Datamodellering og simulering

Why is Google Analytics 4 the most modern data model available for digital marketing analytics? Because rather than simply report what has happened, GA4's new cloud integrations enable more data activationlinking online and offline data across all your streams to provide end-to-end marketing data. This practical book prepares you for the future of digital marketing by demonstrating how GA4 supports these additional cloud integrations.Author Mark Edmondson, Google Developer Expert for Google Analytics and Google Cloud, provides a concise yet comprehensive overview of GA4 and its cloud integrations. Data, business, and marketing analysts will learn major facets of GA4's powerful new analytics model, with topics including data architecture and strategy, and data ingestion, storage, and modeling. You'll explore common data activation use cases and get guidance on how to implement them.You'll learn:How Google Cloud integrates with GA4The potential use cases that GA4 integrations can enableSkills and resources needed to create GA4 integrationsHow much GA4 data capture is necessary to enable use casesThe process of designing dataflows from strategy though data storage, modeling, and activation

Learn how and when to use the right data structures in any situation, strengthening your computational thinking, problem-solving, and programming skills in the process.This accessible and entertaining book provides an in-depth introduction to computational thinking through the lens of data structures — a critical component in any programming endeavor. You’ll learn how to work with more than 15 key data structures, from stacks, queues, and caches to bloom filters, skip lists, and graphs. You’ll also master linked lists by virtually standing in line at a cafe, hash tables by cataloging the history of the summer Olympics, and Quadtrees by neatly organizing your kitchen cabinets, all while becoming familiar with basic computer science concepts, like recursion and running time analysis.

This book constitutes the refereed proceedings of the 14th International Conference on Systems Simulation, Asia Simulation 2014, held in Kitakyushu, Japan, in October 2014. The 32 revised full papers presented were carefully reviewed and selected from 69 submissions. The papers are organized in topical sections on modeling and simulation technology; network simulation; high performance computing and cloud simulation; numerical simulation and visualization; simulation of instrumentation and control application; simulation technology in diversified higher education; general purpose simulation.

This book constitutes the proceedings of the 14th International Conference on Transport Systems Telematics, TST 2014, held in Katowice/Krakow and Ustron, Poland, in October 2014. The 49 papers included in this volume were carefully reviewed and selected from 125 submissions. The papers provide an overview of solutions being developed in the fields of transport telematics and intelligent transport systems.

This book constitutes the proceedings of the 9th International Conference on Bio-inspired Computing: Theories and Applications, BIC-TA 2014, held in Wuhan, China, in October 2014. The 109 revised full papers presented were carefully reviewed and selected from 204 submissions. The papers focus on four main topics, namely evolutionary computing, neural computing, DNA computing, and membrane computing.

This book constitutes the refereed proceedings of the 5th International Conference on Computational Logistics, ICCL 2014, held in Valparaiso, Chile, in September 2014. The 11 papers presented in this volume were carefully reviewed and selected for inclusion in the book. They are organized in topical sections entitled: optimization of transport problems; container terminal applications; simulation and environmental sustainability applications.

This book constitutes the refereed proceedings of the 7th International Conference on Software Language Engineering, SLE 2014, held in Vasteras, Sweden, in September 2014. The 19 revised full papers presented together with 1 invited paper were carefully reviewed and selected from 61 initial submissions. The papers observe software languages from different and yet complementary perspectives: programming languages, model driven engineering, domain specific languages, semantic web, and from different technological spaces: context-free grammars, object-oriented modeling frameworks, rich data, structured data, object-oriented programming, functional programming, logic programming, term-rewriting, attribute grammars, algebraic specification, etc.

This SpringerBrief focuses on the use of egress models to assess the optimal strategy for total evacuation in high-rise buildings. It investigates occupant relocation and evacuation strategies involving the exit stairs, elevators, sky bridges and combinations thereof. Chapters review existing information on this topic and describe case study simulations of a multi-component exit strategy. This review provides the architectural design, regulatory and research communities with a thorough understanding of the current and emerging evacuation procedures and possible future options. A model case study simulates seven possible strategies for the total evacuation of two identical twin towers linked with two sky-bridges at different heights. The authors present the layout of the building and the available egress components including both vertical and horizontal egress components, namely stairs, occupant evacuation elevators (OEEs), service elevators, transfer floors and sky-bridges. The evacuation strategies employ a continuous spatial representation evacuation model (Pathfinder) and are cross-validated by a fine network model (STEPS). Assessment of Total Evacuation Systems for Tall Buildings is intended for practitioners as a tool for analyzing evacuation methods and efficient exit strategies. Researchers working in architecture and fire safety will also find the book valuable.

Mobile Intention Recognition addresses problems of practical relevance for mobile system engineers: how can we make mobile assistance systems more intelligent? How can we model and recognize patterns of human behavior which span more than a limited spatial context? This text provides an overview on plan and intention recognition, ranging from the late 1970s to very recent approaches. This overview is unique as it discusses approaches with respect to the specificities of mobile intention recognition. This book covers problems from research on mobile assistance systems using methods from artificial intelligence and natural language processing. It thus addresses an extraordinary interdisciplinary audience.

In this work, we provide a treatment of the relationship between two models that have been widely used in the implementation of autonomous agents: the Belief DesireIntention (BDI) model and Markov Decision Processes (MDPs). We start with an informal description of the relationship, identifying the common features of the two approaches and the differences between them. Then we hone our understanding of these differences through an empirical analysis of the performance of both models on the TileWorld testbed. This allows us to show that even though the MDP model displays consistently better behavior than the BDI model for small worlds, this is not the case when the world becomes large and the MDP model cannot be solved exactly. Finally we present a theoretical analysis of the relationship between the two approaches, identifying mappings that allow us to extract a set of intentions from a policy (a solution to an MDP), and to extract a policy from a set of intentions.