Datamodellering og simulering

This book highlights the different aspects of the research project ¿E4C Horizon 2020 European Project¿ aimed at fighting the coronavirus by combining the best supercomputing resources and artificial intelligence with state-of-the-art experimental facilities up through clinical validation.Coronavirus disease has become an important public issue across the globe since December 2019. There is an urgent need to develop potent anti-COVID-19 agents for the prevention of the outbreak and stop viral infections.To this aim, a public¿private consortium composed by European and national infrastructures, center of excellence, universities, and a pharmaceutical company started the E4C Horizon 2020 EuropeanProject: Its core idea was to use the EXaSCale smArt pLatform Against paThogEns (EXSCALATE) supercomputing platform for a process known as ¿drug repurposing¿, namely to identify the most promising safe in man drugs for immediate treatment of the already infected population and then novel pan-coronavirus inhibitors to address future emergencies.This ambitious goal exploited a ¿chemical library¿ of 500 billion molecules, thanks to a processing capacity of more than 3 million molecules per second, made available by the computing power of the EXSCALATE platform.

This book constitutes the thoroughly refereed post-conference proceedings of the 8th International Conference on Modelling and Simulation for Autonomous Systems, MESAS 2021, held as a virtual event due COVID-19, in October 2021.The 30 full papers together with 2 short papers included in the volume were carefully reviewed and selected from 50 submissions. They are organized in the following topical sections: M&S of intelligent systems,  R&D and application; and AxS/AI in context of future warfare and security environment and future challenges of Advance M&S Technology.

This book provides a comprehensive review of the latest modelling developments in flow batteries, as well as some new results and insights. Flow batteries have long been considered the most flexible answer to grid scale energy storage, and modelling is a key component in their development. Recent modelling has moved beyond macroscopic methods, towards mesoscopic and smaller scales to select materials and design components. This is important for both fundamental understanding and the design of new electrode, catalyst and electrolyte materials. There has also been a recent explosion in interest in machine learning for electrochemical energy technologies. The scope of the book includes these latest developments and is focused on advanced techniques, rather than traditional modelling paradigms. The aim of this book is to introduce these concepts and methods to flow battery researcher, but the book would have a much broader appeal since these methods also employed in other battery and fuel cell systems and far beyond. The methods will be described in detail (necessary fundamental material in Appendices). The book appeals to graduate students and researchers in academia/industry working in electrochemical systems, or those working in computational chemistry/machine learning wishing to seek new application areas.

Time series data consist of a collection of observations obtained through repeated measurements over time. When the points are plotted on a graph, one of the axes is always time. Time series analysis is a specific way of analyzing a sequence of data points. Time series data are everywhere since time is a constituent of everything that is observable. As our world becomes increasingly digitized, sensors and systems are constantly emitting a relentless stream of time series data, which has numerous applications across various industries. The editors of this book are happy to provide the specialized reader community with this book as a modest contribution to this rapidly developing domain.

With growing interest in data mining and its merits, including the incorporation of historical or experiential information into statistical analysis, Bayesian inference has become an important tool for analyzing complicated data and solving inverse problems in various fields such as artificial intelligence. This book introduces recent developments in Bayesian inference, and covers a variety of topics including robust Bayesian estimation, solving inverse problems via Bayesian theories, hierarchical Bayesian inference, and its applications for scattering experiments. We hope that this book will stimulate more extensive research on Bayesian fronts to include theories, methods, computational algorithms and applications in various fields such as data science, AI, machine learning, and causality analysis.

This book explores the significance, challenges and benefits of digital twin technologies; it focuses in particular on various architectures, applications and challenges in the implementation of digital twins to Machine Learning and Internet of Things capabilities. Through the analysis of smart city and smart manufacturing case studies, the book explores the benefits of digital technologies in the Industry 4.0 Era.

"The Art of Randomness teaches readers to harness the power of randomness (and Python code) to solve real-world problems in programming, science, and art through hands-on experiments-from simulating evolution to encrypting messages to making machine-learning algorithms. Each chapter describes how randomness plays into the given topic area, then proceeds to demonstrate its problem-solving role with hands-on experiments to work through using Python code"--

This volume comprises papers from the 18th Conference on Systems Engineering Research (CSER). The theme of this volume, "e;Recent Trends and Advances in Model-Based Systems Engineering,"e; reflects the fact that systems engineering is undergoing a transformation motivated by mission and system complexity and enabled by technological advances such as model-based systems engineering, digital engineering, and the convergence of systems engineering with other disciplines. This conference is focused on exploring recent trends and advances in model-based systems engineering (MBSE) and the synergy of MBSE with simulation technology and digital engineering. Contributors have submitted papers on MBSE methods, modeling approaches, integration of digital engineering with MBSE, standards, modeling languages, ontologies and metamodels, and economics analysis of MBSE to respond to the challenges posed by 21st century systems. What distinguishes this volume are the latest advances in MBSE research, the convergence of MBSE with digital engineering, and recent advances in applied research in MBSE, including growing convergence with systems science and decision science. This volume is appropriate as a reference text in graduate engineering courses in Model-Based Systems Engineering.

Comprehensive, state-of-the-art coverage of every important simulation techniqueThis fully-revised book has the most comprehensive and up-to-date coverage of all aspects of a simulation study. Equally well suited for use in university courses, simulation practice, and self-study, the book offers clear and intuitive explanations as well as 300 figures, 218 examples, and 217 problems. You will get detailed discussions on modeling and simulation, simulation software, model verification and validation, input modeling, random-number and variate generation, statistical design and analysis of simulation experiments, experimental design, simulation optimization, agent-based simulation, machine learning, and much more.Authored by an operations research analyst and industrial engineer with more than 40 years of experience, Simulation Modeling and Analysis is widely regarded as the "bible" of simulation and now has more than 178,000 copies in print and 23,700 citations. This sixth edition has been streamlined, with several chapters downsized to eliminate outdated simulation programs or statistical techniques that are rarely used in practice and are unnecessarily complicated. Most analyses of simulation output data can now be done using three simple and familiar statistical formulas or expressions. A new chapter covers AI and machine learning and their application to simulation.Covers what are arguably the three most-innovative and popular simulation-software packages: AnyLogic, FlexSim, and SimioIncludes a set of instructor's resourcesHas been used at universities such as University of California-Berkeley, Stanford, Georgia Tech, Michigan, Cornell, Purdue, Virginia Tech, Penn State, Wisconsin, Columbia, Texas A&M, Washington, and Johns HopkinsWritten by a world-class expert in the field and an experienced educator who has presented more than 550 simulation and statistics short courses in 20 countries

This book presents a novel design framework for the development of Digital Twin (DT) models for process- and motion-control applications. It is based on system-data acquisition using cutting-edge computing technologies, modelling of physical-system behavior through detailed simultaneous simulation of different aspects of the system, and optimal dynamic behavior-matching of the process. The design framework is enhanced with real-time data analytics to improve the performance of the DT¿s behavior-matching with the real system or physical twin.The methods of creating a DT detailed in Digital-Twin-Enabled Smart Control Engineering make possible the study of a system for real-time controller tuning and fault detection. They also facilitate life-cycle analysis for multiple critical and dangerous conditions that cannot be explored in the corresponding real system or physical twin. The authors show how a DT can be exploited to enable self-optimizing capabilitiesin feedback control systems.The DT framework and the control-performance assessment, fault diagnosis and prognosis, remaining-useful-life analysis, and self-optimizing control abilities it allows are validated with both process- and motion-control systems and their DTs. Supporting MATLAB-based material for a case study and an expanded introduction to the basic elements of DTs can be accessed on an associated website. This book helps university researchers from many areas of engineering to develop new tools for control design and reliability and life-cycle assessment and helps practicing engineers working with robotic, manufacturing and processing, and mechatronic systems to maintain and develop the mechanical tools they use.

This book focuses on the problem of responsibility voids: these are cases where responsibility for a morally undesirable outcome cannot be attributed to any of the involved agents. Responsibility voids are thought to occur in collective decision-making and in the context of artificial intelligent systems. In these cases, philosophers worry that there is a shortfall of moral responsibility. In particular, such voids are often assumed to justify a notion of collective responsibility that cannot be reduced to individual responsibility. One of the aims of the book is to study how collective responsibility and joint action relate to individual responsibility and individual actions. The book offers a unifying framework for modelling moral responsibility by drawing from modal logic and game theory.The book investigates the possibility and scope of the problem of responsibility voids. One of its characteristics is its pluralistic perspective on moral responsibility: in contrast to giving a unique and all-encompassing definition of it, the book makes progress by spelling out and modelling several conceptions of moral responsibility. One of the appealing features of the book is that a relatively small range of models is used to investigate a variety of conceptions of moral responsibility. The unifying framework can thus be used to characterize the conditions under which responsibility voids are ruled out.

The book consists of a collection of papers from a corresponding conference regarding additive manufacturing. The yearly conference used to be held in German under the title "Konstruktion für die Additive Fertigung" and is held in English since last year. The topics are Specifications, potentials, and solutions Contributions to specifications on components and processes and methods for assessing the suitability of components and the application of additive manufacturing and finding solutions for concepts and design Design and optimization Contributions to the development and design of components, their design to ensure functional requirements and manufacturability, and methods and tools for optimization components Simulation, validation, and quality assurance Contributions to approaches for the computer-aided and physical validation of components, the testing of components and material, and measures to ensure quality aspects Process chain and business modelsContributions to their integration of additive manufacturing processes into existing processes and measures to increase value creation and the creation of new business models.

The textbook is intended for teaching MATLAB language and its applications. The book is composed of three parts: MATLAB programming, scientific computing with MATLAB, and system simulation with Simulink. Since MATLAB is widely used in all fields of science and engineering, a good introduction to the language can not only help students learn how to use it to solve practical problems, but also provide them with the skills to use MATLAB independently in their later courses and research. The three parts of the book are well-balanced and tailored to the needs of engineering students, and the mathematical problems commonly encountered in engineering can be easily solved using MATLAB. This textbook is suitable for undergraduate and graduate students majoring in science and engineering.

The Bioethics of Space Exploration provides a comprehensive discussion of the possible bioethical issues and challenges that may arise when considering future long-term space missions. Because of numerous threats within the space environment, many consider the concept of radically modifying humans to be a serious and perhaps even necessary option. Konrad Szocik presents what types of ethical and bioethical challenges may await participants on commercial, scientific, and colonizing missions, and provides a new perspective into the potential for radical biomedical technologies.

This book helps readers easily learn basic model checking by presenting examples, exercises and case studies. The toolset mCRL2 provides a language to specify the behaviour of distributed systems, in particular where there is concurrency with inter-process communication. This language allows us to analyse a distributed system with respect to its functional requirements. For example, biological cells, supply chain management systems, patient support platforms, and communication protocols.The underlying technique is based on verifying requirements through model checking. The book explains the syntax of mCRL2 and offers modelling tips and tricks.

This book presents the state of the art in High-Performance Computing on modern supercomputer architectures. It addresses trends in hardware and software development in general. The contributions cover a broad range of topics, from performance evaluations in context with power efficiency to Computational Fluid Dynamics and High-Performance Data Analytics. In addition, they explore new topics like the use of High-Performance Computers in the field of Artificial Intelligence and Machine Learning. All contributions are based on selected papers presented in 2021 at the 31st Workshop on Sustained Simulation Performance, WSSP31, held at HLRS in Stuttgart, Germany, and WSSP32, held at Tohoku University in Sendai, Japan.

With the increasing penetration of renewable energy and distributed energy resources, smart grid is facing great challenges, which could be divided into two categories. On the one hand, the endogenous uncertainties of renewable energy and electricity load lead to great difficulties in smart grid forecast. On the other hand, massive electric devices as well as their complex constraint relationships bring about significant difficulties in smart grid dispatch. Owe to the rapid development of artificial intelligence in recent years, several artificial intelligence enabled computational methods have been successfully applied in the smart grid and achieved good performances. Therefore, this book is concerned with the research on the key issues of artificial intelligence enabled computational methods for smart grid forecast and dispatch, which consist of three main parts. (1) Introduction for smart grid forecast and dispatch, in inclusion of reviewing previous contribution of various research methods as well as their drawbacks to analyze characteristics of smart grid forecast and dispatch.(2) Artificial intelligence enabled computational methods for smart grid forecast problems, which are devoted to present the recent approaches of deep learning and machine learning as well as their successful applications in smart grid forecast.(3) Artificial intelligence enabled computational methods for smart grid dispatch problems, consisting of edge-cutting intelligent decision-making approaches, which help determine the optimal solution of smart grid dispatch. The book is useful for university researchers, engineers, and graduate students in electrical engineering and computer science who wish to learn the core principles, methods, algorithms, and applications of artificial intelligence enabled computational methods.

This book reviews the gray system and combines its latest research results in fishery science. The chapters cover the basic concept and theory of gray system, original data processing and gray sequence generation, gray correlation analysis, gray cluster analysis, gray system modeling, gray prediction, gray decision-making, and gray linear programming. The theory of gray system is a new cross-sectional discipline founded in 1982 by Professor Deng Julong, a well-known scholar in China. In recent decades, it has not only been deepened and expanded in theory but also widely used in the fields of society, economy, ocean, agriculture, fishery, and other fields, and made a series of significant scientific achievements. These have laid the foundation for the important position of the gray system theory.Due to the great uncertainty of the fishery resources and the fishery environment involved in the fishery science system, which is completely different from the natural resources onthe land, the data and information belong to the category of ¿poor information¿, and the variability and uncertainty are greater than other natural resources. As an extremely effective analytical method and tool, gray system theory has been applied increasingly in fishery science. The book is developed based on well-read and practical literature and will help scientists and research units engaged in scientific research and teaching in fishery science and related fields to develop new research methods and tools.

This book constitutes the refereed proceedings of the 18th International Conference on Computer-Aided Systems Theory, EUROCAST 2022, held in Las Palmas de Gran Canaria, Spain, during February 20¿25, 2022. The 77 full papers included in this book were carefully reviewed and selected from 110 submissions. They were organized in topical sections as follows: Systems Theory and Applications, Theory and Applications of Metaheuristic Algorithms, Model-Based System Design, Verification and Simulation, Applications of Signal Processing Technology, Artificial Intelligence and Data Mining for Intelligent Transportation Systems and Smart Mobility, Computer Vision, Machine Learning for Image Analysis and Applications, Computer and Systems Based Methods and Electronic Technologies in Medicine, Systems in Industrial Robotics, Automation and IoT, Systems Thinking. Relevance for Technology, Science and Management Professionals.

This fully updated book explores all-new and revised protocols involving the use of in silico models, particularly with regard to pharmaceuticals. Divided into five sections, the volume covers the modeling of pharmaceuticals in the body, toxicity data for modeling purposes, in silico models for multiple endpoints, a number of platforms for evaluating pharmaceuticals, as well as an exploration of challenges, both scientific and sociological. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of detail and implementation advice necessary for successful results. Authoritative and comprehensive, In Silico Methods for Predicting Drug Toxicity, Second Edition aims to guide the reader through the correct procedures needed to harness in silico models, a field which now touches a wide variety of research specialties.

The Wonderful World of Simulation is a composite of the past, current and future of simulation as seen through the lens of the author. This writing presents a documented track of the past, which identifies many of the early pioneers of simulation, along with fascinating examples of early and contemporary simulators. With fifty years of simulation experience including research, acquisition and support, the author injects his personal experiences in the field he has helped to shape. Okraski's background in government, industry and academia enable him to offer the reader an excellent perspective of simulation as it has evolved and an informed opinion on where it is going. His primary motive for this work is to attract promising young talent to an exciting and rewarding career in simulation.

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

This book covers the notion of the digital twin, which has the potential to alter the way systems are governed and manufactured. It also addresses the metaverse as an emerging technology with its roots in literature, cross-platform avatars, and artificial intelligence-oriented cybersecurity issues. The untapped potential of the metaverse and digital twins as enabling technologies for the next-generation industries is emphasized in various chapters. Digital twin technology enables manufacturers to comprehend their products throughout product design better, integrate simulation, tracking, and optimization in real-time, and appropriately analyze operations. Especially for complicated products or systems, testing on a digital twin is more efficient (more accessible, quicker, less error-prone, and less expensive). The product is examined in its virtual version before it is displayed in the actual world. Additionally, the digital twin minimizes operational expensesand increases the longevity of equipment and assets. By prolonging the life of the thing, they represent and enhance its working efficiency; it may minimize operating costs and prospective capital spending. The digital twin idea is becoming a reality as it has begun to be used in several industries, including energy, manufacturing, construction, transportation, aerospace, smart cities, healthcare, cyber security, finance, and agriculture. Academic and industrial experts highlighted the most compelling use cases of digital twins and metaverses and the challenges inherent in their implementation. Readers who want to make more effective systems will find the book useful. Also, people who want to get an idea and vision of how technology will change our lives will benefit from this book.

"This practical guide provides system administrators, DevSecOps engineers, and cloud architects with a concise yet comprehensive overview of using PL/SQL to develop resilient database solutions. Integration specialist Stephen B. Morris helps you understand the language, build a PL/SQL toolkit, and collect a suite of reusable components and patterns. You'll dive into the benefits of combining the toolkit with a requirements-driven, feature-oriented approach and learn how to produce resilient solutions in conjunction with a scale of resilience"--

The healthcare industry is starting to adopt digital twins to improve personalized medicine, healthcare organization performance, and new medicine and devices. These digital twins can create useful models based on information from wearable devices, omics, and patient records to connect the dots across processes that span patients, doctors, and healthcare organizations as well as drug and device manufacturers. Digital twins are digital representations of human physiology built on computer models. The use of digital twins in healthcare is revolutionizing clinical processes and hospital management by enhancing medical care with digital tracking and advancing modelling of the human body. These tools are of great help to researchers in studying diseases, new drugs, and medical devices. Digital Twins and Healthcare: Trends, Techniques, and Challenges facilitates the advancement and knowledge dissemination in methodologies and applications of digital twins in the healthcare and medicine fields. This book raises interest and awareness of the uses of digital twins in healthcare in the research community. Covering topics such as deep neural network, edge computing, and transfer learning method, this premier reference source is an essential resource for hospital administrators, pharmacists, medical professionals, IT consultants, students and educators of higher education, librarians, and researchers.