Menneske-maskine-interaktion

This book presents extensive research on the quality of 360° video perceived by users with HMDs. The book aims to develop a set of standard guidelines for the systematic visual quality assessment of 360° videos. Firstly, conventional subjective test methods such as Absolute Category Rating (ACR) and Double Stimulus Impairment Scale (DSIS) are applied to evaluate video quality, alongside the Modified ACR (M-ACR) method newly proposed. Building on the reliability and general applicability of the procedure across different tests, a methodological framework for 360° video quality assessment is then presented. The author also analyzes simulator sickness to investigate the impact of different influencing factors. The insights gained on simulator sickness related to 360° video contribute to a better understanding of this particular use case of VR and can help to improve comfort among users by suggesting improvements in the technical specifications of 360° video and HMD technology and thusimproving QoE.

Interoperability between the respective S-Series Integrated Product Support (IPS) specifications requires a common understanding of the key concepts to be applied to all the specifications.Thus, SX002D, Common data model for the S-Series IPS specifications includes a conceptual description of all data elements common to more than one S-Series IPS specification, and documents this as a consolidated and harmonized data model using UML. This allows each individual specification to utilize or extend it as required. It describes all classes and attributes that are shared, as well as all relationships and interfaces that these specifications utilize.This data model is key to understand how all S-Series data models interface with each other, and also ensures that the different specifications interact properly with each other and are 100% compatible at data level. As the different XML schemas are generated from the specification data models, SX002D also ensures that the data constructs for data exchange are the same or at least fully interoperable between all the different specifications.Definitions for all classes and attributes defined in the SX002D Common Data Model are published as part of SX001G, Glossary for the S-Series IPS specifications, also available in book format with ISBN 978-84-19125-23-1.

This book gathers original peer-reviewed papers reporting on innovative methods and tools in design, modeling, simulation and optimization, and their applications in engineering design, manufacturing, and other relevant industrial sectors. Based on contributions to the Third International Conference on Design Tools and Methods in Industrial Engineering, ADM 2023, held on September 6¿8, 2023, in Florence, Italy, and organized by the Italian Association of Design Methods and Tools for Industrial Engineering, and the Department of Industrial Engineering of the University of Florence, this first volume of a 2-volume set focuses on advances in design for additive manufacturing, engineering methods in medicine, user-centred design, and industrial design and ergonomics. Further topics include design for sustainability, engineering education, experimental methods for product development, and advanced methods for product and process design. This book provides academicsand professionals with a timely overview and extensive information on trends and technologies in industrial design and manufacturing.

This book constitutes the refereed proceedings of the 18th National Conference on Man-Machine Speech Communication, NCMMSC 2023, held in Suzhou, China, during December 8¿11, 2023.The 20 full papers and 11 short papers included in this book were carefully reviewed and selected from 117 submissions. They deal with topics such as speech recognition, synthesis, enhancement and coding, audio/music/singing synthesis, avatar, speaker recognition and verification, human¿computer dialogue systems, large language models as well as phonetic and linguistic topics such as speech prosody analysis, pathological speech analysis, experimental phonetics, acoustic scene classification.

This monograph explores the synergy of Artificial Intelligence (AI), Augmented Reality (AR) and cognitive processes to enhance spatial abilities ¿ an integral aspect of cognitive development. The ability to comprehend and manipulate spatial information is not only fundamental to our understanding of the physical world but also plays a pivotal role in numerous academic and professional fields. Recognizing the profound impact of spatial ability on scientific disciplines and educational achievement, this monograph takes on the challenge of enhancing spatial skills among users.The authors present the design and development of a mobile training system that incorporates AR features to enhance learners¿ spatial ability. Involving mental generation, transformation, and rotation of visual images for understanding spatial relationships, spatial ability is closely linked to success in various scientific disciplines and educational pursuits. While spatial visualization skills testsare available, this monograph takes a unique approach by focusing on developing targeted interventions to improve spatial ability. It aims to unlock new avenues for cognitive growth and dive into the untapped potential within the realm of spatial intelligence. Beyond its emphasis on spatial ability enhancement, this monograph goes above and beyond traditional approaches by integrating AI techniques into the training system. As such, it aims to provide personalized and adaptive learning experiences for learners. The training system, through intelligent techniques, dynamically analyzes individual learners¿ strengths, weaknesses, and progress, tailoring content and challenges to their specific needs. This effort establishes a new frontier in educational technology, offering a groundbreaking solution that not only augments spatial ability development but also showcases the transformative potential of AI in reshaping the learning experience.The book is a valuable resource for researchers, educators, developers and technology enthusiasts, as it exemplifies the profound impact of AI and AR in shaping the future of online learning experiences.

Take your data preparation, machine learning, and GenAI skills to the next level by learning a range of Python algorithms and tools for data labelingKey FeaturesGenerate labels for regression in scenarios with limited training dataApply generative AI and large language models (LLMs) to explore and label text dataLeverage Python libraries for image, video, and audio data analysis and data labelingPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionData labeling is the invisible hand that guides the power of artificial intelligence and machine learning. In today's data-driven world, mastering data labeling is not just an advantage, it's a necessity. Data Labeling in Machine Learning with Python empowers you to unearth value from raw data, create intelligent systems, and influence the course of technological evolution.With this book, you'll discover the art of employing summary statistics, weak supervision, programmatic rules, and heuristics to assign labels to unlabeled training data programmatically. As you progress, you'll be able to enhance your datasets by mastering the intricacies of semi-supervised learning and data augmentation. Venturing further into the data landscape, you'll immerse yourself in the annotation of image, video, and audio data, harnessing the power of Python libraries such as seaborn, matplotlib, cv2, librosa, openai, and langchain. With hands-on guidance and practical examples, you'll gain proficiency in annotating diverse data types effectively.By the end of this book, you'll have the practical expertise to programmatically label diverse data types and enhance datasets, unlocking the full potential of your data.What you will learnExcel in exploratory data analysis (EDA) for tabular, text, audio, video, and image dataUnderstand how to use Python libraries to apply rules to label raw dataDiscover data augmentation techniques for adding classification labelsLeverage K-means clustering to classify unsupervised dataExplore how hybrid supervised learning is applied to add labels for classificationMaster text data classification with generative AIDetect objects and classify images with OpenCV and YOLOUncover a range of techniques and resources for data annotationWho this book is forThis book is for machine learning engineers, data scientists, and data engineers who want to learn data labeling methods and algorithms for model training. Data enthusiasts and Python developers will be able to use this book to learn data exploration and annotation using Python libraries. Basic Python knowledge is beneficial but not necessary to get started.Table of ContentsExploring Data for Machine LearningLabeling Data for ClassificationLabeling Data for RegressionExploring Image DataLabeling Image Data Using RulesLabeling Image Data Using Data AugmentationLabeling Text DataExploring Video DataLabeling Video DataExploring Audio DataLabeling Audio DataHands-On Exploring Data Labeling Tools

Level up your career by learning best practices for managing the data quality and integrity of your financial dataKey FeaturesAccelerate data integrity management using artificial intelligence-powered solutionsLearn how business intelligence tools, ledger databases, and database locks solve data integrity issuesFind out how to detect fraudulent transactions affecting financial report integrityBook DescriptionData integrity management plays a critical role in the success and effectiveness of organizations trying to use financial and operational data to make business decisions. Unfortunately, there is a big gap between the analysis and management of finance data along with the proper implementation of complex data systems across various organizations.The first part of this book covers the important concepts for data quality and data integrity relevant to finance, data, and tech professionals. The second part then focuses on having you use several data tools and platforms to manage and resolve data integrity issues on financial data. The last part of this the book covers intermediate and advanced solutions, including managed cloud-based ledger databases, database locks, and artificial intelligence, to manage the integrity of financial data in systems and databases.After finishing this hands-on book, you will be able to solve various data integrity issues experienced by organizations globally.What you will learnDevelop a customized financial data quality scorecardUtilize business intelligence tools to detect, manage, and resolve data integrity issuesFind out how to use managed cloud-based ledger databases for financial data integrityApply database locking techniques to prevent transaction integrity issues involving finance dataDiscover the methods to detect fraudulent transactions affecting financial report integrityUse artificial intelligence-powered solutions to resolve various data integrity issues and challengesWho this book is forThis book is for financial analysts, technical leaders, and data professionals interested in learning practical strategies for managing data integrity and data quality using relevant frameworks and tools. A basic understanding of finance concepts, accounting, and data analysis is expected. Knowledge of finance management is not a prerequisite, but it'll help you grasp the more advanced topics covered in this book.Table of ContentsRecognizing the Importance of Data Integrity in FinanceAvoiding Common Data Integrity Issues and Challenges in Finance TeamsMeasuring the Impact of Data Integrity IssuesUnderstanding the Data Integrity Management Capabilities of Business Intelligence ToolsUsing Business Intelligence Tools to Fix Data Integrity IssuesImplementing Best Practices When Using Business Intelligence ToolsDetecting Fraudulent Transactions Affecting Financial Report IntegrityUsing Database Locking Techniques for Financial Transaction IntegrityUsing Managed Ledger Databases for Finance Data IntegrityUsing Artificial Intelligence for Finance Data Quality Management

Quantum computing offers great promise in a wide variety of applications that need computational power beyond the limits of current conventional computers, including machine learning and AI, cryptanalysis, and simulation of quantum physics and chemistry. Fundamentally new programming technologies are required to develop quantum software that can realize the super-power of quantum computing. Foundations of Quantum Programming, Second Edition provides a systematic exposition of the subject of quantum programming. The emphasis is placed on the foundational concepts, methods and techniques that can be widely used for various quantum programming models and languages. It describes how programming methodologies developed for current computers can be extended for quantum computers, along with new programming methodologies that can effectively exploit the unique power of quantum computing. It introduces a chain of quantum programming models from sequential to parallel and distributed programming in the paradigm of superposition-of-data to the paradigm of superposition-of-programs. It also presents a series of logical and mathematical tools for verification and analysis of quantum programs, including invariant generation, termination analysis and abstract interpretation.

The document "How To Make A GPT Model Censored & Uncensored & 350 Different GPT Prompts" offers a comprehensive dive into the realm of Generative Pre-trained Transformers (GPTs), elucidating the intricacies of both censored and uncensored versions, along with an extensive list of 350 diverse GPT prompts. This file is a treasure trove for those intrigued by the evolving landscape of artificial intelligence, especially in the field of natural language processing.Censored GPT Models: The document begins by exploring the censored GPT models. These models are the epitome of AI-driven language generation, meticulously trained on vast datasets sourced from a plethora of internet texts. This intensive training empowers them to perform a multitude of language-based tasks, from engaging in conversation to crafting creative compositions. The pre-training phase imbues these models with an understanding of language patterns and structures, enabling them to predict subsequent words in a sentence and grasp the nuances of grammar, syntax, and even emotional undertones such as sarcasm and humor.However, the unique feature of these models is their censorship mechanism. Censorship in GPTs is an intentional modification to prevent the generation of content that is inappropriate, harmful, or unsuitable for all audiences. This includes a range of content from hate speech to sexually explicit material. Censorship is crucial for ethical considerations, compliance with laws and regulations, and safeguarding the reputation of the organizations using these models.Uncensored GPT Models: Contrastingly, the uncensored GPT models, as discussed in the document, are devoid of these ethical and safety restrictions. These models are theoretically capable of generating responses without any filtration, potentially leading to the production of harmful, offensive, or false content. The creation of an uncensored GPT model involves training on datasets without filtering sensitive or harmful content, removing built-in content filters and guidelines, and entails significant ethical and legal considerations.Challenges and Differences: Both versions come with their unique sets of challenges. The censored models, while ethically compliant, sometimes face issues like over-censorship, contextual misunderstandings, and biases in the decision-making process of what gets censored. On the other hand, uncensored models, while offering a broader range of outputs, pose significant ethical, legal, and social challenges due to their unfiltered nature.Practical Guide and Prompts: In addition to these insights, the document serves as a practical guide, detailing steps for cloning and implementing both censored and uncensored GPT models. It also includes a rich collection of 350 different GPT prompts, spanning various themes and applications, making it an invaluable resource for developers, researchers, and enthusiasts in the field of AI and machine learning.

The Align > Refine > Design series covers conceptual, logical, and physical data modeling (schema design and patterns) for leading technologies, combining proven data modeling practices with database-specific features to produce better applications. Read Cassandra Data Modeling and Schema Design if you are a data professional who needs to expand your modeling skills to include Cassandra or a technologist who knows Cassandra but needs to grow your schema design skills.The book's introduction and three chapters cover the Align, Refine, and Design approach. We include what the level does in the name by rebranding Conceptual, Logical, and Physical into Align, Refine, and Design. The introduction covers the three modeling characteristics of precise, minimal, and visual; the three model components of entities, relationships, and attributes (including keys); the three model levels of conceptual (align), logical (refine), and physical (design); and the three modeling perspectives of relational, dimensional, and query. Chapter 1, Align, is about agreeing on the common business vocabulary so everyone is aligned on terminology and general initiative scope. Chapter 2, Refine, is about capturing the business requirements. That is, refining our knowledge of the initiative to focus on what is essential. Chapter 3, Design, is about the technical requirements. That is, designing to accommodate our model's unique software and hardware needs.Align, Refine, and Design-that's the approach followed in this book and reinforced through an animal shelter case study. If you are interested in learning how to build multiple database solutions, read all the books in the Align > Refine > Design series. Since each book uses the same template, you can quickly skill up on additional database technologies.

Rapid digital transformation is forcing the manufacturing industry to drastically alter its current trajectory for future success. The remarkable convergence of digitalization and manufacturing is reshaping industries, ushering in an era known as Industry 5.0. This revolutionary transition has given birth to digital manufacturing and smart factories, heralding a new dawn in the way we produce goods. The amalgamation of artificial intelligence (AI), robotics, the internet of things (IoT), augmented reality (AR), virtual reality (VR), big data analytics, cloud computing, and additive manufacturing stands poised to unlock unprecedented avenues in the realm of production. Practitioners, researchers, dreamers, and pioneers all are beckoned to explore the uncharted territories of digital innovation in manufacturing. Human-Centered Approaches in Industry 5.0: Human-Machine Interaction, Virtual Reality Training, and Customer Sentiment Analysis spans domains from mechanical and electrical engineering to computer science, from industrial economics to business strategy, and this book addresses this diverse audience. The book embarks on a comprehensive voyage, unveiling the latest evolutions and nascent trends within digital manufacturing and smart factories. From inception to execution, from design optimization to predictive maintenance, every phase of the manufacturing lifecycle is scrutinized through the lens of cutting-edge technologies. Rather than relying exclusively on the theoretical realm, this book also ventures into the crucible of real-world application, offering practical insights drawn from varied industries, including automotive, aerospace, and pharmaceuticals.

This book showcases recent trends in brain-computer interface development. It highlights fascinating results in areas such as language decoding, spinal cord stimulation to enable gait and to restore hand functions. The contributions are based on the 12 nominated brain-computer interface projects of the BCI Award 2022. Every year an international jury selects the most innovate BCI projects and nominates 12 projects before selecting the 1st, 2nd and 3rd place winners. In the book, each project is described in detail by the team of scientists behind it, and the editors provide a concluding discussion of the highlights and overall progress in the field.

This book constitutes the revised selected papers of the 13th International Conference on Videogame Sciences and Arts, VJ 2023, held in Aveiro, Portugal, during November 28¿30, 2023.The 17 full papers and the 6 short papers presented were carefully reviewed and selected from 64 submissions. They are organized in topical sections named: game experience and evaluation; game-based learning and edutainment; games and culture; game design and development.

This book provides an in-depth examination of digital twin technology to take you on an enthralling trip across the intersection of the virtual and real worlds. It explores the transformational impact of digital twins, from their roots in engineering to their widespread applications in manufacturing, health care, and other areas. Real-world case studies highlight the practical benefits, while potential hazards are addressed wisely. This book is your guide to comprehending the present and visualizing a future where digital twins transform innovation, efficiency, and connectedness in our increasingly complicated world. Begin this illuminating trip and embrace the possibilities that exist at the intersection of the physical and digital worlds.

Dive deep into the transformative world of digital services with E-service Digital Innovation, a masterful blend of academic rigor and real-world insights. This text dissects the complexities of user motivation, the symbiotic dance between digital innovations and societal structures, and the collaborative essence of value co-creation. Venture into the heart of banking¿s digital metamorphosis and unravel the strategies shaping today¿s digital business models. With chapters dedicated to the revolutionary Industry 5. 0, the transformative powers of AI and blockchain, and the resilience imperative in business continuity, this book stands as a beacon for scholars and practitioners alike. Beyond the urban digital realms, discover the nuanced dynamics of rural digital adoption and the future of e-service in higher education. Grasp the intricacies of instructional learning design, data monetization ethics, and the innovative potential of IoT in urban planning. E-Service Digital Innovation invites you to engage, learn, and emerge as a contributor to the ever-evolving digital landscape. Your journey toward understanding and shaping the digital future starts here. Key Advantages: ¿Comprehensive coverage: From user psychology to the avant-garde applications of digital innovation ¿Scholarly rigor: A seminal text for academics, researchers, and industry experts ¿Practical wisdom: Real-world insights to navigate and shape the digital future ¿Diverse perspectives: Topics range from AI in e-commerce to the transformative potential of self-financing cities

Wer hat das Skifahren erfunden? Wie machen Vögel Musik? Was ist das Geheimnis unseres Schlafs? Seit 1888 beantwortet das Magazin National Geographic solche und Tausende andere Fragen unaufgeregt, klug und mit bestechend guten Infografiken . Wir haben die besten davon ausgesucht.

How to use design as a tool to create not only things but ideas, to speculate about possible futures.

Explore the latest Figma features with this newly updated 2nd edition, including Variables and Conditional Prototyping. Learn cutting-edge design principles and create captivating interfaces with this full-color guide.Key FeaturesExplore Figma's latest features, including Variables and Conditional Prototyping, to create dynamic and responsive interfacesIntegrate AI capabilities and optimize your workflow with the latest Figma pluginsCreate engaging, interactive prototypes that captivate your users and stakeholdersPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionAre you a UI/UX designer eager to learn the art of creating compelling interfaces using Figma? Look no further! The highly anticipated new edition is here to transform your creative journey.Explore Figma's latest features and delve into the power of variables and conditional Prototyping. Get ready to transform your static designs into dynamic, interactive prototypes, offering users and stakeholders an immersive experience. Stay at the forefront of design innovation with insights into integrating AI capabilities and optimizing your workflow with the latest Figma plugins. With user-centric design at its core, this book guides you through mastering design thinking, enabling you to tackle complex design challenges with ease. One unique aspect of this edition is its focus on effective communication. Learn how to convey your design vision clearly to both technical and non-technical audiences. In the rapidly changing world of UI/UX design, iteration is key. This book will teach you how to gather user feedback and iterate on your designs by creating interactive prototypes.Whether you're new to Figma or a seasoned pro, this comprehensive guide equips you with the skills to create captivating interfaces, fosters creativity and problem-solving, and makes you an indispensable, forward-thinking designer.What you will learnCreate high-quality designs that cater to your users' needs, providing an outstanding experienceMastering mobile-first design and responsive design conceptsIntegrate AI capabilities into your design workflow to boost productivity and explore design innovationCraft immersive prototypes with conditional prototyping and variablesCommunicate effectively to technical and non-technical audiencesDevelop creative solutions for complex design challengesGather and apply user feedback through interactive prototypesWho this book is forThis book is for aspiring UX/UI designers who want to get started with Figma as well as established designers who want to migrate to Figma from other design tools. This guide will provide you a walkthrough of the entire process of creating a full-fledged prototype for a responsive interface using all the tools and features that Figma has to offer. As a result, this book is suitable for both UX and UI designers, product and graphic designers, as well as anyone who wants to explore the complete design process from scratch.Table of ContentsExploring Figma and Transitioning from Other ToolsStructuring Moodboards, Personas, and User Flows within FigJamGetting to Know Your Design EnvironmentWireframing a Mobile-First Experience Using Vector ShapesDesigning Consistently Using Grids, Colors, and TypographyCreating a Responsive Mobile Interface Using Auto LayoutBuilding Components and Variants in a Collaborative WorkspaceUser Interface Design on Tablet, Desktop, and the WebPrototyping with Transitions, Smart Animate, and Interactive Components(N.B. Please use the Look Inside option to see further chapters)

Build faster and efficient real-world applications on the cloud with a fitting database model that's perfect for your needsKey FeaturesFamiliarize yourself with business and technical considerations involved in modeling the right databaseTake your data to applications, analytics, and AI with real-world examplesLearn how to code, build, and deploy end-to-end solutions with expert advicePurchase of the print or Kindle book includes a free PDF eBookBook DescriptionIn the age of lightning-speed delivery, customers want everything developed, built, and delivered at high speed and at scale. Knowledge, design, and choice of database is critical in that journey, but there is no one-size-fits-all solution. This book serves as a comprehensive and practical guide for data professionals who want to design and model their databases efficiently. The book begins by taking you through business, technical, and design considerations for databases. Next, it takes you on an immersive structured database deep dive for both transactional and analytical real-world use cases using Cloud SQL, Spanner, and BigQuery. As you progress, you'll explore semi-structured and unstructured database considerations with practical applications using Firestore, cloud storage, and more. You'll also find insights into operational considerations for databases and the database design journey for taking your data to AI with Vertex AI APIs and generative AI examples. By the end of this book, you will be well-versed in designing and modeling data and databases for your applications using Google Cloud.What you will learnUnderstand different use cases and real-world applications of data in the cloudWork with document and indexed NoSQL databasesGet to grips with modeling considerations for analytics, AI, and MLUse real-world examples to learn about ETL servicesDesign structured, semi-structured, and unstructured data for your applications and analyticsImprove observability, performance, security, scalability, latency SLAs, SLIs, and SLOsWho this book is forThis book is for database developers, data engineers, and architects looking to design, model, and build database applications on the cloud with an extended focus on operational consideration and taking their data to AI. Data scientists, as well ML and AI engineers who want to use Google Cloud services in the data to AI journey will also find plenty of useful information in this book. It will also be useful to data analysts and BI developers who want to use SQL impactfully to generate ML and generative AI insights from their data. Table of ContentsData, Databases, and DesignHandling Data on the CloudDatabase Modeling for Structured DataSetting Up a Fully Managed RDBMSDesigning an Analytical Data WarehouseDesigning for Semi-structured DataUnstructured Data ManagementDevOps and DatabasesData to AI - Modeling Your Databases for Analytics and MLLooking Ahead - Designing for LLM Applications

Harness the power of deep learning to drive productivity and efficiency using this practical guide covering techniques and best practices for the entire deep learning life cycleKey Features:Interpret your models' decision-making process, ensuring transparency and trust in your AI-powered solutionsGain hands-on experience in every step of the deep learning life cycleExplore case studies and solutions for deploying DL models while addressing scalability, data drift, and ethical considerationsPurchase of the print or Kindle book includes a free PDF eBookBook Description:Deep learning enables previously unattainable feats in automation, but extracting real-world business value from it is a daunting task. This book will teach you how to build complex deep learning models and gain intuition for structuring your data to accomplish your deep learning objectives.This deep learning book explores every aspect of the deep learning life cycle, from planning and data preparation to model deployment and governance, using real-world scenarios that will take you through creating, deploying, and managing advanced solutions. You'll also learn how to work with image, audio, text, and video data using deep learning architectures, as well as optimize and evaluate your deep learning models objectively to address issues such as bias, fairness, adversarial attacks, and model transparency.As you progress, you'll harness the power of AI platforms to streamline the deep learning life cycle and leverage Python libraries and frameworks such as PyTorch, ONNX, Catalyst, MLFlow, Captum, Nvidia Triton, Prometheus, and Grafana to execute efficient deep learning architectures, optimize model performance, and streamline the deployment processes. You'll also discover the transformative potential of large language models (LLMs) for a wide array of applications.By the end of this book, you'll have mastered deep learning techniques to unlock its full potential for your endeavors.What You Will Learn:Use neural architecture search (NAS) to automate the design of artificial neural networks (ANNs)Implement recurrent neural networks (RNNs), convolutional neural networks (CNNs), BERT, transformers, and more to build your modelDeal with multi-modal data drift in a production environmentEvaluate the quality and bias of your modelsExplore techniques to protect your model from adversarial attacksGet to grips with deploying a model with DataRobot AutoMLWho this book is for:This book is for deep learning practitioners, data scientists, and machine learning developers who want to explore deep learning architectures to solve complex business problems. Professionals in the broader deep learning and AI space will also benefit from the insights provided, applicable across a variety of business use cases. Working knowledge of Python programming and a basic understanding of deep learning techniques is needed to get started with this book.

Software-Ergonomie ist die Wissenschaft von der benutzer- und anwendungsgerechten Gestaltung der Mensch-Computer-Schnittstelle. Betrachtungen und Empfehlungen der Software-Ergonomie müssen eine Vielzahl wissenschaftlicher Disziplinen einbeziehen, insbesondere Physiologie, Psychologie, Arbeitswissenschaften und Informatik. Trotz des hohen Stellenwerts computerbasierter Werkzeuge verfügen ihre Entwickler nur selten über das notwendige ergonomische Hintergrundwissen. Dieses Buch ist eine wissenschaftliche, aber leicht lesbare Einführung in die Software-Ergonomie. Es ist kein "Kochbuch für Programmierer", sondern eine methodische Einführung in die wesentlichen Aspekte der Mensch-Computer-Kommunikation.