Tag: Simulation

Free Download ROBuST: RCOG Assisted Birth Simulation Training: Course Manual
English | 2024 | ISBN: 100901126X | 165 Pages | PDF | 3 MB
Assisted vaginal birth (AVB) remains a key aspect of respectful, effective care for women in labour. In trained hands, it is associated with better maternal and neonatal outcomes than the alternative of a caesarean section in late labour. Written to accompany the RCOG Assisted Birth Simulation Training (ROBuST) course, this book provides guidance on the only RCOG-approved, evidence-based techniques for when and how to perform AVB and complex caesarean sections. There are clear descriptions of techniques, plus photographs, diagrams and videos to improve learning. Internationally recognised contributors discuss all aspects of assisted birth, including vacuum and forceps-assisted birth; caesarean section at full dilatation; safe and effective practice of Kielland’s forceps; and essential non-technical skills. This second edition includes chapters on providing care within the medico-legal context of modern obstetric practice and on exploring the worldwide trends in AVB. This remains a much-valued, and much-consulted, part of any accoucheur’s library.

Free Download Simulation and the Monte Carlo Method, Second Edition By Reuven Y. Rubinstein, Dirk P. Kroese(auth.)
2008 | 366 Pages | ISBN: 0470177942 | PDF | 8 MB
This accessible new edition explores the major topics in Monte Carlo simulationSimulation and the Monte Carlo Method, Second Edition reflects the latest developments in the field and presents a fully updated and comprehensive account of the major topics that have emerged in Monte Carlo simulation since the publication of the classic First Edition over twenty-five years ago. While maintaining its accessible and intuitive approach, this revised edition features a wealth of up-to-date information that facilitates a deeper understanding of problem solving across a wide array of subject areas, such as engineering, statistics, computer science, mathematics, and the physical and life sciences. The book begins with a modernized introduction that addresses the basic concepts of probability, Markov processes, and convex optimization. Subsequent chapters discuss the dramatic changes that have occurred in the field of the Monte Carlo method, with coverage of many modern topics including: Markov Chain Monte Carlo Variance reduction techniques such as the transform likelihood ratio method and the screening method The score function method for sensitivity analysis The stochastic approximation method and the stochastic counter-part method for Monte Carlo optimization The cross-entropy method to rare events estimation and combinatorial optimization Application of Monte Carlo techniques for counting problems, with an emphasis on the parametric minimum cross-entropy method An extensive range of exercises is provided at the end of each chapter, with more difficult sections and exercises marked accordingly for advanced readers. A generous sampling of applied examples is positioned throughout the book, emphasizing various areas of application, and a detailed appendix presents an introduction to exponential families, a discussion of the computational complexity of stochastic programming problems, and sample MATLAB programs. Requiring only a basic, introductory knowledge of probability and statistics, Simulation and the Monte Carlo Method, Second Edition is an excellent text for upper-undergraduate and beginning graduate courses in simulation and Monte Carlo techniques. The book also serves as a valuable reference for professionals who would like to achieve a more formal understanding of the Monte Carlo method.Content: Chapter 1 Preliminaries (pages 1-47): Chapter 2 Random Number, Random Variable, and Stochastic Process Generation (pages 49-80): Chapter 3 Simulation of Discrete?Event Systems (pages 81-96): Chapter 4 Statistical Analysis of Discrete?Event Systems (pages 97-118): Chapter 5 Controlling the Variance (pages 119-166): Chapter 6 Markov Chain Monte Carlo (pages 167-200): Chapter 7 Sensitivity Analysis and Monte Carlo Optimization (pages 201-234): Chapter 8 The Cross?Entropy Method (pages 235-277): Chapter 9 Counting via Monte Carlo (pages 279-314):

Free Download Simulation and the Monte Carlo Method: Solutions Manual to Accompany, Second Edition By Dirk P. Kroese, Thomas Taimre, Zdravko I. Botev, Rueven Y. Rubinstein(auth.)
2008 | 186 Pages | ISBN: 0470258799 | PDF | 8 MB
This accessible new edition explores the major topics in Monte Carlo simulation Simulation and the Monte Carlo Method, Second Edition reflects the latest developments in the field and presents a fully updated and comprehensive account of the major topics that have emerged in Monte Carlo simulation since the publication of the classic First Edition over twenty-five years ago. While maintaining its accessible and intuitive approach, this revised edition features a wealth of up-to-date information that facilitates a deeper understanding of problem solving across a wide array of subject areas, such as engineering, statistics, computer science, mathematics, and the physical and life sciences. The book begins with a modernized introduction that addresses the basic concepts of probability, Markov processes, and convex optimization. Subsequent chapters discuss the dramatic changes that have occurred in the field of the Monte Carlo method, with coverage of many modern topics including: Markov Chain Monte Carlo Variance reduction techniques such as the transform likelihood ratio method and the screening method The score function method for sensitivity analysis The stochastic approximation method and the stochastic counter-part method for Monte Carlo optimization The cross-entropy method to rare events estimation and combinatorial optimization Application of Monte Carlo techniques for counting problems, with an emphasis on the parametric minimum cross-entropy method An extensive range of exercises is provided at the end of each chapter, with more difficult sections and exercises marked accordingly for advanced readers. A generous sampling of applied examples is positioned throughout the book, emphasizing various areas of application, and a detailed appendix presents an introduction to exponential families, a discussion of the computational complexity of stochastic programming problems, and sample MATLAB® programs. Requiring only a basic, introductory knowledge of probability and statistics, Simulation and the Monte Carlo Method, Second Edition is an excellent text for upper-undergraduate and beginning graduate courses in simulation and Monte Carlo techniques. The book also serves as a valuable reference for professionals who would like to achieve a more formal understanding of the Monte Carlo method. Content: Chapter 1 Preliminaries (pages xi-7): Chapter 2 Random Number, Random Variable, and Stochastic Process Generation (pages 9-13): Chapter 3 Simulation of Discrete?Event Systems (pages 15-17): Chapter 4 Statistical Analysis of Discrete?Event Systems (pages 19-23): Chapter 5 Controlling the Variance (pages 25-30): Chapter 6 Markov Chain Monte Carlo (pages 31-36): Chapter 7 Sensitivity Analysis and Monte Carlo Optimization (pages 37-40): Chapter 8 The Cross?Entropy Method (pages 41-46): Chapter 9 Counting via Monte Carlo (pages 47-49): Chapter 10 Appendix (pages 51-52): Chapter 11 Preliminaries (pages 53-68): Chapter 12 Random Number, Random Variable, and Stochastic Process Generation (pages 69-83): Chapter 13 Simulation of Discrete?Event Systems (pages 85-94): Chapter 14 Statistical Analysis of Discrete?Event Systems (pages 95-103): Chapter 15 Controlling the Variance (pages 105-121): Chapter 16 Markov Chain Monte Carlo (pages 123-144): Chapter 17 Sensitivity Analysis and Monte Carlo Optimization (pages 145-150): Chapter 18 The Cross?Entropy Method (pages 151-175): Chapter 19 Counting via Monte Carlo (pages 177-186): Chapter 20 Appendix (pages 187-188):

Free Download Systemdynamik und Simulation By Prof. Dr. rer. nat. Michael Gipser (auth.)
1999 | 307 Pages | ISBN: 3519027437 | PDF | 11 MB
Seit einigen Jahren wird die Computersimulation bei praktischen Problemen der nichtlinearen Systemdynamik zunehmend zum unverzichtbaren Werkzeug der Entwicklungs-Prozeßkette, ähnlich wie in der Statik schon viel früher die Finite Elemente Methode. Dabei geht es darum, dynamische Systeme rechnertauglich zu beschreiben und rechnergestützt zu analysieren, zu visualisieren, zu bewerten und zu optimieren. Getrieben wird die Entwicklung von Verfahren und Software, wie oft im Computer Aided Engineering (CAE), in besonderem Maß durch Anwendungen in der Fahrzeugtechnik. – Das Buch gibt dem Anwender wie dem zukünftigen Entwickler von Simulationsprogrammen und -modellen eine leicht verständliche, anwendungsorientierte Einführung in einige unverzichtbare theoretische Grundlagen. Darauf aufbauend, werden Methoden zur Beschreibung und Simulation dynamischer Systeme der Technik diskutiert. Einen besonderen Schwerpunkt bilden praxisrelevante Fragen der dabei benötigten Numerik.

Free Download Intelligent Systems Modeling and Simulation III: Artificial Intelligent, Machine Learning, Intelligent Functions and Cyber Security by Samsul Ariffin Abdul Karim
English | PDF EPUB (True) | 2024 | 522 Pages | ISBN : 3031673166 | 82.7 MB
This book continues the previous edition: Samsul Ariffin Abdul Karim (2022). Intelligent Systems Modeling and Simulation II: Machine Learning, Neural Networks, Efficient Numerical Algorithm and Statistical Methods, Studies in Systems, Decision and Control (SSDC, volume 444, 22k Access). After two years, Intelligent Systems Modeling and Simulation have evolved tremendously through the latest and advanced emergence technologies and many highly sophisticated algorithms have been developed by blending artificial intelligence (AI) and mathematics, statistics, data modelling and other related research areas. These blends offer many opportunities and further investigations into the overlapand equality between these areas. It is a well-known fact that most industries and companies have utilized this IR4.0 architecture in various levels of manufacturing and decision processes. Besides, nowadays IR5.0 or Society5.0 has also been embedded into various systems in industries as well as in Teaching and Learning (TL). The combination of IR4.0 and Society 5.0 may result in more impactful outcomes, especially in automated decision-making and reliable simulations-based modelling. Furthermore, IR4.0 and Society5.0 through Data-Driven have made a significant contribution to the government and companies to analyse big data via predictive analytics. Cyber security firewalls on all systems must be up to date to prevent any malicious attacks by hackers. Otherwise, our citizens might be scammed and according to NBC News, the total loss for 2022 is around USD 8.8 billion. These are very huge amount. Just recently, COVID-19 has been spreading all over the world again. To assist the Ministry of Health (MOH) and other government agencies, it is very crucial to identify, predict, detect and quarantine the COVID-19 on the susceptible persons soonest possible. Intelligent Image Processing techniques are very demanding here. This is to ensure that we can control and minimise the spread. Inspire by these latest developments, in this book, various experts in the areas of Artificial Intelligence, Machine Learning, Deep Learning, Neural Networks, Modeling and Simulation, Cyber Security and Awareness, Intelligent Statistical Methods, Big Data Analytics, Sentiment Analytics, Intelligent Function Approximation, Image Processing in medical imaging especially on COVID-19, AI in Teaching and Learning, and Computational Intelligence will share their latest studies and experiences. Their finding is in line with United Nations Sustainable Development Goals (SDGs) such as No. 9: Industry, Innovation, and Infrastructure, particularly Target 9.4, 9.5, 9.a, 9.b and 9.c, No. 11: Sustainable Cities and Communities particularly Target 11.b and Indicators 11.b.1 and 11.b.2, and SDG No. 4: Quality Education; particularly Target 4.7 and Indicator 4.7.1. This book is highly suitable for postgraduate students and researchers to get the state-of-the-art current research directions as well as for the scientists that have an interest and working in intelligent numerical modelling and simulations through AI, Machine Learning, Neural Networks, and its related counterparts.

Free Download Vehicle-Manipulator Systems: Modeling for Simulation, Analysis, and Control By Pål Johan From, Jan Tommy Gravdahl, Kristin Ytterstad Pettersen (auth.)
2014 | 388 Pages | ISBN: 1447154622 | PDF | 5 MB
Furthering the aim of reducing human exposure to hazardous environments, this monograph presents a detailed study of the modeling and control of vehicle-manipulator systems. The text shows how complex interactions can be performed at remote locations using systems that combine the manipulability of robotic manipulators with the ability of mobile robots to locomote over large areas. The first part studies the kinematics and dynamics of rigid bodies and standard robotic manipulators and can be used as an introduction to robotics focussing on robust mathematical modeling. The monograph then moves on to study vehicle-manipulator systems in great detail with emphasis on combining two different configuration spaces in a mathematically sound way. Robustness of these systems is extremely important and Modeling and Control of Vehicle-manipulator Systems effectively represents the dynamic equations using a mathematically robust framework. Several tools from Lie theory and differential geometry are used to obtain globally valid representations of the dynamic equations of vehicle-manipulator systems.The specific characteristics of several different types of vehicle-manipulator systems are included and the various application areas of these systems are discussed in detail. For underwater robots buoyancy and gravity, drag forces, added mass properties, and ocean currents are considered. For space robotics the effects of free fall environments and the strong dynamic coupling between the spacecraft and the manipulator are discussed. For wheeled robots wheel kinematics and non-holonomic motion is treated, and finally the inertial forces are included for robots mounted on a forced moving base. Modeling and Control of Vehicle-manipulator Systems will be of interest to researchers and engineers studying and working on many applications of robotics: underwater, space, personal assistance, and mobile manipulation in general, all of which have similarities in the equations required for modeling and control.

Free Download Underwater Acoustic Modeling and Simulation, Fourth Edition By Paul C. Etter
2013 | 554 Pages | ISBN: 1466564938 | PDF | 14 MB
Underwater Acoustic Modeling and Simulation, Fourth Edition continues to provide the most authoritative overview of currently available propagation, noise, reverberation, and sonar-performance models. This fourth edition of a bestseller discusses the fundamental processes involved in simulating the performance of underwater acoustic systems and emphasizes the importance of applying the proper modeling resources to simulate the behavior of sound in virtual ocean environments. New to the Fourth Edition Extensive new material that addresses recent advances in inverse techniques and marine-mammal protection Problem sets in each chapter Updated and expanded inventories of available models Designed for readers with an understanding of underwater acoustics but who are unfamiliar with the various aspects of modeling, the book includes sufficient mathematical derivations to demonstrate model formulations and provides guidelines for selecting and using the models. Examples of each type of model illustrate model formulations, model assumptions, and algorithm efficiency. Simulation case studies are also included to demonstrate practical applications. Providing a thorough source of information on modeling resources, this book examines the translation of our physical understanding of sound in the sea into mathematical models that simulate acoustic propagation, noise, and reverberation in the ocean. The text shows how these models are used to predict and diagnose the performance of complex sonar systems operating in the undersea environment.

Free Download Modellbildung und Simulation: Eine anwendungsorientierte Einführung By Hans-Joachim Bungartz, Stefan Zimmer, Martin Buchholz, Dirk Pflüger (auth.)
2013 | 400 Pages | ISBN: 364237655X | PDF | 8 MB
Dieses Buch gibt eine Einführung in die mathematische und informatische Modellierung sowie in die Simulation als universelle Methodik. Und so geht es um Klassen von Modellen, um deren Herleitung und um die Vielfalt an Beschreibungsarten, die eingesetzt werden können – diskret oder kontinuierlich, deterministisch oder stochastisch. Aber immer geht es auch darum, wie aus unterschiedlichen abstrakten Modellen ganz konkrete Simulationsergebnisse gewonnen werden können. Nach einem kompakten Repetitorium zum benötigten mathematischen Apparat wird das Konzept „Über das Modell zur Simulation" anhand von 14 Szenarien aus den Bereichen „Spielen – entscheiden – planen", „Verkehr auf Highways und Datenhighways", „Dynamische Systeme" sowie „Physik im Rechner" umgesetzt. Ob Spieltheorie oder Finanzmathematik, Verkehr oder Regelung, ob Populationsdynamik oder Chaos, Molekulardynamik, Kontinuumsmechanik oder Computergraphik – der Leser erhält auf anschauliche und doch systematische Weise Einblicke in die Welt der Modelle und Simulationen.

Free Download Mathematical Modeling and Simulation of Systems
English | 2024 | ISBN: 3031673476 | 429 Pages | PDF EPUB (True) | 63 MB
Modern complex multi-domain systems require increased efficiency, reliability and availability combined with reduced cost. This book contains papers on mathematical modeling and simulation of processes in various areas: in ecology and the environment, production and energy, information technology, samples of special purpose equipment, and cyber-physical systems.

Free Download Large-Scale Simulation: Models, Algorithms, and Applications By Dan Chen, Lizhe Wang, Jingying Chen
2012 | 256 Pages | ISBN: 1439868964 | PDF | 6 MB
Organized to facilitate intuitive learning, this step-by-step manual includes basic and advanced models and algorithms, and software architecture for the implementation of large-scale distributed simulation. An indispensible reference, it offers background information on performance evaluation, and it introduces new computing infrastructures such as Grids, SOA, and Clouds, with coverage of parallel and distributed computing technologies. The book also addresses middleware and software architecture, such as Decoupled Federate Architecture, and fault-tolerant mechanisms, grid-enabled simulation, and federation community. The book tackles simulation cloning methods and mechanisms that support quick evaluation of alternative scenarios, as well as important applications used in business processes, social phenomenology, and neuroscience research.