Algoritmer og datastrukturer

Federated Learning for Digital Healthcare Systems critically examines the key factors that contribute to the problem of applying machine learning in healthcare systems and investigates how federated learning can be employed to address the problem. The book discusses, examines, and compares the applications of federated learning solutions in emerging digital healthcare systems, providing a critical look in terms of the required resources, computational complexity, and system performance. In the first section, chapters examine how to address critical security and privacy concerns and how to revamp existing machine learning models. In subsequent chapters, the book's authors review recent advances to tackle emerging efficient and lightweight algorithms and protocols to reduce computational overheads and communication costs in wireless healthcare systems. Consideration is also given to government and economic regulations as well as legal considerations when federated learning is applied to digital healthcare systems.

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 the only comprehensive multiplayer guide written by experienced game designer and developer, Henrique Campos, 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 Description:The 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 for:If 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.

After providing an in-depth introduction to derivative-free global optimization with various constraints, this book presents new original results from well-known experts on the subject. A primary focus of this book is the well-known class of deterministic DIRECT (DIviding RECTangle)-type algorithms. This book describes a new set of algorithms derived from newly developed partitioning, sampling, and selection approaches in the box- and generally-constrained global optimization, including extensions to multi-objective optimization. DIRECT-type optimization algorithms are discussed in terms of fundamental principles, potential, and boundaries of their applicability. The algorithms are analyzed from various perspectives to offer insight into their main features. This explains how and why they are effective at solving optimization problems. As part of this book, the authors also present several techniques for accelerating the DIRECT-type algorithms through parallelization and implementing efficient data structures by revealing the pros and cons of the design challenges involved. A collection of DIRECT-type algorithms described and analyzed in this book is available in DIRECTGO, a MATLAB toolbox on GitHub. Lastly, the authors demonstrate the performance of the algorithms for solving a wide range of global optimization problems with various constraints ranging from a few to hundreds of variables.Additionally, well-known practical problems from the literature are used to demonstrate the effectiveness of the developed algorithms. It is evident from these numerical results that the newly developed approaches are capable of solving problems with a wide variety of structures and complexity levels.Since implementations of the algorithms are publicly available, this monograph is full of examples showing how to use them and how to choose the most efficient ones, depending on the nature of the problem being solved. Therefore, many specialists, students, researchers, engineers, economists, computer scientists, operations researchers, and others will find this book interesting and helpful.

This book discusses state-of-the-art stochastic optimization algorithms for distributed machine learning and analyzes their convergence speed. The book first introduces stochastic gradient descent (SGD) and its distributed version, synchronous SGD, where the task of computing gradients is divided across several worker nodes. The author discusses several algorithms that improve the scalability and communication efficiency of synchronous SGD, such as asynchronous SGD, local-update SGD, quantized and sparsified SGD, and decentralized SGD. For each of these algorithms, the book analyzes its error versus iterations convergence, and the runtime spent per iteration. The author shows that each of these strategies to reduce communication or synchronization delays encounters a fundamental trade-off between error and runtime.

In recent years, the field of artificial intelligence has witnessed an extraordinary resurgence, with deep learning emerging as the cornerstone of numerous breakthroughs across various domains. "Deep Learning and Applications" embarks on a journey into the captivating realm of deep learning, unraveling its intricate concepts, techniques, and transformative potential.This book serves as a comprehensive guide for both newcomers and seasoned practitioners, delving into the foundations of deep learning while illuminating its diverse applications. The rapid evolution of this field has not only enriched our understanding of machine learning but has also revolutionized industries, from healthcare and finance to art and entertainment.However, this book is not merely a theoretical exposition. It celebrates the synergy between theory and practice. With practical examples, code snippets, and case studies, readers are empowered to embark on their own deep learning odyssey. We showcase how to wield the power of frameworks like TensorFlow and PyTorch, demystifying the process of constructing, training, and fine-tuning deep learning models."Deep Learning and Applications" is an invitation to be part of the transformative wave that is reshaping technology and society. Whether you are an aspiring data scientist, a researcher pushing the boundaries of AI, or a curious mind seeking to comprehend the forces shaping our digital age, this book promises a rewarding voyage into the depths of knowledge and innovation.So, embark on this adventure with us, as we navigate the intricate seas of deep learning and its boundless applications.

In a world driven by data, the synergy of programming and machine learning has transformed how we perceive and interact with information. Welcome to "Python for Machine Learning," a comprehensive guide designed to empower both beginners and experienced programmers with the tools to harness the power of Python in the realm of machine learning.Machine learning, once considered a futuristic concept, has evolved into an essential discipline that powers everyday applications, from personalized recommendations to self-driving cars. At the heart of this revolution lies Python, a versatile and approachable programming language that has become the lingua franca of machine learning practitioners.Our goal is not only to teach you the syntax and mechanics of Python for machine learning, but also to cultivate a deeper understanding of the underlying principles. As you progress through this book, you will develop the ability to think critically about data, algorithms, and their applications.

This book constitutes the proceedings of the 19th IMA International Conference, IMACC 2023, held in London, UK, during December 12¿14, 2023The 14 full papers included in this volume were carefully reviewed and selected from 36 submissions. This volume presents cutting-edge results in a variety of areas, including coding theory, symmetric cryptography, zeroknowledge protocols, digital signature schemes and extensions, post-quantum cryptography and cryptography in practice.

The book synthesizes research on the analysis of biomedical ontologies using formal concept analysis, including through auditing, curation, and enhancement. As the evolution of biomedical ontologies almost inevitably involves manual work, formal methods are a particularly useful tool for ontological engineering and practice, particularly in uncovering unexpected "e;bugs"e; and content materials.  The book first introduces simple but formalized strategies for discovering undesired and incoherent patterns in ontologies before exploring the application of formal concept analysis for semantic completeness. The book then turns to formal concept analysis, a classical approach used in the mathematical treatment of orders and lattices, as an ontological engineering principle, focusing on the structural property of ontologies with respect to its conformation to lattice or not (non-lattice). The book helpfully covers the development of more efficient algorithms for non-lattice detection and extraction required by exhaustive lattice/non-lattice analysis. The book goes on to highlight the power and utility of uncovering non-lattice structure for debugging ontologies and describes methods that leverage the linguistic information in concept names (labels) for ontological analysis. It also addresses visualization and performance evaluation issues before closing with an overview and forward-looking perspectives on the field.  This book is intended for graduate students and researchers interested in biomedical ontologies and their applications. It can be a useful supplement for courses on knowledge representation and engineering and also provide readers with a reference for related scientific publications and literature to assist in identifying potential research topics. All mathematical concepts and notations used in this book can be found in standard discrete mathematics textbooks, and the appendix at the end of the book provides a list of key ontological resources, as well as annotated non-lattice and lattice examples that were discovered using the authors' methods, demonstrating how "e;bugs are fixed"e; by converting non-lattices to lattices with minimal edit changes.

This book constitutes the refereed proceedings of the 34th Australasian Database Conference on Databases Theory and Applications, ADC 2023, held in Melbourne, VIC, Australia, during November 1-3, 2023.The 26 full papers presented in this volume are carefully reviewed and selected from 41 submissions. They were organized in topical sections named: Mining Complex Types of Data, Natural Language Processing and Text Analysis, Machine Learning and Computer Vision, Database Systems and Data Storage, Data Quality and Fairness for Graphs and Graph Mining and Graph Algorithms.

This book constitutes the refereed proceedings of the 5th Iberoamerican Conference and 4th Indo-American Conference on Knowledge Graphs and Semantic Web, KGSWC 2023, held jointly in Zaragoza, Spain, during November 13¿15, 2023.The 18 full and 2 short papers presented were carefully reviewed and selected from 50 submissions. They focus on the following topics: knowledge representation; natural language processing/text mining; and machine/deep learning research.

This book presents Internet transport economics as a new approach to understanding the packet-switching paradigm of Internet infrastructure as a global transport system for data packets. It is a prescient view of the Internet's evolution into a content-centric service platform where the quality of services (QoS) cannot be guaranteed due to the tens of thousands of autonomous systems that enact business decisions on peering, routing, and pricing in a way that determines aspects of the Internet ecosystem like network topology, latency and throughput of traffic flows, and performance of network applications. The trafficking issues created in this environment are a critical concern and barrier for user applications that require real-time responses, such as telesurgery and teleoperation of autonomous vehicles, and the book presents the Internet transport economics model as the solution.                While engineering and business are the prevailing lenses through which the Internet is viewed, the book builds its methodological framework around transport. Further delving into economics, it establishes how the Internet can be understood as providing transport services for data packets, whose demand and supply are driven by the QoS metrics of delay and loss, which can be regarded as congestion costs that result in equilibrium rates of traffic flows sent by content providers (CPs). The book goes on to present a stylized model of content provider-to-access provider (CP-AP) service as well as congestion equilibrium and rate equilibrium solution concepts under the Internet transport economics framework. These are used to analyze the problem domains of service differentiation, market structure, and data pricing. Finally, it discusses various potential future applications. This book will be of interest to graduate students and researchers in areas of computer networking and performance evaluation.

This book comprises select proceedings of the 7th International Conference on Data Science and Engineering (ICDSE 2021). The contents of this book focus on responsible data science. This book tries to integrate research across diverse topics related to data science, such as fairness, trust, ethics, confidentiality, transparency, and accuracy. The chapters in this book represent research from different perspectives that offer novel theoretical implications that span multiple disciplines. The book will serve as a reference resource for researchers and practitioners in academia and industry.