practical insight, Adversarial Machine Learning equips developers, security engineers, and AI decision-makers with the knowledge they need to understand the adversarial landscape and defend their systems with confidence. Jason Edwards, DM, CISSP, is an accomplished cybersecurity leader with extensive experience in the technology, finance, insurance, and energy sectors. Holding a Doctorate in Management, Information Systems, and Technology, Jason specializes in guiding large public and private companies through complex cybersecurity challenges. His career includes leadership roles across the military, insurance, finance, energy, and technology industries. He is a husband, father, former military cyber officer, adjunct professor, avid reader, dog dad, and popular on LinkedIn.
Umweltinformationssysteme - Digitale Innovationen für eine nachhaltige Zukunft
Der neueste Stand der Forschung und Entwicklung auf dem Gebiet der Umweltinformatik (UI) und umweltbezogener IT-Anwendungsbereiche wird in diesem Tagungsband präsentiert und kritisch diskutiert. Dies umfasst sowohl Konzepte und Anwendungen von Umweltinformationssystemen als auch Technologien, die moderne Umweltinformationssysteme unterstützen und ermöglichen.
Practical Playwright Test
Gain cutting-edge skills in crafting reliable, efficient end-to-end tests with Playwright Test. This book is your comprehensive guide to Playwright Test that will help you to create and debug blazing fast tests, and integrate and customize Playwright Test to fit your testing needs. The book begins with an introduction to Playwright and teaches you the fundamentals of how to write tests efficiently. The book then gets into concepts like Locators and explains how to set up a CI using Playwright Test. After this, you will gain experience in two important aspects of testing – speed and customization. You will then be taken through a deep dive into Fixtures followed by an exploration of strategies like mocking and emulation through which you can achieve more control of the testing environment. The book also provides a detailed discussion on flakiness and how Playwright Test can help you with it. It then teaches you how to automate tests and ends with a discussion on how Playwright Test changes the landscape of testing, and how to integrate it in your daily practices and testing strategy. By reading this book, you will become an expert in the specificities of Playwright Test and how to test critical user flows, reduce bugs in production, and ultimately ship reliable software with confidence. What You Will Learn Create and debug reliable end-to-end tests efficiently with the perfect locatorsSet up a CI using Playwright Test to get results, test reports and useful tracesUnderstand how to use and write FixturesCustomize Playwright to fit your needs Who This Book Is For Frontend developers, full-stack developers, QA Engineers, Software Testers, Test Automation Engineers, QA Leads and QA Managers
The LearnEdge(TM) Perspective
Decision Intelligence integrates five elements: 1. Facts under your control. 2. Facts outside of your control. 3. Outcomes expected. 4. Transformation engine. 5. A feedback loop. The essence of success.
Introduction to Programming for Researchers
Enhance your computational and programming skills using Bash and Python to improve productivity and efficiency in research projects. This book is an essential guide for STEM researchers. Structured into several parts, each builds on the previous ones to ensure a solid foundation in programming. You’ll begin with the basics of digital computation and operating systems, then write pipelines and scripts in Bash, focusing on tools for working with datasets in text files. After introducing algorithms and floating-point numbers, the book transitions to Python, emphasizing SciPy libraries and built-in features like type hints and f-strings. IPython and Jupyter notebooks are integrated into the lessons throughout. Programming best practices are taught, alongside programming basics. These include documentation and unit testing. As the target audience is STEM students and professionals, examples make heavy use of datasets and the SciPy software stack, especially NumPy, Matplotlib, Pandas, and SymPy. Introduction to Programming for Researchers will foster a deeper understanding of computational tools and critical programming skills, empowering you to tackle complex datasets and enhance their research capabilities. What You Will Learn Apply programming skills to enhance research productivity and efficiency.Write Bash pipelines and executable scripts.Implement basic algorithms in Python, focusing on time efficiency and structured programming. Who This Book Is For Experienced researchers looking to improve their computational skills; students in the natural sciences and engineering; scientists and engineers from various fields, seeking to integrate programming skills into their research methodologies.
GameMaker Programming Challenges
Upgrade your GameMaker programming skills with 500 programming challenges. The book is a collection of programming challenges, covering a range from simple to advanced concepts. GameMaker is a hugely popular tool and is regarded one of the best approaches for 2D games. GameMaker allows both visual and code-based approach for game development and has been used for multiple hit titles. Each chapter covers a certain programming element, such as Sprite Fonts, Projectiles, Mechanics, etc. The book is designed in a manner where each challenge provides an outline of the problems, useful functions, hints on tackling the challenge, and an example solution. On completion, you will take away new knowledge of GameMaker functions, an ability to think logically when developing code, and a better understanding of game design and planning. What You Will Learn Study the new GML, from basic functions to more evolved concepts.Gain ability to view example solutions when necessary.Increase your understanding of game design concepts. Who Is This Book For Beginners to intermediate level readers with basic understanding of GameMaker’s IDE, including creating object, sprite, and sound assets will benefit from this book.
Regenerative Zukünfte und künstliche Intelligenz
Dieses Buchprojekt erscheint in drei Teilen mit jeweils einem inhaltlichen Schwerpunkt – PLANET, PEOPLE, PROFIT – und beschäftigt sich übergreifend mit den Nachhaltigkeitszielen der Vereinten Nationen (Sustainable Development Goals, SDGs). Dieser dritte Band behandelt die ökonomische Dimension der Nachhaltigkeit und umfasst Beiträge, die explizit oder implizit SDGs mit Wirtschaftsbezug thematisieren. Die Beiträge und Grußworte international renommierter Expert:innen aus Wissenschaft und Praxis werden durch Begleittexte der Herausgebenden ergänzt. „KI hilft uns dabei, die Natur besser zu verstehen und die Maßnahmen zu ihrem Schutz und ihre Wiederherstellung auf ein stabiles Fundament zu stellen. Das wird nicht nur helfen, unsere Lebensgrundlage zu sichern, sondern auch zur Entwicklung neuer Geschäfts- und Finanzierungsmodelle beitragen“, aus dem Grußwort von Dr. Frauke Fischer.
AutoCAD & AutoCAD LT All-in-One For Dummies
From zero to AutoCAD savvy in one book AutoCAD is the standard computer-aided drafting (CAD) software in many industries, and it comes with a learning curve. This All-In-One guide helps you flatten that curve out, making it easy to learn the basics of AutoCAD® and AutoCAD LT®. You’ll learn to create 2D drawings and 3D models that are precise, elegant, and even wow-worthy. When you’re ready for more advanced features, this book has you covered. Plus, you’ll get caught up on collaboration tools and customization options to better your workflow. 9 Books Inside… AutoCAD® Basics2D DraftingAnnotating DrawingsAdvanced DraftingPublishing DrawingsLT DifferencesCollaboration3D ModelingCustomizing AutoCAD® An easy-to-read and up-to-date collection of resources explaining the most recent versions of AutoCAD and AutoCAD LT In the brand-new second edition of AutoCAD & AutoCAD LT All-in-One For Dummies, consultant and industry expert with more than 30 years of experience using and extending AutoCAD along with being a 20-year veteran of AutoCAD education, Lee Ambrosius, walks you through the fundamentals of AutoCAD and AutoCAD LT. He explains the most useful features of both AutoCAD and the more budget-friendly AutoCAD LT, showing you how to choose the right tools and workflows for your projects. From creating architectural drawings, floor plans, and building designs to constructing precise designs, layouts, and technical drawings and blueprints, this all-in collection of easy-to-read guides covers how to set up drawings, draw and modify 2D and 3D designs, annotate your drawings, and perform advanced drafting techniques. AutoCAD & AutoCAD LT All-in-One For Dummies contains several mini-books you can tackle in order and in their entirety or as convenient references that help you get up to speed on specific tasks and projects you're working on in the moment. You'll also find: Step-by-step walkthroughs of popular and useful AutoCAD and AutoCAD LT features, like working with blocks and the electronic sharing and distribution of drawingsDetailed discussions of the differences between AutoCAD and AutoCAD LT, and how to customize each one to suit your needsExplanations of AutoCAD utilities for a variety of use cases Perfect for drafters, engineers, architects, programmers, and trainers interested in AutoCAD and AutoCAD LT, AutoCAD & AutoCAD LT All-in-One For Dummies is an accessible and handy reference for beginning and experienced users of AutoCAD that includes all the latest features, tools, and workflows you need to help you with your projects. Lee Ambrosius is a professional technical writer and consultant with decades of experience teaching others how to use and maximize the capabilities of AutoCAD and AutoCAD LT software. He has authored numerous works on a wide range of AutoCAD-related topics and has presented many sessions at Autodesk University.
Attraktiver Buchsatz mit Scribus
Entdecke die Welt des Buchsatzes mit Scribus! Dieses praxisnahe Sachbuch begleitet dich von den ersten Vorüberlegungen bis zur finalen, druckfertigen PDF-Datei. Lerne, wie Du einen optisch ansprechenden Buchsatzspiegel erstellst, deinen Text importierst, Musterseiten und Textrahmen sicher handhabst und deinen Text mit Hilfe von Stilen in die richtige Form bringst. Mit vielen anschaulichen Schritt-für-Schritt Anleitungen und farbigen Abbildungen gelingt dir die Erstellung eines attraktiven Buchsatzes für dein Taschenbuch spielend leicht.
AI in Legal Tech
Explore the risks, opportunities, and practicalities of generative AI in legal practice In AI in Legal Tech: How Generative AI Is Transforming Legal Technology and the Practice of Law, legal-tech pioneer and guru, Catherine Casey, walks you through the risks and opportunities presented by generative AI in the legal industry. She offers a comprehensive and accessible discussion of generative AI’s immediate and near-future impact on legal practices, ethics, and careers in law. The book translates and simplifies the complexities of generative AI and presents practical advice for anyone interested in harnessing its potential to dramatically redefine legal practice. It balances engaging narrative with expert analysis and is tailored specifically for non-technical legal professionals doing their best to navigate a new—and rapidly evolving—technological frontier. The author has also included a “Prompt Primer: Lawyered Edition” for practicing lawyers. Perfect for practicing lawyers, law students, legal technologists, and law practice managers, AI in Legal Tech is also a must-read resource for everyone who finds themselves at the intersection of law and technology. Explore the potential and risks of generative AI in the legal industry In AI in Legal Tech: How Generative AI Is Transforming Legal Technology and the Practice of Law, legal-tech pioneer and guru Catherine Casey—aka, TechnoCat—delivers a startlingly insightful and up-to-date discussion of the risks and opportunities presented by generative AI in the legal sector. The author walks you through generative AI's impact on the practice of law, legal ethics, and legal careers, offering guidance and clarity on a rapidly evolving technology. Balancing engaging narrative with expert analysis, AI in Legal Tech is written specifically for non-technical legal professionals and students doing their best to navigate the intersection of technology and law. You'll find: Explanations of how AI is shaping new legal careers and what you can do to find success in your ownA “Legal Tech Survival Kit,” complete with a comprehensive Legal AI glossary and must-try tools for tech-savvy lawyersInsights from the “front lines” of legal AI and the people designing the technologies shaping tomorrow's legal industry Perfect for practicing lawyers, law students, and law practice managers, AI in Legal Tech will also prove invaluable to legal technologists, paralegals, and anyone else interested in the application of the latest tech to the legal field. CAT CASEY is the defining voice at the intersection of AI and legal technology. A twenty-year veteran of the field and CEO of The Technocat LLC, she’s led technology and innovation at multiple legal tech Unicorns, the Big Four, and AmLaw 10 firms. Known for her sharp insight, deep technical fluency, and signature irreverence, Cat has helped shape how the legal profession navigates the age of intelligent machines.
Distributed Storage in Practice
A complete and up-to-date overview of popular and practical erasure codes in distributed storage In Distributed Storage in Practice, a team of distinguished researchers delivers a comprehensive discussion on distributed storage coding and distributed storage systems. Divided into two parts, the book first explores distributed storage coding technology based on Maximum Distance Separable (MDS) codes, including array codes, Reed-Solomon codes, locally repairable codes, and regenerating codes. It then goes on to examine the challenges presented by repairing distributed data in real-world scenarios. Distributed Storage in Practice uses two perspectives: practical optimization of distributed storage coding and emerging technologies such as blockchain. It discusses the technical foundations of blockchain and integrates blockchain into distributed storage systems and offers an overview of several popular blockchain-based storage systems. It also includes: A thorough introduction to the current development of quantum technology, including its fundamentals, quantum memory, quantum computers, quantum security, and quantum networks Comprehensive explorations of data recovery methods for specific networked distributed storage scenarios Practical integrations of theory and practice, including classic techniques and the most recent advancements in storage coding A practical example of a distributed secure storage system integrated with blockchain technology Perfect for researchers and undergraduate and graduate students studying computer science, Distributed Storage in Practice will also benefit blockchain professionals. Hui Li, PhD, is a Professor at the Peking University Shenzhen Graduate School, China. His research is focused on network architecture, cyberspace security, distributed storage, blockchain technology, and AI LLM for endogenous security. Hanxu Hou, PhD, is a Professor at the School of Electrical Engineering & Intelligentization, Dongguan University of Technology, China. His research is focused on network coding, error probability, and storage systems. Hong Tan, PhD, is a Research & Development Engineer at the Peking University Shenzhen Graduate School, China. His research is focused on advanced engineering solutions and innovative technologies.
Praxisbuch Workflow Automation mit n8n
No-Code KI für Maker und Entwickler Dieses Buch nimmt Heraklits Leitsatz "Panta rhei – alles fließt" als Ausgangspunkt, um den Wandel und die Dynamik moderner Lebens- und Arbeitswelten zu beleuchten. Arbeitsabläufe – sogenannte Workflows – durchziehen sowohl das private als auch das geschäftliche Umfeld. Sie entstehen aus dem Zusammenspiel einzelner, oft banaler Handlungen, die in eine sinnvolle Reihenfolge gebracht werden. Diese Abläufe lassen sich manuell ausführen, doch durch Automatisierung und digitale Hilfsmittel werden sie deutlich effizienter und belastbarer. Ein besonderer Fokus liegt auf dem Einsatz Künstlicher Intelligenz (KI), die sich mit rasanter Geschwindigkeit in immer mehr Lebensbereiche integriert. Ob automatische Übersetzungen, persönliche Assistenzen oder intelligente Infrastrukturen – KI-Systeme wie ChatGPT oder DeepSeek bieten vielfältige Möglichkeiten zur Prozessvereinfachung. Im privaten Bereich sind smarte Häuser ein Beispiel, im geschäftlichen Umfeld sind es komplexe Reaktionsketten auf bestimmte Situationen, bei denen KI gezielt eingesetzt wird. Für die praktische Umsetzung solcher Prozesse bietet das Buch eine Einführung in das Low-Code-Tool n8n, das es ermöglicht, auch komplexe Workflows ohne klassische Programmierung zu gestalten. Mit über 500 fertigen Integrationen verbindet n8n verschiedenste Anwendungen miteinander und kann durch KI-Module ergänzt werden. Das Buch zeigt auf leicht verständliche Weise, wie sich solche Systeme sowohl im Alltag als auch in Unternehmen nutzen lassen – für mehr Effizienz, Struktur und technologische Souveränität. Alle Linux-Befehle und Dateieinträge zur Konfiguration von Anwendungen stehen für Sie als Download bereit.
AI in Business For Dummies
Unlock productivity and profit with AI AI is suddenly a must-have in today’s business world. AI in Business For Dummies shows you what AI can do for your organization. This practical, jargon-free guide explains how AI works and how you can use it to boost your competitive edge. With step-by-step guidance, you’ll learn to harness AI wins—better decision-making, quicker content generation, more personalized customer interactions, and beyond—without sacrificing the human element. Get on the AI train and future-proof your business with this easy-to-use Dummies guide. Inside… Grasping AI basicsWinning customers with AISpeeding up innovationGetting your team on boardStaying legal and ethicalAvoiding common pitfallsPreparing for the next wave of new AI technologies Create an AI strategy that best fits your business You've heard about how artificial intelligence will revolutionize business, but maybe you're not sure how it will revolutionize your business. In AI in Business For Dummies, AI researcher and consultant Jeffrey Allan delivers clear insight into the capabilities of AI, the AI tools that get the job done, and how to best put artificial intelligence to work in your company. Using the book's step-by-step instructions, you'll learn how to build the latest AI tech in your business strategies. You'll also discover real-world examples of effective AI implementations in tasks like workflow automation, closing sales, handling data analytics, and driving innovation. The book also dives into ideas on how to get your staff and colleagues on board as well as how to use AI in an ethical manner. AI in Business For Dummies also includes: A breakdown of the essentials of AI technology and how each intersects with business useWays to avoid common business AI mistakes and pitfallsTips on future-proofing your AI investment Perfect for managers, executives, entrepreneurs, founders, and other business leaders, AI in Business For Dummies is a must-read resource for anyone with an interest in taking advantage of the newest, most exciting technologies in business. Dr. Jeffrey Allan directs the Institute for Responsible Technology and Artificial Intelligence at Nazareth University, developing AI-focused degree programs. An expert in AI and psychology, he’s advised Fortune 500 firms and Silicon Valley startups, and he coauthored Writing AI Prompts For Dummies.