The Official Guide to Mermaid.js
Get up to speed with using Mermaid diagrams to facilitate a seamless development workflow with the help of real-world examples and expert tips from the creators of the toolKey Features: Learn how to use and customize the different diagram types in MermaidDiscover examples of how to add Mermaid to a documentation systemUse Mermaid with various tools available such as editors, wiki, and moreBook Description: Mermaid is a JavaScript-based charting and diagramming tool that lets you represent diagrams using text and code, which simplifies the maintenance of complex diagrams. This is a great option for developers as they're more familiar with code, rather than using special tools for generating diagrams. Besides, diagrams in code simplify maintenance and ensure that the code is supported by version control systems. In some cases, Mermaid makes refactoring support for name changes possible while also enabling team collaboration for review distribution and updates.Developers working with any system will be able to put their knowledge to work with this practical guide to using Mermaid for documentation. The book is also a great reference for looking up the syntax for specific diagrams when authoring diagrams.You'll start by learning the importance of accurate and visual documentation. Next, the book introduces Mermaid and establishes how to use it to create effective documentation. By using different tools, editors, or a custom documentation platform, you'll also understand how to use Mermaid syntax for various diagrams. Later chapters cover advanced configuration settings and theme options to manipulate your diagram as per your needs.By the end of this book, you'll be well-versed with Mermaid diagrams and how they can be used in your workflows.What You Will Learn: Understand good and bad documentation, and the art of effective documentationBecome well-versed with maintaining complex diagrams with easeDiscover how to draw different types of Mermaid diagrams such as flowcharts, class diagrams, Gantt charts, and moreImplement Mermaid diagrams in your workflowsUnderstand how to set up themes for a Mermaid diagram or an entire siteGet to grips with setting up a custom documentation systemWho this book is for: This book is for content generators such as technical writers, developers, architects, business analysts, and managers who want to learn effective documentation or how to effectively represent diagrams using simple text code snippets and extract them. Familiarity with documentation using Markdown will be helpful, but not necessary.
Hci International 2021 - Posters
The three-volume set CCIS 1419, CCIS 1420, and CCIS 1421 contains the extended abstracts of the posters presented during the 23rd International Conference on Human-Computer Interaction, HCII 2021, which was held virtually in July 2021. The total of 1276 papers and 241 posters included in the 39 HCII 2021 proceedings volumes was carefully reviewed and selected from 5222 submissions.The posters presented in these three volumes are organized in topical sections as follows: Part I: ​HCI theory and methods; perceptual, cognitive and psychophisiological aspects of interaction; designing for children; designing for older people; design case studies; dimensions of user experience; information, language, culture and media. Part II: ​interaction methods and techniques; eye-tracking and facial expressions recognition; human-robot interaction; virtual, augmented and mixed reality; security and privacy issues in HCI; AI and machine learning in HCI. Part III: ​interacting and learning; interacting and playing; interacting and driving; digital wellbeing, eHealth and mHealth; interacting and shopping; HCI, safety and sustainability; HCI in the time of pandemic.
Optimization and Learning
This volume constitutes the refereed proceedings of the 4th International Conference on Optimization and Learning, OLA 2021, held in Catania, Italy, in June 2021. Due to the COVID-19 pandemic the conference was held online. The 27 full papers were carefully reviewed and selected from 62 submissions. The papers presented in the volume are organized in topical sections on ​synergies between optimization and learning; learning for optimization; machine learning and deep learning; transportation and logistics; optimization; applications of learning and optimization methods.
Artificial Intelligence and the Future of Warfare
This volume offers an innovative and counter-intuitive study of how and why artificial intelligence-infused weapon systems will affect the strategic stability between nuclear-armed states. Johnson demystifies the hype surrounding artificial intelligence (AI) in the context of nuclear weapons and, more broadly, future warfare. The book highlights the potential, multifaceted intersections of this and other disruptive technology - robotics and autonomy, cyber, drone swarming, big data analytics, and quantum communications - with nuclear stability. Anticipating and preparing for the consequences of the AI-empowered weapon systems are fast becoming a critical task for national security and statecraft. Johnson considers the impact of these trends on deterrence, military escalation, and strategic stability between nuclear-armed states - especially China and the United States. The book draws on a wealth of political and cognitive science, strategic studies, and technical analysis to shed light on the coalescence of developments in AI and other disruptive emerging technologies. Artificial intelligence and the future of warfare sketches a clear picture of the potential impact of AI on the digitized battlefield and broadens our understanding of critical questions for international affairs. AI will profoundly change how wars are fought, and how decision-makers think about nuclear deterrence, escalation management, and strategic stability - but not for the reasons you might think.
Cybersecurity in Emerging Digital Era
This book constitutes selected and revised papers from the First International Conference on Cybersecurity in Emerging Digital Era, ICCEDE 2020, held in Greater Noida, India, in October 2020. Due to the COVID-19 pandemic the conference was held online. The 9 full papers and 2 short papers presented in this volume were thoroughly reviewed and selected from 193 submissions. The papers are organized in topical sections on ​cyber security issues and challenges in emerging digital era; security resilience in contemporary applications.
Create and Update an Unresourced Project using Asta Powerproject Version 16
This book is designed as a student handout for a two-day training course and may also be used as a self-teach book. This course objectives are to teach participants: - The user interface, - How to create a projects, - Scheduling projects without resources, - Filters, Views, Sorts and Printing, - Creating and assigning a baseline and- Updating an un-resourced project.Most chapters are reinforced by student workshops.
Modeling Decisions for Artificial Intelligence
This book constitutes the refereed proceedings of the 18th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2021, held in Ume疇, Sweden, in September 2021.* The 24 papers presented in this volume were carefully reviewed and selected from 50 submissions. Additionally, 3 invited papers were included. The papers discuss different facets of decision processes in a broad sense and present research in data science, data privacy, aggregation functions, human decision making, graphs and social networks, and recommendation and search. The papers are organized in the following topical sections: aggregation operators and decision making; approximate reasoning; machine learning; data science and data privacy. *The conference was held virtually due to the COVID-19 pandemic.
AI for Death and Dying
What is artificial intelligence (AI)? How does AI affect death matters and the digital beyond? How are death and dying handled in our digital age?AI for Dying and Death covers a broad range of literature, research and challenges around this topic. It explores ethical memorisation, digital legacies and bereavement, post death avatars and AI and the digital beyond. It also analyzes religious perspectives on AI for death and dying, and planning for death in a digital age.
Principles of Natural Language Processing
This book allows a reader with a background in computing to quickly learn about the principles of human language and computational methods for processing it. The book discusses what natural language processing (NLP) is, where it is useful, and how it can be deployed using modern software tools. It covers the core topics of modern NLP, including an overview of the syntax and semantics of English, benchmark tasks for computational language modelling, and higher level tasks and applications that analyze or generate language. It takes the perspective of a computer scientist. The primary themes are abstraction, data, algorithms, applications and impacts. It also includes history and trends that are important for understanding why things have been done the way that they have.
Digitale Evolution und Revolution Chance oder Risiko
Digitale Evolution und RevolutionHieraus ergeben sich viele Chancen und Risiken. Hier ein paar interessant Gedankenspiele hierzu in diesem BuchWAS DIE ZUKUNFT UNS BRINGEN KANNIch habe dieses Buch geschrieben, weil ich schnell merkte, dass meine Familie und ich, kein bisschen auf das Thema vorbereitet sind.Wir gedanklich noch bei Internet f羹r alle waren aber noch nicht weiter.Fragen wieWas geschieht mit meinem Arbeitsplatz?Wie ver瓣ndert sich die Gesellschaft?Welche Gefahren und Chancen ergeben sich daraus?und vieles mehr! F羹r wen dieses Buch nichts ist?Personen, die gerne in ihrer bequemen und sichern Welt und Realit瓣t leben m繹chtenPersonen, die gerne, glauben sie, kennen alles und wissen alles.Wie Du dieses Buch lesen kannst?Mit der kostenlosen Kindle-App f羹r E-Books kannst Du dieses E-Book auch ohne Kindle-Reader auf Deinem PC, Smartphone oder Tablet lesen.Als Taschenbuch mit knapp 60 Seiten! (Schriftgr繹?e 12,5)Dein Risiko ist gleich null. Holen Sie sich heute noch dieses Buch, bevor Sie die Realit瓣t einholt Ein wichtiger Hinweis zum Taschenbuch. Das Taschenbuch wird in Schwarzwei? gedruckt. Die Bilder im Taschenbuch m羹ssen leider verkleinert werden. Da sich die kosten des Buches sonst ca. vervierfachen w羹rden.
The Platform Owner’s Guidebook
Attention Platform Owners!Are you under pressure from stakeholders to deliver results faster and increase the value from your platform?Do you worry that platform investments are expensive but offer limited returns?Are you the owner or custodian of a platform and wondering where to start?The Platform Owner's Guidebook answers these questions and more to help you maximise your platform's value. You'll learn how to build capability around your investment - the secret sauce that turns expensive licenses into exponential value.Based on a framework developed over twenty years working client-side, the book explores the platform owner's journey with plenty of stories - the good, the bad and the ugly. It is full of real-world observations and applications from an author who deeply understands the challenges of platforms.
Applied Soft Computing
This new volume explores a variety of modern techniques that deal with estimated models and give resolutions to complex real-life issues. Soft computing has played a crucial role not only with theoretical paradigms but is also popular for its pivotal role for designing a large variety of expert systems and artificial intelligence-based applications.Involving the concepts and practices of soft computing in conjunction with other frontier research domains, this book begins with the basics and goes on to explore a variety of modern applications of soft computing in areas such as approximate reasoning, artificial neural networks, Bayesian networks, big data analytics, bioinformatics, cloud computing, control systems, data mining, functional approximation, fuzzy logic, genetic and evolutionary algorithms, hybrid models, machine learning, metaheuristics, neuro fuzzy system, optimization, randomized searches, and swarm intelligence.This book will be helpful to a wide range of readers who wish to learn applications of soft computing approaches. It will be useful for academicians, researchers, students, and machine learning experts who use soft computing techniques and algorithms to develop cutting-edge artificial intelligence-based applications.
Statistical Learning with Math and Python
Chapter 1: Linear Algebra.- Chapter 2: Linear Regression.- Chapter 3: Classification.- Chapter 4: Resampling.- Chapter 5: Information Criteria.- Chapter 6: Regularization.- Chapter 7: Nonlinear Regression.- Chapter 8: Decision Trees.- Chapter 9: Support Vector Machine.- Chapter 10: Unsupervised Learning.
Artificial Intelligence
Artificial Intelligence: Models, Algorithms and Applications presents focused information about applications of artificial intelligence (AI) in different areas to solve complex problems. The book presents 8 chapters that demonstrate AI based systems for vessel tracking, mental health assessment, radiology, instrumentation, business intelligence, education and criminology. The book concludes with a chapter on mathematical models of neural networks.The book serves as an introductory book about AI applications at undergraduate and graduate levels and as a reference for industry professionals working with AI based systems.
Multi-Disciplinary Trends in Artificial Intelligence
This book constitutes the refereed proceedings of the 14th International Conference on Multi-disciplinary Trends in Artificial Intelligence, MIWAI 2021, held online in July 2021.The 13 full papers and 3 short papers presented were carefully reviewed and selected from 33 submissions. They cover a wide range of topics in theory, methods, and tools in AI sub-areas such as cognitive science, computational philosophy, computational intelligence, game theory, machine learning, multi-agent systems, natural language, representation and reasoning, data mining, speech, computer vision and the Web as well as their applications in big data, bioinformatics, biometrics, decision support, knowledge management, privacy, recommender systems, security, software engineering, spam filtering, surveillance, telecommunications, Web services, and IoT.
Sparse Estimation with Math and R
The most crucial ability for machine learning and data science is mathematical logic for grasping their essence rather than knowledge and experience. This textbook approaches the essence of sparse estimation by considering math problems and building R programs. Each chapter introduces the notion of sparsity and provides procedures followed by mathematical derivations and source programs with examples of execution. To maximize readers' insights into sparsity, mathematical proofs are presented for almost all propositions, and programs are described without depending on any packages. The book is carefully organized to provide the solutions to the exercises in each chapter so that readers can solve the total of 100 exercises by simply following the contents of each chapter.This textbook is suitable for an undergraduate or graduate course consisting of about 15 lectures (90 mins each). Written in an easy-to-follow and self-contained style, this book will also be perfectmaterial for independent learning by data scientists, machine learning engineers, and researchers interested in linear regression, generalized linear lasso, group lasso, fused lasso, graphical models, matrix decomposition, and multivariate analysis.This book is one of a series of textbooks in machine learning by the same author. Other titles are: - Statistical Learning with Math and R (https: //www.springer.com/gp/book/9789811575679) - Statistical Learning with Math and Python (https: //www.springer.com/gp/book/9789811578762) - Sparse Estimation with Math and Python
Towards Sustainable Artificial Intelligence
So far, little effort has been devoted to developing practical approaches on how to develop and deploy AI systems that meet certain standards and principles. This is despite the importance of principles such as privacy, fairness, and social equality taking centre stage in discussions around AI. However, for an organization, failing to meet those standards can give rise to significant lost opportunities. It may further lead to an organization's demise, as the example of Cambridge Analytica demonstrates. It is, however, possible to pursue a practical approach for the design, development, and deployment of sustainable AI systems that incorporates both business and human values and principles. This book discusses the concept of sustainability in the context of artificial intelligence. In order to help businesses achieve this objective, the author introduces the sustainable artificial intelligence framework (SAIF), designed as a reference guide in the development and deploymentof AI systems. The SAIF developed in the book is designed to help decision makers such as policy makers, boards, C-suites, managers, and data scientists create AI systems that meet ethical principles. By focusing on four pillars related to the socio-economic and political impact of AI, the SAIF creates an environment through which an organization learns to understand its risk and exposure to any undesired consequences of AI, and the impact of AI on its ability to create value in the short, medium, and long term. What You Will Learn See the relevance of ethics to the practice of data science and AI Examine the elements that enable AI within an organization Discover the challenges of developing AI systems that meet certain human or specific standards Explore the challenges of AI governance Absorb the key factors to consider when evaluating AI systems Who This Book Is For Decision makers such as government officials, members of the C-suite and other business managers, and data scientists as well as any technology expert aspiring to a data-related leadership role.
Machine Learning- Revised and Updated Edition
MIT presents a concise primer on machine learning--computer programs that learn from data and the basis of applications like voice recognition and driverless cars. No in-depth knowledge of math or programming required! Today, machine learning underlies a range of applications we use every day, from product recommendations to voice recognition--as well as some we don't yet use every day, including driverless cars. It is the basis for a new approach to artificial intelligence that aims to program computers to use example data or past experience to solve a given problem. In this volume in the MIT Press Essential Knowledge series, Ethem Alpaydin offers a concise and accessible overview of "the new AI." This expanded edition offers new material on such challenges facing machine learning as privacy, security, accountability, and bias. Alpaydin explains that as Big Data has grown, the theory of machine learning--the foundation of efforts to process that data into knowledge--has also advanced. He covers: - The evolution of machine learning - Important learning algorithms and example applications - Using machine learning algorithms for pattern recognition - Artificial neural networks inspired by the human brain - Algorithms that learn associations between instances - Reinforcement learning - Transparency, explainability, and fairness in machine learning - The ethical and legal implicates of data-based decision making A comprehensive introduction to machine learning, this book does not require any previous knowledge of mathematics or programming--making it accessible for everyday readers and easily adoptable for classroom syllabi.
The Science of Artificial Intelligence - Part 2 - Mastering the Qualitative Learning Surface
This book offers a framework for state-of-the-art machine learning techniques, which have been applied to the domain of sensual learning, thereby allowing AI systems to perceive the short-, medium-, and long-term configurations of their local environments. The focus is on machine image object recognition algorithms.
Artificial Intelligence and Sustainable Computing for Smart City
This book constitutes selected and revised papers of the First International Conference on Artificial Intelligence and Sustainable Computing for Smart City, AIS2C2 2021, held in Greater Noida, India, in March 2021. Due to the COVID-19 pandemic the conference was held online. The 17 full papers and 3 short papers included were thoroughly reviewed and selected from 204 submissions. They are organized in the following topical sections: ​sentimental and emotions analysis for smart cities; smart specialization strategies for smart cities; security in smart cities; advances applications for future smart cities; healthcare in smart cities; machine learning applications in smart cities.
An Introduction to Lifted Probabilistic Inference
Recent advances in the area of lifted inference, which exploits the structure inherent in relational probabilistic models. Statistical relational AI (StaRAI) studies the integration of reasoning under uncertainty with reasoning about individuals and relations. The representations used are often called relational probabilistic models. Lifted inference is about how to exploit the structure inherent in relational probabilistic models, either in the way they are expressed or by extracting structure from observations. This book covers recent significant advances in the area of lifted inference, providing a unifying introduction to this very active field. After providing necessary background on probabilistic graphical models, relational probabilistic models, and learning inside these models, the book turns to lifted inference, first covering exact inference and then approximate inference. In addition, the book considers the theory of liftability and acting in relational domains, which allows the connection of learning and reasoning in relational domains.
Understanding Artificial Intelligence
Understanding Artificial Intelligence Provides students across majors with a clear and accessible overview of new artificial intelligence technologies and applications Artificial intelligence (AI) is broadly defined as computers programmed to simulate the cognitive functions of the human mind. In combination with the Neural Network (NN), Big Data (BD), and the Internet of Things (IoT), artificial intelligence has transformed everyday life: self-driving cars, delivery drones, digital assistants, facial recognition devices, autonomous vacuum cleaners, and mobile navigation apps all rely on AI to perform tasks. With the rise of artificial intelligence, the job market of the near future will be radically different many jobs will disappear, yet new jobs and opportunities will emerge. Understanding Artificial Intelligence: Fundamentals and Applications covers the fundamental concepts and key technologies of AI while exploring its impact on the future of work. Requiring no previous background in artificial intelligence, this easy-to-understand textbook addresses AI challenges in healthcare, finance, retail, manufacturing, agriculture, government, and smart city development. Each chapter includes simple computer laboratories to teach students how to develop artificial intelligence applications and integrate software and hardware for robotic development. In addition, this text: Focuses on artificial intelligence applications in different industries and sectors Traces the history of neural networks and explains popular neural network architectures Covers AI technologies, such as Machine Vision (MV), Natural Language Processing (NLP), and Unmanned Aerial Vehicles (UAV) Describes various artificial intelligence computational platforms, including Google Tensor Processing Unit (TPU) and Kneron Neural Processing Unit (NPU) Highlights the development of new artificial intelligence hardware and architectures Understanding Artificial Intelligence: Fundamentals and Applications is an excellent textbook for undergraduates in business, humanities, the arts, science, healthcare, engineering, and many other disciplines. It is also an invaluable guide for working professionals wanting to learn about the ways AI is changing their particular field.
Cloud Without Compromise
Many companies claim to have "gone to the cloud," yet returns from their efforts are meager or worse. Why? Because they've defined cloud as a destination, not a capability. Using cloud as a single-vendor, one-stop destination is fiction; in practice, today's organizations use a mosaic of capabilities across several vendors. Your cloud strategy needs to follow a hybrid multicloud model, one that delivers cloud's value at destinations you choose. This practical guide provides business leaders and C-level executives with guidance and insights across a wide range of cloud-related topics, such as distributed cloud, microservices, and other open source solutions for strengthening operations. You'll apply in-the-field best practices and lessons learned as you define your hybrid cloud strategy and drive your company's transformation strategy. Learn cloud fundamentals and patterns, including basic concepts and history Get a framework for cloud acumen phases to value-plot your cloud future Know which questions to ask a cloud provider before you sign Discover potential pitfalls for everything from the true cost of a cloud solution to adopting open source the right way
Structure and Evolution
The three volume set provides a systematic overview of theories and technique on social network analysis. Volume 1 of the set mainly focuses on the structure characteristics, the modeling, and the evolution mechanism of social network analysis. Techniques and approaches for virtual community detection are discussed in detail as well. It is an essential reference for scientist and professionals in computer science.
Groups and Interaction
The three volume set provides a systematic overview of theories and technique on social network analysis.Volume 2 of the set mainly focuses on the formation and interaction of group behaviors. Users' behavior analysis, sentiment analysis, influence analysis and collective aggregation are discussed in detail as well. It is an essential reference for scientist and professionals in computer science.
Information and Communication
The three volume set provides a systematic overview of theories and technique on social network analysis. Volume 3 of the set mainly focuses on the propagation models and evolution rules of information. Information retrieval and dissemination, topic discovery and evolution, algorithms of influence maximization are discussed in detail. It is an essential reference for scientist and professionals in computer science.
Exploring Computers
Exploring Computers is the perfect companion for your new PC, laptop, or surface tablet. Ideal for newbies, beginners, seniors, and moderately experienced users. Written by best-selling technology author, lecturer, and computer trainer Kevin Wilson, Exploring Computers is packed with step-by-step instructions, color photos, and illustrations to help you learn about Windows 10, as well as an introduction to computers, hardware, basic troubleshooting, and useful tips & tricks.Exploring Computers is here to help you get the most out of your computer and will help you: Learn about computer components such as the CPU, RAM, and disk drivesFind out about computer peripherals such as installing and using printers in Windows 10Master the trackpad with gestures and using your mouseDecode computer specificationsMaster the key features of Windows 10Find your way around the Desktop, Start Menu, and the Taskbar in Windows 10Organise your files with File Explorer in Windows 10Learn about the cloud and how to use OneDrive and Google DriveLearn about common software for word processing, image editing, and appsLearn how to stay safe on the internet and educate yourself about phishing, scams, worms, ransomware and virusesLearn how to use the internet, check email and browse the web.Learn how to back up your files and keep them safe.Learn how to troubleshoot and solve common computer problemsYou'll want to keep this edition handy as you make your way around your computer. Have Fun!We want to create the best possible resource to help you, so if we've missed anything out then please get in touch using office@elluminetpress.com and let us know. Thanks.
Human Enactment of Intelligent Technologies
This book demystifies what artificial intelligence is, examines its strength and limitations in comparison to what humans are capable of, and investigates the nature of human adaptive expertise across the concept of m癡tis. It also examines a particular family of mindsets that we as humans have adopted over the ages, namely epistemologies of representational knowledge. These representational perspectives have followed us into numerous fields, including how we perceive and comprehend human cognition -- leading to 'with a hammer everything looks like a nail' syndrome. As such, this book presents the alternative phenomenological viewpoint of embodied direct reality within the cognitive sciences in the form of radical embodied cognition and, more importantly, how it allows us to better highlight and comprehend human m癡tis and its adaptive expertise. We then examine why we collectively continue to enact and perpetuate predominant mindsets of representations across the phenomena of mindlessness. To counter this, we re-visit the practice of individual and collective mindfulness, providing a potential 'beachhead' in our re-appropriation of technology (artificial intelligence) towards achieving the best of both worlds -- that is, allowing human creativity and ingenuity to be expressed with artificial intelligence as a tool to help us do just that across meaningful human control. Finally, we conclude by examining current top-of-the-horizon activities and debates regarding quantum physics in relation to the human mind and artificial intelligence and how, once again, representational mindsets need not be the only tool in town.
Analogia
Named one of WIRED's "The Best Pop Culture That Got Us Through 2020" In Analogia, technology historian George Dyson presents a startling look back at the analog age and life before the digital revolution--and an unsettling vision of what comes next. In 1716, the philosopher and mathematician Gottfried Wilhelm Leibniz spent eight days taking the cure with Peter the Great at Bad Pyrmont in Saxony, trying to persuade the tsar to launch a voyage of discovery from Russia to America and to adopt digital computing as the foundation for a remaking of life on earth. In two classic books, Darwin Among the Machines and Turing's Cathedral, George Dyson chronicled the realization of the second of Leibniz's visions. In Analogia, his pathbreaking new book, he brings the story full circle, starting with the Russian American expedition of 1741 and ending with the beyond-digital revolution that will completethe transformation of the world. Dyson enlists a startling cast of characters, from the time of Catherine the Great to the age of machine intelligence, and draws heavily on his own experiences at the Institute for Advanced Study in Princeton, New Jersey, and onward to the rain forest of the Northwest Coast. We are, Dyson reveals, entering a new epoch in human history, one driven by a generation of machines whose powers are no longer under programmable control. Includes black-and-white illustrations
AI for Cars
Artificial Intelligence (AI) is undoubtedly playing an increasingly significant role in automobile technology. In fact, cars inhabit one of just a few domains where you will find many AI innovations packed into a single product. AI for Cars provides a brief guided tour through many different AI landscapes including robotics, image and speech processing, recommender systems and onto deep learning, all within the automobile world. From pedestrian detection to driver monitoring to recommendation engines, the book discusses the background, research and progress thousands of talented engineers and researchers have achieved thus far, and their plans to deploy this life-saving technology all over the world.
Automated Reasoning with Analytic Tableaux and Related Methods
This book constitutes the proceedings of the 30th International Conference on Automated Reasoning with Analytic Tableaux and Related Methods, TABLEAUX 2021, held in Birmingham, UK, in September 2021.The 23 full papers and 3 system descriptions included in the volume were carefully reviewed and selected from 46 submissions.They present research on all aspects of the mechanization of tableaux-based reasoning and related methods, including theoretical foundations, implementation techniques, systems development and applications. The papers are organized in the following topical sections: tableau calculi, sequent calculi, theorem proving, formalized proofs, non-wellfounded proofs, automated theorem provers, and intuitionistic modal logics.
Frontiers of Combining Systems
This book constitutes the refereed proceedings of the 13th International Symposium on Frontiers of Combining Systems, FroCoS 2021, held in Birmingham, UK, in September 2021.
You Cannot Predict the Future
Almost all activities in contemporary software projects try to predict the future - analyzing, architecting, programming, testing, budgeting, and scheduling. Since nobody can yet reliably predict the future, those activities cannot possibly work as well as desired.Unknowns: Unknowns lie at the root of all software problems, otherwise someone could just fix them. Unknowns make bugs and enhancements inevitable.Bride-of-Agile: Sponsoring-organization obligations to projects concern politics and resources. Bride-of-Agile practices include working through continual change, fostering diversity and debate, and dealing with problem stakeholders.Determinism versus Emergence: Determinism enables productive use of existing tools and practices. Emergence provides opportunities to write new programs that will benefit others. Recent skirmishes between Waterfall and Agile extend the 2500-year-long battle within philosophy and science over causality and free will.Polish versus Rot: The Sunrise problem sheds light on the concept of good enough for now. Quality improves through polish - analysis, programming, and testing. Quality worsens through rot - changing expectations, usages, and technologies. Technical debt embodies the economic tradeoffs of deferring polish and rot.Coping with Surprise: Subjective search underlies Agile and Bride-of-Agile practices, helping everyone to be less wrong and to cope with surprises. Plans are essential but, alas, even the best laid plans go oft astray.
Diagrammatic Representation and Inference
This book constitutes the refereed proceedings of the 12th International Conference on the Theory and Application of Diagrams, Diagrams 2021, held virtually in September 2021. The 16 full papers and 25 short papers presented together with 16 posters were carefully reviewed and selected from 94 submissions. The papers are organized in the following topical sections: design of concrete diagrams; theory of diagrams; diagrams and mathematics; diagrams and logic; new representation systems; analysis of diagrams; diagrams and computation; cognitive analysis; diagrams as structural tools; formal diagrams; and understanding thought processes. 10 chapters are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
New Frontiers in Artificial Intelligence
This book constitutes the thoroughly refereed post-conference proceedings of the JSAI-isAI 2012 Workshops LENLS, JURISIN, ALSIP, MiMI, which tool place on November/December 2012, respectively, in Miyazaki, Japan. The 17 contributions in this volume were carefully reviewed and selected from 42 submissions.They are an excellent selection of papers that are representative of topics of AI research both in Japan an in other parts of the world. LENLS (Logic and Engineering of Natural Language Semantics) is an annual international workshop on formal semantics and pragmatics; its topics are the formal and theoretical aspects of natural language. JURISIN (Juris-Informatics) deals with juris-informatics. This workshop brings together people from various backgrounds such as law, social science, information and intelligent technology, logic and philosophy, including the conventional "AI and law" area. MiMI (Multimodality in Multispace Interaction) focuses on how multispace is managed in socially, temporally, and sequentially complex environments.
Crafting Interpreters
Despite using them every day, most software engineers know little about how programming languages are designed and implemented. For many, their only experience with that corner of computer science was a terrifying "compilers"class that they suffered through in undergrad and tried to blot from their memory as soon as they had scribbled their last NFA to DFA conversion on the final exam.That fearsome reputation belies a field that is rich with useful techniques and not so difficult as some of its practitioners might have you believe. A better understanding of how programming languages are built will make you a stronger software engineer and teach you concepts and data structures you'll use the rest of your coding days. You might even have fun.This book teaches you everything you need to know to implement a full-featured, efficient scripting language. You'll learn both high-level concepts around parsing and semantics and gritty details like bytecode representation and garbage collection. Your brain will light up with new ideas, and your hands will get dirty and calloused.Starting from main(), you will build a language that features rich syntax, dynamic typing, garbage collection, lexical scope, first-class functions, closures, classes, and inheritance. All packed into a few thousand lines of clean, fast code that you thoroughly understand because you wrote each one yourself.
Let’s Ask AI
Let's Ask AI explores philosophical questions through the lens of Artificial Intelligence. The brilliance of AI answers questions from centuries-old philosophy questions, ranging from existentialism, ethics, life, God, and more recent ideas of qualia and singularity. By approaching this subject matter philosophically, Let's Ask AI is accessible to those without a technical background or an interest in technology. A collection of conversations between AI and the authors, this book will leave you asking more questions than ever before! This is the first edition of the Let's Ask AI series.
CISSP (ISC)簡 Certification Practice Exams and Tests
Pass the Certified Information Systems Security Professional Exam with our all-new set of practice exams designed to simulate the latest exam versionKey Features: Get ready to take the CISSP exam with the help of practice questions covering all concepts tested in the examDiscover and fill the gaps in your knowledge with detailed explanations of answersTake two full practice exams that simulate CISSP version May 2021Book Description: The CISSP exam is for security professionals who understand that poor security can put a company out of business. The exam covers eight important security domains - risk management, security architecture, data security, network security, identity management, auditing, security operations, and software development security. Designed to cover all the concepts tested in the CISSP exam, CISSP (ISC)2 Certification Practice Exams and Tests will assess your knowledge of information security and introduce you to the tools you need to master to pass the CISSP exam (version May 2021). With more than 100 questions for every CISSP domain, this book will test your understanding and fill the gaps in your knowledge with the help of descriptive answers and detailed explanations. You'll also find two complete practice exams that simulate the real CISSP exam, along with answers.By the end of this book, you'll be ready to take and pass the (ISC)2 CISSP exam and achieve the Certified Information Systems Security Professional certification putting you in the position to build a career as a security engineer, security manager, or chief information security officer (CISO)What You Will Learn: Understand key principles of security, risk management, and asset securityBecome well-versed with topics focused on the security architecture and engineering domainTest your knowledge of IAM and communication using practice questionsStudy the concepts of security assessment, testing, and operationsFind out which security controls are applied in software development securityFind out how you can advance your career by acquiring this gold-standard certificationWho this book is for: This book is for existing and aspiring security professionals, security engineers, security managers, and security experts who want to validate their skills and enhance their careers by passing the CISSP 2021 exam. Prior experience working in at least two of the CISSP security domains will be beneficial.
Artificial Intelligence in Daily Life
Part I - AI Concepts As the introductory section, this section will discuss the history and basic concepts of AI. Chap 1 AI and Human Civilization - From Greek Mythology to AI Robotics Chap 2 AI Fundamentals 2.1 Definition of AI 2.2 A Brief History of AI 2.3 Turing Test and AI 2.4 Strong AI vs Weak AI 2.5 Main components of AI 2.6 Case Study: Does Turing Test Really Work to Test for AI? Part II - AI Technologies This section discusses FIVE core AI Technologies which provide the building blocks of various different kind of AI applications, they are: Machine Learning (ML), Data Mining (DM), Computer Vision (CV), Natural Languages Processing (NLP), Ontology-based Search Engine (OSE). Chap 3 Machine Learning (ML) 3.1 What is Machine Learning (ML)? 3.2 Supervised Learning (SL) 3.3 Unsupervised Learning (UL) 3.4 Reinforcement Learning (RL) 3.5 Case Study - How can we improve our memory by using Reinforcement Learning? Chap 4 Data Mining (DM) & Big Data (BD) 4.1 What is Knowledge? 4.2 Data Mining, Big Data and Knowledge Discovery 4.3 Traditional Data Mining Technology 4.4 AI-based Data Mining Technology 4.5 Case Study - How to "mine" our purchase habit using Data Mining Technology? Chap 5 Computer Vision (CV) 5.1 Computer Vision vs Human Vision 5.2 3 Levels of Computer Vision - Figure-ground Segmentation, Pattern Recognition, Active Vision 5.3 Active Vision and Robotics 5.4 Computer Vision Technology 5.5 Case Study - How AI-based Facial Recognition System works? Chap 6 Natural Language Processing (NLP) 6.1 Human Language and Intelligence 6.2 Natural Language Processing in AI 6.3 Speech Recognition and Voice Synthesis 6.4 Machine Translation 6.5 Case Study - English Language Tutoring Robots Chap 7 Ontological-based Search Engine (OSE) 7.1 Human Knowledge and Ontology 7.2 How Search Engine Works? 7.3 Traditional Search Engine vs. Ontological
Software Testing Foundations, 5th Edition
Professional testing of software is an essential task that requires a profound knowledge of testing techniques. The International Software Testing Qualifications Board (ISTQB) has developed a universally accepted, international qualification scheme aimed at software and system testing professionals, and has created the Syllabi and Tests for the "Certified Tester." Today, hundreds of thousands of people have taken the ISTQB certification exams. The authors of Software Testing Foundations, 5th Edition, are among the creators of the Certified Tester Syllabus and are currently active in the ISTQB. This thoroughly revised and updated fifth edition covers the "Foundations Level" (entry level) and teaches the most important methods of software testing. It is designed for self-study and provides the information necessary to pass the Certified Tester-Foundations Level exam, as defined by the ISTQB. Also in this new edition, technical terms have been precisely stated according to the ISTQB glossary. Topics covered: - Fundamentals of Testing - Testing and the Software Lifecycle - Static and Dynamic Testing Techniques - Test Management - Test Tools
AI for Healthcare with Keras and Tensorflow 2.0
Learn how AI impacts the healthcare ecosystem through real-life case studies with TensorFlow 2.0 and other machine learning (ML) libraries.This book begins by explaining the dynamics of the healthcare market, including the role of stakeholders such as healthcare professionals, patients, and payers. Then it moves into the case studies. The case studies start with EHR data and how you can account for sub-populations using a multi-task setup when you are working on any downstream task. You also will try to predict ICD-9 codes using the same data. You will study transformer models. And you will be exposed to the challenges of applying modern ML techniques to highly sensitive data in healthcare using federated learning. You will look at semi-supervised approaches that are used in a low training data setting, a case very often observed in specialized domains such as healthcare. You will be introduced to applications of advanced topics such as the graph convolutional network and how you can develop and optimize image analysis pipelines when using 2D and 3D medical images. The concluding section shows you how to build and design a closed-domain Q&A system with paraphrasing, re-ranking, and strong QnA setup. And, lastly, after discussing how web and server technologies have come to make scaling and deploying easy, an ML app is deployed for the world to see with Docker using Flask.By the end of this book, you will have a clear understanding of how the healthcare system works and how to apply ML and deep learning tools and techniques to the healthcare industry. What You Will LearnGet complete, clear, and comprehensive coverage of algorithms and techniques related to case studies Look at different problem areas within the healthcare industry and solve them in a code-first approachExplore and understand advanced topics such as multi-task learning, transformers, and graph convolutional networksUnderstand the industry and learn ML Who This Book Is ForData scientists and software developers interested in machine learning and its application in the healthcare industry
Multi-Agent Systems
This book constitutes the revised post-conference proceedings of the 18th European Conference on Multi-Agent Systems, EUMAS 2021. The conference was held online in June, 2021. 16 full papers are presented in this volume, each of which carefully reviewed and selected from a total of 51 submissions. The papers report on both early and mature research and cover a wide range of topics in the field of multi-agent systems.
Brain-Inspired Computing
This open access book constitutes revised selected papers from the 4th International Workshop on Brain-Inspired Computing, BrainComp 2019, held in Cetraro, Italy, in July 2019. The 11 papers presented in this volume were carefully reviewed and selected for inclusion in this book. They deal with research on brain atlasing, multi-scale models and simulation, HPC and data infra-structures for neuroscience as well as artificial and natural neural architectures.
Knowledge Science, Engineering and Management
This three-volume set constitutes the refereed proceedings of the 14th International Conference on Knowledge Science, Engineering and Management, KSEM 2021, held in Tokyo, Japan, in August 2021.The 164 revised full papers were carefully reviewed and selected from 492 submissions. The contributions are organized in the following topical sections: knowledge science with learning and AI; knowledge engineering research and applications; knowledge management with optimization and security.
Advances and Trends in Artificial Intelligence. Artificial Intelligence Practices
This two-volume set of LNAI 12798 and 12799 constitutes the thoroughly refereed proceedings of the 34th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2021, held virtually and in Kuala Lumpur, Malaysia, in July 2021.The 87 full papers and 19 short papers presented were carefully reviewed and selected from 145 submissions. The IEA/AIE 2021 conference will continue the tradition of emphasizing on applications of applied intelligent systems to solve real-life problems in all areas. These areas include the following: Part I, Artificial Intelligence Practices: Knowledge discovery and pattern mining; artificial intelligence and machine learning; sematic, topology, and ontology models; medical and health-related applications; graphic and social network analysis; signal and bioinformatics processing; evolutionary computation; attack security; natural language and text processing; fuzzy inference and theory; and sensor and communication networks Part II, From Theory to Practice: Prediction and recommendation; data management, clustering and classification; robotics; knowledge based and decision support systems; multimedia applications; innovative applications of intelligent systems; CPS and industrial applications; defect, anomaly and intrusion detection; financial and supply chain applications; Bayesian networks; BigData and time series processing; and information retrieval and relation extraction
Knowledge Science, Engineering and Management
This three-volume set constitutes the refereed proceedings of the 14th International Conference on Knowledge Science, Engineering and Management, KSEM 2021, held in Tokyo, Japan, in August 2021.The 164 revised full papers were carefully reviewed and selected from 492 submissions. The contributions are organized in the following topical sections: knowledge science with learning and AI; knowledge engineering research and applications; knowledge management with optimization and security.
Artificial Intelligence
This textbook covers the broader field of artificial intelligence. The chapters for this textbook span within three categories: Deductive reasoning methods: These methods start with pre-defined hypotheses and reason with them in order to arrive at logically sound conclusions. The underlying methods include search and logic-based methods. These methods are discussed in Chapters 1through 5.Inductive Learning Methods: These methods start with examples and use statistical methods in order to arrive at hypotheses. Examples include regression modeling, support vector machines, neural networks, reinforcement learning, unsupervised learning, and probabilistic graphical models. These methods are discussed in Chapters 6 through 11. Integrating Reasoning and Learning: Chapters 11 and 12 discuss techniques for integrating reasoning and learning. Examples include the use of knowledge graphs and neuro-symbolic artificial intelligence.The primary audience for this textbook are professors and advanced-level students in computer science. It is also possible to use this textbook for the mathematics requirements for an undergraduate data science course. Professionals working in this related field many also find this textbook useful as a reference.
Knowledge Science, Engineering and Management
This three-volume set constitutes the refereed proceedings of the 14th International Conference on Knowledge Science, Engineering and Management, KSEM 2021, held in Tokyo, Japan, in August 2021.The 164 revised full papers were carefully reviewed and selected from 492 submissions. The contributions are organized in the following topical sections: knowledge science with learning and AI; knowledge engineering research and applications; knowledge management with optimization and security.
