Datamodellering og simulering

Videregående kvantitative metoder behandler avancerede emner inden for statistisk modellering af samfundsvidenskabelige fænomener primært med udgangspunkt i data på individniveau. Emnerne i de enkelte kapitler er udvalgte, så de er dækkende for de typer af data, som man oftest vil støde på i samfundsvidenskaberne.De teoretiske overvejelser i kapitlerne illustreres af grundige empiriske illustrationer fra det sociologiske, politologiske, økonomiske eller socialmedicinske område. Vægten er således lagt på anvendelsen af teorien og vil sætte læseren i stand til trinvist at løse et givet modelleringsproblem.Videregående kvantitative metoder henvender sig særligt til samfundsvidenskabelige forskere, master- og ph.d.-studerende, som med baggrund i en viden om elementær statistik har brug for at opruste sig på avancerede emner inden for området, men kan også anvendes af bachelorstuderende, som følger kvantitative fag, der ligger ud over basal kvantitativ metode.

Unleash the power of Python for your data analysis projects with For Dummies! Python is the preferred programming language for data scientists and combines the best features of Matlab, Mathematica, and R into libraries specific to data analysis and visualization.

"This book debunks 10 myths about how hard it really is to design privacy-friendly systems" --

Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible.Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. Youll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what youve learned along the way.Youll learn how to:Wrangletransform your datasets into a form convenient for analysisProgramlearn powerful R tools for solving data problems with greater clarity and easeExploreexamine your data, generate hypotheses, and quickly test themModelprovide a low-dimensional summary that captures true "e;signals"e; in your datasetCommunicatelearn R Markdown for integrating prose, code, and results

As data management and integration continue to evolve rapidly, storing all your data in one place, such as a data warehouse, is no longer scalable. In the very near future, data will need to be distributed and available for several technological solutions. With this practical book, youll learnhow to migrate your enterprise from a complex and tightly coupled data landscape to a more flexible architecture ready for the modern world of data consumption.Executives, data architects, analytics teams, and compliance and governance staff will learn how to build a modern scalable data landscape using the Scaled Architecture, which you can introduce incrementally without a large upfront investment. Author Piethein Strengholt provides blueprints, principles, observations, best practices, and patterns to get you up to speed.Examine data management trends, including technological developments, regulatory requirements, and privacy concernsGo deep into the Scaled Architecture and learn how the pieces fit togetherExplore data governance and data security, master data management, self-service data marketplaces, and the importance of metadata

Between major privacy regulations like the GDPR and CCPA and expensive and notorious data breaches, there has never been so much pressure to ensure data privacy. Unfortunately, integrating privacy into data systems is still complicated. This essential guide will give you a fundamental understanding of modern privacy building blocks, like differential privacy, federated learning, and encrypted computation. Based on hard-won lessons, this book provides solid advice and best practices for integrating breakthrough privacy-enhancing technologies into production systems. Practical Data Privacy answers important questions such as: What do privacy regulations like GDPR and CCPA mean for my data workflows and data science use cases? What does "anonymized data" really mean? How do I actually anonymize data? How does federated learning and analysis work? Homomorphic encryption sounds great, but is it ready for use? How do I compare and choose the best privacy-preserving technologies and methods? Are there open-source libraries that can help? How do I ensure that my data science projects are secure by default and private by design? How do I work with governance and infosec teams to implement internal policies appropriately?

Attackers have to be only right once, but just one mistake will permanently undo them.Book DescriptionThe "Ultimate Cyberwarfare for Evasive Cyber Tactic" is an all-encompassing guide, meticulously unfolding across pivotal cybersecurity domains, providing a thorough overview of cyber warfare. The book begins by unraveling the tapestry of today's cyber landscape, exploring current threats, implementation strategies, and notable trends. From operational security triumphs to poignant case studies of failures, readers gain valuable insights through real-world case studies.The book delves into the force-multiplying potential of the Information Warfare component, exploring its role in offensive cyber operations. From deciphering programming languages, tools, and frameworks to practical insights on setting up your own malware lab, this book equips readers with hands-on knowledge. The subsequent chapters will immerse you in the world of proof-of-concept evasive malware and master the art of evasive adversarial tradecraft. Concluding with a forward-looking perspective, the book explores emerging threats and trends, making it an essential read for anyone passionate about understanding and navigating the complex terrain of cyber conflicts.Table of Contents1. History of Cyber Conflicts2. Notable Threats and Trends3. Operational Security Successes and Failures4. The Information Warfare Component5. Programming Languages, Tools, and Frameworks6. Setting Up Your Malware Lab7. Proof-of-Concept Evasive Malware8. Evasive Adversarial Tradecraft9. Emerging Threats and Trends Index

This is the first book that sums up test-related modeling of digital circuits and systems by a new structural-decision-diagrams model. The model represents structural and functional information jointly and opens a new area of research.The book introduces and discusses applications of two types of structural decision diagrams (DDs): low-level, structurally synthesized binary DDs (SSBDDs) and high-level DDs (HLDDs) that enable diagnostic modeling of complex digital circuits and systems.Topics and features:Provides the definition, properties and techniques for synthesis, compression and optimization of SSBDDs and HLDDsProvides numerous working examples that illustrate the key points of the textDescribes applications of SSBDDs and HLDDs for various electronic design automation (EDA) tasks, such as logic-level fault modeling and simulation, multi-valued simulation, timing-critical path identification, and test generationDiscusses the advantages of the proposed model to traditional binary decision diagrams and other traditional design representationsCombines SSBDDs with HLDDs for multi-level representation of digital systems for enabling hierarchical and cross-level solving of complex test-related tasksThis unique book is aimed at researchers working in the fields of computer science and computer engineering, focusing on test, diagnosis and dependability of digital systems. It can also serve as a reference for graduate- and advanced undergraduate-level computer engineering and electronics courses.Three authors are affiliated with the Dept. of Computer Systems at the Tallinn University of Technology, Estonia: Raimund Ubar is a retired Professor, Jaan Raik and Maksim Jenihhin are tenured Professors. Artur Jutman, PhD, is a researcher at the same university and the CEO of Testonica Lab Ltd., Estonia.

Commissioned by the Society for Modeling and Simulation International (SCS), this needed, useful new ¿Body of Knowledge¿ (BoK) collects and organizes the common understanding of a wide collection of professionals and professional associations.Modeling and simulation (M&S) is a ubiquitous discipline that lays the computational foundation for real and virtual experimentation, clearly stating boundaries¿and interactions¿of systems, data, and representations. The field is well known, too, for its training support via simulations and simulators. Indeed, with computers increasingly influencing the activities of today¿s world, M&S is the third pillar of scientific understanding, taking its place along with theory building and empirical observation.This valuable new handbook provides intellectual support for all disciplines in analysis, design and optimization. It contributes increasingly to the growing number of computational disciplines, addressing the broad variety of contributing as well as supported disciplines and application domains. Further, each of its sections provide numerous references for further information. Highly comprehensive, the BoK represents many viewpoints and facets, captured under such topics as:Mathematical and Systems Theory FoundationsSimulation Formalisms and ParadigmsSynergies with Systems Engineering and Artificial IntelligenceMultidisciplinary ChallengesEthics and PhilosophyHistorical PerspectivesExamining theoretical as well as practical challenges, this unique volume addresses the many facets of M&S for scholars, students, and practitioners. As such, it affords readers from all science, engineering, and arts disciplines a comprehensive and concise representation of concepts, terms, and activities needed to explain the M&S discipline.Tuncer Ören is Professor Emeritus at the University of Ottawa. Bernard Zeigler is Professor Emeritus at the University of Arizona. Andreas Tolk is Chief Scientist at The MITRE Corporation. All three editors are long-time members and Fellows of the Society for Modeling and Simulation International. Under the leadership of three SCS Fellows, Dr. Ören, University of Ottawa, Dr. Zeigler, The University of Arizona, and Dr. Tolk, The MITRE Corporation, more than 50 international scholars from 15 countries provided insights and experience to compile this initial M&S Body of Knowledge.

"This concise textbook introduces an innovative computational approach to quantum mechanics. Emphasizing learning through implementation and simulation of quantum phenomena, it's packed with exercises and examples. Source code and data files are provided, along with solutions. Extra problems with locked solutions are provided online for instructors"--

Data modeling is the single most overlooked feature in Power BI Desktop, yet it's what sets Power BI apart from other tools on the market. This practical book serves as your fast-forward button for data modeling with Power BI, Analysis Services tabular, and SQL databases. It serves as a starting point for data modeling, as well as a handy refresher. Author Markus Ehrenmueller-Jensen, founder of Savory Data, shows you the basic concepts of Power BI's semantic model with hands-on examples in DAX, Power Query, and T-SQL. If you're looking to build a data warehouse layer, chapters with T-SQL examples will get you started. You'll begin with simple steps and gradually solve more complex problems. This book shows you how to: Normalize and denormalize with DAX, Power Query, and T-SQL Apply best practices for calculations, flags and indicators, time and date, role-playing dimensions and slowly changing dimensions Solve challenges such as binning, budget, localized models, composite models, and key value with DAX, Power Query, and T-SQL Discover and tackle performance issues by applying solutions in DAX, Power Query, and T-SQL Work with tables, relations, set operations, normal forms, dimensional modeling, and ETL

"Data fabric, data lakehouse, and data mesh have recently appeared as viable alternatives to the modern data warehouse. These new architectures have solid benefits, but they're also surrounded by a lot of hyperbole and confusion. This practical book provides a guided tour of these architectures to help data professionals understand the pros and cons of each. James Serra, big data and data warehousing solution architect at Microsoft, examines common data architecture concepts, including how data warehouses have had to evolve to work with data lake features. You'll learn what data lakehouses can help you achieve, and how to distinguish data mesh hype from reality. Best of all, you'll be able to determine the most appropriate data architecture for your needs. With this book, you'll: gain a working understanding of several data architectures; learn the strengths and weakness of each approach; distinguish data architecture theory from the reality; pick the best architecture for your use case; understand the differences between data warehouses and data lakes; learn common data architecture concepts to help you build better solutions; explore the historical evolution and characteristics of data architectures; learn essentials of running an architecture design session, team organization, and project success factors."--

Welcome to "Step into Deep Learning," a comprehensive journey into the fascinating world of artificial intelligence and deep learning. In an era where data-driven decision-making and automation have become pivotal in various domains, understanding the principles and techniques of deep learning is more critical than ever. This book serves as your trusty guide, designed to demystify the complex concepts and empower you to embark on your own deep learning adventures.In the pages that follow, we'll embark on a captivating exploration of deep learning, starting with the fundamentals and gradually progressing to more advanced topics. Whether you're a novice eager to grasp the basics or an experienced practitioner seeking to deepen your knowledge, this book offers something for everyone. Along the way, you'll gain hands-on experience through practical examples and exercises, building a solid foundation that enables you to create and deploy cutting-edge AI models. So, let's dive in together, embrace the power of deep learning, and pave the way for a future shaped by intelligent algorithms and innovative solutions.

This textbook addresses the most recent advances and main digital technologies used in farming. The reader will be able to understand the main concepts and techniques currently used to efficiently manage agricultural production systems. The book covers topics in a general and intuitive way, with examples and good illustrations.

Enterprise risk management has always been important. However, the events of the 21st Century have made it even more critical. The top level of business management became suspect after scandals at ENRON, WorldCom, and other business entities. Financially, many firms experienced difficulties from bubbles. The problems of interacting cultures demonstrated risk from terrorism as well, with numerous terrorist attacks, to include 9/11 in the U.S. Risks can arise in many facets of business. Businesses in fact exist to cope with risk in their area of specialization. Financial risk management has focused on banking, accounting, and finance. We have discussed several aspects of risk, to include information systems, disaster management, and supply chain perspectives. The bulk of this book is devoted to presenting a number of operations research models that have been (or could be) applied to enterprise supply risk management, especially from the supply chain perspective.

This book presents the design of modular architecture flight simulators. Safe transportation of people and goods is one of the main directions for the development of the world economy. At the same time, in conditions of constantly increasing intensity of air traffic, the actions of people, responsible for piloting aircraft and air traffic control are of particular importance. In this regard, special attention should be paid to the process of training such specialists. This book describes various flight simulators of an aircraft, as well as to assess the impact of various characteristics of aviation simulators on the quality of skills of aviation specialists. The book discusses the following issues:1) method of setting dynamic parameters;2) methods of correction of simulator parameters, according to expert opinions of operating organizations;3) modules of simulators of operation of various aircraft units and flight conditions;4) prospects for the development of aviation simulators;5) collection and evaluation of information in the process of training on aviation simulators.

**AS SEEN ON BBC BREAKFAST**Will we ever truly understand our cosmic home? This is the story of the technologies that allow us to look up, to learn and to discover our place in the cosmos.'An electrifying new history of the universe' HANNAH FRY, author of Rutherford and Fry's Complete Guide to Absolutely EverythingWe are part of an incredible chain of events stretching 13.8 billion years into the past and even further into the future. But what does that future hold? And how do scientists study the entire universe?The Universe in a Box is Andrew Pontzen's tribute to simulations - the remarkable computer codes that, over the last century, have allowed us to grasp the distant past and far future of the universe. It reveals the stories of pioneering scientists who unlocked the mysteries of the cosmos, and reframes our understanding of galaxies, black holes and space itself.'I was enlightened, amazed, and profoundly impressed' SIR PHILIP PULLMAN, author of His Dark Materials'Compelling...a veritable treasure chest filled with captivating stories'SCIENCE

Deep Learning Applications in Translational Bioinformatics, a new volume in the Advances in Ubiquitous Sensing Application for Healthcare series, offers a detailed overview of basic bioinformatics, deep learning, and various applications of deep learning in translational bioinformatics, including deep learning ensembles, deep learning in protein classification, detection of various diseases, prediction of antiviral peptides, identification of antibiotic resistance, computer aided drug design and drug formulation. This new volume helps researchers working in the field of machine learning and bioinformatics foster future research and development.

The purpose of this book is to show how high-growth enterprises create their business models. To illustrate the background of this topic, the concepts of business models existing in the literature are presented along with their perspective on further development and external conditions that affect them.

Designed as a reference text. Presents the latest developments in bioinformatics, highlighting the importance of bioinformatics in genomics, transcriptomics, metabolism, and cheminformatics analysis, as well as in drug discovery and development.

This book shares new methodologies, technologies, and practices for resolving issues associated with leveraging AI-centric modeling, data analytics, ML-aided models, IoT-driven applications, and cybersecurity techniques in the era of the Industrial Revolution 4.0.

Work through multiple design projects in this part-color guide to understand how Autodesk Fusion 360 helps improve efficiency and draftingKey Features- Understand the project workflow of Autodesk Fusion 360- Design and redesign projects while learning to fix errors- Gain a better insight into repurposing real-world items into Fusion 360 for custom designs- Purchase of the print or Kindle book includes a free PDF eBookBook DescriptionAutodesk Fusion 360 has become an indispensable tool for designers, tinkerers, and engineers worldwide thanks to its versatility that allows for large-scale assemblies and smaller, quick 3D prints. If you've faced challenges with learning Fusion 360, this book will help you overcome them and build the confidence to design your own projects, explaining step-by-step instructions and the purpose of each tool.In this book, you'll dive into the design workspace and learn sketching fundamentals such as setting up a component, recognizing when a sketch is fully constrained, and parametrically flexing models. Through trial and error, you'll work on multiple easy-to-build projects to create simple, useful items that can be quickly 3D printed for use around the house and then advance to much bigger projects that require joint connectivity and large assemblies.By the end of this book, you'll be able to sketch fully parametric designs, translate them into 3D models, and create your own unique designs.What you will learn- Gain proficiency in Fusion 360 user interface, navigation, and functionality- Create and transform simple 2D sketches into 3D models- Manipulate and control parametric 2D sketches using dimensions- Become familiar with drafting on paper and taking measurements with calipers- Create a bicycle assembly part with Fusion 360- Use the form environment to create organic shapes- Render a 3D model and understand how to apply materials and lighting- Generate 2D assembly model drawings for documentation purposesWho this book is forBeginner or intermediate designers who prefer hands-on learning will find this book useful, especially designers, woodworkers, 3D printing enthusiasts, and hobbyists who enjoy creating things, rather than experienced machinists. The basic projects are accessible without prior CAD skills, although some fundamental CAD understanding is beneficial for those interested in going further. It is highly recommended that you use a 3-button mouse for all projects to fully utilize floating pop-up menus.Table of Contents- Working within the Design Workspace- Planes, Sketches, Constraints, and Parametric Dimensions- Project Building Basics- Creating a Customizable S-Hook- Designing Decorative Doorknobs- Designing a Simple Bottle Holder- Creating a Bike Reference Model- Creating a Bottle Reference Model- Building the Bottle Holder- Improving the Bottle Holder Design- The FORM Environment- Modeling a Scary Tealight Ghost- Using Form and Solid Modeling to Create a Cushioned Chair- Using a Scanned Image to Create a 3D Model- Modeling a Bottle Topper

Traditional data architecture patterns are severely limited. To use these patterns, you have to ETL data into each tool--a cost-prohibitive process for making warehouse features available to all of your data. The lack of flexibility with these patterns requires you to lock into a set of priority tools and formats, which creates data silos and data drift. This practical book shows you a better way. Apache Iceberg provides the capabilities, performance, scalability, and savings that fulfill the promise of an open data lakehouse. By following the lessons in this book, you'll be able to achieve interactive, batch, machine learning, and streaming analytics with this high-performance open source format. Authors Tomer Shiran, Jason Hughes, and Alex Merced from Dremio show you how to get started with Iceberg. With this book, you'll learn: The architecture of Apache Iceberg tables What happens under the hood when you perform operations on Iceberg tables How to further optimize Iceberg tables for maximum performance How to use Iceberg with popular data engines such as Apache Spark, Apache Flink, and Dremio Discover why Apache Iceberg is a foundational technology for implementing an open data lakehouse.