Algoritmer og datastrukturer

This book offers a comprehensive introduction to the central ideas that underpin deep learning. It is intended both for newcomers to machine learning and for those already experienced in the field. Covering key concepts relating to contemporary architectures and techniques, this essential book equips readers with a robust foundation for potential future specialization. The field of deep learning is undergoing rapid evolution, and therefore this book focusses on ideas that are likely to endure the test of time.The book is organized into numerous bite-sized chapters, each exploring a distinct topic, and the narrative follows a linear progression, with each chapter building upon content from its predecessors. This structure is well-suited to teaching a two-semester undergraduate or postgraduate machine learning course, while remaining equally relevant to those engaged in active research or in self-study.A full understanding of machine learning requires some mathematical background and so the book includes a self-contained introduction to probability theory. However, the focus of the book is on conveying a clear understanding of ideas, with emphasis on the real-world practical value of techniques rather than on abstract theory. Complex concepts are therefore presented from multiple complementary perspectives including textual descriptions, diagrams, mathematical formulae, and pseudo-code.Chris Bishop is a Technical Fellow at Microsoft and is the Director of Microsoft Research AI4Science. He is a Fellow of Darwin College Cambridge, a Fellow of the Royal Academy of Engineering, and a Fellow of the Royal Society. Hugh Bishop is an Applied Scientist at Wayve, a deep learning autonomous driving company in London, where he designs and trains deep neural networks. He completed his MPhil in Machine Learning and Machine Intelligence at Cambridge University.¿Chris Bishop wrote a terrific textbook on neural networks in 1995 and has a deep knowledge of the field and its core ideas. His many years of experience in explaining neural networks have made him extremely skillful at presenting complicated ideas in the simplest possible way and it is a delight to see these skills applied to the revolutionary new developments in the field.¿ -- Geoffrey Hinton"With the recent explosion of deep learning and AI as a research topic, and the quickly growing importance of AI applications, a modern textbook on the topic was badly needed. The "New Bishop" masterfully fills the gap, covering algorithms for supervised and unsupervised learning, modern deep learning architecture families, as well as how to apply all of this to various application areas." ¿ Yann LeCun¿This excellent and very educational book will bring the reader up to date with the main concepts and advances in deep learning with a solid anchoring in probability. These concepts are powering current industrial AI systems and are likely to form the basis of further advances towards artificial general intelligence.¿ -- Yoshua Bengio

I 2000-tallet møder vi Ekko i medieteknologien; i virale memes, shitstorme, hekseprocesser og ekkokamre. Den, der får algoritmerne på sin side, vinder opmærksomheds- økonomiens største trofæ: at blive set. Og Ekkos store kærlighed var Narcissus; ham, der druknede i sit eget spejlbillede.I dette essay fletter Lena Lindgren politik, mytologi, psykologi og videnskab sammen med scener fra Silicon Valley. Ekko er en samtidsdiagnose og tanker om nogle af de mest afgørende spørgsmål i vores tid – et forsøg på at skildre menneskehedens blind date med kunstig intelligens.Lena Lindgren (f.1969) bor i Oslo. Hun er til daglig politisk kommentator i Morgenbladet. Ekko – et essay om algoritmer og begær vandt Brageprisen 2021 i Norge.“Lena Lindgren følger sporene som en detektiv. Og det er spændende som en thriller.”– Juryens begrundelse, Brageprisen”… det er strålende tænkt og førsteklasses essayistik.”Kjetil Røed, Vårt Land”Anbefales på det stærkeste!”Marius Wulfsberg, Dagbladet

Get a fundamental understanding of asynchronous programming and Rust's futures by working through examples that show you how everything really worksKey Features- Master asynchronous Rust through examples focusing on key concepts- Build a solid understanding of concepts such as coroutines, fibers, futures, and callbacks- Explore Rust's futures, craft your own runtime, and excel in handling stacks, ABIs, syscalls, and inline assembly- Purchase of the print or Kindle book includes a free PDF eBookBook DescriptionStep into the world of asynchronous programming with confidence by conquering the challenges of unclear concepts with this hands-on guide. Using functional examples, this book simplifies the trickiest concepts, exploring goroutines, fibers, futures, and callbacks to help you navigate the vast Rust async ecosystem with ease.You'll start by building a solid foundation in asynchronous programming and explore diverse strategies for modeling program flow. The book then guides you through concepts like epoll, coroutines, green threads, and callbacks using practical examples. The final section focuses on Rust, examining futures, generators, and the reactor-executor pattern. You'll apply your knowledge to create your own runtime, solidifying expertise in this dynamic domain. Throughout the book, you'll not only gain proficiency in Rust's async features but also see how Rust models asynchronous program flow.By the end of the book, you'll possess the knowledge and practical skills needed to actively contribute to the Rust async ecosystem.What you will learn- Explore the essence of asynchronous program flow and its significance- Understand the difference between concurrency and parallelism- Gain insights into how computers and operating systems handle concurrent tasks- Uncover the mechanics of async/await- Understand Rust's futures by implementing them yourself- Implement green threads from scratch to thoroughly understand themWho this book is forThis book is for programmers who want to enhance their understanding of asynchronous programming, especially those experienced in VM'ed or interpreted languages like C#, Java, Python, JavaScript, and Go. If you work with C or C++ but have had limited exposure to asynchronous programming, this book serves as a resource to broaden your knowledge in this area.Although the examples are predominantly in Rust, the intricacies of Rust's futures are covered in detail. So, anyone with a keen interest in learning Rust or with working knowledge of Rust will be able to get the most out of this book.Table of Contents- An Introduction to Asynchronous Programming- Epoll, Kqueue and IOCP- Epoll example- Different strategies for modelling asynchronous program flow- Stackfull Coroutines/Green Threads/Fibers [Example]- Callbacks and promises [Example]- Futures in Rust- Coroutines and async/await- Runtimes, Wakers, and the Reactor-Executor Pattern- Coroutines, Self-Referential Structs, and Pinning- Creating Your Own Runtime

Delve into the realm of generative AI and large language models (LLMs) while exploring modern deep learning techniques, including LSTMs, GRUs, RNNs with new chapters included in this 50% new edition overhaulPurchase of the print or Kindle book includes a free eBook in PDF format.Key FeaturesFamiliarize yourself with advanced deep learning architecturesExplore newer topics, such as handling hidden bias in data and algorithm explainabilityGet to grips with different programming algorithms and choose the right data structures for their optimal implementationBook DescriptionThe ability to use algorithms to solve real-world problems is a must-have skill for any developer or programmer. This book will help you not only to develop the skills to select and use an algorithm to tackle problems in the real world but also to understand how it works.You'll start with an introduction to algorithms and discover various algorithm design techniques, before exploring how to implement different types of algorithms, with the help of practical examples. As you advance, you'll learn about linear programming, page ranking, and graphs, and will then work with machine learning algorithms to understand the math and logic behind them.Case studies will show you how to apply these algorithms optimally before you focus on deep learning algorithms and learn about different types of deep learning models along with their practical use.You will also learn about modern sequential models and their variants, algorithms, methodologies, and architectures that are used to implement Large Language Models (LLMs) such as ChatGPT.Finally, you'll become well versed in techniques that enable parallel processing, giving you the ability to use these algorithms for compute-intensive tasks.By the end of this programming book, you'll have become adept at solving real-world computational problems by using a wide range of algorithms.What you will learnDesign algorithms for solving complex problemsBecome familiar with neural networks and deep learning techniquesExplore existing data structures and algorithms found in Python librariesImplement graph algorithms for fraud detection using network analysisDelve into state-of-the-art algorithms for proficient Natural Language Processing illustrated with real-world examplesCreate a recommendation engine that suggests relevant movies to subscribersGrasp the concepts of sequential machine learning models and their foundational role in the development of cutting-edge LLMsWho this book is forThis computer science book is for programmers or developers who want to understand the use of algorithms for problem-solving and writing efficient code.Whether you are a beginner looking to learn the most used algorithms concisely or an experienced programmer looking to explore cutting-edge algorithms in data science, machine learning, and cryptography, you'll find this book useful.Python programming experience is a must, knowledge of data science will be helpful but not necessary.Table of ContentsCore AlgorithmsData StructuresSorting and Searching AlgorithmsDesigning AlgorithmsGraph AlgorithmsUnsupervised Machine Learning AlgorithmsSupervised Learning AlgorithmsNeural Network AlgorithmsNatural Language ProcessingSequential ModelsAdvanced Machine Learning ModelsRecommendation EnginesAlgorithmic Strategies for Data Handling Large-Scale AlgorithmsEvaluating Algorithmic SolutionsPractical Considerations

Are you ready to take your programming skills to the next level?Look no further! "The Problem Solver's Guide To Coding" is the ultimate guide that will revolutionize your approach to coding challenges.Inside this book, you'll find a comprehensive collection of meticulously solved and explained coding challenges, accompanied by tips and strategies to enhance your programming skills, especially data structures, algorithms, and techniques. Whether you're a beginner or an experienced coder, this book is designed to challenge and elevate your skills to new heights.This book is not just about providing solutions - it's about empowering you to become a coding champion. Each chapter offers detailed explanations, step-by-step breakdowns, and practical tips to sharpen your coding techniques. You'll learn how to optimize time and space complexity, employ practical algorithms, and easily approach common coding patterns.What people say about the book"The book not only focuses on solving specific problems but also provides guidance on writing clean, efficient, and readable code. It can be a valuable tool for readers who are preparing for coding interviews or want to enhance their problem-solving and coding skills." - Dinh Thai Minh Tam, R&D Director at Mobile Entertainment Corp."Through each specific exercise, you can accumulate more ways of thinking in analyzing and designing algorithms to achieve correct results and effective performance." - Le Nhat-Tung, Software Developer, Founder of TITV.vn."The book provides not only solutions to each selected problem, but also many notes and suggestions, hoping to help readers practice analytical thinking and programming skills." - Nguyen Tuan Hung, Ph.D., Assistant Professor, Tokyo University of Agriculture and Technology."If you spend time reading, practicing, thinking and analyzing all the problems, I believe you will be a master in coding and problem-solving. " - Tran Anh Tuan, Ph.D, Academic Manager at VTC Academy.Learn more at theproblemsolversguidetocoding.com

Delve into the inner workings of JVM and explore internals, memory management, and performance optimizationKey Features:- Uncover the intricacies of JVM, from class loading to garbage collection, and more- Master JVM memory management for efficient resource use and reduced overhead- Apply JVM knowledge through case studies, reinforcing your understanding of internals- Purchase of the print or Kindle book includes a free PDF eBookBook Description:Mastering the Java Virtual Machine is a comprehensive guide that will take you into the heart of the Java programming language, guiding you through the intricate workings of the Java Virtual Machine (JVM) and equipping you with essential skills to become a proficient Java developer.You'll start by understanding the JVM, exploring its architecture and how it executes Java code. Through detailed explanations and real-world examples, you'll gain a deep understanding of JVM internals, enabling you to write efficient and optimized Java applications. As you progress, you'll delve into memory management and execution, unraveling the complexities of heap and stack management, garbage collection, and memory profiling. You'll learn how memory is allocated and reclaimed in the JVM, as well as how to optimize memory usage and identify performance bottlenecks in your applications. With this knowledge, you'll be able to create Java programs that are not only robust but also highly performant.By the end of this Java book, you'll have the skills needed to excel in Java programming, writing efficient and maintainable code.What You Will Learn:- Understand JVM architecture and bytecode execution- Explore memory management and optimize memory usage- Compare and evaluate alternative JVMs like GraalVM- Master reflection for dynamic behavior in Java applications- Use Java annotation processors for code generation- Get to grips with reactive programming principles for scalable applicationsWho this book is for:This book is for Java developers looking to deepen their expertise in the Java Virtual Machine (JVM) and optimize Java applications for peak performance. It is ideal for both intermediate-level and seasoned professionals, who want to explore specific aspects such as JVM internals, memory management, threading, security, and performance tuning.Table of Contents- Introduction to the Java Virtual Machine- Class File Structure- Understanding Bytecodes- Memory Management- Execution Engine- Class Loading and Dynamic Class Loading- Garbage Collection and Memory Profiling- GraalVM- JVM Ecosystem and Alternative JVMs- Java Framework Principles- Reflection- Java Annotation Processor

Dive into the endless possibilities of data structures and algorithms and have fun doing it¿DESCRIPTION Go, designed by Google, is a modern, open-source language known for its simplicity, readability, and efficiency. It excels at building web applications, network tools, and cloud services. Its clear syntax and built-in concurrency features make it a popular choice for modern developers.This guide simplifies the basics by introducing arrays, lists, stacks, queues, maps, trees, and graphs in a practical way. Get hands-on experience, understand essential operations, and compare strengths and weaknesses. Perfect your skills with searching, sorting, and efficient data retrieval techniques. Traverse graphs and trees with ease, all illustrated in the Go code for real-world application, and conclude with insights for ongoing learning.After reading this book, the reader can determine when and why specific data structures should be used and when an algorithm best fits the actual problem's solution.WHAT YOU WILL LEARN¿ Decide which data structure is the most suitable for a particular problem.¿ Implement different algorithms with the Go programming language.¿ Recognize which algorithm is best suited for certain scenarios.¿ Utilize data structures and algorithm implementations from Go's standard library.¿ Learn how real-life problems can be solved and simulated.WHO THIS BOOK IS FORThe book targets beginners and experienced developers who want to learn how to implement particular algorithms. It is also helpful for developers who wish to expand their knowledge of data structures and algorithms.

A hands-on, active learning textbook for CS2 courses.

This project was motivated by the upcoming fiftieth anniversary of the IFIP Human Choice and Computers (HCC) conference, the event that led to IFIP¿s Technical Committee 9 (TC 9). Although IFIP committees are mainly technical, TC 9 is dedicated to research at the intersection of information and communication technology (ICT) with society. In addition to sponsoring HCC, TC 9 supports groups that have specific research interests. In consultation with their members, the leaders of each group offer chapters about their groups¿ history and goals. An additional chapter describes TC 9¿s formation, and an appendix details the national groups that work closely with TC 9. Overall, this volume is a useful guide to the historical development of research on ICT and society, providing readers with important reference works and relevant themes, and also points to likely new trends in these domains.

This book focuses on Krylov subspace methods for solving linear systems, which are known as one of the top 10 algorithms in the twentieth century, such as Fast Fourier Transform and Quick Sort (SIAM News, 2000). Theoretical aspects of Krylov subspace methods developed in the twentieth century are explained and derived in a concise and unified way. Furthermore, some Krylov subspace methods in the twenty-first century are described in detail, such as the COCR method for complex symmetric linear systems, the BiCR method, and the IDR(s) method for non-Hermitian linear systems.The strength of the book is not only in describing principles of Krylov subspace methods but in providing a variety of applications: shifted linear systems and matrix functions from the theoretical point of view, as well as partial differential equations, computational physics, computational particle physics, optimizations, and machine learning from a practical point of view.The book is self-contained in that basic necessary concepts of numerical linear algebra are explained, making it suitable for senior undergraduates, postgraduates, and researchers in mathematics, engineering, and computational science. Readers will find it a useful resource for understanding the principles and properties of Krylov subspace methods and correctly using those methods for solving problems in the future.

This book constitutes the refereed proceedings of the 19th International Conference on Formal Aspects of Component Software, FACS 2023, which took place virtually during October 19-20, 2023.The 11 full papers included in this book were carefully reviewed and selected from 23 submissions. They were organized in topical sections as follows: cloud computing, cyber-physical and critical systems, and the Internet of Things.

This book explores the connections between qualitative data reuse, big social research, and data curation. A review of existing literature identifies the key issues of context, data quality and trustworthiness, data comparability, informed consent, privacy and confidentiality, and intellectual property and data ownership. Through interviews of qualitative researchers, big social researchers, and data curators, the author further examines each key issue and produces new insights about how domain differences affect each community of practice¿s viewpoints, different strategies that researchers and curators use to ensure responsible practice, and different perspectives on data curation. The book suggests that encouraging connections between qualitative researchers, big social researchers, and data curators can support responsible scaling up of social research, thus enhancing discoveries in social and behavioral science.

Master code refactoring techniques, improve code quality, design, and maintainability, and boost your development productivity with this comprehensive handbookKey Features:Get a thorough understanding of code refinement for enhanced codebase efficiencyWork with real-world examples and case studies for hands-on learning and applicationFocus on essential tools, emphasizing development productivity and robust coding habitsPurchase of the print or Kindle book includes a free PDF eBookBook Description:Refactoring in Java serves as an indispensable guide to enhancing your codebase's quality and maintainability.The book begins by helping you get to grips with refactoring fundamentals, including cultivating good coding habits and identifying red flags. You'll explore testing methodologies, essential refactoring techniques, and metaprogramming, as well as designing a good architecture. The chapters clearly explain how to refactor and improve your code using real-world examples and proven techniques. Part two equips you with the ability to recognize code smells, prioritize tasks, and employ automated refactoring tools, testing frameworks, and code analysis tools. You'll discover best practices to ensure efficient code improvement so that you can navigate complexities with ease. In part three, the book focuses on continuous learning, daily practices enhancing coding proficiency, and a holistic view of the architecture. You'll get practical tips to mitigate risks during refactoring, along with guidance on measuring impact to ensure that you become an efficient software craftsperson.By the end of this book, you'll be able to avoid unproductive programming or architecturing, detect red flags, and propose changes to improve the maintainability of your codebase.What You Will Learn:Recognize and address common issues in your codeFind out how to determine which improvements are most importantImplement techniques such as using polymorphism instead of conditionsEfficiently leverage tools for streamlining refactoring processesEnhance code reliability through effective testing practicesDevelop the skills needed for clean and readable code presentationGet to grips with the tools you need for thorough code examinationApply best practices for a more efficient coding workflowWho this book is for:This book is for Java developers, software architects, and technical leads looking for a comprehensive guide to advancing their skills in software design and refactoring. The book is ideal for experienced Java enthusiasts, quality assurance engineers, and codebase maintainers as it provides practical insights, real-world examples, and essential patterns. Development managers who want to foster clean coding practices by using best practices for efficient workflows will also find this book useful.

Build powerful software solutions and develop proficiency in Haskell, from understanding the foundational principles through to mastering advanced functional programming conceptsKey Features:Learn from an expert lecturer and researcher who knows all the ins and outs of HaskellDevelop a clear understanding of Haskell, from the basics through to advanced conceptsGet to grips with all the key functional programming techniquesPurchase of the print or Kindle book includes a free PDF eBookBook Description:With software systems reaching new levels of complexity and programmers aiming for the highest productivity levels, software developers and language designers are turning toward functional programming because of its powerful and mature abstraction mechanisms. This book will help you tap into this approach with Haskell, the programming language that has been leading the way in pure functional programming for over three decades.The book begins by helping you get to grips with basic functions and algebraic datatypes, and gradually adds abstraction mechanisms and other powerful language features. Next, you'll explore recursion, formulate higher-order functions as reusable templates, and get the job done with laziness. As you advance, you'll learn how Haskell reconciliates its purity with the practical need for side effects and comes out stronger with a rich hierarchy of abstractions, such as functors, applicative functors, and monads. Finally, you'll understand how all these elements are combined in the design and implementation of custom domain-specific languages for tackling practical problems such as parsing, as well as the revolutionary functional technique of property-based testing.By the end of this book, you'll have mastered the key concepts of functional programming and be able to develop idiomatic Haskell solutions.What You Will Learn:Write pure functions in all their forms - that is basic, recursive, and higher-order functionsModel your data using algebraic datatypesMaster Haskell's powerful type-class mechanism for ad hoc overloadingFind out how Haskell's laziness gets the job doneReconcile Haskell's functional purity with side effectsFamiliarize yourself with the functor, applicative functor, monad hierarchyDiscover how to solve problems with domain-specific languagesFind more bugs with Haskell's property-based testing approachWho this book is for:If you are a programmer looking to gain knowledge of Haskell who's never been properly introduced to functional programming, this book is for you. Basic experience with programming in a non-functional language is a prerequisite. This book also serves as an excellent guide for programmers with limited exposure to Haskell who want to deepen their understanding and foray further into the language.

Use the computational thinking philosophy to solve complex problems by designing appropriate algorithms to produce optimal results across various domainsKey FeaturesDevelop logical reasoning and problem-solving skills that will help you tackle complex problemsExplore core computer science concepts and important computational thinking elements using practical examplesFind out how to identify the best-suited algorithmic solution for your problemBook DescriptionComputational thinking helps you to develop logical processing and algorithmic thinking while solving real-world problems across a wide range of domains. It's an essential skill that you should possess to keep ahead of the curve in this modern era of information technology. Developers can apply their knowledge of computational thinking to solve problems in multiple areas, including economics, mathematics, and artificial intelligence.This book begins by helping you get to grips with decomposition, pattern recognition, pattern generalization and abstraction, and algorithm design, along with teaching you how to apply these elements practically while designing solutions for challenging problems. You'll then learn about various techniques involved in problem analysis, logical reasoning, algorithm design, clusters and classification, data analysis, and modeling, and understand how computational thinking elements can be used together with these aspects to design solutions. Toward the end, you will discover how to identify pitfalls in the solution design process and how to choose the right functionalities to create the best possible algorithmic solutions.By the end of this algorithm book, you will have gained the confidence to successfully apply computational thinking techniques to software development.What you will learnFind out how to use decomposition to solve problems through visual representationEmploy pattern generalization and abstraction to design solutionsBuild analytical skills to assess algorithmic solutionsUse computational thinking with Python for statistical analysisUnderstand the input and output needs for designing algorithmic solutionsUse computational thinking to solve data processing problemsIdentify errors in logical processing to refine your solution designApply computational thinking in domains, such as cryptography, and machine learningWho this book is forThis book is for students, developers, and professionals looking to develop problem-solving skills and tactics involved in writing or debugging software programs and applications. Familiarity with Python programming is required.Table of ContentsFundamentals of Computer ScienceElements of Computational ThinkingUnderstanding Algorithms and Algorithmic ThinkingUnderstanding Logical ReasoningErrorsExploring Problem AnalysisDesigning Solutions and Solution ProcessesIdentifying Challenges within SolutionsIntroduction to PythonUnderstanding Input and Output to Design a Solution AlgorithmControl FlowUsing Computational Thinkning and Python in Simples ChallengesDebuggingUsing Python in Experimental and Data AnalysisUsing Classification and Clusters Introduction to Machine LearningUsing Computational Thinking and Pythin in Statistical AnalysisApplied Computational Thinking ProblemsAdvanced Applied Computational Thinking ProblemsUsage of Cloud Platforms

Credit Scoring: Definition and Role in Loan Decisions Are you looking to get a mortgage or need a loan to buy a new car? When you apply for any type of loan, banks will consider your credit score. It is a number that tells them about your financial fitness and gives them insight into your ability to repay your loan. What is a Credit Score? A credit score is a three-digit number that ranges from 300 to 900. It is calculated based on your credit history. It takes into account various factors, such as your payment history, outstanding balances, recent credit inquiries, and your credit mix. For example, if you have always made your payments on time and your balances are low, your credit score will be high. On the other hand, if you have late payments or high balances, your score will be low. Role of Credit Scores in Loan Decisions Banks use credit scores to assess your risk as a borrower. They want to make sure that you are likely to repay your loan. A high credit score indicates that you are a low-risk borrower and that you are likely to be approved for a loan. A low credit score indicates that you are a high-risk borrower and that you may be denied a loan or charged a higher interest rate.

This book constitutes the refereed proceedings of the 21st International Workshop on Approximation and Online Algorithms, WAOA 2023, held in Amsterdam, The Netherlands, during September 7¿8, 2023The 16 full papers included in this book are carefully reviewed and selected from 43 submissions. The topics of WAOA 2023 were algorithmic game theory, algorithmic trading, coloring and partitioning, competitive analysis, computational advertising, computational finance, cuts and connectivity, FPT-approximation algorithms, geometric problems, graph algorithms, inapproximability results, mechanism design, network design, packing and covering, paradigms for the design and analysis of approximation and online algorithms, resource augmentation, and scheduling problems

This book constitutes the refereed post-conference proceedings of the 7th International Conference on Future Access Enablers for Ubiquitous and Intelligent Infrastructures, FABULOUS 2023, held in Bratislava, Slovakia, in October 2023. The 14 revised full papers were carefully reviewed and selected from 35 submissions. The papers are organized in thematic sessions on: future access networks; sustainable communications and computing infrastructures; smart environment applications / scenarios.

This book takes readers through the sensational history of blockchains and their potential to revolutionize database systems of the future. In order to demystify blockchains, the book capitalizes on decades of research and field testing of existing database and distributed systems and applies these familiar concepts to the novel blockchain system. It then utilizes this framework to explore the essential block platform underpinning blockchains, which is often misunderstood as a specific attribute of cryptocurrencies rather than the core of the decentralized system independent of application. The book explores the nature of these decentralized systems, which have no single owner and build robustness through a multitude of stakeholder contributions. In this way, blockchains can build trust into existing systems and thus present attractive solutions for various domains across both academia and industry. Despite this, high-impact and real-world applications of blockchain have yet to be realized outside of cryptocurrencies like Bitcoin. The book establishes how this new data system, if properly applied, can disrupt the sector in much the same way databases did so many years ago. The book explores the fundamental technical limitations that may be preventing blockchain from realizing this potential and how to overcome or mitigate them. Readers who are completely new to blockchains will find this book to be a comprehensive survey of the state of the art in blockchain technology. Readers with some experience of blockchains, for example through developing cryptocurrencies, will likely find the book's database perspective enlightening. Finally, researchers already working with blockchain will learn to identify existing gaps in the design space and explore potential solutions for creating the next generation of blockchain systems.

Level up your Godot 4 networking skills with this comprehensive guide featuring dedicated servers and persistent worlds, illustrated with key images in colorKey Features- Ensure player synchronization and coexistence in a game world- Mitigate latency in your multiplayer games to design a seamless shared experience- Optimize and debug your games using profilers and monitors to visualize performance- Purchase of the print or Kindle book includes a free PDF eBookBook DescriptionThe Essential Guide to Creating Multiplayer Games with Godot 4.0 guides you in exploring the built-in network API for online multiplayer games, offering practical knowledge through concrete use cases.Throughout the book, you'll assume the role of a network engineer in a fictional indie game studio, tackling real-world requests from your peers and gaining expertise in adding new network features to the studio's games. Following step-by-step instructions, you'll go from making your first network handshake to optimizing online gameplay. You'll learn how to sync players and pass data over the internet as you add online multiplayer features to a top-down shooter adventure game.This book puts you in a fictional game project team where you set up your first online server before advancing to creating an online chat system and transitioning local gameplay to go online. With a focus on implementing multiplayer features, you'll create shared world adventures and learn optimization techniques to allow more players to join your virtual world.By the end of this book, you'll have learned how to set up a client-server network, implement remote procedure calls (RPCs), sync node properties remotely, and optimize your games to create smooth online multiplayer experiences.What you will learn- Understand the fundamentals of networking and remote data exchange between computers- Use the Godot game engine's built-in API to set up a network for players- Master remote procedure calls and learn how to make function calls on objects remotely- Enhance your GDScript proficiency to get the most out of this powerful language- Explore industry-standard solutions for common online multiplayer challenges- Improve your networking skills and discover how to turn single-player games into multiplayer experiencesWho this book is forIf you're involved in game development with Godot and want to add multiplayer capabilities to enrich the shared gaming experience, then this book is for you. You'll also find this book useful if you're a network engineer looking to gain hands-on experience with practical projects. To get the most out of this book, a prior understanding of the Godot Engine design philosophy, the GDScript programming language, the SceneTree structure, and how nodes work is essential.Table of Contents- Setting up a server for multiplayer game- Sending and receiving data- Making a lobby to gather players together- Creating an online chat- Making an online quiz game- Building an online checkers game- Developing an online Pong- Designing an online co-op platformer- Creating a top-down adventure game- Debugging and profiling the network- Optimizing data requests- Implementing prediction and interpolation- Caching data to decrease bandwidth

The textbook presents basic concepts of signals and systems in a clear manner, based on the author's 15+ years of teaching the undergraduate course for engineering students. To attain full benefit from the content, readers should have a strong knowledge of calculus and be familiar with integration, differentiation, and summation operations. The book starts with an introduction to signals and systems and continues with coverage of basic signal functions and their manipulations; energy, power, convolution, and systems; Fourier analysis of continuous time signals and digital signals; Laplace transform; and Z transforms. Practical applications are included throughout. The book is also packed with solved examples, self-study exercises, and end of chapter problems.