{"title":"Computer modelling and simulation Books","description":"","products":[{"product_id":"simulating-the-cosmos-why-the-universe-looks-the-way-it-does-9781789147148","title":"Simulating the Cosmos: Why the Universe Looks the","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eSimulating the Cosmos is a behind-the-scenes look into one of the hottest and fastest-moving areas of astrophysics today: simulations of cosmology and galaxy formation, which illustrate how everything we see in the universe arose out of the primordial soup of the Big Bang. Leading cosmologist Romeel Davé guides you through the trials and tribulations of what it takes to put the universe into a computer, the amazing new insights revealed by cosmological simulations, and the many mysteries yet to be solved. This rollicking and extraordinary journey is a rare glimpse into science in action, showing how cosmologists are using the laws of physics and supercomputers to uncover the secrets of why the universe looks the way it does.\"","brand":"Reaktion Books","offers":[{"title":"Default Title","offer_id":48741668880727,"sku":"9781789147148","price":15.15,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781789147148.jpg?v=1720058359"},{"product_id":"introduction-to-python-in-earth-science-data-analysis-from-descriptive-statistics-to-machine-learning-9783030780579","title":"Introduction to Python in Earth Science Data","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eThis textbook introduces the use of Python programming for exploring and modelling data in the field of Earth Sciences. It drives the reader from his very first steps with Python, like setting up the environment and starting writing the first lines of codes, to proficient use in visualizing, analyzing, and modelling data in the field of Earth Science. Each chapter contains explicative examples of code, and each script is commented in detail. The book is minded for very beginners in Python programming, and it can be used in teaching courses at master or PhD levels. Also, Early careers and experienced researchers who would like to start learning Python programming for the solution of geological problems will benefit the reading of the book.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003ePart I Python for Geologists, a kick-off; 1. Setting Up Your Python Environment, Easily; 2. Python Essentials for a Geologist; 3. Start Solving Geological Problems Using Python; Part II Describing Geological Data; 4. Graphical Visualization of a Geological Dataset; 5. Descriptive Statistics; Part III Integrals and Differential Equations in Geology; 6. Numerical Integration; 7. Ordinary Differential Equations (ODE); 8. Partial Differential Equations (PDE); Part IV Probability Density Functions and Error Analysis; 9. Probability Density Functions and their Use in Geology; 10. Error Analysis; Part V Robust Statistics and Machine Learning; 11. Introduction to Robust Statistics; 12. Machine Learning; ","brand":"Springer Nature Switzerland AG","offers":[{"title":"Default Title","offer_id":48743049593175,"sku":"9783030780579","price":49.49,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9783030780579.jpg?v=1720063889"},{"product_id":"3d-mesh-processing-and-character-animation-with-examples-using-opengl-openmesh-and-assimp-9783030813567","title":"3D Mesh Processing and Character Animation: With","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003e\u003cb\u003e\u003ci\u003e3D Mesh Processing and Character Animation\u003c\/i\u003e\u003c\/b\u003e focusses specifically on topics that are important in three-dimensional modelling, surface design and real-time character animation. It provides an in-depth coverage of data structures and popular methods used in geometry processing, keyframe and inverse kinematics animations and shader based processing of mesh objects. It also introduces two powerful and versatile libraries, OpenMesh and Assimp, and demonstrates their usefulness through implementations of a wide range of algorithms in mesh processing and character animation respectively. This Textbook is written for students at an advanced undergraduate or postgraduate level who are interested in the study and development of graphics algorithms for three-dimensional mesh modeling and analysis, and animations of rigged character models. \u003c\/p\u003e  The key topics covered in the book are mesh data structures for processing adjacency queries, simplification and subdivision algorithms, mesh parameterization methods, 3D mesh morphing, skeletal animation, motion capture data, scene graphs, quaternions, inverse kinematics algorithms, OpenGL-4 tessellation and geometry shaders, geometry processing and terrain rendering. \u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e1 Introduction.- 2 Mesh Processing Basic.- 3 Mesh Processing Algorithms.- 4 The Geometry Shader.- 5 Mesh Tessellation.- 6 Quaternions.- 7 Character Animation.- 8 Kinematics. ","brand":"Springer Nature Switzerland AG","offers":[{"title":"Default Title","offer_id":48743051657559,"sku":"9783030813567","price":49.49,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9783030813567.jpg?v=1720063898"},{"product_id":"information-modelling-a-pragmatic-approach-9783030988043","title":"Information Modelling: A Pragmatic Approach","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eThis textbook provides solid guidance on how to produce information models in practice. Information modeling has become increasingly relevant as an approach for understanding the active role that data plays within business and management and promoting the planning of business activities. The text promotes a practical approach to information modelling based around the analysis of communicative practice within delimited domains of organization. \u003c\/p\u003e  \u003cp\u003eThe book chapters are designed to be read in sequence. The early chapters build an account of information modelling from the bedrock of a theory of information situations. Later chapters discuss a number of practical issues concerned with the application of this business analysis and design technique. The conclusion demonstrates a larger context for the application and importance of information modelling. Numerous in-text examples of the concepts of information modelling and their application are included throughout the text. A separate chapter is devoted to a range of exercises which the reader can use to test understanding and application of the technique. An appendix with solutions is also provided to support learning.\u003c\/p\u003e  \u003cp\u003eOverall, this textbook provides a step-by-step introduction to information modelling for use in undergraduate and postgraduate modules in information systems, computer science and even digitally focused modules within business and management. No prerequisite knowledge is assumed on the part of the reader. Students and practitioners are tutored in the development of information modelling from first principles. The book covers all the core principles of both entity-relationship diagramming and class diagramming – the two major approaches to information modelling.\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e1. Introduction.- 2. What Is Information?.- 3. Why Model Information?.- 4. Information Modelling From First Principles.- 5. Visualising an Information M.- 6. Composing an Information Model.- 7. Practical Issues in Information Modelling.- 8. Information Modelling and Data Systems.- 9. Information Modelling in Context.- 10. Exercises.","brand":"Springer Nature Switzerland AG","offers":[{"title":"Default Title","offer_id":48743063781719,"sku":"9783030988043","price":37.99,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9783030988043.jpg?v=1720063952"},{"product_id":"body-of-knowledge-for-modeling-and-simulation-a-handbook-by-the-society-for-modeling-and-simulation-international-9783031110849","title":"Body of Knowledge for Modeling and Simulation: A","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eCommissioned 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.\u003ci\u003e\u003c\/i\u003e\u003c\/p\u003e\u003cp\u003eModeling and simulation (M\u0026amp;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\u0026amp;S is the third pillar of scientific understanding, taking its place along with theory building and empirical observation.\u003c\/p\u003e\u003cp\u003eThis 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:\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eMathematical and Systems Theory Foundations\u003c\/li\u003e\n\u003cli\u003eSimulation Formalisms and Paradigms\u003c\/li\u003e\n\u003cli\u003eSynergies with Systems Engineering and Artificial Intelligence\u003c\/li\u003e\n\u003cli\u003eMultidisciplinary Challenges\u003c\/li\u003e\n\u003cli\u003eEthics and Philosophy\u003c\/li\u003e\n\u003cli\u003eHistorical Perspectives\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eExamining theoretical as well as practical challenges, this unique volume addresses the many facets of M\u0026amp;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\u0026amp;S discipline.\u003c\/p\u003e\u003cp\u003e\u003cb\u003eTuncer Ören\u003c\/b\u003e is Professor Emeritus at the University of Ottawa. \u003cb\u003eBernard Zeigler\u003c\/b\u003e is Professor Emeritus at the University of Arizona. \u003cb\u003eAndreas Tolk\u003c\/b\u003e 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\u0026amp;S Body of Knowledge.\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e1.  Preliminary.- 2. M\u0026amp;S BOK Core Areas and the Big Picture.- 3. Simulation as Experimentation.- 4. Simulation as Experience to Enhance Three Types of Skills.- 5. Simulation Games (Simulation as Experience for Entertainment).- 6. Infrastructure.- 7.  Reliability and Quality Assurance of M\u0026amp;S.- 8. Ethics.- 9. Enterprise (Economics of M\u0026amp;S).- 10. Maturity.- 11.  Supporting Domains: Computers and Computation.- 12. Supporting Science Areas.- 13. Supporting Engineering Areas.-14. Supporting Social Science and Management Areas.- 15. Philosophy and Modelling and Simulation.- 16. History.- 17. Core Research Areas.- 18. Trends, Desirable Features, and Challenges. ","brand":"Springer International Publishing AG","offers":[{"title":"Default Title","offer_id":48743069057367,"sku":"9783031110849","price":94.99,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9783031110849.jpg?v=1723812628"},{"product_id":"computer-modelling-for-nutritionists-9783319399928","title":"Computer Modelling for Nutritionists","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eThis book draws on Mark Mc Auley’s wealth of experience to provide an intuitive step-by-step guide to the modelling process. It also provides case studies detailing the creation of biological process models. Mark Mc Auley has over 15 years’ experience of applying computing to challenges in bioscience. Currently he is employed as a Senior Lecturer in Chemical Engineering at the University of Chester. He has published widely on the use of computer modelling in nutrition and uses computer modelling to both enhance and enrich the learning experience of the students that he teaches. He has taught computer modelling to individuals at a wide variety of levels and from different backgrounds, from undergraduate nutrition students to PhD and medical students.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e1. Introduction2. Building a computer model for nutrition research3. Model simulation and software4. Parameter optimisation and sensitivity analysis5. Modelling  cholesterol metabolism and ageing6. Modelling Fatty acid metabolism7. Modelling Folate metabolism and DNA methylation8. Conclusions.","brand":"Springer International Publishing AG","offers":[{"title":"Default Title","offer_id":48743094878551,"sku":"9783319399928","price":80.99,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9783319399928.jpg?v=1720064087"},{"product_id":"an-introductory-course-in-computational-neuroscience-9780262038256","title":"An Introductory Course in Computational","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e","brand":"MIT Press Ltd","offers":[{"title":"Default Title","offer_id":48864300171607,"sku":"9780262038256","price":52.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9780262038256.jpg?v=1722271296"},{"product_id":"simulation-with-arena-ise-9781266275722","title":"Simulation with Arena ISE","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eSimulation with Arena\u003c\/i\u003e provides a comprehensive treatment of simulation using industry-standard Arena software. The textbook begins by having the reader develop simple high-level models, and then progresses to advanced modeling and analysis. Statistical design and analysis of simulation experiments is integrated with the modeling chapters, reflecting the importance of mathematical modeling of these activities. An informal, tutorial writing style is used to aid the beginner in fully understanding the ideas and topics presented. The new edition now reflects Arena version 16.2 (from version 14.5 in the prior edition), which contains many new and useful features.\u003cbr\u003e\u003cbr\u003eThe new edition of Simulation with Arena is also available in McGraw Hill Connect, featuring Adaptive Learning Assignments, the MHeBook, Instructor Resources, and more!\u003cbr\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e1) What Is Simulation?\u003cbr\u003e2) Fundamental Simulation Concepts\u003cbr\u003e3) A Guided Tour Through Arena\u003cbr\u003e4) Modeling Basic Operations and Inputs\u003cbr\u003e5) Modeling Detailed Operations\u003cbr\u003e6) Statistical Analysis of Output from Terminating Simulations\u003cbr\u003e7) Intermediate Modeling and Steady-State Statistical Analysis\u003cbr\u003e8) Entity Transfer\u003cbr\u003e9) A Sampler of Further Modeling Issues and Techniques\u003cbr\u003e10) Arena Integration and Customization\u003cbr\u003e11) Continuous and Combined Discrete\/Continuous Models\u003cbr\u003e12) Further Statistical Issues\u003cbr\u003e13) Conducting Simulation Studies\u003cbr\u003e","brand":"McGraw-Hill Education","offers":[{"title":"Default Title","offer_id":48885329297751,"sku":"9781266275722","price":53.09,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781266275722.jpg?v=1722535936"},{"product_id":"computer-vision-simulation-methods-applications-technology-9781634857901","title":"Computer Vision \u0026 Simulation: Methods,","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e","brand":"Nova Science Publishers Inc","offers":[{"title":"Default Title","offer_id":48887248126295,"sku":"9781634857901","price":148.79,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781634857901.jpg?v=1722543681"},{"product_id":"a-practical-guide-for-nurse-practitioner-faculty-using-simulation-in-competency-based-education-9781975233891","title":"A Practical Guide for Nurse Practitioner Faculty","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eAuthored by expert simulation researchers, educators, nurse practitioner faculty, and clinicians, \u003cb\u003e\u003ci\u003eA Practical Guide for Nurse Practitioner Faculty Using Simulation in Competency-Based Education\u003c\/i\u003e\u003c\/b\u003e looks at topics related to simulation design, development, and implementation for nurse practitioner and other graduate-level nursing programs.  \u003cbr\u003e  \u003cbr\u003e The new educational requirements based on the AACN \u003ci\u003eEssentials\u003c\/i\u003e and move to competency-based outcomes require nursing graduates to provide documented skill competencies to care for all types of patients in all types of diverse healthcare settings. Whether a graduate is working in acute care, primary care, or within the community, clinical simulations serve as a vital approach to creating student-centered, experiential learning that engages and prepares the graduate for real-world practice. \u003cbr\u003e  \u003cbr\u003e Once the exception, clinical simulations are becoming more commonplace in nurse practitioner programs. This book supports nurse practitioner faculty as they learn new pedagogy and teaching strategies using clinical simulations.  It focuses on developing and preparing nurse educators and superusers of simulations as they create, implement, and evaluate this pedagogy in nurse practitioner education.  \u003cbr\u003e  \u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e CHAPTER 1 State of the Science of Clinical Simulations in NP Education\u003cbr\u003e CHAPTER 2 Theoretical Frameworks for Simulation Design, Development, and Implementation\u003cbr\u003e CHAPTER 3 Competency-Based Nursing Education\u003cbr\u003e CHAPTER 4 Student-Centered Learning in NP Education\u003cbr\u003e CHAPTER 5 Integration of Simulation in the NP Curriculum\u003cbr\u003e CHAPTER 6 Healthcare Simulation Standards of Best Practice™ and Nurse Practitioner Education\u003cbr\u003e CHAPTER 7 Attainment of Competency Through Simulation: The ACTS Model\u003cbr\u003e CHAPTER 8 Simulation Operations\u003cbr\u003e CHAPTER 9 Methods and Models for Debriefing in Graduate Clinical Education\u003cbr\u003e CHAPTER 10 Working with Standardized and Simulated Patients\u003cbr\u003e CHAPTER 11 Assessment and Evaluations in Simulation\u003cbr\u003e CHAPTER 12 Simulation to Prepare Nurse Practitioner Students for Role Transition\u003cbr\u003e CHAPTER 13 The Future of Graduate Nurse Practitioner Education: A Case for Simulation\u003cbr\u003e  ","brand":"Wolters Kluwer Health","offers":[{"title":"Default Title","offer_id":48888914444631,"sku":"9781975233891","price":37.99,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781975233891.jpg?v=1722551764"},{"product_id":"higgs-boson-a-mathematical-survey-with-finite-element-method-9798886977851","title":"Higgs Boson A Mathematical Survey with Finite","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e","brand":"Nova Science Publishers, Inc.","offers":[{"title":"Default Title","offer_id":48890371932503,"sku":"9798886977851","price":59.49,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9798886977851.jpg?v=1722558596"},{"product_id":"quantum-information-science-9780198787488","title":"Quantum Information Science","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eThis book provides an introduction to quantum information science, the science at the basis of the new quantum revolution of this century. It teaches the reader to build and program a quantum computer and leverage its potential. Aimed at quantum physicists and computer scientists, the book covers several topics, including quantum algorithms, quantum chemistry, and quantum engineering of superconducting qubits. Written by two professionals in the experimental and theoretical fields of quantum information science and containing over 200 figures and 100 exercises with solutions and summaries at the end of each chapter, this book is set to become a new standard in the field.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003eManenti and Motta provide a tour-de-force of quantum information science. This is the first textbook that I have seen that comprehensively begins with mathematics, moves on to quantum physics, and via quantum algorithms ends up in the discussion of hardware implementations. With detailed explanations, modern references, and further reading tips this book is poised to become one of the classics in every quantum information scientist's bookshelf * Alan Aspuru-Guzik, Professor of Chemistry and Computer Science, University of Toronto and Scientific Advisor, Zapata Computing *\u003cbr\u003eManenti and Motta have navigated the vast field of quantum information science to create a well-rounded and accessible textbook. Though the subject is too broad to be covered in its entirety, the authors have carefully selected key topics and provide clear explanations including advanced topics on quantum simulation and superconducting devices. This is an excellent resource for anyone starting a career in this field. * Jay Gambetta, IBM Fellow and Vice President of IBM Quantum *\u003cbr\u003eThe text 'Quantum Information Science' is an admirable attempt by these two authors, a theorist and an experimentalist in the quantum information field, to guide readers from the very basics to the frontiers of research. The unusual breadth of topics ensures that every reader will learn something new and the inclusion of a large number of problems with detailed solutions means that this work is suitable for instructional use in graduate classes. A much needed and unique tour-de-force. * Garnet Kin-Lic Chan, Bren Professor of Chemistry, Caltech *\u003cbr\u003eManenti and Motta have made a great effort to introduce the basic concepts in the rapidly growing field of quantum information science and technology. With numerous exercises and references, this book will not only be a valuable resource for current students, but also serve as a foundation for the next generation of quantum engineers. * Yasunobu Nakamura, Professor of Quantum Information Physics, University of Tokyo *\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003ePART I - FOUNDATIONS 1: Mathematical tools 2: Computational models 3: Linear algebra 4: Quantum mechanics 5: Quantum circuits PART II - MODERN QUANTUM MECHANICS 6: Density operators 7: Quantum maps 8: Decoherence PART III - APPLICATIONS 9: Entanglement 10: Early quantum algorithms 11: Quantum simulation of Hamiltonian dynamics 12: Quantum simulation of Hamiltonian eigenstates PART IV - QUANTUM ENGINEERING OF SUPERCONDUCTING DEVICES 13: Microwave resonators for superconducting devices 14: Superconducting qubits Appendix A: The rotating wave approximation Appendix B: Advanced quantum mechanics Appendix C: The quantum Fourier transform Appendix D: The molecular Hamiltonian in second quantization","brand":"Oxford University Press","offers":[{"title":"Default Title","offer_id":49083398619479,"sku":"9780198787488","price":52.25,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9780198787488.jpg?v=1725548810"},{"product_id":"data-modelling-for-sap-hana-2-0-9781493217519","title":"Data Modelling for SAP HANA 2.0","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eFind meaning in your business data. Build, manage, and secure calculation views and table functions with the SAP Web IDE for SAP HANA. See how SAP Web IDE, SAP HANA Live, and SAP S\/4HANA embedded analytics all interact to create effective data models. 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It has been expanded to include coverage of mobile robots, visual control and motion planning. A variety of problems is raised throughout, and the proper tools to find engineering-oriented solutions are introduced and explained.\u003cbr\u003e\u003c\/p\u003e\u003cp\u003eThe text includes coverage of fundamental topics like kinematics, and trajectory planning and related technological aspects including actuators and sensors.\u003c\/p\u003e\u003cp\u003eTo impart practical skill, examples and case studies are carefully worked out and interwoven through the text, with frequent resort to simulation. In addition, end-of-chapter exercises are proposed, and the book is accompanied by an electronic solutions manual containing the MATLAB\u003csup\u003e®\u003c\/sup\u003e code for computer problems; this is available free of charge to those adopting this volume as a textbook for courses.\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003e\u003cp\u003e\u003cem\u003eRobotics: Modelling, Planning and Control\u003c\/em\u003e is a book that comprehensively covers all aspects of robotic fundamentals. It is particularly an excellent text for graduate educators, as it covers the fundamentals of the field with a rigorous formalism that is well blended with the technological aspects of robotics. The text covers in detail the theory of manipulators and wheeled robots starting with kinematics, dynamics and motion control, as well interaction with the environment through perception - force and vision sensors. The book is written by technical authorities in the field, and will be in invaluable addition to graduate education as well as a useful guide for industrial practitioners. \u003c\/p\u003e\u003cp\u003eAlexander Zelinsky, CSIRO, Australia \u003c\/p\u003e\u003cp\u003e  \u003c\/p\u003e\u003cp\u003eRobotics is a diverse field bringing together disparate areas from computer science, electrical engineering and mechanical engineering. This book is an integrative but rigorous treatment of all the relevant concepts, with an eye toward modern, practical applications making it an excellent choice for a first year graduate course in robotics. \u003c\/p\u003e\u003cp\u003eVijay Kumar, University of Pennsylvania \u003c\/p\u003e\u003cp\u003e  \u003c\/p\u003e\u003cp\u003eThis book provides rock-solid foundations for the study of classical mechanics and control of robots, with the authoritative character of a reference where you can surely find the correct expression and the rigorous derivation of the results you need. On top of this, new chapters on motion planning, visual servoing, and mobile robot control provide support to teaching wider and more interdisciplinary aspects of robotics, and open up vistas that will certainly inspire a new generation of scholars to embrace this incredibly rich and fertile research field. \u003c\/p\u003e\u003cp\u003eAntonio Bicchi, University of Pisa, Italy \u003c\/p\u003e\u003cp\u003e  \u003c\/p\u003e\u003cp\u003eThis book offers a well-balanced and intellectually satisfying treatment of robot mechanics, planning, and control – from the choice and sequence of topics, to the level of detail in the analysis, and the clear connections made between the latest technologies and the theoretical foundations of robotics, this book is an essential element in the library of every aspiring young robotics researcher. \u003c\/p\u003e\u003cp\u003eFrank Chongwoo Park, Seoul National University \u003c\/p\u003e\u003cp\u003e  \u003c\/p\u003e\u003cp\u003e\u003cem\u003eRobotics: Modeling, Planning and Control\u003c\/em\u003e is a historiography from the materialistic view of robotics. Authors clearly explain physical and mathematical foundation to understand the most up-to-date robotics, so faithfully to bibliography and terminology in robotics. Unquestionably, the best textbook for senior students and graduate students and the closest reference book for engineers and scientists! \u003c\/p\u003e\u003cp\u003eYoshihiko Nakamura, University of Tokyo \u003c\/p\u003e\u003cp\u003e  \u003c\/p\u003e\u003cp\u003eExceptional! A text with such a span of robotics fundamentals and advanced research in both manipulation and mobility, and a treatment that creatively balances mathematical depth and physical intuition – a fresh and certainly unique reference for researchers and engineers in the field of robotics. \u003c\/p\u003e\u003cp\u003eOussama Khatib, Stanford University \u003c\/p\u003e\u003cp\u003e  \u003c\/p\u003e\u003cp\u003eCertainly because of its youth, robotics is not always considered as a discipline as such. It is often introduced as a technological \"area\" integrating various aspects of mechanics, automatic control and computer science. Such a dispersed view is prejudicial for students. The book by Siciliano \u003cem\u003eet al.\u003c\/em\u003e achieves the introduction of the basic concepts in a coherent, self-contained and didactic way. In that sense, when reading \u003cem\u003eRobotics: Modelling, Planning and Control\u003c\/em\u003e the reader – from the undergraduate student to the researcher – understands that a new discipline is born, with its own foundations. \u003c\/p\u003e\u003cp\u003eJean-Paul Laumond, LAAS-CNRS\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003eKinematics.- Differential Kinematics and Statics.- Trajectory Planning.- Actuators and Sensors.- Control Architecture.- Dynamics.- Motion Control.- Force Control.- Visual Servoing.- Mobile Robots.- Motion Planning.","brand":"Springer London Ltd","offers":[{"title":"Default Title","offer_id":49084533834071,"sku":"9781846286414","price":85.49,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781846286414.jpg?v=1725552479"},{"product_id":"augmented-and-virtual-reality-in-industry-5-0-9783110789997","title":"Augmented and Virtual Reality in Industry 5.0","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eThis edited volume collects a series of studies concerning the most recent developments in the industrial applications of augmented and virtual reality. Each chapter outlines the most recent advancements in the theory and applications of augmented and virtual reality to different sectors of technology, industry and society. The book thus contributes to a study of the interaction between humans and machines in Industry 5.0. \u003c\/p\u003e","brand":"De Gruyter","offers":[{"title":"Default Title","offer_id":49372696248663,"sku":"9783110789997","price":97.5,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9783110789997.jpg?v=1730163847"},{"product_id":"augmented-and-virtual-reality-in-social-learning-technological-impacts-and-challenges-9783110994926","title":"Augmented and Virtual Reality in Social Learning:","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eThis book focuses on the design, development, and analysis of augmented and virtual reality (AR\/VR)-based systems, along with the technological impacts and challenges in social learning. Social Learning provides a comprehensive approach to researching methods in the emerging fields of AR\/VR. The contributors of this book outline the state-of-the-art implementation of AR\/VR for the Internet of Things, Blockchains, Big Data, and 5G within AR\/VR systems.","brand":"De Gruyter","offers":[{"title":"Default Title","offer_id":49372696478039,"sku":"9783110994926","price":123.5,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9783110994926.jpg?v=1730163847"},{"product_id":"what-is-cgi-9780007186679","title":"What Is CGI","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eArtist Jon Stuart shows how he produces computer-generated images. The process starts with a simple block of cubes, which are added to, given texture, before being bent, stretched, twisted into the correct shape and size. He then adds background, lighting and colour to bring the whole scene to life.This is a Band 06\/Orange book in the Collins Big Cat reading programme which offers varied text and characters, with action sustained over several pages. This is an information book with a flow chart on pages 22 and 23 that summarises the process of producing CGI. Contents are listed on page 1 while a glossary and index are detailed on pages 20 and 21. This book supports learning around art and design, and investigates different kinds of art, design and craft. It also supports ICT education, and is an introduction to modelling and creating pictures. This book has been levelled for Reading Recovery. For more guided reading books in this Collins Big Cat band, try Pompeii (9780007461875) writte","brand":"HarperCollins Publishers","offers":[{"title":"Default Title","offer_id":49399366418775,"sku":"9780007186679","price":9.05,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9780007186679.jpg?v=1730467316"},{"product_id":"science-in-the-age-of-computer-simulation-9780226902043","title":"Science in the Age of Computer Simulation","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eDigital computer simulation helps study phenomena of great complexity, but how much do we know about the limits and possibilities of this new scientific practice? How do simulations compare to traditional experiments? And are they reliable? The author seeks to answer these questions.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003e\"This is the first book-length study of the role of simulation models from the standpoint of philosophy of science. It will be required reading for all who follow.\" - Ronald Giere, University of Minnesota\"","brand":"The University of Chicago Press","offers":[{"title":"Default Title","offer_id":49400150360407,"sku":"9780226902043","price":28.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9780226902043.jpg?v=1730469886"},{"product_id":"computer-modeling-in-bioengineering-9780470060353","title":"Computer Modeling in Bioengineering","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eBioengineering is a broad-based engineering discipline that applies engineering principles and design to challenges in human health and medicine, dealing with bio-molecular and molecular processes, product design, sustainability and analysis of biological systems. Applications that benefit from bioengineering include medical devices, diagnostic equipment and biocompatible materials, amongst others.  \u003cp\u003e\u003ci\u003eComputer Modeling in Bioengineering\u003c\/i\u003e offers a comprehensive reference for a large number of bioengineering topics, presenting important computer modeling problems and solutions for research and medical practice. Starting with basic theory and fundamentals, the book progresses to more advanced methods and applications, allowing the reader to become familiar with different topics to the desired extent. It includes unique and original topics alongside classical computational modeling methods, and each application is structured to explain the physiological background, phenomena that ar\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003eContributors.  \u003c\/p\u003e\u003cp\u003ePreface.\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart I: Theoretical Background of Computational Methods.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1. Notation - Matrices and Tensors.\u003c\/p\u003e \u003cp\u003e2. Fundamentals of Continuum Mechanics.\u003c\/p\u003e \u003cp\u003e3. Heat Transfer, Diffusion, Fluid Mechanics, and Fluid Flow through Porous Deformable Media.\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart II: Fundamentals of Computational Methods.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4. Isoparametric Formulation of Finite Elements.\u003c\/p\u003e \u003cp\u003e5. Dynamic Finite Element Analysis.\u003c\/p\u003e \u003cp\u003e6. Introduction to Nonlinear Finite Element Analysis.\u003c\/p\u003e \u003cp\u003e7. Finite Element Modeling of Field Problems.\u003c\/p\u003e \u003cp\u003e8. Discrete Particle Methods for Modeling of Solids and Fluids.\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart III: Computational Methods in Bioengineering.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9. Introduction to Bioengineering.\u003c\/p\u003e \u003cp\u003e10. Bone Modeling.\u003c\/p\u003e \u003cp\u003e11. Biological Soft Tissue.\u003c\/p\u003e \u003cp\u003e12. Skeletal Muscles.\u003c\/p\u003e \u003cp\u003e13. Blood Flow and Blood Vessels.\u003c\/p\u003e \u003cp\u003e14. Modeling Mass Transport and Thrombosis in Arteries.\u003c\/p\u003e \u003cp\u003e15. Cartilage Mechanics.\u003c\/p\u003e \u003cp\u003e16. Cell Mechanics.\u003c\/p\u003e \u003cp\u003e17. Extracellular Mechanotransduction: Modeling Ligand Concentration Dynamics in the Lateral Intercellular Space of Compressed Airway Epithelial Cells.\u003c\/p\u003e \u003cp\u003e18. Spider Silk: Modeling Solvent Removal during Synthetic and Nephila clavipes Fiber Spinning.\u003c\/p\u003e \u003cp\u003e19. Modeling in Cancer Nanotechnology.\u003c\/p\u003e \u003cp\u003eIndex.\u003c\/p\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49402276544855,"sku":"9780470060353","price":117.85,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9780470060353.jpg?v=1730479921"},{"product_id":"essential-simulation-in-clinical-education-9780470671160","title":"Essential Simulation in Clinical Education","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eThis new addition to the popular Essentials series provides a broad, general introduction to the topic of simulation within clinical education.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eContributors vii\u003c\/p\u003e \u003cp\u003eForeword x\u003c\/p\u003e \u003cp\u003eGlossary and abbreviations xii\u003c\/p\u003e \u003cp\u003eFeatures contained within your textbook xvi\u003c\/p\u003e \u003cp\u003e1 Essential simulation in clinical education 1\u003cbr\u003e \u003ci\u003eJudy McKimm and Kirsty Forrest\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e2 Medical simulation: the journey so far 11\u003cbr\u003e \u003ci\u003eAidan Byrne\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e3 The evidence: what works, why and how? 26\u003cbr\u003e \u003ci\u003eDoris Østergaard and Jacob Rosenberg\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e4 Pedagogy in simulation-based training in healthcare 43\u003cbr\u003e \u003ci\u003ePeter Dieckmann and Charlotte Ringsted\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e5 Assessment 59\u003cbr\u003e \u003ci\u003eThomas Gale and Martin Roberts\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e6 The roles of faculty and simulated patients in simulation 87\u003cbr\u003e \u003ci\u003eBryn Baxendale, Frank Coffey and Andrew Buttery\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e7 Surgical technical skills 111\u003cbr\u003e \u003ci\u003eRajesh Aggarwal and Amit Mishra\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e8 The non-technical skills 131\u003cbr\u003e \u003ci\u003eNikki Maran, Simon Edgar and Alistair May\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e9 Teamwork 146\u003cbr\u003e \u003ci\u003eJennifer M. Weller\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e10 Designing effective simulation activities 168\u003cbr\u003e \u003ci\u003eJoanne Barrott, Ann B. Sunderland, Jane P. Nicklin and Michelle McKenzie Smith\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e11 Distributed simulation 196\u003cbr\u003e \u003ci\u003eJessica Janice Tang, Jimmy Kyaw Tun, Roger L Kneebone and Fernando Bello\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e12 Providing effective simulation activities 213\u003cbr\u003e \u003ci\u003eWalter J. Eppich, Lanty O’Connor and Mark Adler\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 Simulation in practice 235\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eJean Ker\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eSimulation for learning cardiology 236\u003cbr\u003e \u003ci\u003eRoss J. Scalese\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eAssessing leadership skills in medical undergraduates 238\u003cbr\u003e \u003ci\u003eHelen O’Sullivan, Arpan Guha and Michael Moneypenny\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eSimulation for interprofessional learning 240\u003cbr\u003e \u003ci\u003eStuart Marshall\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eUse of in situ simulations to identify barriers to patient care for multidisciplinary teams in developing countries 242\u003cbr\u003e \u003ci\u003eNicole Shilkofski\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eClinical skills assessment for paediatric postgraduate physicians 244\u003cbr\u003e \u003ci\u003eJoseph O. Lopreiato\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eThe challenge of doctors in difficulty: using simulated healthcare contexts to develop a national assessment programme 246\u003cbr\u003e \u003ci\u003eKevin Stirling, Jean Ker and Fiona Anderson\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eSimulation for remote and rural practice 250\u003cbr\u003e \u003ci\u003eJerry Morse, Jean Ker and Sarah Race\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eThe use of incognito standardized patients in general practice 252\u003cbr\u003e \u003ci\u003eJan-Joost Rethans\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eIntegration of simulation-based training for the trauma team in a university hospital 253\u003cbr\u003e \u003ci\u003eAnne-Mette Helsø and Doris Østergaard\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eConclusion 254\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 The future for simulation 258\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eHorizon scanning: the impact of technological change 259\u003cbr\u003e \u003ci\u003eIliana Harrysson, Rajesh Aggarwal and Ara Darzi\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eGuiding the role of simulation through paradigm shifts in medical education 267\u003cbr\u003e \u003ci\u003eViren N. Naik and Stanley J. Hamstra\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eThe future of training in simulation 273\u003cbr\u003e \u003ci\u003eRonnie Glavin\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eIndex 283\u003c\/p\u003e","brand":"John Wiley and Sons Ltd","offers":[{"title":"Default Title","offer_id":49402399588695,"sku":"9780470671160","price":49.35,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9780470671160.jpg?v=1730480282"},{"product_id":"reviews-in-computational-chemistry-volume-2-9780471188100","title":"Reviews in Computational Chemistry Volume 2","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eThis second volume of the series ''Reviews in Computational Chemistry'' explores new applications, new methodologies, and new perspectives. The topics covered include conformational analysis, protein folding, force field parameterizations, hydrogen bonding, charge distributions, electrostatic potentials, electronic spectroscopy, molecular property correlations, and the computational chemistry literature. Methodologies described include conformational search strategies, distance geometry, molecular mechanics, molecular dynamics, ab initio and semiempirical molecular orbital calculations, and quantitative structure-activity relationships (QSAR) using topological and electronic descriptors. \u003cbr\u003e \u003cbr\u003e A compendium of molecular modeling software will help users select the computational tools they need. Each chapter in ''Reviews in Computational Chemistry'' serves as a brief tutorial for organic, physical, pharmaceutical, and biological chemists new to the field. Practitioners will be intere\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003eA Survey of Methods for Searching thr Conformational Space of Small and Medium-Sized Molecules (A. Leach).\u003cbr\u003e \u003cbr\u003e Simplified Models for Understanding and Predicting Protein Structure (J. Troyer and F. Cohen).\u003cbr\u003e \u003cbr\u003e Moleculaar Mechanics: The Art and Science of Parameterization (J. Bowen and N. Allinger).\u003cbr\u003e \u003cbr\u003e New Approaches to Empirical Force Fields (U. Dinur and A. Hagler).\u003cbr\u003e \u003cbr\u003e Calculating the Properties of Hydrogen Bonds by ab Initio Methods (S. Scheiner).\u003cbr\u003e \u003cbr\u003e Net Atomic Charge and Multiple Models for the ab Initio Molecular Electric Potential (D. Williams).\u003cbr\u003e \u003cbr\u003e Molecular Electrostatic Potentials and Chemical Reactivity (P. Politzer and J. Murray).\u003cbr\u003e \u003cbr\u003e Semiempirical Molecular Orbital Methods (M. Zerner).\u003cbr\u003e \u003cbr\u003e The Molecular Connectivity Chi Indexes and Kappa Shape Indexes in Structure-Property Modeling (L. Hall and L. Kier).\u003cbr\u003e \u003cbr\u003e The Electron-Topological Approach to the QSAR Problem (I. Bersuker and A. Dimoglo).\u003cbr\u003e \u003cbr\u003e The Computational Chemistry Literature (D. Boyd).\u003cbr\u003e \u003cbr\u003e Appendix: Compendium of Software for Molecular Modeling (D. Boyd).\u003cbr\u003e \u003cbr\u003e Author Index.\u003cbr\u003e \u003cbr\u003e Subject Index.","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49402520699223,"sku":"9780471188100","price":252.86,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9780471188100.jpg?v=1730480647"},{"product_id":"reviews-in-computational-chemistry-20-9780471445258","title":"Reviews in Computational Chemistry 20","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eTHIS VOLUME, LIKE THOSE PRIOR TO IT, FEATURES CHAPTERS BY EXPERTS IN VARIOUS FIELDS OF COMPUTATIONAL CHEMISTRY. TOPICS COVERED IN VOLUME 20 INCLUDE VALENCE THEORY, ITS HISTORY, FUNDAMENTALS, AND APPLICATIONS; MODELING OF SPIN-FORBIDDEN REACTIONS; CALCULATION OF THE ELECTRONIC SPECTRA OF LARGE MOLECULES; SIMULATING CHEMICAL WAVES AND PATTERNS; FUZZY SOFT-COMPUTING METHODS AND THEIR APPLICATIONS IN CHEMISTRY; AND DEVELOPMENT OF COMPUTATIONAL MODELS FOR ENZYMES, TRANSPORTERS, CHANNELS, AND RECEPTORS RELEVANT TO ADME\/TOX.\u003cbr\u003e FROM REVIEWS OF THE SERIES\u003cbr\u003e Reviews in Computational Chemistry remains the most valuable reference to methods and techniques in computational chemistry.\u003cbr\u003e -JOURNAL OF MOLECULAR GRAPHICS AND MODELING\u003cbr\u003e One cannot generally do better than to try to find an appropriate article in the highly successful Reviews in Computational Chemistry. The basic philosophy of the editors seems to be to help the authors produce chapters that are complete, accurate, clear, \u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003e“The editors have done an excellent job and the book is a must on every book shelf of computational chemistry literature.” (\u003ci\u003eChemPhysChem\u003c\/i\u003e, 2005; Vol. 6; 7)  \u003cp\u003e\"…this volume continues the traditions and standards of this series as a prime resource for anyone with an interest in theoretical and computational chemistry…a welcome addition to any library collection.\" (\u003ci\u003eJournal of the American Chemical Society\u003c\/i\u003e, March 9, 2005)\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e1. Valence Bond Theory, Its History, Fundamentals, and Applications: A Primer (Sason Shaik and Philippe C. Hiberty).  \u003cp\u003eIntroduction.\u003c\/p\u003e \u003cp\u003eA Story of Valence Bond Theory, Its Rivalry with Molecular Orbital Theory, Its Demise, and Eventual Resurgence.\u003c\/p\u003e \u003cp\u003eRoots of VB Theory.\u003c\/p\u003e \u003cp\u003eOrigins of MO Theory and the Roots of VB–MO Rivalry.\u003c\/p\u003e \u003cp\u003eThe ‘‘Dance’’ of Two Theories: One Is Up, the Other Is Down.\u003c\/p\u003e \u003cp\u003eAre the Failures of VB Theory Real Ones?\u003c\/p\u003e \u003cp\u003eModern VB Theory: VB Theory Is Coming of Age.\u003c\/p\u003e \u003cp\u003eBasic VB Theory.\u003c\/p\u003e \u003cp\u003eWriting and Representing VB Wave Functions.\u003c\/p\u003e \u003cp\u003eThe Relationship between MO and VB Wave Functions.\u003c\/p\u003e \u003cp\u003eFormalism Using the Exact Hamiltonian.\u003c\/p\u003e \u003cp\u003eQualitative VB Theory.\u003c\/p\u003e \u003cp\u003eSome Simple Formulas for Elementary Interactions.\u003c\/p\u003e \u003cp\u003eInsights of Qualitative VB Theory.\u003c\/p\u003e \u003cp\u003eAre the ‘‘Failures’’ of VB Theory Real?\u003c\/p\u003e \u003cp\u003eCan VB Theory Bring New Insight into Chemical Bonding?\u003c\/p\u003e \u003cp\u003eVB Diagrams for Chemical Reactivity.\u003c\/p\u003e \u003cp\u003eVBSCD: A General Model for Electronic Delocalization and Its Comparison with the Pseudo-Jahn–Teller Model.\u003c\/p\u003e \u003cp\u003eWhat Is the Driving Force, s or p, Responsible for the D6h Geometry of Benzene?\u003c\/p\u003e \u003cp\u003eVBSCD: The Twin-State Concept and Its Link to Photochemical Reactivity.\u003c\/p\u003e \u003cp\u003eThe Spin Hamiltonian VB Theory.\u003c\/p\u003e \u003cp\u003eTheory.\u003c\/p\u003e \u003cp\u003eApplications.\u003c\/p\u003e \u003cp\u003eAb Initio VB Methods.\u003c\/p\u003e \u003cp\u003eOrbital-Optimized Single-Configuration Methods.\u003c\/p\u003e \u003cp\u003eOrbital-Optimized Multiconfiguration VB Methods.\u003c\/p\u003e \u003cp\u003eProspective.\u003c\/p\u003e \u003cp\u003eAppendix.\u003c\/p\u003e \u003cp\u003eA.1 Expansion of MO Determinants in Terms of AO Determinants.\u003c\/p\u003e \u003cp\u003eA.2 Guidelines for VB Mixing.\u003c\/p\u003e \u003cp\u003eA.3 Computing Mono-Determinantal VB Wave Functions with Standard Ab Initio Programs.\u003c\/p\u003e \u003cp\u003eAcknowledgments.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e2. Modeling of Spin-Forbidden Reactions (Nikita Matsunaga and Shiro Koseki).\u003c\/p\u003e \u003cp\u003eOverview of Reactions Requiring Two States.\u003c\/p\u003e \u003cp\u003eSpin-Forbidden Reaction, Intersystem Crossing.\u003c\/p\u003e \u003cp\u003eSpin–Orbit Coupling as a Mechanism for Spin-Forbidden Reaction.\u003c\/p\u003e \u003cp\u003eGeneral Considerations.\u003c\/p\u003e \u003cp\u003eAtomic Spin–Orbit Coupling.\u003c\/p\u003e \u003cp\u003eMolecular Spin–Orbit Coupling.\u003c\/p\u003e \u003cp\u003eCrossing Probability.\u003c\/p\u003e \u003cp\u003eFermi Golden Rule.\u003c\/p\u003e \u003cp\u003eLandau–Zener Semiclassical Approximation.\u003c\/p\u003e \u003cp\u003eMethodologies for Obtaining Spin–Orbit Matrix Elements.\u003c\/p\u003e \u003cp\u003eElectron Spin in Nonrelativistic Quantum Mechanics.\u003c\/p\u003e \u003cp\u003eKlein–Gordon Equation.\u003c\/p\u003e \u003cp\u003eDirac Equation.\u003c\/p\u003e \u003cp\u003eFoldy–Wouthuysen Transformation.\u003c\/p\u003e \u003cp\u003eBreit–Pauli Hamiltonian.\u003c\/p\u003e \u003cp\u003eZ\u003csup\u003eeff\u003c\/sup\u003e Method.\u003c\/p\u003e \u003cp\u003eEffective Core Potential-Based Method.\u003c\/p\u003e \u003cp\u003eModel Core Potential-Based Method.\u003c\/p\u003e \u003cp\u003eDouglas–Kroll Transformation.\u003c\/p\u003e \u003cp\u003ePotential Energy Surfaces.\u003c\/p\u003e \u003cp\u003eMinimum Energy Crossing-Point Location.\u003c\/p\u003e \u003cp\u003eAvailable Programs for Modeling Spin-Forbidden Reactions.\u003c\/p\u003e \u003cp\u003eApplications to Spin-Forbidden Reactions.\u003c\/p\u003e \u003cp\u003eDiatomic Molecules.\u003c\/p\u003e \u003cp\u003ePolyatomic Molecules.\u003c\/p\u003e \u003cp\u003ePhenyl Cation.\u003c\/p\u003e \u003cp\u003eNorborene.\u003c\/p\u003e \u003cp\u003eConjugated Polymers.\u003c\/p\u003e \u003cp\u003eCH(\u003csup\u003e2\u003c\/sup\u003eII) + N2 -- HCN + N(\u003csup\u003e4\u003c\/sup\u003eS).\u003c\/p\u003e \u003cp\u003eMolecular Properties.\u003c\/p\u003e \u003cp\u003eDynamical Aspects.\u003c\/p\u003e \u003cp\u003eOther Reactions.\u003c\/p\u003e \u003cp\u003eBiological Chemistry.\u003c\/p\u003e \u003cp\u003eConcluding Remarks.\u003c\/p\u003e \u003cp\u003eAcknowledgments.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e3. Calculation of the Electronic Spectra of Large Molecules (Stefan Grimme).\u003c\/p\u003e \u003cp\u003eIntroduction.\u003c\/p\u003e \u003cp\u003eTypes of Electronic Spectra.\u003c\/p\u003e \u003cp\u003eTypes of Excited States.\u003c\/p\u003e \u003cp\u003eTheory.\u003c\/p\u003e \u003cp\u003eExcitation Energies.\u003c\/p\u003e \u003cp\u003eTransition Moments.\u003c\/p\u003e \u003cp\u003eVibrational Structure.\u003c\/p\u003e \u003cp\u003eQuantum Chemical Methods.\u003c\/p\u003e \u003cp\u003eCase Studies.\u003c\/p\u003e \u003cp\u003eVertical Absorption Spectra.\u003c\/p\u003e \u003cp\u003eCircular Dichroism.\u003c\/p\u003e \u003cp\u003eVibrational Structure.\u003c\/p\u003e \u003cp\u003eSummary and Outlook.\u003c\/p\u003e \u003cp\u003eAcknowledgments.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e4. Simulating Chemical Waves and Patterns (Raymond Kapral).\u003c\/p\u003e \u003cp\u003eIntroduction.\u003c\/p\u003e \u003cp\u003eReaction–Diffusion Systems.\u003c\/p\u003e \u003cp\u003eCellular Automata.\u003c\/p\u003e \u003cp\u003eCoupled Map Lattices.\u003c\/p\u003e \u003cp\u003eMesoscopic Models.\u003c\/p\u003e \u003cp\u003eSummary.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e5. Fuzzy Soft-Computing Methods and Their Applicationsin Chemistry (Costel Saˆrbu and Horia F. Pop).\u003c\/p\u003e \u003cp\u003eIntroduction.\u003c\/p\u003e \u003cp\u003eMethods for Exploratory Data Analysis.\u003c\/p\u003e \u003cp\u003eVisualization of High-Dimensional Data.\u003c\/p\u003e \u003cp\u003eClustering Methods.\u003c\/p\u003e \u003cp\u003eProjection Methods.\u003c\/p\u003e \u003cp\u003eLinear Projection Methods.\u003c\/p\u003e \u003cp\u003eNonlinear Projection Methods.\u003c\/p\u003e \u003cp\u003eArtificial Neural Networks.\u003c\/p\u003e \u003cp\u003ePerceptron.\u003c\/p\u003e \u003cp\u003eMultilayer Nets: Backpropagation.\u003c\/p\u003e \u003cp\u003eAssociative Memories: Hopfield Net.\u003c\/p\u003e \u003cp\u003eSelf-Organizing Map.\u003c\/p\u003e \u003cp\u003eProperties.\u003c\/p\u003e \u003cp\u003eMathematical Characterization.\u003c\/p\u003e \u003cp\u003eRelation between SOM and MDS.\u003c\/p\u003e \u003cp\u003eMultiple Views of the SOM.\u003c\/p\u003e \u003cp\u003eOther Architectures.\u003c\/p\u003e \u003cp\u003eEvolutionary Algorithms.\u003c\/p\u003e \u003cp\u003eGenetic Algorithms.\u003c\/p\u003e \u003cp\u003eCanonical GA.\u003c\/p\u003e \u003cp\u003eEvolution Strategies.\u003c\/p\u003e \u003cp\u003eEvolutionary Programming.\u003c\/p\u003e \u003cp\u003eFuzzy Sets and Fuzzy Logic.\u003c\/p\u003e \u003cp\u003eFuzzy Sets.\u003c\/p\u003e \u003cp\u003eFuzzy Logic.\u003c\/p\u003e \u003cp\u003eFuzzy Clustering.\u003c\/p\u003e \u003cp\u003eFuzzy Regression.\u003c\/p\u003e \u003cp\u003eFuzzy Principal Component Analysis (FPCA).\u003c\/p\u003e \u003cp\u003eFuzzy PCA (Optimizing the First Component).\u003c\/p\u003e \u003cp\u003eFuzzy PCA (Nonorthogonal Procedure).\u003c\/p\u003e \u003cp\u003eFuzzy PCA (Orthogonal).\u003c\/p\u003e \u003cp\u003eFuzzy Expert Systems (Fuzzy Controllers).\u003c\/p\u003e \u003cp\u003eHybrid Systems.\u003c\/p\u003e \u003cp\u003eCombinations of Fuzzy Systems and Neutral Networks.\u003c\/p\u003e \u003cp\u003eFuzzy Genetic Algorithms.\u003c\/p\u003e \u003cp\u003eNeuro-Genetic Systems.\u003c\/p\u003e \u003cp\u003eFuzzy Characterization and Classification of the Chemical Elements and Their Properties.\u003c\/p\u003e \u003cp\u003eHierarchical Fuzzy Classification of Chemical Elements Based on Ten Physical Properties.\u003c\/p\u003e \u003cp\u003eHierarchical Fuzzy Classification of Chemical Elements Based on Ten Physical, Chemical, and Structural Properties.\u003c\/p\u003e \u003cp\u003eFuzzy Hierarchical Cross-Classification of Chemical Elements Based on Ten Physical Properties.\u003c\/p\u003e \u003cp\u003eFuzzy Hierarchical Characteristics Clustering.\u003c\/p\u003e \u003cp\u003eFuzzy Horizontal Characteristics Clustering.\u003c\/p\u003e \u003cp\u003eCharacterization and Classification of Lanthanides and Their Properties by PCA and FPCA.\u003c\/p\u003e \u003cp\u003eProperties of Lanthanides Considered in This Study.\u003c\/p\u003e \u003cp\u003eClassical PCA.\u003c\/p\u003e \u003cp\u003eFuzzy PCA.\u003c\/p\u003e \u003cp\u003eMiscellaneous Applications of FPCA.\u003c\/p\u003e \u003cp\u003eFuzzy Modeling of Environmental, SAR and QSAR Data.\u003c\/p\u003e \u003cp\u003eSpectral Library Search and Spectra Interpretation.\u003c\/p\u003e \u003cp\u003eFuzzy Calibration of Analytical Methods and Fuzzy Robust Estimation of Location and Spread.\u003c\/p\u003e \u003cp\u003eApplication of Fuzzy Neural Networks Systems in Chemistry.\u003c\/p\u003e \u003cp\u003eApplications of Fuzzy Sets Theory and Fuzzy Logic in Theoretical Chemistry.\u003c\/p\u003e \u003cp\u003eConclusions and Remarks.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003e6. Development of Computational Models for Enzymes, Transporters, Channels, and Receptors Relevant to ADME\/Tox (Sean Ekins and Peter W. Swaan).\u003c\/p\u003e \u003cp\u003eIntroduction.\u003c\/p\u003e \u003cp\u003eADME\/Tox Modeling: An Expansive Vision.\u003c\/p\u003e \u003cp\u003eThe Concerted Actions of Transport and Metabolism.\u003c\/p\u003e \u003cp\u003eMetabolism.\u003c\/p\u003e \u003cp\u003eTransporters.\u003c\/p\u003e \u003cp\u003eApproaches to Modeling Enzymes, Transporters, Channels, and Receptors.\u003c\/p\u003e \u003cp\u003eClassical QSAR.\u003c\/p\u003e \u003cp\u003ePharmacophore Models.\u003c\/p\u003e \u003cp\u003eHomology Modeling.\u003c\/p\u003e \u003cp\u003eTransporter Modeling.\u003c\/p\u003e \u003cp\u003eApplications of Transporters.\u003c\/p\u003e \u003cp\u003eThe Human Small Peptide Transporter, hPEPT1.\u003c\/p\u003e \u003cp\u003eThe Apical Sodium-Dependent Bile Acid Transporter.\u003c\/p\u003e \u003cp\u003eP-Glycoprotein.\u003c\/p\u003e \u003cp\u003eVitamin Transporters.\u003c\/p\u003e \u003cp\u003eOrganic Cation Transporter.\u003c\/p\u003e \u003cp\u003eOrganic AnionTransporters.\u003c\/p\u003e \u003cp\u003eNucleoside Transporter.\u003c\/p\u003e \u003cp\u003eBreast Cancer Resistance Protein.\u003c\/p\u003e \u003cp\u003eSodium Taurocholate Transporting Polypeptide.\u003c\/p\u003e \u003cp\u003eEnzymes.\u003c\/p\u003e \u003cp\u003eCytochrome P450.\u003c\/p\u003e \u003cp\u003eEpoxide Hydrolase.\u003c\/p\u003e \u003cp\u003eMonoamine Oxidase.\u003c\/p\u003e \u003cp\u003eFlavin-Containing Monooxygenase.\u003c\/p\u003e \u003cp\u003eSulfotransferases.\u003c\/p\u003e \u003cp\u003eGlucuronosyltransferases.\u003c\/p\u003e \u003cp\u003eGlutathione S-transferases.\u003c\/p\u003e \u003cp\u003eChannels.\u003c\/p\u003e \u003cp\u003eHuman Ether-a-gogo Related Gene.\u003c\/p\u003e \u003cp\u003eReceptors.\u003c\/p\u003e \u003cp\u003ePregnane X-Receptor.\u003c\/p\u003e \u003cp\u003eConstitutive Androstane Receptor.\u003c\/p\u003e \u003cp\u003eFuture Developments.\u003c\/p\u003e \u003cp\u003eAcknowledgments.\u003c\/p\u003e \u003cp\u003eAbbreviations.\u003c\/p\u003e \u003cp\u003eReferences.\u003c\/p\u003e \u003cp\u003eAuthor Index.\u003c\/p\u003e \u003cp\u003eSubject Index.\u003c\/p\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49402596229463,"sku":"9780471445258","price":252.86,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9780471445258.jpg?v=1730480906"},{"product_id":"agentbased-and-individualbased-modeling-9780691190839","title":"AgentBased and IndividualBased Modeling","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003e\u003cp\u003ePraise for the first edition \u003c\/p\u003e\u003cp\u003e\"Biologists . . . have been relatively slow to take advantage of enhanced computing power and unlock the potential of these techniques. This book removes any excuse.\"\u003cb\u003e—\u003ci\u003eFrontiers of Biogeography\u003c\/i\u003e\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003e\"This volume would be an excellent text for an introductory course in modeling as science, or for self-study by a mature researcher interested in learning about this important new way of doing science.\"\u003cb\u003e—H. Van Dyke Parunak, \u003ci\u003eJASSS\u003c\/i\u003e\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003e\"This book represents something I have been [awaiting] for some years now: a good and solid introduction to the field of individual- and agent-based models. . . . The book is not only a practical guide but also serves as a good introduction to the basics of 'healthy' programming. These authors are the right ones to do this as they have a strong background in the philosophical aspects as well as the practical issues of modelling.\"\u003cb\u003e—\u003ci\u003eBasic and Applied Ecology\u003c\/i\u003e\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003e\"\u003ci\u003eAgent-Based and Individual-Based Modeling\u003c\/i\u003e has the potential to foster an appreciation of the value and place of individual-based models in our field in the next generation of emerging ecologists.\"\u003cb\u003e—Christopher X. Jon Jensen, \u003ci\u003eEcology\u003c\/i\u003e\u003c\/b\u003e\u003c\/p\u003e","brand":"Princeton University Press","offers":[{"title":"Default Title","offer_id":49403868905815,"sku":"9780691190839","price":49.3,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9780691190839.jpg?v=1730484759"},{"product_id":"computing-the-climate-9781107589926","title":"Computing the Climate","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eThis accessible, non-technical book reveals how, starting in the 1800s, scientists have used mathematical models and computer simulations to demonstrate that climate change is real  and accelerating. Readers will learn where the key scientific ideas came from, how they were tested, and what future these models forecast for our planet.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003e'Numerical climate models are a critical tool for assessing the threat posed by climate change and investigating the options available to mitigate that threat. Yet, an understanding of these models-how they work, what they tell us, and how their tested and validated-has remained evasive for all but the most math and physics-literate. In Computing the Climate, computer scientist Steve Easterbook takes us on a journey through the world of climate modeling, making the science accessible to lay readers, and showing us why we should trust the models and heed their warnings, before it's too late.' Michael Mann, University of Pennsylvania, author of The New Climate War\u003cbr\u003e'Computing the Climate provides an impressively detailed history of how climate models evolved from simple equations calculated by hand to giant programs running on supercomputers. Avoiding jargon, this book explains to a general audience how the laws of physics and the principles of software engineering are combined to build climate models.' R. Saravanan, Texas A\u0026amp;M University, author of The Climate Demon\u003cbr\u003e'Computing the Climate takes a unique look at the history of computational modeling the Earth's climate system, the processes represented in these models, their evaluation, and how they are being used to project the potential changes in the future of our climate. When combined with more detailed analyses of concurrent issues being addressed in these models such as cloud and convection processes, this would be an excellent book for a university course on climate modeling.' Don Wuebbles, University of Illinois\u003cbr\u003e'I teach several courses in climate change and climate modeling for general and specialized audiences, and I am so excited to incorporate this new text by Easterbrook into those classes. While climate models are derived from first physical principles, climate models are developed by people and communities. I think that this book's approach of the tracing of revolutionary ideas and herculean efforts by generations of scientists to develop deep understanding and predictive capability for weather and climate does the topic justice. The logical progression of concepts, chapter by chapter is excellent as is the extensive, but not obtrusive, referencing throughout. Many difficult concepts, including: the greenhouse effect, chaos and predicability, computational instability, parallel computing, the difference between predictions and projections, are explained very well and accessibly. This book will be compelling reading both for students and people who simply want to know more.' Matthew Huber, Purdue University\u003cbr\u003e'Easterbrook's non-technical survey of climate modeling uniquely expands the climate change genre. Students will benefit from its broad scope and equation-free conceptual explanations, and climate modelers will appreciate its historical approach linking nineteenth century experiments and ideas to twenty-first century breakthroughs.' Baylor Fox-Kemper, Brown University\u003cbr\u003e'This is a very readable personal account of climate model development throughout history. It focuses on several individuals and modeling groups\/countries. It often refers to 'you' and 'we'. I learned a lot and enjoyed the book, and I recommend it to anyone faced with making decisions involving the future climate.' Kevin Trenberth, University of Auckland, author of The Changing Flow of Energy Through the Climate System\u003cbr\u003e'This engaging, beautifully written book brings alive the scientists who created climate models, how they did it, and what the models can (and cannot) tell us - all in straightforward, nontechnical language and enlightening illustrations. If you want to understand how modern climate science works, start here.' Paul N. Edwards, Stanford University, author of A Vast Machine: Computer Models, Climate Data, and the Politics of Global Warming\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e1. Introduction; 2. The world's first climate model; 3. The forecast factory; 4. Taming chaos; 5. The heart of the machine; 6. The well-equipped physics lab; 7. Plug and play; 8. Sound science; 9. Choosing a future; References; Index.","brand":"Cambridge University Press","offers":[{"title":"Default Title","offer_id":49406810030423,"sku":"9781107589926","price":25.99,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781107589926.jpg?v=1730497191"},{"product_id":"modeling-and-simulation-of-discrete-event-systems-9781118386996","title":"Modeling and Simulation of Discrete Event Systems","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eComputer modeling and simulation (M\u0026amp;S) allows engineers to study and analyze complex systems. Discrete-event system (DES)-M\u0026amp;S is used in modern management, industrial engineering, computer science, and the military. As computer speeds and memory capacity increase, so DES-M\u0026amp;S tools become more powerful and more widely used in solving real-life problems.\u003c\/p\u003e \u003cp\u003eBased on over 20 years of evolution within a classroom environment, as well as on decades-long experience in developing simulation-based solutions for high-tech industries, \u003ci\u003eModeling and Simulation of Discrete-Event Systems\u003c\/i\u003e is the only book on DES-M\u0026amp;S in which all the major DES modeling formalisms  activity-based, process-oriented, state-based, and event-based  are covered in a unified manner:\u003c\/p\u003e \u003cul\u003e \u003cli\u003eA well-defined procedure for building a formal model in the form of event graph, ACD, or state graph\u003c\/li\u003e \u003cli\u003eDiverse types of modeling templates and examples that can be used as building blocks for a complex, real-life\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003ePREFACE xvii\u003c\/p\u003e \u003cp\u003eABBREVIATIONS xix\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART I BASICS OF SYSTEM MODELING AND SIMULATION 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1. Overview of Computer Simulation 3\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 Introduction 3\u003c\/p\u003e \u003cp\u003e1.2 What Is a System? 4\u003c\/p\u003e \u003cp\u003e1.3 What Is Computer Simulation? 6\u003c\/p\u003e \u003cp\u003e1.4 What Is Discrete-Event Simulation? 9\u003c\/p\u003e \u003cp\u003e1.5 What Is Continuous Simulation? 11\u003c\/p\u003e \u003cp\u003e1.6 What Is Monte Carlo Simulation? 12\u003c\/p\u003e \u003cp\u003e1.7 What Are Simulation Experimentation and Optimization? 15\u003c\/p\u003e \u003cp\u003e1.8 Review Questions 16\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2. Basics of Discrete-Event System Modeling and Simulation 17\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction 17\u003c\/p\u003e \u003cp\u003e2.2 How Is a Discrete-Event Simulation Carried Out? 17\u003c\/p\u003e \u003cp\u003e2.3 Framework of Discrete-Event System Modeling 23\u003c\/p\u003e \u003cp\u003e2.4 Illustrative Examples of DES Modeling and Simulation 32\u003c\/p\u003e \u003cp\u003e2.5 Application Frameworks for Discrete-Event System Modeling and Simulation 38\u003c\/p\u003e \u003cp\u003e2.6 What to Cover in a Simulation Class 40\u003c\/p\u003e \u003cp\u003e2.7 Review Questions 42\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART II FUNDAMENTALS OF DISCRETE-EVENT SYSTEM MODELING AND SIMULATION 43\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3. Input Modeling for Simulation 45\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction 45\u003c\/p\u003e \u003cp\u003e3.2 Empirical Input Modeling 46\u003c\/p\u003e \u003cp\u003e3.3 Overview of Theoretical Distribution Fitting 48\u003c\/p\u003e \u003cp\u003e3.4 Theoretical Modeling of Arrival Processes 50\u003c\/p\u003e \u003cp\u003e3.5 Theoretical Modeling of Service Times 53\u003c\/p\u003e \u003cp\u003e3.6 Input Modeling for Special Applications 57\u003c\/p\u003e \u003cp\u003e3.7 Review Questions 59\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4. Introduction to Event-Based Modeling and Simulation 69\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 Introduction 69\u003c\/p\u003e \u003cp\u003e4.2 Modeling and Simulation of a Single Server System 70\u003c\/p\u003e \u003cp\u003e4.3 Execution Rules and Specifications of Event Graph Models 72\u003c\/p\u003e \u003cp\u003e4.4 Event Graph Modeling Templates 75\u003c\/p\u003e \u003cp\u003e4.5 Event Graph Modeling Examples 82\u003c\/p\u003e \u003cp\u003e4.6 Execution of Event Graph Models with SIGMA 91\u003c\/p\u003e \u003cp\u003e4.7 Developing Your Own Event Graph Simulator 99\u003c\/p\u003e \u003cp\u003e4.8 Review Questions 106\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5. Parameterized Event Graph Modeling and Simulation 107\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction 107\u003c\/p\u003e \u003cp\u003e5.2 Parameterized Event Graph Examples 108\u003c\/p\u003e \u003cp\u003e5.3 Execution Rules and Specifications of the Parameterized Event Graph 110\u003c\/p\u003e \u003cp\u003e5.4 Parameterized Event Graph Modeling of Tandem Lines 112\u003c\/p\u003e \u003cp\u003e5.5 Parameterized Event Graph Modeling of Job Shops 115\u003c\/p\u003e \u003cp\u003e5.6 Execution of Parameterized Event Graph Models Using SIGMA 122\u003c\/p\u003e \u003cp\u003e5.7 Developing Your Own Parameterized Event Graph Simulator 137\u003c\/p\u003e \u003cp\u003e5.8 Review Questions 142\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6. Introduction to Activity-Based Modeling and Simulation 143\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction 143\u003c\/p\u003e \u003cp\u003e6.2 Definitions and Specifications of an Activity Cycle Diagram 145\u003c\/p\u003e \u003cp\u003e6.3 Activity Cycle Diagram Modeling Templates 150\u003c\/p\u003e \u003cp\u003e6.4 Activity-Based Modeling Examples 156\u003c\/p\u003e \u003cp\u003e6.5 Parameterized Activity Cycle Diagram and Its Application 163\u003c\/p\u003e \u003cp\u003e6.6 Execution of Activity Cycle Diagram Models with a Formal Simulator ACE® 171\u003c\/p\u003e \u003cp\u003e6.7 Review Questions 183\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7. Simulation of ACD Models Using Arena 184\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction 184\u003c\/p\u003e \u003cp\u003e7.2 Arena Basics 185\u003c\/p\u003e \u003cp\u003e7.3 Activity Cycle Diagram-to-Arena Conversion Templates 197\u003c\/p\u003e \u003cp\u003e7.4 Activity Cycle Diagram-Based Arena Modeling Examples 209\u003c\/p\u003e \u003cp\u003e7.5 Review Questions 223\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8. Output Analysis and Optimization 224\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction 224\u003c\/p\u003e \u003cp\u003e8.2 Framework of Simulation Output Analyses 225\u003c\/p\u003e \u003cp\u003e8.3 Qualitative Output Analyses 228\u003c\/p\u003e \u003cp\u003e8.4 Statistical Output Analyses 230\u003c\/p\u003e \u003cp\u003e8.5 Linear Regression Modeling for Output Analyses 234\u003c\/p\u003e \u003cp\u003e8.6 Response Surface Methodology for Simulation Optimization 241\u003c\/p\u003e \u003cp\u003e8.7 Review Questions 247\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART III ADVANCES IN DISCRETE-EVENT SYSTEM MODELING AND SIMULATION 253\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9. State-Based Modeling and Simulation 255\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction 255\u003c\/p\u003e \u003cp\u003e9.2 Finite State Machine 256\u003c\/p\u003e \u003cp\u003e9.3 Timed Automata 261\u003c\/p\u003e \u003cp\u003e9.4 State Graphs 267\u003c\/p\u003e \u003cp\u003e9.5 System Modeling with State Graph 271\u003c\/p\u003e \u003cp\u003e9.6 Simulation of Composite State Graph Models 283\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10. Advanced Topics in Activity-Based Modeling and Simulation 299\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10.1 Introduction 299\u003c\/p\u003e \u003cp\u003e10.2 Developing Your Own Activity Cycle Diagram Simulators 300\u003c\/p\u003e \u003cp\u003e10.3 Modeling with Canceling Arc 310\u003c\/p\u003e \u003cp\u003e10.4 Cycle Time Analysis of Work Cells via an Activity Cycle Diagram 313\u003c\/p\u003e \u003cp\u003e10.5 Activity Cycle Diagram Modeling of a Flexible Manufacturing System 322\u003c\/p\u003e \u003cp\u003e10.6 Formal Model Conversion 329\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11. Advanced Event Graph Modeling for Integrated Fab Simulation 338\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e11.1 Introduction 338\u003c\/p\u003e \u003cp\u003e11.2 Flat Panel Display Fabrication System 339\u003c\/p\u003e \u003cp\u003e11.3 Production Simulation of a Flat Panel Display Fab 343\u003c\/p\u003e \u003cp\u003e11.4 Integrated Simulation of a Flat Panel Display Fab 350\u003c\/p\u003e \u003cp\u003e11.5 Automated Material Handling Systems-Embedded Integrated Simulation of Flat Panel Display Fab 362\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12. Concepts and Applications of Parallel Simulation 371\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e12.1 Introduction 371\u003c\/p\u003e \u003cp\u003e12.2 Parallel Simulation of Workflow Management System 372\u003c\/p\u003e \u003cp\u003e12.3 Overview of High-Level Architecture\/Run-Time Infrastructure 378\u003c\/p\u003e \u003cp\u003e12.4 Implementation of a Parallel Simulation with High-Level Architecture\/Run-Time Infrastructure 383\u003c\/p\u003e \u003cp\u003eREFERENCES 395\u003c\/p\u003e \u003cp\u003eINDEX 400\u003c\/p\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49406862688599,"sku":"9781118386996","price":96.26,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781118386996.jpg?v=1730497372"},{"product_id":"large-strain-finite-element-method-9781118405307","title":"Large Strain Finite Element Method","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003e\u003cb\u003eAn introductory approach to the subject of large strains and large displacements in finite elements.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003ci\u003eLarge Strain Finite Element Method: A Practical Course\u003c\/i\u003e, takes an introductory approach to the subject of large strains and large displacements in finite elements and starts from the basic concepts of finite strain deformability, including finite rotations and finite displacements. The necessary elements of vector analysis and tensorial calculus on the lines of modern understanding of the concept of tensor will also be introduced.\u003c\/p\u003e \u003cp\u003eThis book explains how tensors and vectors can be described using matrices and also introduces different stress and strain tensors. Building on these, step by step finite element techniques for both hyper and hypo-elastic approach will be considered.\u003c\/p\u003e \u003cp\u003eMaterial models including isotropic, unisotropic, plastic and viscoplastic materials will be independently discussed to facilitate clarity and ease of learning. Elements of tra\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003ePreface xiii\u003c\/p\u003e \u003cp\u003eAcknowledgements xv\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART ONE FUNDAMENTALS 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Introduction 3\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 Assumption of Small Displacements 3\u003c\/p\u003e \u003cp\u003e1.2 Assumption of Small Strains 6\u003c\/p\u003e \u003cp\u003e1.3 Geometric Nonlinearity 6\u003c\/p\u003e \u003cp\u003e1.4 Stretches 8\u003c\/p\u003e \u003cp\u003e1.5 Some Examples of Large Displacement Large Strain Finite Element Formulation 8\u003c\/p\u003e \u003cp\u003e1.6 The Scope and Layout of the Book 13\u003c\/p\u003e \u003cp\u003e1.7 Summary 13\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Matrices 15\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Matrices in General 15\u003c\/p\u003e \u003cp\u003e2.2 Matrix Algebra 16\u003c\/p\u003e \u003cp\u003e2.3 Special Types of Matrices 21\u003c\/p\u003e \u003cp\u003e2.4 Determinant of a Square Matrix 22\u003c\/p\u003e \u003cp\u003e2.5 Quadratic Form 24\u003c\/p\u003e \u003cp\u003e2.6 Eigenvalues and Eigenvectors 24\u003c\/p\u003e \u003cp\u003e2.7 Positive Definite Matrix 26\u003c\/p\u003e \u003cp\u003e2.8 Gaussian Elimination 26\u003c\/p\u003e \u003cp\u003e2.9 Inverse of a Square Matrix 28\u003c\/p\u003e \u003cp\u003e2.10 Column Matrices 30\u003c\/p\u003e \u003cp\u003e2.11 Summary 32\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Some Explicit and Iterative Solvers 35\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 The Central Difference Solver 35\u003c\/p\u003e \u003cp\u003e3.2 Generalized Direction Methods 43\u003c\/p\u003e \u003cp\u003e3.3 The Method of Conjugate Directions 50\u003c\/p\u003e \u003cp\u003e3.4 Summary 63\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Numerical Integration 65\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 Newton-Cotes Numerical Integration 65\u003c\/p\u003e \u003cp\u003e4.2 Gaussian Numerical Integration 67\u003c\/p\u003e \u003cp\u003e4.3 Gaussian Integration in 2D 70\u003c\/p\u003e \u003cp\u003e4.4 Gaussian Integration in 3D 71\u003c\/p\u003e \u003cp\u003e4.5 Summary 72\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Work of Internal Forces on Virtual Displacements 75\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 The Principle of Virtual Work 75\u003c\/p\u003e \u003cp\u003e5.2 Summary 78\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART TWO PHYSICAL QUANTITIES 79\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Scalars 81\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 Scalars in General 81\u003c\/p\u003e \u003cp\u003e6.2 Scalar Functions 81\u003c\/p\u003e \u003cp\u003e6.3 Scalar Graphs 82\u003c\/p\u003e \u003cp\u003e6.4 Empirical Formulas 82\u003c\/p\u003e \u003cp\u003e6.5 Fonts 83\u003c\/p\u003e \u003cp\u003e6.6 Units 83\u003c\/p\u003e \u003cp\u003e6.7 Base and Derived Scalar Variables 85\u003c\/p\u003e \u003cp\u003e6.8 Summary 85\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Vectors in 2D 87\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 Vectors in General 87\u003c\/p\u003e \u003cp\u003e7.2 Vector Notation 91\u003c\/p\u003e \u003cp\u003e7.3 Matrix Representation of Vectors 91\u003c\/p\u003e \u003cp\u003e7.4 Scalar Product 92\u003c\/p\u003e \u003cp\u003e7.5 General Vector Base in 2D 93\u003c\/p\u003e \u003cp\u003e7.6 Dual Base 94\u003c\/p\u003e \u003cp\u003e7.7 Changing Vector Base 95\u003c\/p\u003e \u003cp\u003e7.8 Self-duality of the Orthonormal Base 97\u003c\/p\u003e \u003cp\u003e7.9 Combining Bases 98\u003c\/p\u003e \u003cp\u003e7.10 Examples 104\u003c\/p\u003e \u003cp\u003e7.11 Summary 108\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Vectors in 3D 109\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 Vectors in 3D 109\u003c\/p\u003e \u003cp\u003e8.2 Vector Bases 111\u003c\/p\u003e \u003cp\u003e8.3 Summary 114\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Vectors in n-Dimensional Space 117\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1 Extension from 3D to 4-Dimensional Space 117\u003c\/p\u003e \u003cp\u003e9.2 The Dual Base in 4D 118\u003c\/p\u003e \u003cp\u003e9.3 Changing the Base in 4D 120\u003c\/p\u003e \u003cp\u003e9.4 Generalization to n-Dimensional Space 121\u003c\/p\u003e \u003cp\u003e9.5 Changing the Base in n-Dimensional Space 124\u003c\/p\u003e \u003cp\u003e9.6 Summary 127\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 First Order Tensors 129\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10.1 The Slope Tensor 129\u003c\/p\u003e \u003cp\u003e10.2 First Order Tensors in 2D 131\u003c\/p\u003e \u003cp\u003e10.3 Using First Order Tensors 132\u003c\/p\u003e \u003cp\u003e10.4 Using Different Vector Bases in 2D 134\u003c\/p\u003e \u003cp\u003e10.5 Differential of a 2D Scalar Field as the First Order Tensor 137\u003c\/p\u003e \u003cp\u003e10.6 First Order Tensors in 3D 141\u003c\/p\u003e \u003cp\u003e10.7 Changing the Vector Base in 3D 142\u003c\/p\u003e \u003cp\u003e10.8 First Order Tensor in 4D 143\u003c\/p\u003e \u003cp\u003e10.9 First Order Tensor in n-Dimensions 147\u003c\/p\u003e \u003cp\u003e10.10 Differential of a 3D Scalar Field as the First Order Tensor 149\u003c\/p\u003e \u003cp\u003e10.11 Scalar Field in n-Dimensional Space 152\u003c\/p\u003e \u003cp\u003e10.12 Summary 153\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Second Order Tensors in 2D 155\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e11.1 Stress Tensor in 2D 155\u003c\/p\u003e \u003cp\u003e11.2 Second Order Tensor in 2D 158\u003c\/p\u003e \u003cp\u003e11.3 Physical Meaning of Tensor Matrix in 2D 159\u003c\/p\u003e \u003cp\u003e11.4 Changing the Base 161\u003c\/p\u003e \u003cp\u003e11.5 Using Two Different Bases in 2D 163\u003c\/p\u003e \u003cp\u003e11.6 Some Special Cases of Stress Tensor Matrices in 2D 167\u003c\/p\u003e \u003cp\u003e11.7 The First Piola-Kirchhoff Stress Tensor Matrix 168\u003c\/p\u003e \u003cp\u003e11.8 The Second Piola-Kirchhoff Stress Tensor Matrix 169\u003c\/p\u003e \u003cp\u003e11.9 Summary 174\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Second Order Tensors in 3D 175\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e12.1 Stress Tensor in 3D 175\u003c\/p\u003e \u003cp\u003e12.2 General Base for Surfaces 179\u003c\/p\u003e \u003cp\u003e12.3 General Base for Forces 182\u003c\/p\u003e \u003cp\u003e12.4 General Base for Forces and Surfaces 184\u003c\/p\u003e \u003cp\u003e12.5 The Cauchy Stress Tensor Matrix in 3D 186\u003c\/p\u003e \u003cp\u003e12.6 The First Piola-Kirchhoff Stress Tensor Matrix in 3D 186\u003c\/p\u003e \u003cp\u003e12.7 The Second Piola-Kirchhoff Stress Tensor Matrix in 3D 188\u003c\/p\u003e \u003cp\u003e12.8 Summary 189\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 Second Order Tensors in nD 191\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e13.1 Second Order Tensor in n-Dimensions 191\u003c\/p\u003e \u003cp\u003e13.2 Summary 200\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART THREE DEFORMABILITY AND MATERIAL MODELING 201\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 Kinematics of Deformation in 1D 203\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e14.1 Geometric Nonlinearity in General 203\u003c\/p\u003e \u003cp\u003e14.2 Stretch 205\u003c\/p\u003e \u003cp\u003e14.3 Material Element and Continuum Assumption 208\u003c\/p\u003e \u003cp\u003e14.4 Strain 209\u003c\/p\u003e \u003cp\u003e14.5 Stress 213\u003c\/p\u003e \u003cp\u003e14.6 Summary 214\u003c\/p\u003e \u003cp\u003e\u003cb\u003e15 Kinematics of Deformation in 2D 217\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e15.1 Isotropic Solids 217\u003c\/p\u003e \u003cp\u003e15.2 Homogeneous Solids 217\u003c\/p\u003e \u003cp\u003e15.3 Homogeneous and Isotropic Solids 217\u003c\/p\u003e \u003cp\u003e15.4 Nonhomogeneous and Anisotropic Solids 218\u003c\/p\u003e \u003cp\u003e15.5 Material Element Deformation 221\u003c\/p\u003e \u003cp\u003e15.6 Cauchy Stress Matrix for the Solid Element 225\u003c\/p\u003e \u003cp\u003e15.7 Coordinate Systems in 2D 227\u003c\/p\u003e \u003cp\u003e15.8 The Solid- and the Material-Embedded Vector Bases 228\u003c\/p\u003e \u003cp\u003e15.9 Kinematics of 2D Deformation 229\u003c\/p\u003e \u003cp\u003e15.10 2D Equilibrium Using the Virtual Work of Internal Forces 231\u003c\/p\u003e \u003cp\u003e15.11 Examples 235\u003c\/p\u003e \u003cp\u003e15.12 Summary 238\u003c\/p\u003e \u003cp\u003e\u003cb\u003e16 Kinematics of Deformation in 3D 241\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e16.1 The Cartesian Coordinate System in 3D 241\u003c\/p\u003e \u003cp\u003e16.2 The Solid-Embedded Coordinate System 241\u003c\/p\u003e \u003cp\u003e16.3 The Global and the Solid-Embedded Vector Bases 243\u003c\/p\u003e \u003cp\u003e16.4 Deformation of the Solid 244\u003c\/p\u003e \u003cp\u003e16.5 Generalized Material Element 246\u003c\/p\u003e \u003cp\u003e16.6 Kinematic of Deformation in 3D 247\u003c\/p\u003e \u003cp\u003e16.7 The Virtual Work of Internal Forces 249\u003c\/p\u003e \u003cp\u003e16.8 Summary 255\u003c\/p\u003e \u003cp\u003e\u003cb\u003e17 The Unified Constitutive Approach in 2D 257\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e17.1 Introduction 257\u003c\/p\u003e \u003cp\u003e17.2 Material Axes 259\u003c\/p\u003e \u003cp\u003e17.3 Micromechanical Aspects and Homogenization 260\u003c\/p\u003e \u003cp\u003e17.4 Generalized Homogenization 263\u003c\/p\u003e \u003cp\u003e17.5 The Material Package 264\u003c\/p\u003e \u003cp\u003e17.6 Hyper-Elastic Constitutive Law 265\u003c\/p\u003e \u003cp\u003e17.7 Hypo-Elastic Constitutive Law 266\u003c\/p\u003e \u003cp\u003e17.8 A Unified Framework for Developing Anisotropic Material Models in 2D 267\u003c\/p\u003e \u003cp\u003e17.9 Generalized Hyper-Elastic Material 267\u003c\/p\u003e \u003cp\u003e17.10 Converting the Munjiza Stress Matrix to the Cauchy Stress Matrix 274\u003c\/p\u003e \u003cp\u003e17.11 Developing Constitutive Laws 279\u003c\/p\u003e \u003cp\u003e17.12 Generalized Hypo-Elastic Material 288\u003c\/p\u003e \u003cp\u003e17.13 Unified Constitutive Approach for Strain Rate and Viscosity 292\u003c\/p\u003e \u003cp\u003e17.14 Summary 293\u003c\/p\u003e \u003cp\u003e\u003cb\u003e18 The Unified Constitutive Approach in 3D 295\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e18.1 Material Package Framework 295\u003c\/p\u003e \u003cp\u003e18.2 Generalized Hyper-Elastic Material 295\u003c\/p\u003e \u003cp\u003e18.3 Generalized Hypo-Elastic Material 299\u003c\/p\u003e \u003cp\u003e18.4 Developing Material Models 302\u003c\/p\u003e \u003cp\u003e18.5 Calculation of the Cauchy Stress Tensor Matrix 302\u003c\/p\u003e \u003cp\u003e18.6 Summary 312\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART FOUR THE FINITE ELEMENT METHOD IN 2D 315\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e19 2D Finite Element: Deformation Kinematics Using the Homogeneous Deformation Triangle 317\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e19.1 The Finite Element Mesh 317\u003c\/p\u003e \u003cp\u003e19.2 The Homogeneous Deformation Finite Element 317\u003c\/p\u003e \u003cp\u003e19.3 Summary 326\u003c\/p\u003e \u003cp\u003e\u003cb\u003e20 2D Finite Element: Deformation Kinematics Using Iso-Parametric Finite Elements 327\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e20.1 The Finite Element Library 327\u003c\/p\u003e \u003cp\u003e20.2 The Shape Functions 327\u003c\/p\u003e \u003cp\u003e20.3 Nodal Positions 330\u003c\/p\u003e \u003cp\u003e20.4 Positions of Material Points inside a Single Finite Element 331\u003c\/p\u003e \u003cp\u003e20.5 The Solid-Embedded Vector Base 332\u003c\/p\u003e \u003cp\u003e20.6 The Material-Embedded Vector Base 334\u003c\/p\u003e \u003cp\u003e20.7 Some Examples of 2D Finite Elements 337\u003c\/p\u003e \u003cp\u003e20.8 Summary 340\u003c\/p\u003e \u003cp\u003e\u003cb\u003e21 Integration of Nodal Forces over Volume of 2D Finite Elements 343\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e21.1 The Principle of Virtual Work in the 2D Finite Element Method 343\u003c\/p\u003e \u003cp\u003e21.2 Nodal Forces for the Homogeneous Deformation Triangle 348\u003c\/p\u003e \u003cp\u003e21.3 Nodal Forces for the Six-Noded Triangle 352\u003c\/p\u003e \u003cp\u003e21.4 Nodal Forces for the Four-Noded Quadrilateral 353\u003c\/p\u003e \u003cp\u003e21.5 Summary 355\u003c\/p\u003e \u003cp\u003e\u003cb\u003e22 Reduced and Selective Integration of Nodal Forces over Volume of 2D Finite Elements 357\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e22.1 Volumetric Locking 357\u003c\/p\u003e \u003cp\u003e22.2 Reduced Integration 358\u003c\/p\u003e \u003cp\u003e22.3 Selective Integration 359\u003c\/p\u003e \u003cp\u003e22.4 Shear Locking 362\u003c\/p\u003e \u003cp\u003e22.5 Summary 364\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART FIVE THE FINITE ELEMENT METHOD IN 3D 365\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e23 3D Deformation Kinematics Using the Homogeneous Deformation Tetrahedron Finite Element 367\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e23.1 Introduction 367\u003c\/p\u003e \u003cp\u003e23.2 The Homogeneous Deformation Four-Noded Tetrahedron Finite Element 368\u003c\/p\u003e \u003cp\u003e23.3 Summary 377\u003c\/p\u003e \u003cp\u003e\u003cb\u003e24 3D Deformation Kinematics Using Iso-Parametric Finite Elements 379\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e24.1 The Finite Element Library 379\u003c\/p\u003e \u003cp\u003e24.2 The Shape Functions 379\u003c\/p\u003e \u003cp\u003e24.3 Nodal Positions 381\u003c\/p\u003e \u003cp\u003e24.4 Positions of Material Points inside a Single Finite Element 382\u003c\/p\u003e \u003cp\u003e24.5 The Solid-Embedded Infinitesimal Vector Base 383\u003c\/p\u003e \u003cp\u003e24.6 The Material-Embedded Infinitesimal Vector Base 386\u003c\/p\u003e \u003cp\u003e24.7 Examples of Deformation Kinematics 387\u003c\/p\u003e \u003cp\u003e24.8 Summary 392\u003c\/p\u003e \u003cp\u003e\u003cb\u003e25 Integration of Nodal Forces over Volume of 3D Finite Elements 393\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e25.1 Nodal Forces Using Virtual Work 393\u003c\/p\u003e \u003cp\u003e25.2 Four-Noded Tetrahedron Finite Element 396\u003c\/p\u003e \u003cp\u003e25.3 Reduce Integration for Eight-Noded 3D Solid 399\u003c\/p\u003e \u003cp\u003e25.4 Selective Stretch Sampling-Based Integration for the Eight-Noded Solid Finite Element 400\u003c\/p\u003e \u003cp\u003e25.5 Summary 401\u003c\/p\u003e \u003cp\u003e\u003cb\u003e26 Integration of Nodal Forces over Boundaries of Finite Elements 403\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e26.1 Stress at Element Boundaries 403\u003c\/p\u003e \u003cp\u003e26.2 Integration of the Equivalent Nodal Forces over the Triangle Finite Element 404\u003c\/p\u003e \u003cp\u003e26.3 Integration over the Boundary of the Composite Triangle 407\u003c\/p\u003e \u003cp\u003e26.4 Integration over the Boundary of the Six-Noded Triangle 408\u003c\/p\u003e \u003cp\u003e26.5 Integration of the Equivalent Internal Nodal Forces over the Tetrahedron Boundaries 409\u003c\/p\u003e \u003cp\u003e26.6 Summary 412\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART SIX THE FINITE ELEMENT METHOD IN 2.5D 415\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e27 Deformation in 2.5D Using Membrane Finite Elements 417\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e27.1 Solids in 2.5D 417\u003c\/p\u003e \u003cp\u003e27.2 The Homogeneous Deformation Three-Noded Triangular Membrane Finite Element 419\u003c\/p\u003e \u003cp\u003e27.3 Summary 438\u003c\/p\u003e \u003cp\u003e\u003cb\u003e28 Deformation in 2.5D Using Shell Finite Elements 439\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e28.1 Introduction 439\u003c\/p\u003e \u003cp\u003e28.2 The Six-Noded Triangular Shell Finite Element 440\u003c\/p\u003e \u003cp\u003e28.3 The Solid-Embedded Coordinate System 441\u003c\/p\u003e \u003cp\u003e28.4 Nodal Coordinates 442\u003c\/p\u003e \u003cp\u003e28.5 The Coordinates of the Finite Element’s Material Points 443\u003c\/p\u003e \u003cp\u003e28.6 The Solid-Embedded Infinitesimal Vector Base 444\u003c\/p\u003e \u003cp\u003e28.7 The Solid-Embedded Vector Base versus the Material-Embedded Vector Base 447\u003c\/p\u003e \u003cp\u003e28.8 The Constitutive Law 449\u003c\/p\u003e \u003cp\u003e28.9 Selective Stretch Sampling Based Integration of the Equivalent Nodal Forces 449\u003c\/p\u003e \u003cp\u003e28.10 Multi-Layered Shell as an Assembly of Single Layer Shells 455\u003c\/p\u003e \u003cp\u003e28.11 Improving the CPU Performance of the Shell Element 456\u003c\/p\u003e \u003cp\u003e28.12 Summary 462\u003c\/p\u003e \u003cp\u003eIndex 463\u003c\/p\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49406865146199,"sku":"9781118405307","price":93.05,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781118405307.jpg?v=1730497380"},{"product_id":"modeling-and-simulation-support-for-system-of-systems-engineering-applications-9781118460313","title":"Modeling and Simulation Support for System of","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e. a much-needed handbook with contributions from well-chosen practitioners.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eForeword xi\u003c\/p\u003e \u003cp\u003eList of Contributors xiii\u003c\/p\u003e \u003cp\u003eNotes on Contributors xvii\u003c\/p\u003e \u003cp\u003eList of Acronyms xxxi\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart I Overview and Introduction\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1. Overview and Introduction to Modeling and Simulation Support for System of Systems Engineering Applications 3\u003cbr\u003e\u003ci\u003eLarry B. Rainey and Andreas Tolk\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e2. The Role of Modeling and Simulation in System of Systems Development 11\u003cbr\u003e\u003ci\u003eMark W. Maier\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart II Theoretical and Methodological Considerations\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3. Composability 45\u003cbr\u003e\u003ci\u003eMichael C. Jones\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e4. An Approach for System of Systems Tradespace Exploration 75\u003cbr\u003e\u003ci\u003eAdam M. Ross and Donna H. Rhodes\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e5. Data Policy Definition and Verification for System of Systems Governance 99\u003cbr\u003e\u003ci\u003eDaniele Gianni\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e6. System Health Management 131\u003cbr\u003e\u003ci\u003eStephen B. Johnson\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e7. Model Methodology for a Department of Defense Architecture Design 145\u003cbr\u003e\u003ci\u003eR. William Maule\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart III Theoretical and Methodological Considerations with Applications and Lessons Learned\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8. An Agent-Oriented Perspective on System of Systems for Multiple Domains 187\u003cbr\u003e\u003ci\u003eAgostino G. Bruzzone, Alfredo Garro, Francesco Longo, and Marina Massei\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e9. Building Analytical Support for Homeland Security 219\u003cbr\u003e\u003ci\u003eSanjay Jain, Charles W. Hutchings, and Yung-Tsun Tina Lee\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e10. Air Transportation Systems 249\u003cbr\u003e\u003ci\u003eWilliam Crossley and Daniel DeLaurentis\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e11. Systemigram Modeling for Contextualizing Complexity in System of Systems 273\u003cbr\u003e\u003ci\u003eBrian Sauser and John Boardman\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e12. Using Modeling and Simulation for System of Systems Engineering Applications in the European Space Agency 303\u003cbr\u003e\u003ci\u003eJoachim Fuchs and Niklas Lindman\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e13. System of Systems Modeling and Simulation for Microgrids Using DDDAMS 337\u003cbr\u003e\u003ci\u003eAristotelis E. Thanos, DeLante E. Moore, Xiaoran Shi, and Nurcin Celik\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e14. Composition of Behavior Models for Systems Architecture 361\u003cbr\u003e\u003ci\u003eClifford A. Whitcomb, Mikhail Auguston, and Kristin Giammarco\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e15. Joint Training 393\u003cbr\u003e\u003ci\u003eJames Harrington, Laura Hinton, and Michael Wright\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e16. Human in the Loop in System of Systems (SoS) Modeling and Simulation: Applications to Live, Virtual, and Constructive (LVC) Distributed Mission Operations (DMO) Training 415\u003cbr\u003e\u003ci\u003eSaurabh Mittal, Margery J. Doyle, and Antoinette M. Portrey\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e17. On Analysis of Ballistic Missile Defense Architecture through Surrogate Modeling and Simulation 453\u003cbr\u003e\u003ci\u003eTommer R. Ender, Philip D. West, William Dale Blair, and Paul A. Miceli\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e18. Medical Enhancements to Sustain Life during Extreme Trauma Care 479\u003cbr\u003e\u003ci\u003eL. Drew Pihera, Nathan L. Adams, Tommer R. Ender, and Matthew L. Paden\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e19. Utility: Problem-Focused, Effects-Based Analysis (aka Information Value Chain Analysis) 515\u003cbr\u003e\u003ci\u003eThomas W. O’Brien and John F. Sarkesain\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e20. A Framework for Achieving Dynamic Cyber Effects through Distributed Cyber Command and Control\/Battle Management (C2\/BM) 531\u003cbr\u003e\u003ci\u003eJohn F. Sarkesain and Thomas W. O’Brien\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e21. System of Systems Security 565\u003cbr\u003e\u003ci\u003eBharat B. Madan\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart IV Conclusions\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e22. Toward a Research Agenda for M\u0026amp;S Support of System of Systems Engineering 583\u003cbr\u003e\u003ci\u003eAndreas Tolk and Larry B. Rainey\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eIndex 593\u003c\/p\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49406874485079,"sku":"9781118460313","price":109.76,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781118460313.jpg?v=1730497410"},{"product_id":"mathematical-and-computational-modeling-9781118853986","title":"Mathematical and Computational Modeling","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cb\u003eMathematical\u003c\/b\u003e \u003ci\u003eand\u003c\/i\u003e \u003cb\u003eComputational Modeling\u003c\/b\u003e  \u003cp\u003e\u003cb\u003eIllustrates the application of mathematical and computational modeling in a variety of disciplines\u003c\/b\u003e \u003c\/p\u003e\u003cp\u003eWith an emphasis on the interdisciplinary nature of mathematical and computational modeling, \u003ci\u003eMathematical and Computational Modeling: With Applications in the Natural and Social Sciences, Engineering, and the Arts\u003c\/i\u003e features chapters written by well-known, international experts in these fields and presents readers with a host of state-of-theart achievements in the development of mathematical modeling and computational experiment methodology. The book is a valuable guide to the methods, ideas, and tools of applied and computational mathematics as they apply to other disciplines such as the natural and social sciences, engineering, and technology. The book also features: \u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eRigorous mathematical procedures and applications as the driving force behind mathematical innovation and discovery\u003c\/li\u003e \u003cli\u003eNumerous e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eList of Contributors xiii\u003c\/p\u003e \u003cp\u003ePreface xv\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSection 1 Introduction 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Universality of Mathematical Models in Understanding Nature Society and Man-Made World 3\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eRoderick Melnik\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e1.1 Human Knowledge Models and Algorithms 3\u003c\/p\u003e \u003cp\u003e1.2 Looking into the Future from a Modeling Perspective 7\u003c\/p\u003e \u003cp\u003e1.3 What This Book Is About 10\u003c\/p\u003e \u003cp\u003e1.4 Concluding Remarks 15\u003c\/p\u003e \u003cp\u003eReferences 16\u003c\/p\u003e \u003cp\u003eSection 2 Advanced Mathematical and Computational Models in Physics and Chemistry 17\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Magnetic Vortices Abrikosov Lattices and Automorphic Functions 19\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eIsrael Michael Sigal\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction 19\u003c\/p\u003e \u003cp\u003e2.2 The Ginzburg–Landau Equations 20\u003c\/p\u003e \u003cp\u003e2.2.1 Ginzburg–Landau energy 21\u003c\/p\u003e \u003cp\u003e2.2.2 Symmetries of the equations 21\u003c\/p\u003e \u003cp\u003e2.2.3 Quantization of flux 22\u003c\/p\u003e \u003cp\u003e2.2.4 Homogeneous solutions 22\u003c\/p\u003e \u003cp\u003e2.2.5 Type I and Type II superconductors 23\u003c\/p\u003e \u003cp\u003e2.2.6 Self-dual case κ=1\/ √ 2 24\u003c\/p\u003e \u003cp\u003e2.2.7 Critical magnetic fields 24\u003c\/p\u003e \u003cp\u003e2.2.8 Time-dependent equations 25\u003c\/p\u003e \u003cp\u003e2.3 Vortices 25\u003c\/p\u003e \u003cp\u003e2.3.1 n-vortex solutions 25\u003c\/p\u003e \u003cp\u003e2.3.2 Stability 26\u003c\/p\u003e \u003cp\u003e2.4 Vortex Lattices 30\u003c\/p\u003e \u003cp\u003e2.4.1 Abrikosov lattices 31\u003c\/p\u003e \u003cp\u003e2.4.2 Existence of Abrikosov lattices 31\u003c\/p\u003e \u003cp\u003e2.4.3 Abrikosov lattices as gauge-equivariant states 34\u003c\/p\u003e \u003cp\u003e2.4.4 Abrikosov function 34\u003c\/p\u003e \u003cp\u003e2.4.5 Comments on the proofs of existence results 35\u003c\/p\u003e \u003cp\u003e2.4.6 Stability of Abrikosov lattices 40\u003c\/p\u003e \u003cp\u003e2.4.7 Functions γ δ (τ),δ \u0026gt;0 42\u003c\/p\u003e \u003cp\u003e2.4.8 Key ideas of approach to stability 45\u003c\/p\u003e \u003cp\u003e2.5 Multi-Vortex Dynamics 48\u003c\/p\u003e \u003cp\u003e2.6 Conclusions 51\u003c\/p\u003e \u003cp\u003eAppendix 2.A Parameterization of the equivalence classes [L] 51\u003c\/p\u003e \u003cp\u003eAppendix 2.B Automorphy factors 52\u003c\/p\u003e \u003cp\u003eReferences 54\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Numerical Challenges in a Cholesky-Decomposed Local Correlation Quantum Chemistry Framework 59\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eDavid B. Krisiloff, Johannes M. Dieterich, Florian Libisch and Emily A. Carter\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction 59\u003c\/p\u003e \u003cp\u003e3.2 Local MRSDCI 61\u003c\/p\u003e \u003cp\u003e3.2.1 Mrsdci 61\u003c\/p\u003e \u003cp\u003e3.2.2 Symmetric group graphical approach 62\u003c\/p\u003e \u003cp\u003e3.2.3 Local electron correlation approximation 64\u003c\/p\u003e \u003cp\u003e3.2.4 Algorithm summary 66\u003c\/p\u003e \u003cp\u003e3.3 Numerical Importance of Individual Steps 67\u003c\/p\u003e \u003cp\u003e3.4 Cholesky Decomposition 68\u003c\/p\u003e \u003cp\u003e3.5 Transformation of the Cholesky Vectors 71\u003c\/p\u003e \u003cp\u003e3.6 Two-Electron Integral Reassembly 72\u003c\/p\u003e \u003cp\u003e3.7 Integral and Execution Buffer 76\u003c\/p\u003e \u003cp\u003e3.8 Symmetric Group Graphical Approach 77\u003c\/p\u003e \u003cp\u003e3.9 Summary and Outlook 87\u003c\/p\u003e \u003cp\u003eReferences 87\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Generalized Variational Theorem in Quantum Mechanics 92\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eMel Levy and Antonios Gonis\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e4.1 Introduction 92\u003c\/p\u003e \u003cp\u003e4.2 First Proof 93\u003c\/p\u003e \u003cp\u003e4.3 Second Proof 95\u003c\/p\u003e \u003cp\u003e4.4 Conclusions 96\u003c\/p\u003e \u003cp\u003eReferences 97\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSection 3 Mathematical and Statistical Models in Life And Climate Science Applications 99\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 A Model for the Spread of Tuberculosis with Drug-Sensitive and Emerging Multidrug-Resistant and Extensively Drug-Resistant Strains 101\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eJulien Arino and Iman A. Soliman\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction 101\u003c\/p\u003e \u003cp\u003e5.1.1 Model formulation 102\u003c\/p\u003e \u003cp\u003e5.1.2 Mathematical Analysis 107\u003c\/p\u003e \u003cp\u003e5.1.2.1 Basic properties of solutions 107\u003c\/p\u003e \u003cp\u003e5.1.2.2 Nature of the disease-free equilibrium 108\u003c\/p\u003e \u003cp\u003e5.1.2.3 Local asymptotic stability of the DFE 108\u003c\/p\u003e \u003cp\u003e5.1.2.4 Existence of subthreshold endemic equilibria 110\u003c\/p\u003e \u003cp\u003e5.1.2.5 Global stability of the DFE when the bifurcation is “forward” 113\u003c\/p\u003e \u003cp\u003e5.1.2.6 Strain-specific global stability in “forward” bifurcation cases 115\u003c\/p\u003e \u003cp\u003e5.2 Discussion 117\u003c\/p\u003e \u003cp\u003eReferences 119\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 The Need for More Integrated Epidemic Modeling with Emphasis on Antibiotic Resistance 121\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eEili Y. Klein, Julia Chelen, Michael D. Makowsky and Paul E. Smaldino\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction 121\u003c\/p\u003e \u003cp\u003e6.2 Mathematical Modeling of Infectious Diseases 122\u003c\/p\u003e \u003cp\u003e6.3 Antibiotic Resistance Behavior and Mathematical Modeling 125\u003c\/p\u003e \u003cp\u003e6.3.1 Why an integrated approach? 125\u003c\/p\u003e \u003cp\u003e6.3.2 The role of symptomology 127\u003c\/p\u003e \u003cp\u003e6.4 Conclusion 128\u003c\/p\u003e \u003cp\u003eReferences 129\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSection 4 Mathematical Models and Analysis for Science and Engineering 135\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Data-Driven Methods for Dynamical Systems: Quantifying Predictability and Extracting Spatiotemporal Patterns 137\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eDimitrios Giannakis and Andrew J. Majda\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e7.1 Quantifying Long-Range Predictability and Model Error through Data Clustering and Information Theory 138\u003c\/p\u003e \u003cp\u003e7.1.1 Background 138\u003c\/p\u003e \u003cp\u003e7.1.2 Information theory predictability and model error 140\u003c\/p\u003e \u003cp\u003e7.1.2.1 Predictability in a perfect-model environment 140\u003c\/p\u003e \u003cp\u003e7.1.2.2 Quantifying the error of imperfect models 143\u003c\/p\u003e \u003cp\u003e7.1.3 Coarse-graining phase space to reveal long-range predictability 144\u003c\/p\u003e \u003cp\u003e7.1.3.1 Perfect-model scenario 144\u003c\/p\u003e \u003cp\u003e7.1.3.2 Quantifying the model error in long-range forecasts 147\u003c\/p\u003e \u003cp\u003e7.1.4 K-means clustering with persistence 149\u003c\/p\u003e \u003cp\u003e7.1.5 Demonstration in a double-gyre ocean model 152\u003c\/p\u003e \u003cp\u003e7.1.5.1 Predictability bounds for coarse-grained observables 154\u003c\/p\u003e \u003cp\u003e7.1.5.2 The physical properties of the regimes 157\u003c\/p\u003e \u003cp\u003e7.1.5.3 Markov models of regime behavior in the 1.5-layer ocean model 159\u003c\/p\u003e \u003cp\u003e7.1.5.4 The model error in long-range predictions with coarse-grained Markov models 162\u003c\/p\u003e \u003cp\u003e7.2 NLSA Algorithms for Decomposition of Spatiotemporal Data 163\u003c\/p\u003e \u003cp\u003e7.2.1 Background 163\u003c\/p\u003e \u003cp\u003e7.2.2 Mathematical framework 165\u003c\/p\u003e \u003cp\u003e7.2.2.1 Time-lagged embedding 166\u003c\/p\u003e \u003cp\u003e7.2.2.2 Overview of singular spectrum analysis 167\u003c\/p\u003e \u003cp\u003e7.2.2.3 Spaces of temporal patterns 167\u003c\/p\u003e \u003cp\u003e7.2.2.4 Discrete formulation 169\u003c\/p\u003e \u003cp\u003e7.2.2.5 Dynamics-adapted kernels 171\u003c\/p\u003e \u003cp\u003e7.2.2.6 Singular value decomposition 173\u003c\/p\u003e \u003cp\u003e7.2.2.7 Setting the truncation level 174\u003c\/p\u003e \u003cp\u003e7.2.2.8 Projection to data space 175\u003c\/p\u003e \u003cp\u003e7.2.3 Analysis of infrared brightness temperature satellite data for tropical dynamics 175\u003c\/p\u003e \u003cp\u003e7.2.3.1 Dataset description 176\u003c\/p\u003e \u003cp\u003e7.2.3.2 Modes recovered by NLSA 176\u003c\/p\u003e \u003cp\u003e7.2.3.3 Reconstruction of the TOGA COARE MJOs 183\u003c\/p\u003e \u003cp\u003e7.3 Conclusions 184\u003c\/p\u003e \u003cp\u003eReferences 185\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 On Smoothness Concepts in Regularization for Nonlinear Inverse Problems in Banach Spaces 192\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eBernd Hofmann\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction 192\u003c\/p\u003e \u003cp\u003e8.2 Model Assumptions Existence and Stability 195\u003c\/p\u003e \u003cp\u003e8.3 Convergence of Regularized Solutions 197\u003c\/p\u003e \u003cp\u003e8.4 A Powerful Tool for Obtaining Convergence Rates 200\u003c\/p\u003e \u003cp\u003e8.5 How to Obtain Variational Inequalities? 206\u003c\/p\u003e \u003cp\u003e8.5.1 Bregman distance as error measure: the benchmark case 206\u003c\/p\u003e \u003cp\u003e8.5.2 Bregman distance as error measure: violating the benchmark 210\u003c\/p\u003e \u003cp\u003e8.5.3 Norm distance as error measure: l 1 -regularization 213\u003c\/p\u003e \u003cp\u003e8.6 Summary 215\u003c\/p\u003e \u003cp\u003eReferences 215\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Initial and Initial-Boundary Value Problems for First-Order Symmetric Hyperbolic Systems with Constraints 222\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eNicolae Tarfulea\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction 222\u003c\/p\u003e \u003cp\u003e9.2 FOSH Initial Value Problems with Constraints 223\u003c\/p\u003e \u003cp\u003e9.2.1 FOSH initial value problems 224\u003c\/p\u003e \u003cp\u003e9.2.2 Abstract formulation 225\u003c\/p\u003e \u003cp\u003e9.2.3 FOSH initial value problems with constraints 228\u003c\/p\u003e \u003cp\u003e9.3 FOSH Initial-Boundary Value Problems with Constraints 230\u003c\/p\u003e \u003cp\u003e9.3.1 FOSH initial-boundary value problems 232\u003c\/p\u003e \u003cp\u003e9.3.2 FOSH initial-boundary value problems with constraints 234\u003c\/p\u003e \u003cp\u003e9.4 Applications 236\u003c\/p\u003e \u003cp\u003e9.4.1 System of wave equations with constraints 237\u003c\/p\u003e \u003cp\u003e9.4.2 Applications to Einstein’s equations 240\u003c\/p\u003e \u003cp\u003e9.4.2.1 Einstein–Christoffel formulation 243\u003c\/p\u003e \u003cp\u003e9.4.2.2 Alekseenko–Arnold formulation 246\u003c\/p\u003e \u003cp\u003eReferences 250\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Information Integration Organization and Numerical Harmonic Analysis 254\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eRonald R. Coifman, Ronen Talmon, Matan Gavish and Ali Haddad\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e10.1 Introduction 254\u003c\/p\u003e \u003cp\u003e10.2 Empirical Intrinsic Geometry 257\u003c\/p\u003e \u003cp\u003e10.2.1 Manifold formulation 259\u003c\/p\u003e \u003cp\u003e10.2.2 Mahalanobis distance 261\u003c\/p\u003e \u003cp\u003e10.3 Organization and Harmonic Analysis of Databases\/Matrices 263\u003c\/p\u003e \u003cp\u003e10.3.1 Haar bases 264\u003c\/p\u003e \u003cp\u003e10.3.2 Coupled partition trees 265\u003c\/p\u003e \u003cp\u003e10.4 Summary 269\u003c\/p\u003e \u003cp\u003eReferences 270\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSection 5 Mathematical Methods in Social Sciences And Arts 273\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Satisfaction Approval Voting 275\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eSteven J. Brams and D. Marc Kilgour\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e11.1 Introduction 275\u003c\/p\u003e \u003cp\u003e11.2 Satisfaction Approval Voting for Individual Candidates 277\u003c\/p\u003e \u003cp\u003e11.3 The Game Theory Society Election 285\u003c\/p\u003e \u003cp\u003e11.4 Voting for Multiple Candidates under SAV: A Decision-Theoretic Analysis 287\u003c\/p\u003e \u003cp\u003e11.5 Voting for Political Parties 291\u003c\/p\u003e \u003cp\u003e11.5.1 Bullet voting 291\u003c\/p\u003e \u003cp\u003e11.5.2 Formalization 292\u003c\/p\u003e \u003cp\u003e11.5.3 Multiple-party voting 294\u003c\/p\u003e \u003cp\u003e11.6 Conclusions 295\u003c\/p\u003e \u003cp\u003e11.7 Summary 296\u003c\/p\u003e \u003cp\u003eReferences 297\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Modeling Musical Rhythm Mutations with Geometric Quantization 299\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eGodfried T. Toussaint\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e12.1 Introduction 299\u003c\/p\u003e \u003cp\u003e12.2 Rhythm Mutations 301\u003c\/p\u003e \u003cp\u003e12.2.1 Musicological rhythm mutations 301\u003c\/p\u003e \u003cp\u003e12.2.2 Geometric rhythm mutations 302\u003c\/p\u003e \u003cp\u003e12.3 Similarity-Based Rhythm Mutations 303\u003c\/p\u003e \u003cp\u003e12.3.1 Global rhythm similarity measures 304\u003c\/p\u003e \u003cp\u003e12.4 Conclusion 306\u003c\/p\u003e \u003cp\u003eReferences 307\u003c\/p\u003e \u003cp\u003eIndex 309\u003c\/p\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49406935302487,"sku":"9781118853986","price":78.26,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781118853986.jpg?v=1730497611"},{"product_id":"principles-of-objectoriented-modeling-and-simulation-with-modelica-3-3-9781118859124","title":"Principles of ObjectOriented Modeling and","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eFritzson covers the Modelica language in impressive depth from the basic concepts such as cyber-physical, equation-base, object-oriented, system, model, and simulation, while also incorporating over a hundred exercises and their solutions for a tutorial, easy-to-read experience.\u003cbr\u003e\u003cbr\u003e \u003cul\u003e \u003cli\u003eThe only book with complete Modelica 3.3 coverage\u003c\/li\u003e \u003cli\u003eOver one hundred exercises and solutions\u003c\/li\u003e \u003cli\u003eExamines basic concepts such as cyber-physical, equation-based, object-oriented, system, model, and simulation\u003c\/li\u003e \u003c\/ul\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003ePreface v\u003c\/p\u003e \u003cp\u003eAbout the Author v\u003c\/p\u003e \u003cp\u003eAbout this Book v\u003c\/p\u003e \u003cp\u003eReading Guide vi\u003c\/p\u003e \u003cp\u003eAcknowledgements vii\u003c\/p\u003e \u003cp\u003eContributions to Examples ix\u003c\/p\u003e \u003cp\u003eContributors to the Modelica Standard Library, Version 3.2.1 xii\u003c\/p\u003e \u003cp\u003eContributors to the Modelica Standard Library, Versions 1.0 to 2.1 xiii\u003c\/p\u003e \u003cp\u003eContributors to the Modelica Language, Version 3.3 xiii\u003c\/p\u003e \u003cp\u003eContributors to the Modelica Language, Version 3.2 xiv\u003c\/p\u003e \u003cp\u003eContributors to the Modelica Language, Version 3.0 xv\u003c\/p\u003e \u003cp\u003eContributors to the Modelica Language, Version 2.0 xvi\u003c\/p\u003e \u003cp\u003eContributors to the Modelica Language, up to Version 1.3 xvi\u003c\/p\u003e \u003cp\u003eModelica Association Member Companies and Organizations 2013 xvii\u003c\/p\u003e \u003cp\u003eFunding Contributions xviii\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart I Introduction 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eChapter 1 Introduction to Modeling and Simulation 3\u003c\/p\u003e \u003cp\u003eChapter 2 A Quick Tour of Modelica 19\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart II The Modelica Language 79\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eChapter 3 Classes, Types, Declarations, and Lookup 81\u003c\/p\u003e \u003cp\u003eChapter 4 Inheritance, Modifications, and Generics 137\u003c\/p\u003e \u003cp\u003eChapter 5 Components, Connectors, and Connections 189\u003c\/p\u003e \u003cp\u003eChapter 6 Literals, Operators, and Expressions 269\u003c\/p\u003e \u003cp\u003eChapter 7 Arrays 313\u003c\/p\u003e \u003cp\u003eChapter 8 Equations 349\u003c\/p\u003e \u003cp\u003eChapter 9 Algorithms and Functions 423\u003c\/p\u003e \u003cp\u003eChapter 10 Packages 497\u003c\/p\u003e \u003cp\u003eChapter 11 Annotations, Units, and Quantities 521\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart III Modeling and Applications 567\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eChapter 12 Cyber-Physical System Modeling Methodology 569\u003c\/p\u003e \u003cp\u003eChapter 13 Discrete Events, Hybrid and Embedded System Modeling 593\u003c\/p\u003e \u003cp\u003eChapter 14 Basic Laws of Nature 747\u003c\/p\u003e \u003cp\u003eChapter 15 Application Examples 795\u003c\/p\u003e \u003cp\u003eChapter 16 Modelica Library Overview 909\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart IV Technology and Tools 977\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eChapter 17 A Mathematical Representation for Modelica Models 979\u003c\/p\u003e \u003cp\u003eChapter 18 Techniques and Research 993\u003c\/p\u003e \u003cp\u003eChapter 19 Environments 1029\u003c\/p\u003e \u003cp\u003eAppendix A Glossary 1063\u003c\/p\u003e \u003cp\u003eAppendix B Modelica Formal Syntax 1071\u003c\/p\u003e \u003cp\u003eAppendix C Solutions to Exercises 1083\u003c\/p\u003e \u003cp\u003eAppendix D Modelica Standard Library Samples 1093\u003c\/p\u003e \u003cp\u003eAppendix E Modelica and Python Scripting 1123\u003c\/p\u003e \u003cp\u003eAppendix F Related Equation-Based Object Oriented Modeling Languages 1153\u003c\/p\u003e \u003cp\u003eAppendix G FMI – Functional Mockup Interface 1163\u003c\/p\u003e \u003cp\u003eG.1 Summary 1163\u003c\/p\u003e \u003cp\u003eG.2 Overview 1164\u003c\/p\u003e \u003cp\u003eG.3 FMI for Model Exchange 1168\u003c\/p\u003e \u003cp\u003eG.4 FMI for Co-Simulation 1169\u003c\/p\u003e \u003cp\u003eG.5 Literature 1172\u003c\/p\u003e \u003cp\u003eReferences 1175\u003c\/p\u003e \u003cp\u003eIndex 1197\u003c\/p\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49406936318295,"sku":"9781118859124","price":102.56,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781118859124.jpg?v=1730497614"},{"product_id":"atomistic-simulations-of-glasses-9781118939062","title":"Atomistic Simulations of Glasses","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eThis book is the first introduction\/reference to the computer simulation of glass materials, which are growing in their applications such as telephone technology, construction materials, aerospace materials and more.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eModeling and simulation are crucial for understanding structure-property relationships in glass-forming systems and for accelerating the design of next-generation glassy materials. \u003ci\u003eAtomistic Simulations of Glasses\u003c\/i\u003e is a comprehensive volume dedicated to the topic of atomic-scale modeling of glassy materials, with particular emphasis on silicate glasses of practical industrial interest. As such, this book fills a critical gap in the literature, offering an excellent introduction for newcomers to atomistic modeling, as well as a comprehensive and state-of-the-art reference for practitioners in the field.\u003c\/p\u003e \u003cp\u003e\u003ci\u003eAtomistic Simulations of Glasses\u003c\/i\u003e, published by ACerS-Wiley, consists of 15 chapters written by experts from around the world. It is edited by two leading authorities in computational glass science: Jincheng Du (University of North Texas) and Alastair N. Cormack (Alfred University). The book itself is gorgeous, printed in full color on high-quality paper. It is designed in a reader-friendly format, including a comprehensive index, an extensive list of references at the end of each chapter, and a helpful table to decode every acronym used throughout the book. Each chapter is well written and has been carefully polished. The text also flows smoothly across chapters, which is sometimes a problem in edited volumes.\u003c\/p\u003e \u003cp\u003eThe first five chapters are devoted to fundamentals of atomistic modeling techniques for glassy systems, including classical simulation methods (Chapter 1), quantum mechanical techniques (Chapter 2), reverse Monte Carlo (Chapter 3), structural analysis methods (Chapter 4), and topological constraint theory (Chapter 5). Each of these chapters does a great job at providing both foundational knowledge and discussing the state-of-the-art in methods and tools. The chapter on topological constraint theory is especially interesting because this is a family of techniques developed specifically for glassy materials.\u003c\/p\u003e \u003cp\u003eThe latter 10 chapters of the book focus on application of these techniques for simulating various glass families of interest. These chapters cover a wide range of silicate, aluminosilicate, and borosilicate glasses, as well as phosphate, fluoride, and oxyfluoride systems. The coverage of transition metal and rare-earth-containing glasses is also a nice touch. There is a particular emphasis on bioactive glasses and glasses for nuclear waste immobilization. As a whole, the 10 application-focused chapters do an excellent job demonstrating the utility and versatility of atomistic simulation approaches for addressing problems of practical concern in the glass science and engineering community. These chapters also provide good perspective on specific needs for future developments in the field.\u003c\/p\u003e \u003cp\u003eThere are a few missing topics that would have been valuable to include in the book. While reactive force fields are mentioned briefly, an entire chapter devoted to the principles and applications of reactive force fields such as ReaxFF would have been a nice addition, especially because reactive force fields are becoming increasingly important in the glass science community. Also, given the importance of thermal history in governing the structure and properties of glasses, it would have been worthwhile to include a chapter on accessing long time scales, e.g., using kinetic Monte Carlo, meta-dynamics, or the activation-relaxation technique, all of which have been applied to noncrystalline systems in the literature and can enable simulations to access experimental time scales. It also would have been helpful to expand the chapter on reverse Monte Carlo to include other Monte Carlo techniques more broadly; for example, Metropolis Monte Carlo is a computationally efficient alternative to molecular dynamics for calculating glass structure and static properties. Finally, given the large amount of research activity in modeling of metallic glasses, a chapter on atomistic simulations of metallic glasses would be a nice addition.\u003c\/p\u003e \u003cp\u003eOverall, \u003ci\u003eAtomistic Simulations of Glasses\u003c\/i\u003e is a very welcome addition to the literature and highly recommended for both students and professionals in the field of computational glass science.\u003cbr\u003e—\u003cb\u003eJohn C. Mauro is a Dorothy Pate Enright Professor in the Department of Materials Science and Engineering at The Pennsylvania State University\u003c\/b\u003e\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003ePreface\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart I Fundamentals of Atomistic Simulations\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 1 Classical simulation methods \u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eAbstract\u003c\/p\u003e \u003cp\u003e1.1 Introduction\u003c\/p\u003e \u003cp\u003e1.2 Simulation techniques\u003c\/p\u003e \u003cp\u003e1.2.1 Molecular dynamics (MD)\u003c\/p\u003e \u003cp\u003e1.2.1.1 Integrating the equations of motion\u003c\/p\u003e \u003cp\u003e1.2.1.2 Thermostats and barostats\u003c\/p\u003e \u003cp\u003e1.2.2 Monte Carlo (MC) eimulations\u003c\/p\u003e \u003cp\u003e1.2.2.1 Kinetic Monte Carlo\u003c\/p\u003e \u003cp\u003e1.2.2.2 Reverse Monte Carlo\u003c\/p\u003e \u003cp\u003e1.3 The Born Model\u003c\/p\u003e \u003cp\u003e1.3.1 Ewald summation\u003c\/p\u003e \u003cp\u003e1.3.2 Potentials\u003c\/p\u003e \u003cp\u003e1.3.2.1 Transferability of potential parameters: Self-consistent sets\u003c\/p\u003e \u003cp\u003e1.3.2.2 Ion polarizability\u003c\/p\u003e \u003cp\u003e1.3.2.3 Potential models for borates\u003c\/p\u003e \u003cp\u003e1.3.2.4 Modelling reactivity: electron transfer\u003c\/p\u003e \u003cp\u003e1.4 Calculation of Observables\u003c\/p\u003e \u003cp\u003e1.4.1 Atomic structure\u003c\/p\u003e \u003cp\u003e1.4.2 Hyperdynamics and peridynamics\u003c\/p\u003e \u003cp\u003e1.5 Glass Formation\u003c\/p\u003e \u003cp\u003e1.5.1 Bulk structures\u003c\/p\u003e \u003cp\u003e1.5.2 Surfaces and fibers\u003c\/p\u003e \u003cp\u003e1.6 Geometry optimization and property calculations\u003c\/p\u003e \u003cp\u003e1.7 References\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 2 Ab initio simulation of amorphous solids \u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eAbstract\u003c\/p\u003e \u003cp\u003e2.1 Introduction\u003c\/p\u003e \u003cp\u003e2.1.1 Big picture\u003c\/p\u003e \u003cp\u003e2.1.2 The limits of experiment\u003c\/p\u003e \u003cp\u003e2.1.3 Synergy between experiment and modeling\u003c\/p\u003e \u003cp\u003e2.1.4 History of simulations and the need for ab initio methods\u003c\/p\u003e \u003cp\u003e2.1.5 The difference between ab initio and classical MD\u003c\/p\u003e \u003cp\u003e2.1.6 Ingredients of DFT\u003c\/p\u003e \u003cp\u003e2.1.7 What DFT can provide\u003c\/p\u003e \u003cp\u003e2.1.8 The emerging solution for large systems and long times: Machine Learning\u003c\/p\u003e \u003cp\u003e2.1.9 A practical aid: Databases\u003c\/p\u003e \u003cp\u003e2.2 Methods to produce models\u003c\/p\u003e \u003cp\u003e2.2.1 Simulation Paradigm: Melt Quench\u003c\/p\u003e \u003cp\u003e2.2.2 Information Paradigm\u003c\/p\u003e \u003cp\u003e2.2.3 Teaching chemistry to RMC: FEAR\u003c\/p\u003e \u003cp\u003e2.2.4 Gap Sculpting\u003c\/p\u003e \u003cp\u003e2.3 Analyzing the models\u003c\/p\u003e \u003cp\u003e2.3.1 Structure\u003c\/p\u003e \u003cp\u003e2.3.2 Electronic Structure\u003c\/p\u003e \u003cp\u003e2.3.3 Vibrational Properties\u003c\/p\u003e \u003cp\u003e2.4 Conclusion\u003c\/p\u003e \u003cp\u003e2.5 Acknowledgements\u003c\/p\u003e \u003cp\u003e2.6 References\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 3 Reverse Monte Carlo simulations of non-crystalline solids \u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eAbstract\u003c\/p\u003e \u003cp\u003e3.1 Introduction -- why RMC is needed?\u003c\/p\u003e \u003cp\u003e3.2 Reverse Monte Carlo modeling\u003c\/p\u003e \u003cp\u003e3.2.1. Basic RMC algorithm\u003c\/p\u003e \u003cp\u003e3.2.2. Information deficiency\u003c\/p\u003e \u003cp\u003e3.2.3. Preparation of reference structures: hard sphere Monte Carlo\u003c\/p\u003e \u003cp\u003e3.2.4. Other methods for preparing suitable structural models\u003c\/p\u003e \u003cp\u003e3.3 Topological analyses\u003c\/p\u003e \u003cp\u003e 3.3.1. Ring statistics\u003c\/p\u003e \u003cp\u003e 3.3.2. Cavity analyses\u003c\/p\u003e \u003cp\u003e 3.3.3. Persistent homology analyses\u003c\/p\u003e \u003cp\u003e3.4 Applications\u003c\/p\u003e \u003cp\u003e3.4.1 Single component liquid and amorphous materials\u003c\/p\u003e \u003cp\u003e3.4.1.1 l-Si and a-Si\u003c\/p\u003e \u003cp\u003e3.4.1.2 l-P under high pressure and high temperature\u003c\/p\u003e \u003cp\u003e3.4.2 Oxide glasses\u003c\/p\u003e \u003cp\u003e3.4.2.1 SiO2 glass\u003c\/p\u003e \u003cp\u003e3.4.2.2 R2O-SiO2 glasses (R=Na, K)\u003c\/p\u003e \u003cp\u003e3.4.2.3 CaO-Al2O3 glass\u003c\/p\u003e \u003cp\u003e3.4.3 Chalcogenide glasses\u003c\/p\u003e \u003cp\u003e3.4.4 Metallic glasses\u003c\/p\u003e \u003cp\u003e3.5 Summary\u003c\/p\u003e \u003cp\u003e3.6 Acknowledgments\u003c\/p\u003e \u003cp\u003e3.7 References\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 4 Structure analysis and property calculations \u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eabstract\u003c\/p\u003e \u003cp\u003e4.1 Introduction\u003c\/p\u003e \u003cp\u003e4.2 Structure Analysis\u003c\/p\u003e \u003cp\u003e4.2.1 Salient features of glass structures\u003c\/p\u003e \u003cp\u003e4.2.2 Classification of the range order.\u003c\/p\u003e \u003cp\u003e4.3 Real Space Correlation functions.Spectroscopic properties: validating the structural models\u003c\/p\u003e \u003cp\u003e4.3.1 X-ray and Neutron diffraction spectra\u003c\/p\u003e \u003cp\u003e4.3.2 Vibrational spectra\u003c\/p\u003e \u003cp\u003e4.3.3 NMR spectra\u003c\/p\u003e \u003cp\u003e4.4 Transport properties\u003c\/p\u003e \u003cp\u003e4.4.1 Diffusion coefficient and diffusion activation energy\u003c\/p\u003e \u003cp\u003e4.4.2 Viscosity\u003c\/p\u003e \u003cp\u003e4.4.3 Thermal conductivity\u003c\/p\u003e \u003cp\u003e4.5 Mechanical Properties\u003c\/p\u003e \u003cp\u003e4.5.1 Elastic constants\u003c\/p\u003e \u003cp\u003e4.5.2 Stress-strain diagrams and fracture mechanism\u003c\/p\u003e \u003cp\u003e4.6 Concluding remarks\u003c\/p\u003e \u003cp\u003e4.7 References\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 5 Topological constraint theory of glass: counting constraints by molecular dynamics simulations \u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eAbstract\u003c\/p\u003e \u003cp\u003e5.1 Introduction\u003c\/p\u003e \u003cp\u003e5.2 Background and topological constraint theory\u003c\/p\u003e \u003cp\u003e5.2.1 Rigidity of mechanical networks\u003c\/p\u003e \u003cp\u003e5.2.2 Application to atomic networks\u003c\/p\u003e \u003cp\u003e5.2.3 Constraint enumeration under mean-field approximation\u003c\/p\u003e \u003cp\u003e5.2.4 Polytope-based description of glass rigidity\u003c\/p\u003e \u003cp\u003e5.2.5 Impact of temperature\u003c\/p\u003e \u003cp\u003e5.2.6 Need for molecular dynamics simulations\u003c\/p\u003e \u003cp\u003e5.3 Counting constraints from molecular dynamics simulations\u003c\/p\u003e \u003cp\u003e5.3.1 Constraint enumeration based on the relative motion between atoms\u003c\/p\u003e \u003cp\u003e5.3.2 Computation of the internal stress\u003c\/p\u003e \u003cp\u003e5.3.3 Computation of the floppy modes\u003c\/p\u003e \u003cp\u003e5.3.5 Dynamical matrix analysis\u003c\/p\u003e \u003cp\u003e5.4 Conclusions\u003c\/p\u003e \u003cp\u003e5.5 References\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart II Applications of Atomistic Simulations in Glass Research\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 6 History of atomistic simulations of glasses \u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eAbstract\u003c\/p\u003e \u003cp\u003e6.1 Introduction\u003c\/p\u003e \u003cp\u003e6.2 Simulation techniques\u003c\/p\u003e \u003cp\u003e6.2.1 Monte Carlo techniques\u003c\/p\u003e \u003cp\u003e6.2.2 Molecular dynamics\u003c\/p\u003e \u003cp\u003e6.3 Classical simulations: interatomic potentials\u003c\/p\u003e \u003cp\u003e6.3.1 Potential models for silica\u003c\/p\u003e \u003cp\u003e 6.3.1.1 Silica: quantum mechanical simulations\u003c\/p\u003e \u003cp\u003e6.3.2 Modified silicates and aluminosilicates\u003c\/p\u003e \u003cp\u003e6.3.3 Borate glasses\u003c\/p\u003e \u003cp\u003e 6.3.3.1 Borates: quantum mechanical simulations\u003c\/p\u003e \u003cp\u003e6.4 Simulation of surfaces\u003c\/p\u003e \u003cp\u003e6.5 Computer science and engineering\u003c\/p\u003e \u003cp\u003e6.6.1 Software\u003c\/p\u003e \u003cp\u003e6.6.2 Hardware\u003c\/p\u003e \u003cp\u003e6.6 References\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 7 Silica and silicate glasses\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eAbstract\u003c\/p\u003e \u003cp\u003e7.1 Introduction\u003c\/p\u003e \u003cp\u003e7.2 Atomistic simulations of silicate glasses: ingredients and critical aspects\u003c\/p\u003e \u003cp\u003e7.3 Characterization and experimental validation of structural and dynamic features of simulated glasses\u003c\/p\u003e \u003cp\u003e7.3.1 Structural characterizations\u003c\/p\u003e \u003cp\u003e7.3.2 Dynamic properties of simulated glasses\u003c\/p\u003e \u003cp\u003e7.3.3 Validation and experimental confirmation of structural and dynamic properties\u003c\/p\u003e \u003cp\u003e7.3.3.1 Diffraction methods\u003c\/p\u003e \u003cp\u003e7.3.3.2 Nuclear Magnetic Resonance\u003c\/p\u003e \u003cp\u003e7.3.3.3 Vibrational spectral characterization\u003c\/p\u003e \u003cp\u003e7.4 MD simulations of silica glasses\u003c\/p\u003e \u003cp\u003e7.5 MD simulations of alkali silicate and alkali earth silicate glasses\u003c\/p\u003e \u003cp\u003e7.5.1 Local environments and distribution of alkali ions\u003c\/p\u003e \u003cp\u003e7.5.2 The mixed alkali effect\u003c\/p\u003e \u003cp\u003e7.6 MD simulations of aluminosilicate glasses\u003c\/p\u003e \u003cp\u003e7.7 MD simulations of nanoporous silica and silicate glasses\u003c\/p\u003e \u003cp\u003e7.8 AIMD simulations of silica and silicate glasses\u003c\/p\u003e \u003cp\u003e7.9 Summary and Outlook\u003c\/p\u003e \u003cp\u003eAcknowledgements\u003c\/p\u003e \u003cp\u003eReferences\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 8 Borosilicate and boroaluminosilicate glasses \u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 Abstract\u003c\/p\u003e \u003cp\u003e8.2 Introduction\u003c\/p\u003e \u003cp\u003e8.3 Experimental determination and theoretical models of boron N4 values in borosilicate glass\u003c\/p\u003e \u003cp\u003e8.3.1 Experimental results on boron coordination number\u003c\/p\u003e \u003cp\u003e8.3.2 Theoretical models in predicting boron N4 value\u003c\/p\u003e \u003cp\u003e8.4 ab initio versus classical MD simulations of borosilicate glasses\u003c\/p\u003e \u003cp\u003e8.5 Empirical potentials for borate and borosilicate glasses\u003c\/p\u003e \u003cp\u003e8.5.1 Recent development of rigid ion potentials for borosilicate glasses\u003c\/p\u003e \u003cp\u003e8.5.2 Development of polarizable potentials for borate and borosilicate glasses\u003c\/p\u003e \u003cp\u003e8.6 Evaluation of the potentials\u003c\/p\u003e \u003cp\u003e8.7 Effects of cooling rate and system size on simulated borosilicate glass structures\u003c\/p\u003e \u003cp\u003e8.8 Applications of MD simulations of borosilicate glasses\u003c\/p\u003e \u003cp\u003e8.8.1 Borosilicate glass\u003c\/p\u003e \u003cp\u003e8.8.2 Boroaluminosilicate glasses\u003c\/p\u003e \u003cp\u003e8.8.3 Boron oxide-containing multi-component glass\u003c\/p\u003e \u003cp\u003e8.9 Conclusions\u003c\/p\u003e \u003cp\u003e8.10 Appendix: Available empirical potentials for boron-containing systems\u003c\/p\u003e \u003cp\u003e8.10.1 Borosilicate and boroaluminosilicate potentials-Kieu et al and Deng\u0026amp;Du\u003c\/p\u003e \u003cp\u003e8.10.2 Borosilicate potential- Wang et al\u003c\/p\u003e \u003cp\u003e8.10.3 Borosilicate potential-Inoue et al\u003c\/p\u003e \u003cp\u003e8.10.4 Boroaluminosilicate potential-Ha and Garofalini\u003c\/p\u003e \u003cp\u003e8.10.5 Borosilicate and boron-containing oxide glass potential-Deng and Du\u003c\/p\u003e \u003cp\u003e8.10.6 Borate, boroaluminate and borosilicate potential-Sundararaman et al\u003c\/p\u003e \u003cp\u003e8.10.7 Borate and borosilicate polarizable potential-Yu et al\u003c\/p\u003e \u003cp\u003e8.10 Acknowledgements\u003c\/p\u003e \u003cp\u003e8.11 References\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 9 Nuclear waste glasses \u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1 Preamble\u003c\/p\u003e \u003cp\u003e9.2 Introduction to French nuclear glass\u003c\/p\u003e \u003cp\u003e9.2.1 Chemical composition\u003c\/p\u003e \u003cp\u003e9.2.2 About the long term behavior (irradiation, glass alteration, He accumulation)\u003c\/p\u003e \u003cp\u003e9.2.3 What can atomistic simulations contribute?\u003c\/p\u003e \u003cp\u003e9.3 Computational methodology\u003c\/p\u003e \u003cp\u003e9.3.1 Review of existing classical potentials for borosilicate glasses\u003c\/p\u003e \u003cp\u003e9.3.2 Preparation of a glass\u003c\/p\u003e \u003cp\u003e9.3.3 Displacement cascade simulations\u003c\/p\u003e \u003cp\u003e9.3.4 Short bibliography about simplified nuclear glass structure studies\u003c\/p\u003e \u003cp\u003e9.4 Simulation of radiation effects in simplified nuclear glasses\u003c\/p\u003e \u003cp\u003e9.4.1 Accumulation of displacement cascades and the thermal quench model\u003c\/p\u003e \u003cp\u003e9.4.2 Preparation of disordered and depolymerized glasses\u003c\/p\u003e \u003cp\u003e9.4.3 Origin of the hardness change under irradiation\u003c\/p\u003e \u003cp\u003e9.4.4 Origin of the fracture toughness change under irradiation\u003c\/p\u003e \u003cp\u003e9.5 Simulation of glass alteration by water\u003c\/p\u003e \u003cp\u003e9.5.1 Contribution from ab initio calculations\u003c\/p\u003e \u003cp\u003e9.5.2 Contribution from Monte Carlo simulations\u003c\/p\u003e \u003cp\u003e9.6 Gas incorporation: radiation effects on He solubility\u003c\/p\u003e \u003cp\u003e9.6.1 Solubility model\u003c\/p\u003e \u003cp\u003e9.6.2 Interstitial sites in SiO2-B2O3-Na2O glasses\u003c\/p\u003e \u003cp\u003e9.6.3 Discussion about He solubility in relation to the radiation effects\u003c\/p\u003e \u003cp\u003e9.7 Conclusions\u003c\/p\u003e \u003cp\u003e9.8 Acknowledgements\u003c\/p\u003e \u003cp\u003e9.9 References\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 10 Phosphate glasses \u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e Abstract\u003c\/p\u003e \u003cp\u003e10.1 Introduction to phosphate glasses\u003c\/p\u003e \u003cp\u003e10.1.1 Applications of phosphate glasses\u003c\/p\u003e \u003cp\u003e10.1.2 Synthesis of phosphate glasses\u003c\/p\u003e \u003cp\u003e10.1.3 The modified random network model applied to phosphate glasses\u003c\/p\u003e \u003cp\u003e10.1.4 The tetrahedral phosphate glass network\u003c\/p\u003e \u003cp\u003e10.1.5 Modifier cations in phosphate glasses\u003c\/p\u003e \u003cp\u003e10.2 Modelling methods for phosphate glasses\u003c\/p\u003e \u003cp\u003e10.2.1 Configurations of atomic coordinates\u003c\/p\u003e \u003cp\u003e10.2.2 Molecular modelling versus reverse Monte Carlo modelling\u003c\/p\u003e \u003cp\u003e10.2.3 Classical vs. ab initio molecular modelling\u003c\/p\u003e \u003cp\u003e10.2.4 Evaluating the simulation of interatomic interactions\u003c\/p\u003e \u003cp\u003e10.2.5 Evaluating models of glasses by comparison with experimental data\u003c\/p\u003e \u003cp\u003e10.3 Modelling pure vitreous P2O5\u003c\/p\u003e \u003cp\u003e10.3.1 Modelling of crystalline P2O5\u003c\/p\u003e \u003cp\u003e10.3.2 Modelling of vitreous P2O5\u003c\/p\u003e \u003cp\u003e10.3.3 Cluster models of vitreous P2O5\u003c\/p\u003e \u003cp\u003e10.4 Modelling phosphate glasses with monovalent cations\u003c\/p\u003e \u003cp\u003e10.4.1 Modelling lithium phosphate glasses\u003c\/p\u003e \u003cp\u003e10.4.2 Modelling sodium phosphate glasses\u003c\/p\u003e \u003cp\u003e10.4.3 Modelling phosphate glasses with other monovalent cations\u003c\/p\u003e \u003cp\u003e10.4.4 Modelling phosphate glasses with monovalent cations and addition of halides\u003c\/p\u003e \u003cp\u003e10.4.5 Cluster models of alkali phosphate glasses\u003c\/p\u003e \u003cp\u003e10.5 Modelling phosphate glasses with divalent cations\u003c\/p\u003e \u003cp\u003e10.5.1 Modelling zinc phosphate glasses\u003c\/p\u003e \u003cp\u003e10.5.2 Modelling zinc phosphate glasses with additional cations\u003c\/p\u003e \u003cp\u003e10.5.3 Modelling alkaline earth phosphate glasses\u003c\/p\u003e \u003cp\u003e10.5.4 Modelling lead phosphate glasses\u003c\/p\u003e \u003cp\u003e10.6 Modelling phosphate based glasses for biomaterials applications\u003c\/p\u003e \u003cp\u003e10.6.1 Modelling Na2O-CaO-P2O5 glasses with 45 mol% P2O5\u003c\/p\u003e \u003cp\u003e10.6.2 Modelling Na2O-CaO-P2O5 glasses with 50 mol% P2O5\u003c\/p\u003e \u003cp\u003e10.6.3 Modelling Na2O-CaO-P2O5 glasses with additional cations\u003c\/p\u003e \u003cp\u003e10.7 Modelling phosphate glasses with trivalent cations\u003c\/p\u003e \u003cp\u003e10.7.1 Modelling iron phosphate glasses\u003c\/p\u003e \u003cp\u003e10.7.2 Cluster models of iron phosphate glasses\u003c\/p\u003e \u003cp\u003e10.7.3 Modelling trivalent rare earth phosphate glasses\u003c\/p\u003e \u003cp\u003e10.7.4 Modelling aluminophosphate glasses\u003c\/p\u003e \u003cp\u003e10.8 Modelling phosphate glasses with tetravalent and pentavalent cations\u003c\/p\u003e \u003cp\u003e10.9 Modelling phosphate glasses with mixed network formers\u003c\/p\u003e \u003cp\u003e10.9.1 Modelling borophosphate glasses\u003c\/p\u003e \u003cp\u003e10.9.2 Modelling phosphosilicate glasses\u003c\/p\u003e \u003cp\u003e10.10 Modelling bioglass 45S and related glasses\u003c\/p\u003e \u003cp\u003e10.10.1 Modelling bioglass 45S and related glasses from the same system\u003c\/p\u003e \u003cp\u003e10.10.2 Modelling bioglass 45S and related glasses with additional components\u003c\/p\u003e \u003cp\u003e10.11 Summary\u003c\/p\u003e \u003cp\u003e10.12 References\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 11 Bioactive glasses \u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eAbstract\u003c\/p\u003e \u003cp\u003e11.1 Introduction\u003c\/p\u003e \u003cp\u003e11.2 Methodology\u003c\/p\u003e \u003cp\u003e11.3 Development of interatomic potentials\u003c\/p\u003e \u003cp\u003e11.4 Structure of 45S5 Bioglass\u003c\/p\u003e \u003cp\u003e11.5 Inclusion of ions into bioactive glass and the effect on structure and bioactivity\u003c\/p\u003e \u003cp\u003e11.6 Glass nanoparticles and surfaces\u003c\/p\u003e \u003cp\u003e11.7 Discussion and future work\u003c\/p\u003e \u003cp\u003eBibliography\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 12 Rare earth and transition metal containing glasses \u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e Abstract\u003c\/p\u003e \u003cp\u003e12.1 Introduction\u003c\/p\u003e \u003cp\u003e12.1.1 Transition metal and rare earth oxides in glasses: importance and potential applications\u003c\/p\u003e \u003cp\u003e12.1.2 Effects of local structures and clustering behaviors of RE and TM ions on properties\u003c\/p\u003e \u003cp\u003e12.1.3 Redox reaction and multioxidation states of TM and RE ions\u003c\/p\u003e \u003cp\u003e12.1.4 Effect of composition on multioxidation states in glasses containing TM\u003c\/p\u003e \u003cp\u003e12.1.5 The role of MD in investigating TM and RE containing glasses\u003c\/p\u003e \u003cp\u003e12.2 Simulation methodologies\u003c\/p\u003e \u003cp\u003e12.2.1 Interatomic potentials and glass simulations\u003c\/p\u003e \u003cp\u003e12.2.2 Cation environment and clustering analysis\u003c\/p\u003e \u003cp\u003e12.2.3 Diffusion and dynamic property calculations\u003c\/p\u003e \u003cp\u003e12.2.4 Electronic structure calculations\u003c\/p\u003e \u003cp\u003e12.3 Case studies of MD simulations of RE and TM containing glasses\u003c\/p\u003e \u003cp\u003e12.3.1 Rare earth doped silicate and aluminophosphate glasses for optical applications\u003c\/p\u003e \u003cp\u003e12.3.1.1 Erbium doped silica and silicate glasses: from melt-quench to ion implantation\u003c\/p\u003e \u003cp\u003e12.3.1.2 Europium and praseodymium doped silicate glasses\u003c\/p\u003e \u003cp\u003e12.3.1.3 Cerium doped aluminophosphate glasses: atomic structure and charge trapping\u003c\/p\u003e \u003cp\u003e12.3.2 Alkali vanadophosphate glasses as a mixed conductor\u003c\/p\u003e \u003cp\u003e12.3.2.1 General features of vanadophosphate glasses\u003c\/p\u003e \u003cp\u003e12.3.2.2 Sodium vanadophosphate glass\u003c\/p\u003e \u003cp\u003e12.3.2.3 Lithium vanadophosphate glass\u003c\/p\u003e \u003cp\u003e12.3.3 Zirconia containing aluminosilicate and borosilicate glasses for nuclear waste disposal\u003c\/p\u003e \u003cp\u003e12.4 Conclusions\u003c\/p\u003e \u003cp\u003eAcknowledgement\u003c\/p\u003e \u003cp\u003eReferences\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 13 Halide and oxyhalide glasses \u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eAbstract\u003c\/p\u003e \u003cp\u003e13.1 Introduction\u003c\/p\u003e \u003cp\u003e13.2 General Structure Features of Fluoride and Oxyfluoride Glasses\u003c\/p\u003e \u003cp\u003e13.2.1 Structure Features of Fluoride Glasses\u003c\/p\u003e \u003cp\u003e13.2.2 Structure Features of Oxyfluoride Glasses\u003c\/p\u003e \u003cp\u003e13.2.3 Phase Separation in Fluoride and Oxyfluoride Glasses\u003c\/p\u003e \u003cp\u003e13.3 Structures and Properties of Fluoride Glasses from MD Simulations\u003c\/p\u003e \u003cp\u003e13.3.1 General Structures from MD simulations\u003c\/p\u003e \u003cp\u003e13.3.2 Cation Coordination and Structural Roles\u003c\/p\u003e \u003cp\u003e13.3.3 Fluorine Environments\u003c\/p\u003e \u003cp\u003e13.4 MD Simulations of Fluoroaluminosilicate Oxyfluoride Glasses\u003c\/p\u003e \u003cp\u003e13.4.1 Oxide and Fluoride Glass Phase Separation Observed from MD Simulations\u003c\/p\u003e \u003cp\u003e13.4.2 Oxide-Fluoride Interfacial Structure Features from MD simulations\u003c\/p\u003e \u003cp\u003e13.4.3 Correlation of Structural Features between MD and Crystallization\u003c\/p\u003e \u003cp\u003e13.5 ab initio MD simulations of oxyfluoride glasses\u003c\/p\u003e \u003cp\u003e13.6 Conclusions\u003c\/p\u003e \u003cp\u003eAcknowledgements\u003c\/p\u003e \u003cp\u003eReferences\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 14 Glass surface simulations \u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eabstract\u003c\/p\u003e \u003cp\u003e14.1 Introduction\u003c\/p\u003e \u003cp\u003e14.2 Classical molecular dynamics surface simulations\u003c\/p\u003e \u003cp\u003e14.2.1 amorphous silica surfaces\u003c\/p\u003e \u003cp\u003e14.2.2 Multicomponent oxide glass surfaces\u003c\/p\u003e \u003cp\u003e14.2.2.1 Bioactive glasses\u003c\/p\u003e \u003cp\u003e14.2.3 Wet glass surfaces\u003c\/p\u003e \u003cp\u003e14.2.3.1 Reactive potentials\u003c\/p\u003e \u003cp\u003e14.3 First Principles Surface Simulations\u003c\/p\u003e \u003cp\u003e14.3.1 Silica glass surfaces\u003c\/p\u003e \u003cp\u003e14.3.2 Multicomponent glass surfaces\u003c\/p\u003e \u003cp\u003e14.3.3 Wet glass surfaces\u003c\/p\u003e \u003cp\u003e14.4 Summary\u003c\/p\u003e \u003cp\u003eAcknowledgements\u003c\/p\u003e \u003cp\u003eReferences\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 15 Simulations of glass - water interactions \u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eAbstract\u003c\/p\u003e \u003cp\u003e15.1 Introduction\u003c\/p\u003e \u003cp\u003e15.1.1 Glass Dissolution Process and Experimental Characterizations\u003c\/p\u003e \u003cp\u003e15.1.2 Types of Atomistic Simulation Methods for Studying Glass-Water Interactions\u003c\/p\u003e \u003cp\u003e15.2 First-Principles Simulations of Glass-Water Interactions\u003c\/p\u003e \u003cp\u003e15.2.1 Brief Introduction to Methods\u003c\/p\u003e \u003cp\u003e15.2.2 Energy Barriers for Si-O-Si Bond Breakage\u003c\/p\u003e \u003cp\u003e15.2.3 Reaction Mechanism for Si-O-Si Bond Breakage\u003c\/p\u003e \u003cp\u003e15.2.4 Strained Si-O-Si linkages\u003c\/p\u003e \u003cp\u003e15.2.5 Reaction Energies for Multicomponent Linkages\u003c\/p\u003e \u003cp\u003e15.2.6 Effect of pH on Si-O-Si Hydrolysis Reactions\u003c\/p\u003e \u003cp\u003e15.2.7 Nanoconfinement of water in porous materials\u003c\/p\u003e \u003cp\u003e15.2.8 Oniom or QM\/MM simulations\u003c\/p\u003e \u003cp\u003e15.2.9 Areas for improvement\/additional research\u003c\/p\u003e \u003cp\u003e15.3 Classical Molecular Dynamics Simulations of water-glass interactions\u003c\/p\u003e \u003cp\u003e15.3.1 Brief Introduction and History\u003c\/p\u003e \u003cp\u003e15.3.2 Non-Reactive Potentials\u003c\/p\u003e \u003cp\u003e15.3.3 Reactive Potentials\u003c\/p\u003e \u003cp\u003e15.3.4 Silica Glass-Water Interactions\u003c\/p\u003e \u003cp\u003e15.3.5 Silicate Glass – Water Interactions\u003c\/p\u003e \u003cp\u003e15.3.6 Other glasses – water interactions\u003c\/p\u003e \u003cp\u003e15.3.7 Areas for Improvement\u003c\/p\u003e \u003cp\u003e15.4 Challenges and Outlook\u003c\/p\u003e \u003cp\u003e15.4.1 Extending the Length and Time Scales of Atomistic Simulation\u003c\/p\u003e \u003cp\u003e15.4.2 Reactive Potential Development\u003c\/p\u003e \u003cp\u003e15.5 Conclusion Remarks\u003c\/p\u003e \u003cp\u003e15.6 Acknowledgements\u003c\/p\u003e \u003cp\u003e15.7 References\u003c\/p\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49406951620951,"sku":"9781118939062","price":146.66,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781118939062.jpg?v=1730497670"},{"product_id":"bim-and-construction-management-9781118942765","title":"BIM and Construction Management","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eA sleeker, more comprehensive approach to construction projects   BIM and Construction Management, Second Edition is a complete integration guide, featuring practical advice, project tested methods and workflows, and tutorials for implementing Building Information Modeling and technology in construction.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eIntroduction xvii\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 1 Why Is Technology So Important to Construction Management? 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe Promise of BIM 2\u003c\/p\u003e \u003cp\u003eProcesses 4\u003c\/p\u003e \u003cp\u003eTechnologies 5\u003c\/p\u003e \u003cp\u003eBehaviors 7\u003c\/p\u003e \u003cp\u003eThe Value of BIM in Construction 8\u003c\/p\u003e \u003cp\u003eWhere Does BIM Play a Role in Construction Management? 15\u003c\/p\u003e \u003cp\u003eTeam Engagement 16\u003c\/p\u003e \u003cp\u003eProject Pursuit and Business Development 16\u003c\/p\u003e \u003cp\u003ePlanning for BIM Success 19\u003c\/p\u003e \u003cp\u003eUsing Contracts in Planning 19\u003c\/p\u003e \u003cp\u003eScheduling 20\u003c\/p\u003e \u003cp\u003eLogistics 22\u003c\/p\u003e \u003cp\u003eEstimating Cost 23\u003c\/p\u003e \u003cp\u003eConstructability 25\u003c\/p\u003e \u003cp\u003eAnalyzing Data in BIM 27\u003c\/p\u003e \u003cp\u003eDesigning for Prefabrication 29\u003c\/p\u003e \u003cp\u003eCoordinating Construction 31\u003c\/p\u003e \u003cp\u003eUsing Mobile Devices 32\u003c\/p\u003e \u003cp\u003eControlling Schedules 33\u003c\/p\u003e \u003cp\u003eControlling Cost 34\u003c\/p\u003e \u003cp\u003eManaging Change 35\u003c\/p\u003e \u003cp\u003eMaterial Management 37\u003c\/p\u003e \u003cp\u003eTracking Equipment 37\u003c\/p\u003e \u003cp\u003eCloseout 38\u003c\/p\u003e \u003cp\u003eManaging Facilities 39\u003c\/p\u003e \u003cp\u003eKnowledge Platform Population 40\u003c\/p\u003e \u003cp\u003eWhere the Industry Is Headed 42\u003c\/p\u003e \u003cp\u003eLeadership Buy-In 42\u003c\/p\u003e \u003cp\u003eThe Evolving Role of the BIM Manager 43\u003c\/p\u003e \u003cp\u003eWhat Have Been the Results? 43\u003c\/p\u003e \u003cp\u003eSummary 44\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 2 Project Planning 45\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eDelivery Methods 46\u003c\/p\u003e \u003cp\u003eDesign-Bid-Build 47\u003c\/p\u003e \u003cp\u003eConstruction Manager at Risk 52\u003c\/p\u003e \u003cp\u003eDesign-Build 56\u003c\/p\u003e \u003cp\u003eIntegrated Project Delivery 62\u003c\/p\u003e \u003cp\u003eBIM Addenda (Contracts) 63\u003c\/p\u003e \u003cp\u003eAIA: Document E202 65\u003c\/p\u003e \u003cp\u003eAGC: ConsensusDocs 301 65\u003c\/p\u003e \u003cp\u003eDBIA: Document E-BIMWD 65\u003c\/p\u003e \u003cp\u003eAIA: Document E203 66\u003c\/p\u003e \u003cp\u003eContracts Summary 66\u003c\/p\u003e \u003cp\u003eThe Fundamental Uses of BIM 67\u003c\/p\u003e \u003cp\u003eLevel of Development 68\u003c\/p\u003e \u003cp\u003eModel-Based Coordination 69\u003c\/p\u003e \u003cp\u003eModel-Based Scheduling 72\u003c\/p\u003e \u003cp\u003eModel-Based Estimating 72\u003c\/p\u003e \u003cp\u003eModel-Based Facilities Management 73\u003c\/p\u003e \u003cp\u003eModel-Based Analysis 74\u003c\/p\u003e \u003cp\u003eBIM Execution Plan 75\u003c\/p\u003e \u003cp\u003eHistory of the BIM Execution Plan 75\u003c\/p\u003e \u003cp\u003eCommunication 77\u003c\/p\u003e \u003cp\u003eExpectation 83\u003c\/p\u003e \u003cp\u003eOrganization 85\u003c\/p\u003e \u003cp\u003eSummary 89\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 3 How to Market BIM and Win the Project 91\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eBIM Marketing Background 92\u003c\/p\u003e \u003cp\u003eBuilding Your Team 94\u003c\/p\u003e \u003cp\u003eMarketing Your Brand of BIM 97\u003c\/p\u003e \u003cp\u003eDoes What You Are Proposing Show Clear and Demonstrable Value? 98\u003c\/p\u003e \u003cp\u003eIs This a Proven Tool or Process, a Developing One, or an Innovative One? 99\u003c\/p\u003e \u003cp\u003eCan You Show Real Results from the Impact of Implementation? 102\u003c\/p\u003e \u003cp\u003eIs This What the Owner Wants? 104\u003c\/p\u003e \u003cp\u003eIs This Something You Can Deliver? 105\u003c\/p\u003e \u003cp\u003eUsing BIM to Enhance the Proposal 108\u003c\/p\u003e \u003cp\u003eAddressing BIM in the RFP 108\u003c\/p\u003e \u003cp\u003eProject Pursuit Images 110\u003c\/p\u003e \u003cp\u003eProject Simulations 112\u003c\/p\u003e \u003cp\u003eProject Pursuit Virtual\/Augmented Reality Simulations 113\u003c\/p\u003e \u003cp\u003eOther Marketing Tools 116\u003c\/p\u003e \u003cp\u003eTailor-Fit Your Offerings 116\u003c\/p\u003e \u003cp\u003eClient Alignment 117\u003c\/p\u003e \u003cp\u003ePushing the Envelope 118\u003c\/p\u003e \u003cp\u003eSeeking Value and Focusing on Results 118\u003c\/p\u003e \u003cp\u003eSummary 121\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 4 BIM and Preconstruction 123\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eLeaning on the Past 124\u003c\/p\u003e \u003cp\u003eThe Empire State Building 125\u003c\/p\u003e \u003cp\u003eAdopting New Technology 132\u003c\/p\u003e \u003cp\u003eThe Journey to BIM 134\u003c\/p\u003e \u003cp\u003eThe Kickoff 136\u003c\/p\u003e \u003cp\u003eGetting the Right People in the Room 136\u003c\/p\u003e \u003cp\u003eCreating the Vision 138\u003c\/p\u003e \u003cp\u003eOpening the Lines of Communication 139\u003c\/p\u003e \u003cp\u003eAccounting for the Expectation Bias 139\u003c\/p\u003e \u003cp\u003eScheduling Design 139\u003c\/p\u003e \u003cp\u003eDesign Structure Matrix 145\u003c\/p\u003e \u003cp\u003eScheduling the LOD 148\u003c\/p\u003e \u003cp\u003eConstructability Review 149\u003c\/p\u003e \u003cp\u003eLeverage the Plans 150\u003c\/p\u003e \u003cp\u003eLeverage the Details 153\u003c\/p\u003e \u003cp\u003eLeverage the People 158\u003c\/p\u003e \u003cp\u003eEstimating 163\u003c\/p\u003e \u003cp\u003eRevit Schedules for Estimating 164\u003c\/p\u003e \u003cp\u003eCost Trending with Assemble 171\u003c\/p\u003e \u003cp\u003eAnalysis 175\u003c\/p\u003e \u003cp\u003eThe 2030 Challenge 176\u003c\/p\u003e \u003cp\u003eOverview of Sustainability and BIM 177\u003c\/p\u003e \u003cp\u003eSustainability Analysis with Sefaira 182\u003c\/p\u003e \u003cp\u003eLogistics and Planning 188\u003c\/p\u003e \u003cp\u003eSummary 190\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 5 BIM and Construction 191\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eOverview of BIM in Construction 192\u003c\/p\u003e \u003cp\u003eModel Coordination 194\u003c\/p\u003e \u003cp\u003eBIM and Site Coordination 194\u003c\/p\u003e \u003cp\u003eClash Detection 196\u003c\/p\u003e \u003cp\u003eNavisworks Conflict Exercise 196\u003c\/p\u003e \u003cp\u003eFabrication 208\u003c\/p\u003e \u003cp\u003eBIM Scheduling 213\u003c\/p\u003e \u003cp\u003eScheduling Software 217\u003c\/p\u003e \u003cp\u003eCompleting the Feedback Loop 226\u003c\/p\u003e \u003cp\u003eSystems Installation 228\u003c\/p\u003e \u003cp\u003eInstallation Management 228\u003c\/p\u003e \u003cp\u003eInstallation Verification 232\u003c\/p\u003e \u003cp\u003eConstruction Activity Tracking 234\u003c\/p\u003e \u003cp\u003eField Issue Management 235\u003c\/p\u003e \u003cp\u003eBIM and Safety 236\u003c\/p\u003e \u003cp\u003eProducing Better Field Information 238\u003c\/p\u003e \u003cp\u003eBeginning with the End in Mind 239\u003c\/p\u003e \u003cp\u003eWhat Information Do You Need to Build? 242\u003c\/p\u003e \u003cp\u003eModel Redlining Exercise 242\u003c\/p\u003e \u003cp\u003eVideo Embedding Exercise 250\u003c\/p\u003e \u003cp\u003eThe Virtual Job Trailer 252\u003c\/p\u003e \u003cp\u003eThe Conference Room 252\u003c\/p\u003e \u003cp\u003eThe Plans and Specifications Hub 254\u003c\/p\u003e \u003cp\u003eThe Jobsite Office as a Server 254\u003c\/p\u003e \u003cp\u003eThe Jobsite Office as a Communication Hub 255\u003c\/p\u003e \u003cp\u003eSetting Up the Job Trailer 255\u003c\/p\u003e \u003cp\u003eSummary 256\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 6 BIM and Construction Administration 257\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe Battle for BIM 258\u003c\/p\u003e \u003cp\u003eTraining Field Personnel 261\u003c\/p\u003e \u003cp\u003eTraining Goals for Basic Skills 263\u003c\/p\u003e \u003cp\u003eAdvanced Training Goals for Model Creation 263\u003c\/p\u003e \u003cp\u003eTraining Courses for Additional Uses 265\u003c\/p\u003e \u003cp\u003eDocument Control 270\u003c\/p\u003e \u003cp\u003eCreating a Digital Plan Room with Bluebeam Revu eXtreme 272\u003c\/p\u003e \u003cp\u003eThe Real Value of 4D 281\u003c\/p\u003e \u003cp\u003eDeveloping BIM Intuition 284\u003c\/p\u003e \u003cp\u003eStarting with a Door 284\u003c\/p\u003e \u003cp\u003eAssemble Systems: Beyond the Basics 286\u003c\/p\u003e \u003cp\u003eImporting Search Sets into Navisworks 288\u003c\/p\u003e \u003cp\u003eMapping Equipment to BIM 360 Field 291\u003c\/p\u003e \u003cp\u003eInformation Loading and QR Coding 295\u003c\/p\u003e \u003cp\u003eUsing 360 Field to Status Material 299\u003c\/p\u003e \u003cp\u003eVisualizing Equipment Status in the Model 301\u003c\/p\u003e \u003cp\u003eEndless Possibilities 304\u003c\/p\u003e \u003cp\u003eSmall Wins to Big Change 305\u003c\/p\u003e \u003cp\u003eSummary 305\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 7 BIM and Close Out 307\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eTrue Costs of Facility Operations 308\u003c\/p\u003e \u003cp\u003eArtifact Deliverables 310\u003c\/p\u003e \u003cp\u003eConstant Deliverables 315\u003c\/p\u003e \u003cp\u003eTaking a Hybrid Approach 317\u003c\/p\u003e \u003cp\u003eOwners and BIM 317\u003c\/p\u003e \u003cp\u003eOwner Options 318\u003c\/p\u003e \u003cp\u003eIntegration of a Record BIM 320\u003c\/p\u003e \u003cp\u003eBIM and Information Handover 325\u003c\/p\u003e \u003cp\u003eMaintaining the Model 329\u003c\/p\u003e \u003cp\u003eOngoing Investment and Logistics for Facility Management BIM 330\u003c\/p\u003e \u003cp\u003eTraining 332\u003c\/p\u003e \u003cp\u003eModel Maintenance 333\u003c\/p\u003e \u003cp\u003eOne BIM = One Source of Information 334\u003c\/p\u003e \u003cp\u003eSummary 337\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 8 The Future of BIM 339\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eWhat Will BIM Be? 340\u003c\/p\u003e \u003cp\u003eIndustry Trends 340\u003c\/p\u003e \u003cp\u003eBIM and Prefabrication 342\u003c\/p\u003e \u003cp\u003eNew Processes and Roles 343\u003c\/p\u003e \u003cp\u003eInteroperability 345\u003c\/p\u003e \u003cp\u003eBIM and Education 349\u003c\/p\u003e \u003cp\u003eBIM and the New Construction Manager 351\u003c\/p\u003e \u003cp\u003eBIM and the New Team 354\u003c\/p\u003e \u003cp\u003eBIM and the New Process 356\u003c\/p\u003e \u003cp\u003eFuture Opportunities 357\u003c\/p\u003e \u003cp\u003eFuture Relationships 359\u003c\/p\u003e \u003cp\u003eVirtual Builder Certification 360\u003c\/p\u003e \u003cp\u003eSummary 362\u003c\/p\u003e \u003cp\u003eIndex 363\u003c\/p\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49406952112471,"sku":"9781118942765","price":39.85,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781118942765.jpg?v=1730497670"},{"product_id":"how-to-implement-market-models-using-vba-9781118962008","title":"How to Implement Market Models Using VBA","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eAccessible VBA coding for complex financial modelling    How to Implement Market Models Using VBA makes solving complex valuation issues accessible to any financial professional with a taste for mathematics.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003ePreface ix\u003c\/p\u003e \u003cp\u003eAcknowledgements xi\u003c\/p\u003e \u003cp\u003eAbbreviations xiii\u003c\/p\u003e \u003cp\u003eAbout the Author xv\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 1 The Basics of VBA Programming 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 Getting started 1\u003c\/p\u003e \u003cp\u003e1.2 VBA objects and syntax 2\u003c\/p\u003e \u003cp\u003e1.2.1 The object-oriented basic syntax 3\u003c\/p\u003e \u003cp\u003e1.2.2 Using objects 3\u003c\/p\u003e \u003cp\u003e1.3 Variables 5\u003c\/p\u003e \u003cp\u003e1.3.1 Variable declaration 5\u003c\/p\u003e \u003cp\u003e1.3.2 Some usual objects 7\u003c\/p\u003e \u003cp\u003e1.3.3 Arrays 9\u003c\/p\u003e \u003cp\u003e1.4 Arithmetic 10\u003c\/p\u003e \u003cp\u003e1.5 Subroutines and functions 13\u003c\/p\u003e \u003cp\u003e1.5.1 Subroutines 14\u003c\/p\u003e \u003cp\u003e1.5.2 Functions 15\u003c\/p\u003e \u003cp\u003e1.5.3 Operations on one-dimensional arrays 16\u003c\/p\u003e \u003cp\u003e1.5.4 Operations on two-dimensional arrays (matrices) 16\u003c\/p\u003e \u003cp\u003e1.5.5 Operations with dates 19\u003c\/p\u003e \u003cp\u003e1.6 Custom objects 21\u003c\/p\u003e \u003cp\u003e1.6.1 Types 21\u003c\/p\u003e \u003cp\u003e1.6.2 Classes 22\u003c\/p\u003e \u003cp\u003e1.7 Debugging 24\u003c\/p\u003e \u003cp\u003e1.7.1 Error handling 24\u003c\/p\u003e \u003cp\u003e1.7.2 Tracking the code execution 25\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 2 Mathematical Algorithms 29\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction 29\u003c\/p\u003e \u003cp\u003e2.2 Sorting lists 29\u003c\/p\u003e \u003cp\u003e2.2.1 Shell sort 29\u003c\/p\u003e \u003cp\u003e2.2.2 Quick sort 32\u003c\/p\u003e \u003cp\u003e2.3 Implicit equations 34\u003c\/p\u003e \u003cp\u003e2.4 Search for extrema 36\u003c\/p\u003e \u003cp\u003e2.4.1 The Nelder-Mead algorithm 36\u003c\/p\u003e \u003cp\u003e2.4.2 The simulated annealing 40\u003c\/p\u003e \u003cp\u003e2.5 Linear algebra 43\u003c\/p\u003e \u003cp\u003e2.5.1 Matrix inversion 44\u003c\/p\u003e \u003cp\u003e2.5.2 Cholesky decomposition 46\u003c\/p\u003e \u003cp\u003e2.5.3 Interpolation 48\u003c\/p\u003e \u003cp\u003e2.5.4 Integration 57\u003c\/p\u003e \u003cp\u003e2.5.5 Principal Component Analysis 60\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 3 Vanilla Instruments 67\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 Definitions 67\u003c\/p\u003e \u003cp\u003e3.2 Fixed income 67\u003c\/p\u003e \u003cp\u003e3.2.1 Bond market 68\u003c\/p\u003e \u003cp\u003e3.2.2 Interbank market 72\u003c\/p\u003e \u003cp\u003e3.3 Vanilla derivatives 75\u003c\/p\u003e \u003cp\u003e3.3.1 Forward contracts 75\u003c\/p\u003e \u003cp\u003e3.3.2 Swaps 77\u003c\/p\u003e \u003cp\u003e3.3.3 Bond futures 81\u003c\/p\u003e \u003cp\u003e3.4 Options basics 84\u003c\/p\u003e \u003cp\u003e3.4.1 Brownian motion 84\u003c\/p\u003e \u003cp\u003e3.4.2 Ito integral 85\u003c\/p\u003e \u003cp\u003e3.4.3 Ito formula 86\u003c\/p\u003e \u003cp\u003e3.4.4 Black–Scholes basic model 89\u003c\/p\u003e \u003cp\u003e3.4.5 Risk-neutral probability 90\u003c\/p\u003e \u003cp\u003e3.4.6 Change of probability 90\u003c\/p\u003e \u003cp\u003e3.4.7 Martingale and numeraires 92\u003c\/p\u003e \u003cp\u003e3.4.8 European-style options pricing 94\u003c\/p\u003e \u003cp\u003e3.5 First generation exotic options 95\u003c\/p\u003e \u003cp\u003e3.5.1 Barrier options 95\u003c\/p\u003e \u003cp\u003e3.5.2 Quanto options 102\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 4 Numerical Solutions 105\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 Finite differences 105\u003c\/p\u003e \u003cp\u003e4.1.1 Generic equation 105\u003c\/p\u003e \u003cp\u003e4.1.2 Implementation 106\u003c\/p\u003e \u003cp\u003e4.2 Trees 112\u003c\/p\u003e \u003cp\u003e4.2.1 Binomial trees 112\u003c\/p\u003e \u003cp\u003e4.2.2 Trinomial trees 116\u003c\/p\u003e \u003cp\u003e4.3 Monte-Carlo scenarios 116\u003c\/p\u003e \u003cp\u003e4.3.1 Uniform number generator 117\u003c\/p\u003e \u003cp\u003e4.3.2 From uniform to Gaussian numbers 127\u003c\/p\u003e \u003cp\u003e4.4 Simulation and regression 129\u003c\/p\u003e \u003cp\u003e4.5 Double-barrier analytical approximation 134\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 5 Monte-Carlo Pricing Issues 139\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 Multi-asset simulation 139\u003c\/p\u003e \u003cp\u003e5.1.1 The correlations issue 139\u003c\/p\u003e \u003cp\u003e5.1.2 The Gaussian case 139\u003c\/p\u003e \u003cp\u003e5.1.3 Exotics 143\u003c\/p\u003e \u003cp\u003e5.2 Discretization schemes 146\u003c\/p\u003e \u003cp\u003e5.3 Variance reduction techniques 147\u003c\/p\u003e \u003cp\u003e5.3.1 Antithetic variates 147\u003c\/p\u003e \u003cp\u003e5.3.2 Importance sampling 148\u003c\/p\u003e \u003cp\u003e5.3.3 Control variates 153\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 6 Yield Curve Models 163\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 Short rate models 163\u003c\/p\u003e \u003cp\u003e6.1.1 Introduction 163\u003c\/p\u003e \u003cp\u003e6.1.2 Hull and White one-factor model 164\u003c\/p\u003e \u003cp\u003e6.1.3 Gaussian two-factor model 180\u003c\/p\u003e \u003cp\u003e6.1.4 Hull and White two-factor model 203\u003c\/p\u003e \u003cp\u003e6.2 Forward rate models 204\u003c\/p\u003e \u003cp\u003e6.2.1 Generic Heath-Jarrow-Morton 205\u003c\/p\u003e \u003cp\u003e6.2.2 LMM (LIBOR market model) 216\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 7 Stochastic Volatilities 233\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 The Heston model 234\u003c\/p\u003e \u003cp\u003e7.1.1 Code 234\u003c\/p\u003e \u003cp\u003e7.1.2 A faster algorithm 239\u003c\/p\u003e \u003cp\u003e7.1.3 Calibration 248\u003c\/p\u003e \u003cp\u003e7.2 Barrier options 254\u003c\/p\u003e \u003cp\u003e7.2.1 Numerical results 257\u003c\/p\u003e \u003cp\u003e7.2.2 Code 257\u003c\/p\u003e \u003cp\u003e7.3 Asian-style options 260\u003c\/p\u003e \u003cp\u003e7.4 SABR model 264\u003c\/p\u003e \u003cp\u003e7.4.1 Caplets 264\u003c\/p\u003e \u003cp\u003e7.4.2 Code 265\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 8 Interest Rate Exotics 267\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 CMS swaps 267\u003c\/p\u003e \u003cp\u003e8.1.1 Code 269\u003c\/p\u003e \u003cp\u003e8.2 Cancelable swaps 272\u003c\/p\u003e \u003cp\u003e8.2.1 Code 272\u003c\/p\u003e \u003cp\u003e8.2.2 Tree approximation 276\u003c\/p\u003e \u003cp\u003e8.3 Target redemption note 281\u003c\/p\u003e \u003cp\u003e8.3.1 Code 282\u003c\/p\u003e \u003cp\u003eBibliography 287\u003c\/p\u003e \u003cp\u003eIndex 289\u003c\/p\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49406956831063,"sku":"9781118962008","price":57.0,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781118962008.jpg?v=1730497686"},{"product_id":"how-to-estimate-with-rsmeans-data-9781118977965","title":"How to Estimate with RSMeans Data","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e","brand":"R.S. Means Company Ltd","offers":[{"title":"Default Title","offer_id":49406961549655,"sku":"9781118977965","price":65.66,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781118977965.jpg?v=1730497704"},{"product_id":"advanced-engineering-materials-and-modeling-9781119242468","title":"Advanced Engineering Materials and Modeling","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eThe engineering of materials with advanced features is driving the research towards the design of innovative materials with high performances. New materials often deliver the best solution for structural applications, precisely contributing towards the finest combination of mechanical properties and low weight.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003ePreface xiii\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 1 Engineering of Materials, Characterizations, and Applications\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Mechanical Behavior and Resistance of Structural Glass Beams in Lateral–Torsional Buckling (LTB) with Adhesive Joints 3\u003c\/b\u003e\u003cbr\u003e \u003ci\u003eChiara Bedon and Jan Belis\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e1.1 Introduction 4\u003c\/p\u003e \u003cp\u003e1.2 Overview on Structural Glass Applications in Buildings 5\u003c\/p\u003e \u003cp\u003e1.3 Glass Beams in LTB 5\u003c\/p\u003e \u003cp\u003e1.3.1 Susceptibility of Glass Structural Elements to Buckling Phenomena 5\u003c\/p\u003e \u003cp\u003e1.3.2 Mechanical and Geometrical Influencing Parameters in Structural Glass Beams 8\u003c\/p\u003e \u003cp\u003e1.3.3 Mechanical Joints 9\u003c\/p\u003e \u003cp\u003e1.3.4 Adhesive Joints 10\u003c\/p\u003e \u003cp\u003e1.4 Theoretical Background for Structural Members in LTB 14\u003c\/p\u003e \u003cp\u003e1.4.1 General LTB Method for Laterally Unrestrained (LU) Members 14\u003c\/p\u003e \u003cp\u003e1.4.2 LTB Method for Laterally Unrestrained (LU) Glass Beams 17\u003c\/p\u003e \u003cp\u003e1.4.2.1 Equivalent Thickness Methods for Laminated Glass Beams 18\u003c\/p\u003e \u003cp\u003e1.4.3 Laterally Restrained (LR) Beams in LTB 23\u003c\/p\u003e \u003cp\u003e1.4.3.1 Extended Literature Review on LR Beams 23\u003c\/p\u003e \u003cp\u003e1.4.3.2 Closed-form Formulation for LR Beams in LTB 24\u003c\/p\u003e \u003cp\u003e1.4.3.3 LR Glass Beams Under Positive Bending Moment My 28\u003c\/p\u003e \u003cp\u003e1.5 Finite-element Numerical Modeling 31\u003c\/p\u003e \u003cp\u003e1.5.1 FE Solving Approach and Parametric Study 32\u003c\/p\u003e \u003cp\u003e1.5.1.1 Linear Eigenvalue Buckling Analyses (lba) 32\u003c\/p\u003e \u003cp\u003e1.5.1.2 Incremental Nonlinear Analyses (inl) 35\u003c\/p\u003e \u003cp\u003e1.6 LTB Design Recommendations 38\u003c\/p\u003e \u003cp\u003e1.6.1 LR Beams Under Positive Bending Moment My 38\u003c\/p\u003e \u003cp\u003e1.6.2 Further Extension and Developments of the Current Outcomes 39\u003c\/p\u003e \u003cp\u003e1.7 Conclusions 42\u003c\/p\u003e \u003cp\u003eReferences 44\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Room Temperature Mechanosynthesis of Nanocrystalline Metal Carbides and Their Microstructure Characterization 49\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eS.K. Pradhan and H. Dutta\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction 50\u003c\/p\u003e \u003cp\u003e2.1.1 Application 50\u003c\/p\u003e \u003cp\u003e2.1.2 Different Methods for Preparation of Metal Carbide 50\u003c\/p\u003e \u003cp\u003e2.1.3 Mechanical Alloying 51\u003c\/p\u003e \u003cp\u003e2.1.4 Planetary Ball Mill 51\u003c\/p\u003e \u003cp\u003e2.1.5 The Merits and Demerits of Planetary Ball Mill 52\u003c\/p\u003e \u003cp\u003e2.1.6 Review of Works on Metal Carbides by Other Authors 53\u003c\/p\u003e \u003cp\u003e2.1.7 Significance of the Study 54\u003c\/p\u003e \u003cp\u003e2.1.8 Objectives of the Study 55\u003c\/p\u003e \u003cp\u003e2.2 Experimental 56\u003c\/p\u003e \u003cp\u003e2.3 Theoretical Consideration 58\u003c\/p\u003e \u003cp\u003e2.3.1 Microstructure Evaluation by X-ray Diffraction 58\u003c\/p\u003e \u003cp\u003e2.3.2 General Features of Structure 60\u003c\/p\u003e \u003cp\u003e2.4 Results and Discussions 60\u003c\/p\u003e \u003cp\u003e2.4.1 XRD Pattern Analysis 60\u003c\/p\u003e \u003cp\u003e2.4.2 Variation of Mol Fraction 65\u003c\/p\u003e \u003cp\u003e2.4.3 Phase Formation Mechanism 69\u003c\/p\u003e \u003cp\u003e2.4.4 Is Ball-milled Prepared Metal Carbide Contains Contamination? 71\u003c\/p\u003e \u003cp\u003e2.4.5 Variation of Particle Size 72\u003c\/p\u003e \u003cp\u003e2.4.6 Variation of Strain 74\u003c\/p\u003e \u003cp\u003e2.4.7 High-Resolution Transmission Electron Microscopy Study 76\u003c\/p\u003e \u003cp\u003e2.4.8 Comparison Study between Binary and Ternary Ti-based Metal Carbides 76\u003c\/p\u003e \u003cp\u003e2.5 Conclusion 80\u003c\/p\u003e \u003cp\u003eAcknowledgment 80\u003c\/p\u003e \u003cp\u003eReferences 80\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Toward a Novel SMA-reinforced Laminated Glass Panel 87\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eChiara Bedon and Filipe Amarante dos Santos\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction 87\u003c\/p\u003e \u003cp\u003e3.2 Glass in Buildings 89\u003c\/p\u003e \u003cp\u003e3.2.1 Actual Reinforcement Techniques for Structural Glass Applications 92\u003c\/p\u003e \u003cp\u003e3.3 Structural Engineering Applications of Shape-Memory Alloys (SMAs) 93\u003c\/p\u003e \u003cp\u003e3.4 The Novel SMA-Reinforced Laminated Glass Panel Concept 94\u003c\/p\u003e \u003cp\u003e3.4.1 Design Concept 94\u003c\/p\u003e \u003cp\u003e3.4.2 Exploratory Finite-Element (FE) Numerical Study 96\u003c\/p\u003e \u003cp\u003e3.4.2.1 General FE Model Assembly Approach and Solving Method 96\u003c\/p\u003e \u003cp\u003e3.4.2.2 Mechanical Characterization of Materials 98\u003c\/p\u003e \u003cp\u003e3.5 Discussion of Parametric FE Results 101\u003c\/p\u003e \u003cp\u003e3.5.1 Roof Glass Panel (M1) 101\u003c\/p\u003e \u003cp\u003e3.5.1.1 Short-term Loads and Temperature Variations 102\u003c\/p\u003e \u003cp\u003e3.5.1.2 First-cracking Configuration 106\u003c\/p\u003e \u003cp\u003e3.5.2 Point-supported Façade Panel (M2) 109\u003c\/p\u003e \u003cp\u003e3.5.2.1 Short-term Loads and Temperature Variations 111\u003c\/p\u003e \u003cp\u003e3.6 Conclusions 114\u003c\/p\u003e \u003cp\u003eReferences 117\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Sustainable Sugarcane Bagasse Cellulose for Papermaking 121\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eNoé Aguilar-Rivera\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e4.1 Pulp and Paper Industry 122\u003c\/p\u003e \u003cp\u003e4.2 Sugar Industry 123\u003c\/p\u003e \u003cp\u003e4.3 Sugarcane Bagasse 124\u003c\/p\u003e \u003cp\u003e4.4 Advantageous Utilizations of SCB 129\u003c\/p\u003e \u003cp\u003e4.5 Applications of SCB Wastes 130\u003c\/p\u003e \u003cp\u003e4.6 Problematic of Nonwood Fibers in Papermaking 131\u003c\/p\u003e \u003cp\u003e4.7 SCB as Raw Material for Pulp and Paper 134\u003c\/p\u003e \u003cp\u003e4.8 Digestion 135\u003c\/p\u003e \u003cp\u003e4.9 Bleaching 135\u003c\/p\u003e \u003cp\u003e4.10 Properties of Bagasse Pulps 136\u003c\/p\u003e \u003cp\u003e4.10.1 Pulp Strength 137\u003c\/p\u003e \u003cp\u003e4.10.2 Pulp Properties 137\u003c\/p\u003e \u003cp\u003e4.10.3 Washing Technology 138\u003c\/p\u003e \u003cp\u003e4.10.4 Paper Machine Operation 138\u003c\/p\u003e \u003cp\u003e4.11 Objectives 138\u003c\/p\u003e \u003cp\u003e4.12 Old Corrugated Container Pulps 139\u003c\/p\u003e \u003cp\u003e4.13 Synergistic Delignification SCB–OCC 141\u003c\/p\u003e \u003cp\u003e4.14 Elemental Chlorine-Free Bleaching of SCB Pulps 150\u003c\/p\u003e \u003cp\u003e4.15 Conclusions 156\u003c\/p\u003e \u003cp\u003eReferences 158\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Bio-inspired Composites: Using Nature to Tackle Composite Limitations 165\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eF. Libonati\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction 166\u003c\/p\u003e \u003cp\u003e5.2 Bio-inspiration: Bone as Biomimetic Model 169\u003c\/p\u003e \u003cp\u003e5.3 Case Studies Using Biomimetic Approach 172\u003c\/p\u003e \u003cp\u003e5.3.1 Fiber-reinforced Bone-inspired Composites 172\u003c\/p\u003e \u003cp\u003e5.3.2 Fiber-reinforced Bone-inspired Composites with CNTs 176\u003c\/p\u003e \u003cp\u003e5.3.3 Bone-inspired Composites via 3D Printing 177\u003c\/p\u003e \u003cp\u003e5.4 Methods 179\u003c\/p\u003e \u003cp\u003e5.4.1 Composite Lamination 180\u003c\/p\u003e \u003cp\u003e5.4.2 Additive Manufacturing 181\u003c\/p\u003e \u003cp\u003e5.4.3 Computational Modeling 182\u003c\/p\u003e \u003cp\u003e5.5 Conclusions 183\u003c\/p\u003e \u003cp\u003eReferences 185\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 2 Computational Modeling of Materials\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 On the Electronic Structure and Band Gap of ZnSxSe1–x 193\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eGhassan H. E. Al-Shabeeb and A. K. Arof\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction 193\u003c\/p\u003e \u003cp\u003e6.2 Computational Method 194\u003c\/p\u003e \u003cp\u003e6.3 The k·p Perturbation Theory with the Effect of Spin–Orbit Interaction 197\u003c\/p\u003e \u003cp\u003e6.4 Results and Discussion 202\u003c\/p\u003e \u003cp\u003eAcknowledgment 205\u003c\/p\u003e \u003cp\u003eReferences 205\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Application of First Principles Theory to the Design of Advanced Titanium Alloys 207\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eY. Song, J. H. Dai, and R. Yang\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction 207\u003c\/p\u003e \u003cp\u003e7.2 Basic Concepts of First Principles 208\u003c\/p\u003e \u003cp\u003e7.3 Theoretical Models of Alloy Design 211\u003c\/p\u003e \u003cp\u003e7.3.1 The Hume-Rothery Theory 211\u003c\/p\u003e \u003cp\u003e7.3.2 Discrete Variational Method and d-Orbital Method 216\u003c\/p\u003e \u003cp\u003e7.3.2.1 Discrete Variational Method 216\u003c\/p\u003e \u003cp\u003e7.3.2.2 d-Electrons Alloy Theory 218\u003c\/p\u003e \u003cp\u003e7.4 Applications 219\u003c\/p\u003e \u003cp\u003e7.4.1 Phase Stability 219\u003c\/p\u003e \u003cp\u003e7.4.1.1 Binary Alloy 219\u003c\/p\u003e \u003cp\u003e7.4.1.2 Multicomponent Alloys 222\u003c\/p\u003e \u003cp\u003e7.4.2 Elastic Properties 223\u003c\/p\u003e \u003cp\u003e7.4.3 Examples 226\u003c\/p\u003e \u003cp\u003e7.4.3.1 Gum Metal 226\u003c\/p\u003e \u003cp\u003e7.4.3.2 Ti2448 (Ti–24Nb–4Zr–8Sn) 227\u003c\/p\u003e \u003cp\u003e7.5 Conclusions 230\u003c\/p\u003e \u003cp\u003eAcknowledgment 230\u003c\/p\u003e \u003cp\u003eReferences 230\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Digital Orchid: Creating Realistic Materials 233\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eIftikhar B. Abbasov\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction 234\u003c\/p\u003e \u003cp\u003e8.2 Conclusion 243\u003c\/p\u003e \u003cp\u003eReferences 243\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Transformation Optics-based Computational Materials for Stochastic Electromagnetics 245\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eOzlem Ozgun and Mustafa Kuzuoglu\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction 246\u003c\/p\u003e \u003cp\u003e9.2 Theory of Transformation Optics 249\u003c\/p\u003e \u003cp\u003e9.3 Scattering from Rough Sea Surfaces 252\u003c\/p\u003e \u003cp\u003e9.3.1 Numerical Validation and Monte Carlo Simulations 256\u003c\/p\u003e \u003cp\u003e9.4 Scattering from Obstacles with Rough Surfaces or Shape Deformations 258\u003c\/p\u003e \u003cp\u003e9.4.1 Numerical Validation and Monte Carlo Simulations 263\u003c\/p\u003e \u003cp\u003e9.4.2 Combining Perturbation Theory and Transformation Optics for Weakly Perturbed Surfaces 264\u003c\/p\u003e \u003cp\u003e9.5 Scattering from Randomly Positioned Array of Obstacles 268\u003c\/p\u003e \u003cp\u003e9.5.1 Separate Transformation Media 269\u003c\/p\u003e \u003cp\u003e9.5.1.1 Numerical Validation \u0026amp; Monte Carlo Simulations 271\u003c\/p\u003e \u003cp\u003e9.5.2 A Single Transformation Medium 273\u003c\/p\u003e \u003cp\u003e9.5.2.1 Numerical Validation \u0026amp; Monte Carlo Simulations 275\u003c\/p\u003e \u003cp\u003e9.5.3 Recurring Scaling and Translation Transformations 276\u003c\/p\u003e \u003cp\u003e9.5.3.1 Numerical Validation \u0026amp; Monte Carlo Simulations 278\u003c\/p\u003e \u003cp\u003e9.6 Propagation in a Waveguide with Rough or Randomly Varying Surface 278\u003c\/p\u003e \u003cp\u003e9.3.1 Numerical Validation and Monte Carlo\u003c\/p\u003e \u003cp\u003eSimulations 283\u003c\/p\u003e \u003cp\u003e9.7 Conclusion 287\u003c\/p\u003e \u003cp\u003eReferences 288\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Superluminal Photons Tunneling through Brain Microtubules Modeled as Metamaterials and Quantum Computation 291\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eLuigi Maxmilian Caligiuri and Takaaki Musha\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e10.1 Introduction 292\u003c\/p\u003e \u003cp\u003e10.2 QED Coherence in Water: A Brief Overview 295\u003c\/p\u003e \u003cp\u003e10.3 “Electronic” QED Coherence in Brain Microtubules 301\u003c\/p\u003e \u003cp\u003e10.4 Evanescent Field of Coherent Photons and Their Superluminal Tunneling through MTs 305\u003c\/p\u003e \u003cp\u003e10.5 Coupling between Nearby MTs and their Superluminal Interaction through the Exchange of Virtual Superradiant Photons 312\u003c\/p\u003e \u003cp\u003e10.6 Discussion 316\u003c\/p\u003e \u003cp\u003e10.7 Brain Microtubules as “Natural” Metamaterials and the Amplification of Evanescent Tunneling Wave Amplitude 319\u003c\/p\u003e \u003cp\u003e10.8 Quantum Computation by Means of Superluminal Photons 325\u003c\/p\u003e \u003cp\u003e10.9 Conclusions 329\u003c\/p\u003e \u003cp\u003eReferences 330\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Advanced Fundamental-solution-based Computational Methods for Thermal Analysis of Heterogeneous Materials 335\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eHui Wang and Qing-Hua Qin\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e11.1 Introduction 336\u003c\/p\u003e \u003cp\u003e11.2 Basic Formulation of MFS 338\u003c\/p\u003e \u003cp\u003e11.2.1 Standard MFS 338\u003c\/p\u003e \u003cp\u003e11.2.2 Modified MFS 340\u003c\/p\u003e \u003cp\u003e11.2.2.1 RBF Interpolation for the Particular Solution 341\u003c\/p\u003e \u003cp\u003e11.2.2.2 MFS for the Homogeneous Solution 342\u003c\/p\u003e \u003cp\u003e11.2.2.3 Complete Solution 343\u003c\/p\u003e \u003cp\u003e11.3 Basic Formulation of HFS-FEM 344\u003c\/p\u003e \u003cp\u003e11.3.1 Problem Statement 344\u003c\/p\u003e \u003cp\u003e11.3.2 Implementation of the HFS-FEM 346\u003c\/p\u003e \u003cp\u003e11.3.4 Recovery of Rigid-body Motion 349\u003c\/p\u003e \u003cp\u003e11.4 Applications in Functionally Graded Materials 349\u003c\/p\u003e \u003cp\u003e11.4.1 Basic Equations in Functionally Graded Materials 349\u003c\/p\u003e \u003cp\u003e11.4.2 MFS for Functionally Graded Materials 350\u003c\/p\u003e \u003cp\u003e11.4.3 HFS-FEM for Functionally Graded Materials 353\u003c\/p\u003e \u003cp\u003e11.5 Applications in Composite Materials 357\u003c\/p\u003e \u003cp\u003e11.5.1 Basic Equations of Composite Materials 357\u003c\/p\u003e \u003cp\u003e11.5.2 MFS for Composite Materials 360\u003c\/p\u003e \u003cp\u003e11.5.2.1 MFS for the Matrix Domain 360\u003c\/p\u003e \u003cp\u003e11.5.2.2 MFS for the Fiber Domain 360\u003c\/p\u003e \u003cp\u003e11.5.2.3 Complete Linear Equation System 361\u003c\/p\u003e \u003cp\u003e11.5.3 HFS-FEM for Composite Materials 362\u003c\/p\u003e \u003cp\u003e11.5.3.1 Special Fundamental Solutions 362\u003c\/p\u003e \u003cp\u003e11.5.3.2 Special n-Sided Fiber\/Matrix Elements 363\u003c\/p\u003e \u003cp\u003e11.6 Conclusions 365\u003c\/p\u003e \u003cp\u003eAcknowledgments 366\u003c\/p\u003e \u003cp\u003eConflict of Interest 366\u003c\/p\u003e \u003cp\u003eReferences 366\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Understanding the SET\/RESET Characteristics of Forming Free TiOx\/TiO2–x Resistive-Switching Bilayer Structures through Experiments and Modeling 373\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eP. Bousoulas and D. Tsoukalas\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e12.1 Introduction 374\u003c\/p\u003e \u003cp\u003e12.2 Experimental Methodology 376\u003c\/p\u003e \u003cp\u003e12.3 Bipolar Switching Model 378\u003c\/p\u003e \u003cp\u003e12.3.1 Resistive-Switching Performance 378\u003c\/p\u003e \u003cp\u003e12.3.2 Resistive-Switching Model 383\u003c\/p\u003e \u003cp\u003e12.4 RESET Simulations 389\u003c\/p\u003e \u003cp\u003e12.4.1 I–V Response 389\u003c\/p\u003e \u003cp\u003e12.4.2 Influence of TE on the CFs Broken Region 393\u003c\/p\u003e \u003cp\u003e12.5 SET Simulations 398\u003c\/p\u003e \u003cp\u003e12.6 Simulation of Time-dependent SET\/RESET Processes 401\u003c\/p\u003e \u003cp\u003e12.7 Conclusions 403\u003c\/p\u003e \u003cp\u003eAcknowledgments 404\u003c\/p\u003e \u003cp\u003eReferences 404\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 Advanced Materials and Three-dimensional Computer-aided Surgical Workflow in Cranio-maxillofacial Reconstruction 411\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eLuis Miguel Gonzalez-Perez, Borja Gonzalez-Perez-Somarriba Gabriel Centeno, Carpóforo Vallellano, and Juan Jose Egea-Guerrero\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e13.1 Introduction 412\u003c\/p\u003e \u003cp\u003e13.2 Methodology 413\u003c\/p\u003e \u003cp\u003e13.3 Findings 418\u003c\/p\u003e \u003cp\u003e13.4 Discussion 427\u003c\/p\u003e \u003cp\u003eReferences 436\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 Displaced Multiwavelets and Splitting Algorithms 439\u003cbr\u003e \u003c\/b\u003e\u003ci\u003eBoris M. Shumilov\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e14.1 An Algorithm with Splitting of Wavelet Transformation of Splines of the First Degree 443\u003c\/p\u003e \u003cp\u003e14.1.1 “Lazy” Wavelets 444\u003c\/p\u003e \u003cp\u003e14.1.2 Examples of Wavelet Decomposition of a Signal of Length 8 447\u003c\/p\u003e \u003cp\u003e14.1.3 “Orthonormal” Wavelets 450\u003c\/p\u003e \u003cp\u003e14.1.4 An Example of Function of Harten 454\u003c\/p\u003e \u003cp\u003e14.2 An Algorithm for Constructing Orthogonal to Polynomials Multiwavelet Bases 456\u003c\/p\u003e \u003cp\u003e14.2.1 Creation of System of Basic Multiwavelets of Any Odd Degree on a Closed Interval 456\u003c\/p\u003e \u003cp\u003e14.2.2 Creation of the Block of Filters 459\u003c\/p\u003e \u003cp\u003e14.2.3 Example of Orthogonal to Polynomials Multiwavelet Bases 461\u003c\/p\u003e \u003cp\u003e14.2.4 The Discussion of Approximation on a Closed Interval 463\u003c\/p\u003e \u003cp\u003e14.3 The Tridiagonal Block Matrix Algorithm 464\u003c\/p\u003e \u003cp\u003e14.3.1 Inverse of the Block of Filters 464\u003c\/p\u003e \u003cp\u003e14.3.2 Example of the Hermite Quintic Spline Function Supported on [−1, 1] 465\u003c\/p\u003e \u003cp\u003e14.3.3 Example of the Hermite Septimus Spline Function Supported on [−1, 1] 467\u003c\/p\u003e \u003cp\u003e14.3.4 Numerical Example of Approximation of Polynomial Function 470\u003c\/p\u003e \u003cp\u003e14.3.5 Numerical Example with Two Ruptures of the First Kind and a Corner 471\u003c\/p\u003e \u003cp\u003e14.4 Problem of Optimization of Wavelet Transformation of Hermite Splines of Any Odd Degree 475\u003c\/p\u003e \u003cp\u003e14.4.1 An Algorithm with Splitting for Wavelet Transformation of Hermite Splines of Fifth Degree 478\u003c\/p\u003e \u003cp\u003e14.4.2 Examples 485\u003c\/p\u003e \u003cp\u003e14.5 Application to Data Processing of Laser Scanning of Roads490\u003c\/p\u003e \u003cp\u003e14.5.1 Calculation of Derivatives on Samples 490\u003c\/p\u003e \u003cp\u003e14.5.2 Example of Wavelet Compression of One Track of Data of Laser Scanning 490\u003c\/p\u003e \u003cp\u003e14.5.3 Modeling of Surfaces 490\u003c\/p\u003e \u003cp\u003e14.5.4 Functions of a Package of Applied Programs for Modeling of Routes and Surfaces of Highways 492\u003c\/p\u003e \u003cp\u003e14.6 Conclusions 494\u003c\/p\u003e \u003cp\u003eReferences 494\u003c\/p\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49407017746775,"sku":"9781119242468","price":176.36,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781119242468.jpg?v=1730497891"},{"product_id":"workflows-9781119317845","title":"Workflows","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eWorkflows are being rethought and remodelled across the architecture, engineering and construction (AEC) spectrum. The synthesis of building information modelling (BIM) platforms with digital simulation techniques and increasing access to data, charting building performance, is allowing architects to engage in the generation of new workflows across multidisciplinary teams.\u003cbr\u003e\u003cbr\u003eBy merging digital design operations with construction activities, project delivery and post-occupation scenarios, architects are becoming instrumental in the shaping of buildings as well as the design process. Workflows expand the territory of architectural practice by extending designers' remit beyond the confines of the design stage. The implications for the AEC industry and architecture as a profession could not be greater. These new collaborative models are becoming as important as the novel buildings they allow us to produce.\u003cbr\u003e\u003cbr\u003eContributors include: Shajay Bhooshan, John Cays, Randy Deuts\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003eAbout the Guest-Editor 05\u003cbr\u003e\u003ci\u003eRichard Garber\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eIntroduction Digital Workflows and the Expanded Territory of the Architect 06\u003cbr\u003e\u003ci\u003eRichard Garber\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSketching with Glass\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eA Return to the Hand-Driven Workflow 14\u003cbr\u003e\u003ci\u003eSean A Gallagher\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eGeologic Workflows\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe Metamorphosis of the Great Rock 22\u003cbr\u003e\u003ci\u003ePéter Kis and Sándor Bardóczi\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eThe Fifth Dimension\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eArchitect-Led Design–Build 28\u003cbr\u003e\u003ci\u003eStacie Wong\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eMashup and Assemblage in Digital Workflows\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe Role of Integrated Software Platforms in the Production of Architecture\u003cbr\u003e\u003ci\u003eAdam Modesitt\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePutting BIM at the Heart of a Small Practice 42\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eDavid Miller\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eEncrypted Workflows\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe Secret World of Objects 48\u003cbr\u003e\u003ci\u003eRhett Russo\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eUnderstanding Architectural Workflows in Global Practice 56\u003cbr\u003e\u003c\/b\u003e\u003ci\u003eRandy Deutsch\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eExpansive Workflows\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eDownstream Coordination in the Design of Sporting Facilities 68\u003cbr\u003e\u003ci\u003eJonathan Mallie\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eFrom Pencils to Partners\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe Next Role of Computation in Building Design 74\u003cbr\u003e\u003ci\u003eIan Keough and Anthony Hauck\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCollaborative Design\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eCombining Computer-Aided Geometry Design and Building Information Modelling 82\u003cbr\u003e\u003ci\u003eShajay Bhooshan\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eRuptured Flows\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eAn Argument for Nonlinear Workflows 90\u003cbr\u003e\u003ci\u003eKutan Ayata\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eLife-Cycle Assessment\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eReducing Environmental Impact Risk with Workflow Data You Can Trust 96\u003cbr\u003e\u003ci\u003eJohn Cays\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eComing Full Circle\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eNew Ruralism 104\u003cbr\u003e\u003ci\u003eRichard Garber\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eEcological Workflows \u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eZhangdu Lake Farm, Hubei Province, China 114\u003cbr\u003e\u003ci\u003eRichard Garber\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAdvanced Engineering with Building Information Modelling\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eEstablishing Flexible Frameworks for the Design and Documentation of Complex Buildings 120\u003cbr\u003e\u003ci\u003eKen Goldup, Zak Kostura, Tabitha Tavolaro and Seth Wolfe\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eSinuous Workflows\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eMAD Architects, The Harbin Opera House 128\u003cbr\u003e\u003ci\u003eRichard Garber\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCounterpoint \u003c\/b\u003e\u003cb\u003eArchitects at the Mixing Desk\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eWorkflows Cutting Across the Whole-Life Process 136\u003cbr\u003e\u003ci\u003eDale Sinclair\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003eContributors 142\u003c\/p\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49407033246039,"sku":"9781119317845","price":25.6,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781119317845.jpg?v=1730497943"},{"product_id":"simulation-and-computational-red-teaming-for-problem-solving-9781119527176","title":"Simulation and Computational Red Teaming for","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eAn authoritative guide to computer simulation grounded in a multi-disciplinary approach for solving complex problems Simulation and Computational Red Teaming for Problem Solvingoffers a review of computer simulation that is grounded in a multi-disciplinary approach. The authors present the theoretical foundations of simulation and modeling paradigms from the perspective of an analyst. The book provides the fundamental background information needed for designing and developing consistent and useful simulations. In addition to this basic information, the authors explore several advanced topics.    The book's advanced topics demonstrate how modern artificial intelligence and computational intelligence concepts and techniques can be combined with various simulation paradigms for solving complex and critical problems. Authors examine the concept of Computational Red Teaming to reveal how the combined fundamentals and advanced techniques are used successfully for solving and testing complex real-world problems. This important book:  Demonstrates how computer simulation and Computational Red Teaming support each other for solving complex problems  Describes the main approaches to modeling real-world phenomena and embedding these models into computer simulations  Explores how a number of advanced artificial intelligence and computational intelligence concepts are used in conjunction with the fundamental aspects of simulation Written for researchers and students in the computational modelling and data analysis fields,Simulation and Computational Red Teaming for Problem Solvingcovers the foundation and the standard elements of the process of building a simulation and explores the simulation topic with a modern research approach.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003ePreface xi\u003c\/p\u003e \u003cp\u003eList of Figures xv\u003c\/p\u003e \u003cp\u003eList of Tables xxv\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart I On Problem Solving, Computational Red Teaming, and Simulation 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1. Problem Solving, Simulation, and Computational Red Teaming 3\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 Introduction 3\u003c\/p\u003e \u003cp\u003e1.2 Problem Solving 4\u003c\/p\u003e \u003cp\u003e1.3 Computational Red Teaming and Self-‘Verification and Validation’ 8\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2. Introduction to Fundamentals of Simulation 11\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction 11\u003c\/p\u003e \u003cp\u003e2.2 System 14\u003c\/p\u003e \u003cp\u003e2.3 Concepts in Simulation 17\u003c\/p\u003e \u003cp\u003e2.4 Simulation Types 21\u003c\/p\u003e \u003cp\u003e2.5 Tools for Simulation 23\u003c\/p\u003e \u003cp\u003e2.6 Conclusion 24\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart II Before Simulation Starts 25\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3. The Simulation Process 27\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction 27\u003c\/p\u003e \u003cp\u003e3.2 Define the System and its Environment 27\u003c\/p\u003e \u003cp\u003e3.3 Build a Model 29\u003c\/p\u003e \u003cp\u003e3.4 Encode a Simulator 30\u003c\/p\u003e \u003cp\u003e3.5 Design Sampling Mechanisms 32\u003c\/p\u003e \u003cp\u003e3.6 Run Simulator Under Different Samples 33\u003c\/p\u003e \u003cp\u003e3.7 Summarise Results 33\u003c\/p\u003e \u003cp\u003e3.8 Make a Recommendation 34\u003c\/p\u003e \u003cp\u003e3.9 An Evolutionary Approach 35\u003c\/p\u003e \u003cp\u003e3.10 A Battle Simulation by Lanchester Square Law 35\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4. Simulation Worldview and Conflict Resolution 57\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 Simulation Worldview 57\u003c\/p\u003e \u003cp\u003e4.2 Simultaneous Events and Conflicts in Simulation 64\u003c\/p\u003e \u003cp\u003e4.3 Priority Queue and Binary Heap 68\u003c\/p\u003e \u003cp\u003e4.4 Conclusion 72\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5. The Language of Abstraction and Representation 73\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction 73\u003c\/p\u003e \u003cp\u003e5.2 Informal Representation 75\u003c\/p\u003e \u003cp\u003e5.3 Semi-formal Representation 76\u003c\/p\u003e \u003cp\u003e5.4 Formal Representation 82\u003c\/p\u003e \u003cp\u003e5.5 Finite-state Machine 86\u003c\/p\u003e \u003cp\u003e5.6 Ant in Maze Modelled by Finite-state Machine 89\u003c\/p\u003e \u003cp\u003e5.7 Conclusion 99\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6. Experimental Design 101\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction 101\u003c\/p\u003e \u003cp\u003e6.2 Factor Screening 103\u003c\/p\u003e \u003cp\u003e6.3 Metamodel and Response Surface 113\u003c\/p\u003e \u003cp\u003e6.4 Input Sampling 116\u003c\/p\u003e \u003cp\u003e6.5 Output Analysis 117\u003c\/p\u003e \u003cp\u003e6.6 Conclusion 120\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart III Simulation Methodologies 121\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7. Discrete Event Simulation 123\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 Discrete Event Systems 123\u003c\/p\u003e \u003cp\u003e7.2 Discrete Event Simulation 126\u003c\/p\u003e \u003cp\u003e7.3 Conclusion 142\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8. Discrete Time Simulation 143\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction 143\u003c\/p\u003e \u003cp\u003e8.2 Discrete Time System and Modelling 145\u003c\/p\u003e \u003cp\u003e8.3 Sample Path 148\u003c\/p\u003e \u003cp\u003e8.4 Discrete Time Simulation and Discrete Event Simulation 149\u003c\/p\u003e \u003cp\u003e8.5 A Case Study: Car-following Model 151\u003c\/p\u003e \u003cp\u003e8.6 Conclusion 154\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9. Continuous Simulation 157\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1 Continuous System 157\u003c\/p\u003e \u003cp\u003e9.2 Continuous Simulation 159\u003c\/p\u003e \u003cp\u003e9.3 Numerical Solution Techniques for Continuous Simulation 164\u003c\/p\u003e \u003cp\u003e9.4 System Dynamics Approach 172\u003c\/p\u003e \u003cp\u003e9.5 Combined Discrete–continuous Simulation 174\u003c\/p\u003e \u003cp\u003e9.6 Conclusion 176\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10. Agent-based Simulation 179\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10.1 Introduction 179\u003c\/p\u003e \u003cp\u003e10.2 Agent-based Simulation 181\u003c\/p\u003e \u003cp\u003e10.3 Examples of Agent-based Simulation 185\u003c\/p\u003e \u003cp\u003e10.4 Conclusion 194\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart IV Simulation and Computational Red Teaming Systems 197\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11. Knowledge Acquisition 199\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e11.1 Introduction 199\u003c\/p\u003e \u003cp\u003e11.2 Agent-enabled Knowledge Acquisition: Core Processes 202\u003c\/p\u003e \u003cp\u003e11.3 Human Agents 203\u003c\/p\u003e \u003cp\u003e11.4 Human-inspired Agents 208\u003c\/p\u003e \u003cp\u003e11.5 Machine Agents 211\u003c\/p\u003e \u003cp\u003e11.6 Summary Discussion and Perspectives on Knowledge Acquisition 215\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12. Computational Intelligence 219\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e12.1 Introduction 219\u003c\/p\u003e \u003cp\u003e12.2 Evolutionary Computation 223\u003c\/p\u003e \u003cp\u003e12.3 Artificial Neural Networks 232\u003c\/p\u003e \u003cp\u003e12.4 Conclusion 239\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13. Computational Red Teaming 241\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e13.1 Introduction 241\u003c\/p\u003e \u003cp\u003e13.2 Computational Red Teaming: The Challenge Loop 242\u003c\/p\u003e \u003cp\u003e13.3 Computational Red Teaming Objects 243\u003c\/p\u003e \u003cp\u003e13.4 Computational Red Teaming Purposes 244\u003c\/p\u003e \u003cp\u003e13.5 Objectives of Red Teaming Exercises in Computational Red Teaming Purposes 245\u003c\/p\u003e \u003cp\u003e13.6 Discovering Biases 246\u003c\/p\u003e \u003cp\u003e13.7 Computational Red Teaming Lifecycle: A Systematic Approach to Red Teaming Exercises 247\u003c\/p\u003e \u003cp\u003e13.8 Conclusion 251\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart V Simulation and Computational Red Teaming Applications 253\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14. Computational Red Teaming for Battlefield Management 255\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e14.1 Introduction 255\u003c\/p\u003e \u003cp\u003e14.2 Battlefield Management Simulation 256\u003c\/p\u003e \u003cp\u003e14.3 Conclusion 261\u003c\/p\u003e \u003cp\u003e\u003cb\u003e15. Computational Red Teaming for Air Traffic Management 263\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e15.1 Introduction 263\u003c\/p\u003e \u003cp\u003e15.2 Air Traffic Simulation 263\u003c\/p\u003e \u003cp\u003e15.3 A Human-in-the-loop Application 270\u003c\/p\u003e \u003cp\u003e15.4 Conclusion 271\u003c\/p\u003e \u003cp\u003e\u003cb\u003e16. Computational Red Teaming Application for Skill-based Performance Assessment 273\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e16.1 Introduction 273\u003c\/p\u003e \u003cp\u003e16.2 Cognitive Task Analysis-based Skill Modelling and Assessment Methodology 274\u003c\/p\u003e \u003cp\u003e16.3 Sudoku and Human Players 276\u003c\/p\u003e \u003cp\u003e16.4 Sudoku and Computational Solvers 280\u003c\/p\u003e \u003cp\u003e16.5 The Proposed Skill-based Computational Solver 283\u003c\/p\u003e \u003cp\u003e16.6 Discussion of Simulation Results 293\u003c\/p\u003e \u003cp\u003e16.7 Conclusions 300\u003c\/p\u003e \u003cp\u003e\u003cb\u003e17. Computational Red Teaming for Driver Assessment 301\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e17.1 Introduction 301\u003c\/p\u003e \u003cp\u003e17.2 Background on Cognitive Agents 303\u003c\/p\u003e \u003cp\u003e17.3 The Society of Mind Agent 306\u003c\/p\u003e \u003cp\u003e17.4 Society of Mind Agents in an Artificial Environment 312\u003c\/p\u003e \u003cp\u003e17.5 Case Study 325\u003c\/p\u003e \u003cp\u003e17.6 Conclusion 330\u003c\/p\u003e \u003cp\u003e\u003cb\u003e18. Computational Red Teaming for Trusted Autonomous Systems 333\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e18.1 Introduction 333\u003c\/p\u003e \u003cp\u003e18.2 Trust for Influence and Shaping 334\u003c\/p\u003e \u003cp\u003e18.3 The Model 335\u003c\/p\u003e \u003cp\u003e18.4 Experiment Design and Parameter Settings 342\u003c\/p\u003e \u003cp\u003e18.5 Results and Discussion 344\u003c\/p\u003e \u003cp\u003e18.6 Conclusion 347\u003c\/p\u003e \u003cp\u003e\u003cb\u003eA. Probability and Statistics in Simulation 349\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eA.1 Foundation of Probability and Statistics 349\u003c\/p\u003e \u003cp\u003eA.2 Useful Distributions 369\u003c\/p\u003e \u003cp\u003eA.3 Mathematical Characteristics of Random Variables 390\u003c\/p\u003e \u003cp\u003eA.4 Conclusion 396\u003c\/p\u003e \u003cp\u003e\u003cb\u003eB Sampling and Random Numbers 397\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eB.1 Introduction 397\u003c\/p\u003e \u003cp\u003eB.2 Random Number Generator 400\u003c\/p\u003e \u003cp\u003eB.3 Testing Random Number Generators 408\u003c\/p\u003e \u003cp\u003eB.4 Approaches to Generating Random Variates 413\u003c\/p\u003e \u003cp\u003eB.5 Generating Random Variates 416\u003c\/p\u003e \u003cp\u003eB.6 Monte Carlo Method 423\u003c\/p\u003e \u003cp\u003eB.7 Conclusion 432\u003c\/p\u003e \u003cp\u003eBibliography 435\u003c\/p\u003e \u003cp\u003eIndex 459\u003c\/p\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49407073419607,"sku":"9781119527176","price":108.86,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781119527176.jpg?v=1730498085"},{"product_id":"airport-building-information-modelling-9781138329331","title":"Airport Building Information Modelling","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eThis book details how Building Information Modelling is being successfully deployed in the planning, design, construction and future operation of the Istanbul New Airport, a mega-scale construction project incorporating a varying mix of infrastructures including terminals, runways, passenger gates, car parks, railways and roads. The book demonstrates how Airport Building Information Modelling (ABIM) is being used to:\u003c\/p\u003e\u003cp\u003e facilitate collaboration, cooperation and integrated project delivery \u003c\/p\u003e\u003cp\u003e manage subcontractors and eliminate cost over-runs \u003c\/p\u003e\u003cp\u003e reduce waste on site and enhance overall quality\u003c\/p\u003e\u003cp\u003e connect people in a virtual environment to encourage collaborative working \u003c\/p\u003e\u003cp\u003e provide clients with an effective interface for lifecycle management including: design development, construction documentation, construction phases and BIM and Big Data Integration for future facilities management\u003c\/p\u003e\u003cp\u003eThe book presents a best practice BIM project, demonstrating concurrent e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e1\u003c\/p\u003e\u003cp\u003eINTRODUCTION\u003c\/p\u003e\u003cp\u003e2\u003c\/p\u003e\u003cp\u003eAIRPORT DESIGN AND CONSTRUCTION\u003c\/p\u003e\u003cp\u003e3\u003c\/p\u003e\u003cp\u003eAIRPORT BUILDING INFORMATION MODELLING\u003c\/p\u003e\u003cp\u003e4\u003c\/p\u003e\u003cp\u003eCONCURRENT DESIGN AND CONSTRUCTION WITH BIM\u003c\/p\u003e\u003cp\u003e5\u003c\/p\u003e\u003cp\u003eMOBILE BIM FOR THE AIRPORT CONSTRUCTION\u003c\/p\u003e\u003cp\u003e6\u003c\/p\u003e\u003cp\u003eKEY LEARNINGS ABOUT ABIM AND PAVING THE WAY FOR THE AIRPORT OPERATIONS \u003c\/p\u003e\u003cp\u003e7\u003c\/p\u003e\u003cp\u003eCONCLUSION\u003c\/p\u003e","brand":"Taylor \u0026 Francis Ltd","offers":[{"title":"Default Title","offer_id":49407218647383,"sku":"9781138329331","price":124.87,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781138329331.jpg?v=1730498610"},{"product_id":"simulating-innovation-computer-based-tools-for-rethinking-innovation-9781783472451","title":"Simulating Innovation: Computer-based Tools for","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eThis book brings together computer models and simulation approaches that allow the investigation of a wide range of innovation related issues, and hence will be of interest for academics and researchers from a variety of innovation related disciplines.\u003c\/i\u003e'\u003cbr\u003e- Mercedes Bleda, Journal of Artificial Societies and Social Simulation\u003cp\u003eChristopher Watts and Nigel Gilbert explore the generation, diffusion and impact of innovations, which can now be studied using computer simulations.\u003c\/p\u003e\u003cp\u003eAgent-based simulation models can be used to explain the innovation that emerges from interactions among complex, adaptive, diverse networks of firms, people, technologies, practices and resources. This book provides a critical review of recent advances in agent-based modeling and other forms of the simulation of innovation. Elements explored include: diffusion of innovations, social networks, organizational learning, science models, adopting and adapting, and technological evolution and innovation networks. Many of the models featured in the book can be downloaded from the book's accompanying website.\u003c\/p\u003e\u003cp\u003eBringing together simulation models from several innovation-related fields, this book will prove a fascinating read for academics and researchers in a wide range of disciplines, including: innovation studies, evolutionary economics, complexity science, organization studies, social networks, and science and technology studies. Scholars and researchers in the areas of computer science, operational research and management science will also be interested in the uses of simulation models to improve the understanding of organization.\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003eThis book brings together computer models and simulation approaches that allow the investigation of a wide range of innovation related issues, and hence will be of interest for academics and researchers from a variety of innovation related disciplines. --\u003cbr\u003e- Mercedes Bleda, \u003ci\u003eJournal of Artificial Societies and Social Simulation\u003c\/i\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003eContents: Preface  1. Why Simulate Innovation?  2. The Variability and Variety of Diffusion Models  3. Diffusion and Path Dependence in a Social Network  4. Explore and Exploit  5. Science Models  6. Adopting and Adapting: Innovation Diffusion in Complex Contexts  7. Technological Evolution and Innovation Networks  8. Conclusions   Bibliography","brand":"Edward Elgar Publishing Ltd","offers":[{"title":"Default Title","offer_id":49412044226903,"sku":"9781783472451","price":35.95,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781783472451.jpg?v=1730515474"},{"product_id":"ecosystems-knowledge-modeling-and-analysis-method-for-information-and-communication-9781786300645","title":"Ecosystems Knowledge: Modeling and Analysis","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eTo analyze complex situations we use everyday analogies that allow us to invest in an unknown domain knowledge we have acquired in a known field. In this work the author proposes a modeling and analysis method that uses the analogy of the ecosystem to embrace the complexity of an area of knowledge. After a history of the ecosystem concept and these derivatives (nature, ecology, environment ) from antiquity to the present, the analysis method based on the modeling of socio-semantic ontologies is presented, followed by practical examples of this approach in the areas of software development, digital humanities, Big Data, and more generally in the area of complex analysis.\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eIntroduction ix\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 1. Use of the Ecosystem Concept on the Web 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1. For marketing 2\u003c\/p\u003e \u003cp\u003e1.2. For personal data 4\u003c\/p\u003e \u003cp\u003e1.3. For services and applications 5\u003c\/p\u003e \u003cp\u003e1.4. For dynamic interactivity 7\u003c\/p\u003e \u003cp\u003e1.5. For pictorial analogies 8\u003c\/p\u003e \u003cp\u003e1.6. For the information and communication sciences 12\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 2. Ecosystem Modeling: A Generic Method of Analysis 15\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1. Hypertextual gardening fertilized by the chaos of John Cage 16\u003c\/p\u003e \u003cp\u003e2.2. An entrepreneurial experience 17\u003c\/p\u003e \u003cp\u003e2.2.1. Objectives 18\u003c\/p\u003e \u003cp\u003e2.2.2. Principle of the game 18\u003c\/p\u003e \u003cp\u003e2.2.3. Motivations 19\u003c\/p\u003e \u003cp\u003e2.2.3.1. Why model a cognitive ecology? 19\u003c\/p\u003e \u003cp\u003e2.2.3.2. The relevance of the garden analogy 20\u003c\/p\u003e \u003cp\u003e2.2.4. Strategic interests and potential benefits 23\u003c\/p\u003e \u003cp\u003e2.3. The maturation of a research project 24\u003c\/p\u003e \u003cp\u003e2.3.1. Evaluating index activity 24\u003c\/p\u003e \u003cp\u003e2.3.2. Folksonomies explorer 28\u003c\/p\u003e \u003cp\u003e2.3.3. Tweet Palette: Semantic mapping 34\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 3. Fundamental Principles for Modeling an Existence 41\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1. Key concepts for thinking about knowledge ecosystems 42\u003c\/p\u003e \u003cp\u003e3.1.1. The noosphere 42\u003c\/p\u003e \u003cp\u003e3.1.2. Enaction 44\u003c\/p\u003e \u003cp\u003e3.1.3. Complexity 45\u003c\/p\u003e \u003cp\u003e3.1.4. Trajective reason 46\u003c\/p\u003e \u003cp\u003e3.1.5. Agency 47\u003c\/p\u003e \u003cp\u003e3.2. Spinozist principles for an ethical ontology 48\u003c\/p\u003e \u003cp\u003e3.2.1. Spinoza: ethical ontology 49\u003c\/p\u003e \u003cp\u003e3.2.2. Limitations of Spinozism 50\u003c\/p\u003e \u003cp\u003e3.2.3. Three dimensions of existence and three kinds of knowledge 51\u003c\/p\u003e \u003cp\u003e3.2.4. Spinozist symbol politics 55\u003c\/p\u003e \u003cp\u003e3.2.5. Spinozist ethics for the Web 57\u003c\/p\u003e \u003cp\u003e3.2.6. The ontological principles of Descola 58\u003c\/p\u003e \u003cp\u003e3.2.7. Principles of ontological matrices 59\u003c\/p\u003e \u003cp\u003e3.2.8. The Web as analogist ontology 63\u003c\/p\u003e \u003cp\u003e3.2.9. Principles of computer models 67\u003c\/p\u003e \u003cp\u003e3.2.10. From Zeno to Turing via Spinoza 68\u003c\/p\u003e \u003cp\u003e3.2.11. The search for the perfect language 74\u003c\/p\u003e \u003cp\u003e3.3. Semantic knowledge management 77\u003c\/p\u003e \u003cp\u003e3.3.1. The boundaries of ontologies 77\u003c\/p\u003e \u003cp\u003e3.3.2. The semantic sphere IEML 78\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 4. Graphical Specifications for Modeling Existences 89\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1. Principles of graphical modeling 90\u003c\/p\u003e \u003cp\u003e4.1.1. Unified modeling language 90\u003c\/p\u003e \u003cp\u003e4.1.2. Graphic partitions and diagrams 92\u003c\/p\u003e \u003cp\u003e4.1.3. Fixed image versus dynamic diagram 94\u003c\/p\u003e \u003cp\u003e4.2. Semantic maps 97\u003c\/p\u003e \u003cp\u003e4.2.1. Maps of physical spaces 97\u003c\/p\u003e \u003cp\u003e4.2.2. Time maps 99\u003c\/p\u003e \u003cp\u003e4.2.3. Maps of conceptual spaces 101\u003c\/p\u003e \u003cp\u003e4.2.4. Interpretation maps 107\u003c\/p\u003e \u003cp\u003e4.3. Graphical modeling rules 110\u003c\/p\u003e \u003cp\u003e4.3.1. Physical dimensions 110\u003c\/p\u003e \u003cp\u003e4.3.2. Actors 111\u003c\/p\u003e \u003cp\u003e4.3.3. Concepts 111\u003c\/p\u003e \u003cp\u003e4.3.4. Relations 112\u003c\/p\u003e \u003cp\u003e4.3.5. Calculating the complexity of an ecosystem 113\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 5. Web Platform Specifications for Knowledge Ecosystems 117\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1. The generic management of resources 119\u003c\/p\u003e \u003cp\u003e5.1.1. Non-digital resources 119\u003c\/p\u003e \u003cp\u003e5.1.2. Digital resources 122\u003c\/p\u003e \u003cp\u003e5.1.3. Management of digital resources 131\u003c\/p\u003e \u003cp\u003e5.2. Principles for developing a Web ecosystem platform 138\u003c\/p\u003e \u003cp\u003e5.2.1. Databases as a model of the ecosystem 138\u003c\/p\u003e \u003cp\u003e5.2.2. Algorithmic platform to manage the ecosystem 153\u003c\/p\u003e \u003cp\u003e5.2.3. Editorial platform for controlling collaborative practices 157\u003c\/p\u003e \u003cp\u003e5.2.4. Client applications to explore ecosystem views 162\u003c\/p\u003e \u003cp\u003e5.2.5. From technical specification to the organization of collective intelligence 171\u003c\/p\u003e \u003cp\u003eConclusion 173\u003c\/p\u003e \u003cp\u003eAppendix 185\u003c\/p\u003e \u003cp\u003eBibliography 201\u003c\/p\u003e \u003cp\u003eIndex 217\u003c\/p\u003e","brand":"ISTE Ltd and John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49412271440215,"sku":"9781786300645","price":125.06,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781786300645.jpg?v=1730516217"},{"product_id":"virtual-work-approach-to-mechanical-modeling-9781786302953","title":"Virtual Work Approach to Mechanical Modeling","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eThis book is centred about the Principle of virtual work and the related method for mechanical modelling. It aims at showing and enhancing the polyvalence and versatility of the virtual work approach in the mechanical modelling process. The virtual work statement is set as the principle at the root of a force modelling method that can be implemented on any geometrical description. After experimentally induced hypotheses have been made on the geometrical parameters that describe the concerned system and subsystems, the method provides a unifying framework for building up consistently associated force models where external and internal forces are introduced through their virtual rates of work. Systems described as three-dimensional, curvilinear or planar continua are considered: force models are established with the corresponding equations of motion; the validation process points out that enlarging the domain of relevance of the model for practical applications calls for an enrichment of the geometrical description that takes into account the underlying microstructure.\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eNotice to Readers iii\u003c\/p\u003e \u003cp\u003eAbout the Authors v\u003c\/p\u003e \u003cp\u003ePreface vii\u003c\/p\u003e \u003cp\u003eAcknowledgments ix\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Increased Complexity and Mounting Challenges: Time to Prepare 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eCall to Action 6\u003c\/p\u003e \u003cp\u003eConclusion 6\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Roles of the Board and Management 9\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eGovernance in the 21st Century 10\u003c\/p\u003e \u003cp\u003ePurpose of the Governing Board 11\u003c\/p\u003e \u003cp\u003eBoard Committees 12\u003c\/p\u003e \u003cp\u003eLegal Responsibilities of the Board 13\u003c\/p\u003e \u003cp\u003eLesson Learned 13\u003c\/p\u003e \u003cp\u003eLesson Learned 13\u003c\/p\u003e \u003cp\u003eLesson Learned 14\u003c\/p\u003e \u003cp\u003eIRS Form 990 and Governance 14\u003c\/p\u003e \u003cp\u003eFrameworks for Good Governance 15\u003c\/p\u003e \u003cp\u003ePanel on the Nonprofit Sector Framework—Good Governance Model 16\u003c\/p\u003e \u003cp\u003eLegal Compliance and Public Disclosure 17\u003c\/p\u003e \u003cp\u003eEffective Governance 20\u003c\/p\u003e \u003cp\u003eConclusion 30\u003c\/p\u003e \u003cp\u003eAppendix A—Comparison of Key Objectives of the Board of Directors With the Good Governance Framework and Questions From IRS Form 990 32\u003c\/p\u003e \u003cp\u003eAppendix B—Example Dashboard for Board Evaluation 35\u003c\/p\u003e \u003cp\u003eAppendix C—Sample Board Self-Assessment Document 37\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Legal and Ethical Imperatives for Leadership 39\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eLegal Accountability 40\u003c\/p\u003e \u003cp\u003eEthical Accountability 41\u003c\/p\u003e \u003cp\u003eWho is Accountable for Accountability? 43\u003c\/p\u003e \u003cp\u003eHow to Instill Ethical and Legal Accountability 44\u003c\/p\u003e \u003cp\u003eHonest Communications 44\u003c\/p\u003e \u003cp\u003eStrong Relationships 44\u003c\/p\u003e \u003cp\u003eInternal Controls 45\u003c\/p\u003e \u003cp\u003eClear Expectations 45\u003c\/p\u003e \u003cp\u003eSkilled Boards 45\u003c\/p\u003e \u003cp\u003eInvolved and Informed Boards 45\u003c\/p\u003e \u003cp\u003eFinancial, Document, and Ethics Audits 45\u003c\/p\u003e \u003cp\u003eCompliance Officers 46\u003c\/p\u003e \u003cp\u003eResolving Dilemmas 46\u003c\/p\u003e \u003cp\u003eWhat About WholeHealth? 48\u003c\/p\u003e \u003cp\u003eConclusion 49\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 When Management and the Governing Board Disagree 51\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe Head Game 52\u003c\/p\u003e \u003cp\u003eCommunication 53\u003c\/p\u003e \u003cp\u003eConstructive Norms 55\u003c\/p\u003e \u003cp\u003eNegotiation 57\u003c\/p\u003e \u003cp\u003eAssisted Resolution 59\u003c\/p\u003e \u003cp\u003eConclusion 60\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Understanding the Financial Statements of Nonprofit Organizations 61\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eCharacteristics of Nonprofits 62\u003c\/p\u003e \u003cp\u003eResponsibility for Financial Information 62\u003c\/p\u003e \u003cp\u003eBasis of Presentation for Financial Information 63\u003c\/p\u003e \u003cp\u003eCash Basis of Accounting Versus Accrual Basis 63\u003c\/p\u003e \u003cp\u003eBasic Financial Statements 64\u003c\/p\u003e \u003cp\u003eFootnotes to the Financial Statements 65\u003c\/p\u003e \u003cp\u003eFund Accounting 66\u003c\/p\u003e \u003cp\u003eAssets 70\u003c\/p\u003e \u003cp\u003eLiquidity 70\u003c\/p\u003e \u003cp\u003eCash and Cash Equivalents 71\u003c\/p\u003e \u003cp\u003eRevenue, Receivables, and Deferred Revenue 72\u003c\/p\u003e \u003cp\u003eIn-Kind Contributions 75\u003c\/p\u003e \u003cp\u003eLong Term Contributions 76\u003c\/p\u003e \u003cp\u003eConditional Promises to Give 77\u003c\/p\u003e \u003cp\u003eEndowments 78\u003c\/p\u003e \u003cp\u003eSplit Interest Agreements 79\u003c\/p\u003e \u003cp\u003eAgency Transactions 81\u003c\/p\u003e \u003cp\u003eNonprofit Serves as a Conduit for Cash or Noncash Donations 81\u003c\/p\u003e \u003cp\u003eNonprofit Solicits Funds for Another Nonprofit Organization (Unrelated) 82\u003c\/p\u003e \u003cp\u003eNonprofit Holds Funds for Another Nonprofit Organization (Unrelated) 82\u003c\/p\u003e \u003cp\u003eNonprofit Enters Into Transactions With Related Foundations 83\u003c\/p\u003e \u003cp\u003eInventories 83\u003c\/p\u003e \u003cp\u003ePrepaid Expenses and Investments 84\u003c\/p\u003e \u003cp\u003eAlternative Investments 84\u003c\/p\u003e \u003cp\u003eProperty and Equipment 85\u003c\/p\u003e \u003cp\u003eLiabilities 85\u003c\/p\u003e \u003cp\u003eAccounts Payable and Accrued Expenses 85\u003c\/p\u003e \u003cp\u003eMortgages and Notes Payable 86\u003c\/p\u003e \u003cp\u003eNet Assets 86\u003c\/p\u003e \u003cp\u003eRevenues and Expenses 86\u003c\/p\u003e \u003cp\u003eConclusion 87\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Risk Management 89\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eSome Risks Can Be Mitigated With Insurance 89\u003c\/p\u003e \u003cp\u003eCyber Risk—A Growing Threat 90\u003c\/p\u003e \u003cp\u003eRisk in a Complex World 90\u003c\/p\u003e \u003cp\u003eA Nonprofit’s Most Important Resource 91\u003c\/p\u003e \u003cp\u003eRisk Management Approach 93\u003c\/p\u003e \u003cp\u003eEnterprise Risk Management 93\u003c\/p\u003e \u003cp\u003eERM Component One 94\u003c\/p\u003e \u003cp\u003eERM Component Two 94\u003c\/p\u003e \u003cp\u003eERM Component Three 94\u003c\/p\u003e \u003cp\u003eERM Component Four 95\u003c\/p\u003e \u003cp\u003eERM Component Five 96\u003c\/p\u003e \u003cp\u003eERM Component Six 96\u003c\/p\u003e \u003cp\u003eERM Component Seven 99\u003c\/p\u003e \u003cp\u003eExample Application of a Risk Management System to a Nonprofit Organization 99\u003c\/p\u003e \u003cp\u003eERM in Smaller Nonprofit Organizations 102\u003c\/p\u003e \u003cp\u003eRisk Management Committee 103\u003c\/p\u003e \u003cp\u003eCrisis Management 104\u003c\/p\u003e \u003cp\u003eRevisiting Uncertainty 105\u003c\/p\u003e \u003cp\u003eConclusion 105\u003c\/p\u003e \u003cp\u003eAppendix A—Risk Management Checklist 107\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Internal Controls: What Every Executive and Board Member Needs to Know 113\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eCharacteristics of Nonprofits 113\u003c\/p\u003e \u003cp\u003eInternal Control Defined 114\u003c\/p\u003e \u003cp\u003eCOSO Framework Updated for Changing Times 115\u003c\/p\u003e \u003cp\u003eDistinguishing Error From Fraud 116\u003c\/p\u003e \u003cp\u003eControls for Smaller Organizations 118\u003c\/p\u003e \u003cp\u003eElements of Internal Control 119\u003c\/p\u003e \u003cp\u003eControl Activities 121\u003c\/p\u003e \u003cp\u003eDesigning a System of Internal Control 123\u003c\/p\u003e \u003cp\u003eEntity Controls 123\u003c\/p\u003e \u003cp\u003eControl Activities 127\u003c\/p\u003e \u003cp\u003eAntifraud Programs and Controls 131\u003c\/p\u003e \u003cp\u003eMisappropriation of Assets 131\u003c\/p\u003e \u003cp\u003eFraudulent Financial Reporting 132\u003c\/p\u003e \u003cp\u003eRevenue Recognition and Management Override 132\u003c\/p\u003e \u003cp\u003eControl Environment 133\u003c\/p\u003e \u003cp\u003eFraud Risk Assessment 133\u003c\/p\u003e \u003cp\u003eInformation and Communication 133\u003c\/p\u003e \u003cp\u003eMonitoring 134\u003c\/p\u003e \u003cp\u003eBilling Schemes, Check Tampering, and Expense Fraud 136\u003c\/p\u003e \u003cp\u003eUse of Analytical Techniques to Identify Unusual Disbursement Transactions for Investigation 140\u003c\/p\u003e \u003cp\u003eSkimming and Larceny 141\u003c\/p\u003e \u003cp\u003ePayroll Fraud 143\u003c\/p\u003e \u003cp\u003eControls Over Noncash Items 146\u003c\/p\u003e \u003cp\u003eWhen Processing Is Outsourced 146\u003c\/p\u003e \u003cp\u003eCybersecurity and Not-for-Profits 147\u003c\/p\u003e \u003cp\u003eInternal Controls Evolve 148\u003c\/p\u003e \u003cp\u003eConclusion 149\u003c\/p\u003e \u003cp\u003eAppendix A—2013 COSO Framework 17 Principles—Summary 150\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Focus on Tax-Exempt Status 155\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eNonprofit Organizations and Tax-Exempt Status 156\u003c\/p\u003e \u003cp\u003eIRS Filings 157\u003c\/p\u003e \u003cp\u003eDifferences Between Nonprofit and Commercial Organizations 158\u003c\/p\u003e \u003cp\u003eRecognition of Tax-Exempt Status 162\u003c\/p\u003e \u003cp\u003eLobbying 164\u003c\/p\u003e \u003cp\u003ePublic Charity or Private Foundation 166\u003c\/p\u003e \u003cp\u003ePublic Support Test for Charitable Organizations 167\u003c\/p\u003e \u003cp\u003eTest 1 (509(a)(1))—Compute the Public Support Percentage 168\u003c\/p\u003e \u003cp\u003eTest 2 (509(a)(2))—Compute the Public Support Percentage 169\u003c\/p\u003e \u003cp\u003eSupporting Organizations 170\u003c\/p\u003e \u003cp\u003eCharitable Contributions 172\u003c\/p\u003e \u003cp\u003eFiling Form 990 175\u003c\/p\u003e \u003cp\u003eUnrelated Business Income 177\u003c\/p\u003e \u003cp\u003eIRS Audits 179\u003c\/p\u003e \u003cp\u003eConclusion 180\u003c\/p\u003e \u003cp\u003eAppendix A—Guide for the Board’s Review of Form 990 181\u003c\/p\u003e \u003cp\u003eAppendix B—Important Filings for Tax-Exempt Organizations 185\u003c\/p\u003e \u003cp\u003eAppendix C—Governance Policies and Procedures 188\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 The Courage to Lead 189\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eMoral Courage 189\u003c\/p\u003e \u003cp\u003eBarriers to Ethical Action 191\u003c\/p\u003e \u003cp\u003eStrategies for Ethical Action 194\u003c\/p\u003e \u003cp\u003eHave a Clear Compass 194\u003c\/p\u003e \u003cp\u003eKnow Your Objective 195\u003c\/p\u003e \u003cp\u003eSeek Advisers and Allies 195\u003c\/p\u003e \u003cp\u003eWalk the Walk 196\u003c\/p\u003e \u003cp\u003eUnderstand Change Strategies 196\u003c\/p\u003e \u003cp\u003ePractice Considerate Communication 197\u003c\/p\u003e \u003cp\u003eConclusion 197\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Change Management 199\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eUnderstanding Change 200\u003c\/p\u003e \u003cp\u003eBe Clear About What You Want 202\u003c\/p\u003e \u003cp\u003eAssess Before You Act 203\u003c\/p\u003e \u003cp\u003eCreate Awareness and Urgency 204\u003c\/p\u003e \u003cp\u003eCreate a Powerful Coalition 205\u003c\/p\u003e \u003cp\u003eCommunicate 207\u003c\/p\u003e \u003cp\u003eAddress Obstacles and Blockers 208\u003c\/p\u003e \u003cp\u003eCreate Short TermWins 210\u003c\/p\u003e \u003cp\u003eGive People the Tools to Succeed 210\u003c\/p\u003e \u003cp\u003eSolidify Changes 211\u003c\/p\u003e \u003cp\u003eSuggestions for Sonja 212\u003c\/p\u003e \u003cp\u003eBe Clear About What You Want 212\u003c\/p\u003e \u003cp\u003eAssess Before You Act 212\u003c\/p\u003e \u003cp\u003eCreate Awareness and Urgency 213\u003c\/p\u003e \u003cp\u003eCreate a Powerful Coalition 214\u003c\/p\u003e \u003cp\u003eAddress Obstacles 214\u003c\/p\u003e \u003cp\u003eCommunicate 215\u003c\/p\u003e \u003cp\u003eCreate Short Term Wins 215\u003c\/p\u003e \u003cp\u003eGive People the Tools to Succeed 215\u003c\/p\u003e \u003cp\u003eSolidify Changes 215\u003c\/p\u003e \u003cp\u003eConclusion 215\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Integration for Action 217\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eCase One: AWoman Scorned 217\u003c\/p\u003e \u003cp\u003ePrevent 218\u003c\/p\u003e \u003cp\u003eAddress 219\u003c\/p\u003e \u003cp\u003eImprove 220\u003c\/p\u003e \u003cp\u003eCase Two: The Indeterminate Sentence 221\u003c\/p\u003e \u003cp\u003ePrevent 222\u003c\/p\u003e \u003cp\u003eAddress 225\u003c\/p\u003e \u003cp\u003eImprove 225\u003c\/p\u003e \u003cp\u003eCase Three: Your Turn 226\u003c\/p\u003e \u003cp\u003eSustained Success 227\u003c\/p\u003e \u003cp\u003eConclusion 227\u003c\/p\u003e \u003cp\u003eGlossary 229\u003c\/p\u003e \u003cp\u003eBibliography 235\u003c\/p\u003e \u003cp\u003eSuggested Reading 239\u003c\/p\u003e","brand":"ISTE Ltd and John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49412277469527,"sku":"9781786302953","price":125.06,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781786302953.jpg?v=1730516238"},{"product_id":"performance-evaluation-by-simulation-and-analysis-with-applications-to-computer-networks-9781848217478","title":"Performance Evaluation by Simulation and Analysis","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eThis book is devoted to the most used methodologies for performance evaluation: simulation using specialized software and mathematical modeling. An important part is dedicated to the simulation, particularly in its theoretical framework and the precautions to be taken in the implementation of the experimental procedure.  These principles are illustrated by concrete examples achieved through operational simulation languages ​​(OMNeT ++, OPNET). Presented under the complementary approach, the mathematical method is essential for the simulation. Both methodologies based largely on the theory of probability and statistics in general and particularly Markov processes, a reminder of the basic results is also available.\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eLIST OF TABLES xv\u003c\/p\u003e \u003cp\u003eLIST OF FIGURES xvii\u003c\/p\u003e \u003cp\u003eLIST OF LISTINGS xxi\u003c\/p\u003e \u003cp\u003ePREFACE xxiii\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 1. PERFORMANCE EVALUATION 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1. Performance evaluation 1\u003c\/p\u003e \u003cp\u003e1.2. Performance versus resources provisioning 3\u003c\/p\u003e \u003cp\u003e1.2.1. Performance indicators 3\u003c\/p\u003e \u003cp\u003e1.2.2. Resources provisioning 4\u003c\/p\u003e \u003cp\u003e1.3. Methods of performance evaluation 4\u003c\/p\u003e \u003cp\u003e1.3.1. Direct study 4\u003c\/p\u003e \u003cp\u003e1.3.2. Modeling 5\u003c\/p\u003e \u003cp\u003e1.4. Modeling 6\u003c\/p\u003e \u003cp\u003e1.4.1. Shortcomings 6\u003c\/p\u003e \u003cp\u003e1.4.2. Advantages 7\u003c\/p\u003e \u003cp\u003e1.4.3. Cost of modeling 7\u003c\/p\u003e \u003cp\u003e1.5. Types of modeling 8\u003c\/p\u003e \u003cp\u003e1.6. Analytical modeling versus simulation 8\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART 1. SIMULATION 11\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 2. INTRODUCTION TO SIMULATION 13\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1. Presentation 13\u003c\/p\u003e \u003cp\u003e2.2. Principle of discrete event simulation 15\u003c\/p\u003e \u003cp\u003e2.2.1. Evolution of a event-driven system 15\u003c\/p\u003e \u003cp\u003e2.2.2. Model programming 16\u003c\/p\u003e \u003cp\u003e2.3. Relationship with mathematical modeling 18\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 3. MODELING OF STOCHASTIC BEHAVIORS 21\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1. Introduction 21\u003c\/p\u003e \u003cp\u003e3.2. Identification of stochastic behavior 23\u003c\/p\u003e \u003cp\u003e3.3. Generation of random variables 24\u003c\/p\u003e \u003cp\u003e3.4. Generation of U(0, 1) r.v. 25\u003c\/p\u003e \u003cp\u003e3.4.1. Importance of U(0, 1) r.v. 25\u003c\/p\u003e \u003cp\u003e3.4.2. Von Neumann’s generator 26\u003c\/p\u003e \u003cp\u003e3.4.3. The LCG generators 28\u003c\/p\u003e \u003cp\u003e3.4.4. Advanced generators 31\u003c\/p\u003e \u003cp\u003e3.4.5. Precaution and practice 33\u003c\/p\u003e \u003cp\u003e3.5. Generation of a given distribution 35\u003c\/p\u003e \u003cp\u003e3.5.1. Inverse transformation method 35\u003c\/p\u003e \u003cp\u003e3.5.2. Acceptance–rejection method 36\u003c\/p\u003e \u003cp\u003e3.5.3. Generation of discrete r.v. 38\u003c\/p\u003e \u003cp\u003e3.5.4. Particular case 39\u003c\/p\u003e \u003cp\u003e3.6. Some commonly used distributions and their generation 40\u003c\/p\u003e \u003cp\u003e3.6.1. Uniform distribution 41\u003c\/p\u003e \u003cp\u003e3.6.2. Triangular distribution 41\u003c\/p\u003e \u003cp\u003e3.6.3. Exponential distribution 42\u003c\/p\u003e \u003cp\u003e3.6.4. Pareto distribution 43\u003c\/p\u003e \u003cp\u003e3.6.5. Normal distribution 44\u003c\/p\u003e \u003cp\u003e3.6.6. Log-normal distribution 45\u003c\/p\u003e \u003cp\u003e3.6.7. Bernoulli distribution 45\u003c\/p\u003e \u003cp\u003e3.6.8. Binomial distribution 46\u003c\/p\u003e \u003cp\u003e3.6.9. Geometric distribution 47\u003c\/p\u003e \u003cp\u003e3.6.10. Poisson distribution 48\u003c\/p\u003e \u003cp\u003e3.7. Applications to computer networks 48\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 4. SIMULATION LANGUAGES 53\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1. Simulation languages 53\u003c\/p\u003e \u003cp\u003e4.1.1. Presentation 53\u003c\/p\u003e \u003cp\u003e4.1.2. Main programming features 54\u003c\/p\u003e \u003cp\u003e4.1.3. Choice of a simulation language 54\u003c\/p\u003e \u003cp\u003e4.2. Scheduler 56\u003c\/p\u003e \u003cp\u003e4.3. Generators of random variables 57\u003c\/p\u003e \u003cp\u003e4.4. Data collection and statistics 58\u003c\/p\u003e \u003cp\u003e4.5. Object-oriented programming 58\u003c\/p\u003e \u003cp\u003e4.6. Description language and control language 59\u003c\/p\u003e \u003cp\u003e4.7. Validation 59\u003c\/p\u003e \u003cp\u003e4.7.1. Generality 59\u003c\/p\u003e \u003cp\u003e4.7.2. Verification of predictions 60\u003c\/p\u003e \u003cp\u003e4.7.3. Some specific and typical errors 61\u003c\/p\u003e \u003cp\u003e4.7.4. Various tests 62\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 5. SIMULATION RUNNING AND DATA ANALYSIS 63\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1. Introduction 63\u003c\/p\u003e \u003cp\u003e5.2. Outputs of a simulation 64\u003c\/p\u003e \u003cp\u003e5.2.1. Nature of the data produced by a simulation 64\u003c\/p\u003e \u003cp\u003e5.2.2. Stationarity 65\u003c\/p\u003e \u003cp\u003e5.2.3. Example 66\u003c\/p\u003e \u003cp\u003e5.2.4. Transient period 68\u003c\/p\u003e \u003cp\u003e5.2.5. Duration of a simulation 69\u003c\/p\u003e \u003cp\u003e5.3. Mean value estimation 70\u003c\/p\u003e \u003cp\u003e5.3.1. Mean value of discrete variables 71\u003c\/p\u003e \u003cp\u003e5.3.2. Mean value of continuous variables 72\u003c\/p\u003e \u003cp\u003e5.3.3. Estimation of a proportion 72\u003c\/p\u003e \u003cp\u003e5.3.4. Confidence interval 73\u003c\/p\u003e \u003cp\u003e5.4. Running simulations 73\u003c\/p\u003e \u003cp\u003e5.4.1. Replication method 73\u003c\/p\u003e \u003cp\u003e5.4.2. Batch-means method 75\u003c\/p\u003e \u003cp\u003e5.4.3. Regenerative method 76\u003c\/p\u003e \u003cp\u003e5.5. Variance reduction 77\u003c\/p\u003e \u003cp\u003e5.5.1. Common random numbers 78\u003c\/p\u003e \u003cp\u003e5.5.2. Antithetic variates 79\u003c\/p\u003e \u003cp\u003e5.6. Conclusion 80\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 6. OMNET++ 81\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1. A summary presentation 81\u003c\/p\u003e \u003cp\u003e6.2. Installation 82\u003c\/p\u003e \u003cp\u003e6.2.1. Preparation 82\u003c\/p\u003e \u003cp\u003e6.2.2. Installation 83\u003c\/p\u003e \u003cp\u003e6.3. Architecture of OMNeT++ 83\u003c\/p\u003e \u003cp\u003e6.3.1. Simple module 84\u003c\/p\u003e \u003cp\u003e6.3.2. Channel 85\u003c\/p\u003e \u003cp\u003e6.3.3. Compound module 85\u003c\/p\u003e \u003cp\u003e6.3.4. Simulation model (network) 85\u003c\/p\u003e \u003cp\u003e6.4. The NED langage 85\u003c\/p\u003e \u003cp\u003e6.5. The IDE of OMNeT++ 86\u003c\/p\u003e \u003cp\u003e6.6. The project 86\u003c\/p\u003e \u003cp\u003e6.6.1. Workspace and projects 87\u003c\/p\u003e \u003cp\u003e6.6.2. Creation of a project 87\u003c\/p\u003e \u003cp\u003e6.6.3. Opening and closing of a project 87\u003c\/p\u003e \u003cp\u003e6.6.4. Import of a project 88\u003c\/p\u003e \u003cp\u003e6.7. A first example 88\u003c\/p\u003e \u003cp\u003e6.7.1. Creation of the modules 88\u003c\/p\u003e \u003cp\u003e6.7.2. Compilation 92\u003c\/p\u003e \u003cp\u003e6.7.3. Initialization 92\u003c\/p\u003e \u003cp\u003e6.7.4. Launching of the simulation 93\u003c\/p\u003e \u003cp\u003e6.8. Data collection and statistics 93\u003c\/p\u003e \u003cp\u003e6.8.1. The Signal mechanism 94\u003c\/p\u003e \u003cp\u003e6.8.2. The collectors 95\u003c\/p\u003e \u003cp\u003e6.8.3. Extension of the model with statistics 95\u003c\/p\u003e \u003cp\u003e6.8.4. Data analysis 98\u003c\/p\u003e \u003cp\u003e6.9. A FIFO queue 98\u003c\/p\u003e \u003cp\u003e6.9.1. Construction of the queue 98\u003c\/p\u003e \u003cp\u003e6.9.2. Extension of MySource 101\u003c\/p\u003e \u003cp\u003e6.9.3. Configuration 103\u003c\/p\u003e \u003cp\u003e6.10. An elementary distributed system 105\u003c\/p\u003e \u003cp\u003e6.10.1. Presentation 105\u003c\/p\u003e \u003cp\u003e6.10.2. Coding 107\u003c\/p\u003e \u003cp\u003e6.10.3. Modular construction of a larger system 114\u003c\/p\u003e \u003cp\u003e6.10.4. The system 115\u003c\/p\u003e \u003cp\u003e6.10.5. Configuration of the simulation and its scenarios 115\u003c\/p\u003e \u003cp\u003e6.11. Building large systems: an example with INET 117\u003c\/p\u003e \u003cp\u003e6.11.1. The system 117\u003c\/p\u003e \u003cp\u003e6.11.2. Ethernet card with LLC 119\u003c\/p\u003e \u003cp\u003e6.11.3. The new entity MyApp 121\u003c\/p\u003e \u003cp\u003e6.11.4. Simulation 125\u003c\/p\u003e \u003cp\u003e6.11.5. Conclusion 126\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART 2. QUEUEING THEORY 129\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 7. INTRODUCTION TO THE QUEUEING THEORY 131\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1. Presentation 131\u003c\/p\u003e \u003cp\u003e7.2. Modeling of the computer networks 133\u003c\/p\u003e \u003cp\u003e7.3. Description of a queue 133\u003c\/p\u003e \u003cp\u003e7.4. Main parameters 135\u003c\/p\u003e \u003cp\u003e7.5. Performance indicators 136\u003c\/p\u003e \u003cp\u003e7.5.1. Usual parameters 136\u003c\/p\u003e \u003cp\u003e7.5.2. Performance in steady state 136\u003c\/p\u003e \u003cp\u003e7.6. The Little’s law 137\u003c\/p\u003e \u003cp\u003e7.6.1. Presentation 137\u003c\/p\u003e \u003cp\u003e7.6.2. Applications 138\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 8. POISSON PROCESS 141\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1. Definition 141\u003c\/p\u003e \u003cp\u003e8.1.1. Definition 141\u003c\/p\u003e \u003cp\u003e8.1.2. Distribution of a Poisson process 142\u003c\/p\u003e \u003cp\u003e8.2. Interarrival interval 143\u003c\/p\u003e \u003cp\u003e8.2.1. Definition 143\u003c\/p\u003e \u003cp\u003e8.2.2. Distribution of the interarrival interval Δ 144\u003c\/p\u003e \u003cp\u003e8.2.3. Relation between N(t) and Δ 145\u003c\/p\u003e \u003cp\u003e8.3. Erlang distribution 145\u003c\/p\u003e \u003cp\u003e8.4. Superposition of independent Poisson processes 146\u003c\/p\u003e \u003cp\u003e8.5. Decomposition of a Poisson process 147\u003c\/p\u003e \u003cp\u003e8.6. Distribution of arrival instants over a given interval 150\u003c\/p\u003e \u003cp\u003e8.7. The PASTA property 151\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 9. MARKOV QUEUEING SYSTEMS 153\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1. Birth-and-death process 153\u003c\/p\u003e \u003cp\u003e9.1.1. Definition 153\u003c\/p\u003e \u003cp\u003e9.1.2. Differential equations 154\u003c\/p\u003e \u003cp\u003e9.1.3. Steady-state solution 156\u003c\/p\u003e \u003cp\u003e9.2. The M\/M\/1 queues 158\u003c\/p\u003e \u003cp\u003e9.3. The M\/M\/∞ queues 160\u003c\/p\u003e \u003cp\u003e9.4. The M\/M\/m queues 161\u003c\/p\u003e \u003cp\u003e9.5. The M\/M\/1\/K queues 163\u003c\/p\u003e \u003cp\u003e9.6. The M\/M\/m\/m queues 164\u003c\/p\u003e \u003cp\u003e9.7. Examples 165\u003c\/p\u003e \u003cp\u003e9.7.1. Two identical servers with different activation thresholds 165\u003c\/p\u003e \u003cp\u003e9.7.2. A cybercafe 167\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 10. THE M\/G\/1 QUEUES 169\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10.1. Introduction 169\u003c\/p\u003e \u003cp\u003e10.2. Embedded Markov chain 170\u003c\/p\u003e \u003cp\u003e10.3. Length of the queue 171\u003c\/p\u003e \u003cp\u003e10.3.1. Number of arrivals during a service period 172\u003c\/p\u003e \u003cp\u003e10.3.2. Pollaczek–Khinchin formula 173\u003c\/p\u003e \u003cp\u003e10.3.3. Examples 175\u003c\/p\u003e \u003cp\u003e10.4. Sojourn time 178\u003c\/p\u003e \u003cp\u003e10.5. Busy period 179\u003c\/p\u003e \u003cp\u003e10.6. Pollaczek–Khinchin mean value formula 181\u003c\/p\u003e \u003cp\u003e10.7. M\/G\/1 queue with server vacation 183\u003c\/p\u003e \u003cp\u003e10.8. Priority queueing systems 185\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 11. QUEUEING NETWORKS 189\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e11.1. Generality 189\u003c\/p\u003e \u003cp\u003e11.2. Jackson network 192\u003c\/p\u003e \u003cp\u003e11.3. Closed network 197\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePART 3. PROBABILITY AND STATISTICS 201\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 12. AN INTRODUCTION TO THE THEORY OF PROBABILITY 203\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e12.1. Axiomatic base 203\u003c\/p\u003e \u003cp\u003e12.1.1. Introduction 203\u003c\/p\u003e \u003cp\u003e12.1.2. Probability space 204\u003c\/p\u003e \u003cp\u003e12.1.3. Set language versus probability language 206\u003c\/p\u003e \u003cp\u003e12.2. Conditional probability 206\u003c\/p\u003e \u003cp\u003e12.2.1. Definition 206\u003c\/p\u003e \u003cp\u003e12.2.2. Law of total probability 207\u003c\/p\u003e \u003cp\u003e12.3. Independence 207\u003c\/p\u003e \u003cp\u003e12.4. Random variables 208\u003c\/p\u003e \u003cp\u003e12.4.1. Definition 208\u003c\/p\u003e \u003cp\u003e12.4.2. Cumulative distribution function 208\u003c\/p\u003e \u003cp\u003e12.4.3. Discrete random variables 209\u003c\/p\u003e \u003cp\u003e12.4.4. Continuous random variables 210\u003c\/p\u003e \u003cp\u003e12.4.5. Characteristic function 212\u003c\/p\u003e \u003cp\u003e12.5. Some common distributions 212\u003c\/p\u003e \u003cp\u003e12.5.1. Bernoulli distribution 212\u003c\/p\u003e \u003cp\u003e12.5.2. Binomial distribution 213\u003c\/p\u003e \u003cp\u003e12.5.3. Poisson distribution 213\u003c\/p\u003e \u003cp\u003e12.5.4. Geometric distribution 214\u003c\/p\u003e \u003cp\u003e12.5.5. Uniform distribution 215\u003c\/p\u003e \u003cp\u003e12.5.6. Triangular distribution 215\u003c\/p\u003e \u003cp\u003e12.5.7. Exponential distribution 216\u003c\/p\u003e \u003cp\u003e12.5.8. Normal distribution 217\u003c\/p\u003e \u003cp\u003e12.5.9. Log-normal distribution 219\u003c\/p\u003e \u003cp\u003e12.5.10. Pareto distribution 219\u003c\/p\u003e \u003cp\u003e12.6. Joint probability distribution of multiple random variables 220\u003c\/p\u003e \u003cp\u003e12.6.1. Definition 220\u003c\/p\u003e \u003cp\u003e12.6.2. Independence and covariance 221\u003c\/p\u003e \u003cp\u003e12.6.3. Mathematical expectation 221\u003c\/p\u003e \u003cp\u003e12.7. Some interesting inequalities 222\u003c\/p\u003e \u003cp\u003e12.7.1. Markov’s inequality 222\u003c\/p\u003e \u003cp\u003e12.7.2. Chebyshev’s inequality 222\u003c\/p\u003e \u003cp\u003e12.7.3. Cantelli’s inequality 223\u003c\/p\u003e \u003cp\u003e12.8. Convergences 223\u003c\/p\u003e \u003cp\u003e12.8.1. Types of convergence 224\u003c\/p\u003e \u003cp\u003e12.8.2. Law of large numbers 226\u003c\/p\u003e \u003cp\u003e12.8.3. Central limit theorem 227\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 13. AN INTRODUCTION TO STATISTICS 229\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e13.1. Introduction 229\u003c\/p\u003e \u003cp\u003e13.2. Description of a sample 230\u003c\/p\u003e \u003cp\u003e13.2.1. Graphic representation 230\u003c\/p\u003e \u003cp\u003e13.2.2. Mean and variance of a given sample 231\u003c\/p\u003e \u003cp\u003e13.2.3. Median 231\u003c\/p\u003e \u003cp\u003e13.2.4. Extremities and quartiles 232\u003c\/p\u003e \u003cp\u003e13.2.5. Mode and symmetry 232\u003c\/p\u003e \u003cp\u003e13.2.6. Empirical cumulative distribution function and histogram 233\u003c\/p\u003e \u003cp\u003e13.3. Parameters estimation 236\u003c\/p\u003e \u003cp\u003e13.3.1. Position of the problem 236\u003c\/p\u003e \u003cp\u003e13.3.2. Estimators 236\u003c\/p\u003e \u003cp\u003e13.3.3. Sample mean and sample variance 237\u003c\/p\u003e \u003cp\u003e13.3.4. Maximum-likelihood estimation 237\u003c\/p\u003e \u003cp\u003e13.3.5. Method of moments 239\u003c\/p\u003e \u003cp\u003e13.3.6. Confidence interval 240\u003c\/p\u003e \u003cp\u003e13.4. Hypothesis testing 241\u003c\/p\u003e \u003cp\u003e13.4.1. Introduction 241\u003c\/p\u003e \u003cp\u003e13.4.2. Chi-square (χ2) test 241\u003c\/p\u003e \u003cp\u003e13.4.3. Kolmogorov–Smirnov test 244\u003c\/p\u003e \u003cp\u003e13.4.4. Comparison between the χ2 test and the K-S test 246\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 14. MARKOV PROCESS 247\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e14.1. Stochastic process 247\u003c\/p\u003e \u003cp\u003e14.2. Discrete-time Markov chains 248\u003c\/p\u003e \u003cp\u003e14.2.1. Definitions 248\u003c\/p\u003e \u003cp\u003e14.2.2. Properties 251\u003c\/p\u003e \u003cp\u003e14.2.3. Transition diagram 253\u003c\/p\u003e \u003cp\u003e14.2.4. Classification of states 254\u003c\/p\u003e \u003cp\u003e14.2.5. Stationarity 255\u003c\/p\u003e \u003cp\u003e14.2.6. Applications 257\u003c\/p\u003e \u003cp\u003e14.3. Continuous-time Markov chain 260\u003c\/p\u003e \u003cp\u003e14.3.1. Definitions 260\u003c\/p\u003e \u003cp\u003e14.3.2. Properties 262\u003c\/p\u003e \u003cp\u003e14.3.3. Structure of a Markov process 263\u003c\/p\u003e \u003cp\u003e14.3.4. Generators 266\u003c\/p\u003e \u003cp\u003e14.3.5. Stationarity 267\u003c\/p\u003e \u003cp\u003e14.3.6. Transition diagram 270\u003c\/p\u003e \u003cp\u003e14.3.7. Applications 272\u003c\/p\u003e \u003cp\u003eBIBLIOGRAPHY 273\u003c\/p\u003e \u003cp\u003eINDEX 277\u003c\/p\u003e","brand":"ISTE Ltd and John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49413718737239,"sku":"9781848217478","price":125.06,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781848217478.jpg?v=1730521156"},{"product_id":"analytical-modeling-of-wireless-communication-systems-9781848219441","title":"Analytical Modeling of Wireless Communication","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eWireless networks represent an inexpensive and convenient way to connect to the Internet. However, despite their applications across several technologies, one challenge still remains: to understand the behavior of wireless sensor networks and assess their performance in large-scale scenarios.\u003c\/p\u003e \u003cp\u003eWhen a large number of network nodes need to interact, developing suitable analytical models is essential to ensure the appropriate coverage and throughput of these networks and to enhance user mobility. This is intrinsically difficult due to the size and number of different network nodes and users.\u003c\/p\u003e \u003cp\u003eThis book highlights some examples which show how this problem can be overcome with the use of different techniques. An intensive parameter analysis shows the reader how to the exploit analytical models for an effective development and management of different types of wireless networks.\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003ePreface ix\u003c\/p\u003e \u003cp\u003eIntroduction xi\u003c\/p\u003e \u003cp\u003eList of Acronyms xv\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 1. Sensor Networks 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 1. Fluid Models and Energy Issues 3\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1. The fluid-based approach 4\u003c\/p\u003e \u003cp\u003e1.1.1. Sensor density and traffic generation 5\u003c\/p\u003e \u003cp\u003e1.1.2. Data routing 5\u003c\/p\u003e \u003cp\u003e1.1.3. Local and relay traffic rates 6\u003c\/p\u003e \u003cp\u003e1.1.4. Channel contention and data transmission 6\u003c\/p\u003e \u003cp\u003e1.1.5. Mean packet delivery delay  7\u003c\/p\u003e \u003cp\u003e1.1.6. Sensor active\/sleep behavior 7\u003c\/p\u003e \u003cp\u003e1.2. Network scenario 7\u003c\/p\u003e \u003cp\u003e1.3. The sensor network model 11\u003c\/p\u003e \u003cp\u003e1.3.1. A minimum energy routing strategy: computing u(r:r) 11\u003c\/p\u003e \u003cp\u003e1.3.2. Channel contention and data transmission: computing s(r) and PR(r) 17\u003c\/p\u003e \u003cp\u003e1.3.3. Mean packet delivery delay: computing q(r) 22\u003c\/p\u003e \u003cp\u003e1.4. Results 24\u003c\/p\u003e \u003cp\u003e1.4.1. Model validation 25\u003c\/p\u003e \u003cp\u003e1.4.2. Model exploitation  28\u003c\/p\u003e \u003cp\u003e1.4.3. Model solution complexity and accuracy  35\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 2. Hybrid Automata for Transient Delay Analysis 37\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1. Event detection in WSNs 37\u003c\/p\u003e \u003cp\u003e2.1.1. The 802.15.4 MAC protocol 39\u003c\/p\u003e \u003cp\u003e2.2. Model for single-hop network topologies 40\u003c\/p\u003e \u003cp\u003e2.2.1. Single message transfer 40\u003c\/p\u003e \u003cp\u003e2.2.2. Multiple message transfers 43\u003c\/p\u003e \u003cp\u003e2.3. Solution technique 44\u003c\/p\u003e \u003cp\u003e2.3.1. Time discretization 44\u003c\/p\u003e \u003cp\u003e2.3.2. Transient solution 46\u003c\/p\u003e \u003cp\u003e2.3.3. Performance metrics computation 49\u003c\/p\u003e \u003cp\u003e2.4. Model for multi-hop network topologies 50\u003c\/p\u003e \u003cp\u003e2.5. Model validation and exploitation results 52\u003c\/p\u003e \u003cp\u003e2.6. Discussion 57\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 2. Vehicular Networks 59\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 3. Safety Message Broadcasting 61\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1. System description 62\u003c\/p\u003e \u003cp\u003e3.2. Dissemination of safety messages 63\u003c\/p\u003e \u003cp\u003e3.2.1. The spatial differentiation approach 63\u003c\/p\u003e \u003cp\u003e3.2.2. The safety application 64\u003c\/p\u003e \u003cp\u003e3.3. Assumptions and notations 65\u003c\/p\u003e \u003cp\u003e3.4. Model outline 66\u003c\/p\u003e \u003cp\u003e3.5. Computation of the block probability 67\u003c\/p\u003e \u003cp\u003e3.6. Computation of the probability of first reception 69\u003c\/p\u003e \u003cp\u003e3.6.1. A Gaussian approximation to the transient system behavior 73\u003c\/p\u003e \u003cp\u003e3.7. Performance evaluation 77\u003c\/p\u003e \u003cp\u003e3.7.1. The impact of power capture 77\u003c\/p\u003e \u003cp\u003e3.7.2. The case of occupation probability ρ = 1 79\u003c\/p\u003e \u003cp\u003e3.7.3. The case of homogeneous occupation probability ρ \u0026lt; 1 80\u003c\/p\u003e \u003cp\u003e3.7.4. The case of inhomogeneous occupation probability 83\u003c\/p\u003e \u003cp\u003e3.7.5. The impact of the forwarding policy 85\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 4. Modeling Information Sharing 89\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1. System scenario 89\u003c\/p\u003e \u003cp\u003e4.2. Modeling information exchange in IVN 90\u003c\/p\u003e \u003cp\u003e4.2.1. Model description 91\u003c\/p\u003e \u003cp\u003e4.3. Computation of the probability of successful information retrieval 93\u003c\/p\u003e \u003cp\u003e4.4. Model validation and exploitation 98\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart 3. Cellular Networks 103\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 5. Multi-RAT Algorithms 105\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1. RAT network 106\u003c\/p\u003e \u003cp\u003e5.1.1. Scenario 107\u003c\/p\u003e \u003cp\u003e5.1.2. RAT selection strategy 108\u003c\/p\u003e \u003cp\u003e5.2. Network model 109\u003c\/p\u003e \u003cp\u003e5.2.1. Functional rates 110\u003c\/p\u003e \u003cp\u003e5.3. Model solution 115\u003c\/p\u003e \u003cp\u003e5.3.1. Analytical approach 115\u003c\/p\u003e \u003cp\u003e5.3.2. Computation of performance metrics 117\u003c\/p\u003e \u003cp\u003e5.4. Performance evaluation  118\u003c\/p\u003e \u003cp\u003e5.4.1. Setting and results 119\u003c\/p\u003e \u003cp\u003eBibliography 123\u003c\/p\u003e \u003cp\u003eIndex 127\u003c\/p\u003e","brand":"ISTE Ltd and John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49413723488599,"sku":"9781848219441","price":125.06,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781848219441.jpg?v=1730521174"},{"product_id":"mathematics-for-modeling-and-scientific-computing-9781848219885","title":"Mathematics for Modeling and Scientific Computing","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eThis book provides the mathematical basis for investigating numerically equations from physics, life sciences or engineering. Tools for analysis and algorithms are confronted to a large set of relevant examples that show the difficulties and the limitations of the most naïve approaches. These examples not only provide the opportunity to put into practice mathematical statements, but modeling issues are also addressed in detail, through the mathematical perspective.\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003ePreface ix\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 1. Ordinary Differential Equations 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1. Introduction to the theory of ordinary differential equations  1\u003c\/p\u003e \u003cp\u003e1.1.1. Existence–uniqueness of first-order ordinary differential equations 1\u003c\/p\u003e \u003cp\u003e1.1.2. The concept of maximal solution  11\u003c\/p\u003e \u003cp\u003e1.1.3. Linear systems with constant coefficients  16\u003c\/p\u003e \u003cp\u003e1.1.4. Higher-order differential equations 20\u003c\/p\u003e \u003cp\u003e1.1.5. Inverse function theorem and implicit function theorem  21\u003c\/p\u003e \u003cp\u003e1.2. Numerical simulation of ordinary differential equations, Euler schemes, notions of convergence, consistence and stability  27\u003c\/p\u003e \u003cp\u003e1.2.1. Introduction  27\u003c\/p\u003e \u003cp\u003e1.2.2. Fundamental notions for the analysis of numerical ODE methods 29\u003c\/p\u003e \u003cp\u003e1.2.3. Analysis of explicit and implicit Euler schemes  33\u003c\/p\u003e \u003cp\u003e1.2.4. Higher-order schemes 50\u003c\/p\u003e \u003cp\u003e1.2.5. Leslie’s equation (Perron–Frobenius theorem, power method)  51\u003c\/p\u003e \u003cp\u003e1.2.6. Modeling red blood cell agglomeration 78\u003c\/p\u003e \u003cp\u003e1.2.7. SEI model 87\u003c\/p\u003e \u003cp\u003e1.2.8. A chemotaxis problem  93\u003c\/p\u003e \u003cp\u003e1.3. Hamiltonian problems 102\u003c\/p\u003e \u003cp\u003e1.3.1. The pendulum problem  106\u003c\/p\u003e \u003cp\u003e1.3.2. Symplectic matrices; symplectic schemes 112\u003c\/p\u003e \u003cp\u003e1.3.3. Kepler problem  125\u003c\/p\u003e \u003cp\u003e1.3.4. Numerical results 129\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 2. Numerical Simulation of Stationary Partial Differential Equations: Elliptic Problems  141\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1. Introduction  141\u003c\/p\u003e \u003cp\u003e2.1.1. The 1D model problem; elements of modeling and analysis  144\u003c\/p\u003e \u003cp\u003e2.1.2. A radiative transfer problem 155\u003c\/p\u003e \u003cp\u003e2.1.3. Analysis elements for multidimensional problems 163\u003c\/p\u003e \u003cp\u003e2.2. Finite difference approximations to elliptic equations 166\u003c\/p\u003e \u003cp\u003e2.2.1. Finite difference discretization principles  166\u003c\/p\u003e \u003cp\u003e2.2.2. Analysis of the discrete problem 173\u003c\/p\u003e \u003cp\u003e2.3. Finite volume approximation of elliptic equations 180\u003c\/p\u003e \u003cp\u003e2.3.1. Discretization principles for finite volumes 180\u003c\/p\u003e \u003cp\u003e2.3.2. Discontinuous coefficients  187\u003c\/p\u003e \u003cp\u003e2.3.3. Multidimensional problems 189\u003c\/p\u003e \u003cp\u003e2.4. Finite element approximations of elliptic equations  191\u003c\/p\u003e \u003cp\u003e2.4.1. P1 approximation in one dimension 191\u003c\/p\u003e \u003cp\u003e2.4.2. P2 approximations in one dimension  197\u003c\/p\u003e \u003cp\u003e2.4.3. Finite element methods, extension to higher dimensions  200\u003c\/p\u003e \u003cp\u003e2.5. Numerical comparison of FD, FV and FE methods  204\u003c\/p\u003e \u003cp\u003e2.6. Spectral methods  205\u003c\/p\u003e \u003cp\u003e2.7. Poisson–Boltzmann equation; minimization of a convex function, gradient descent algorithm 217\u003c\/p\u003e \u003cp\u003e2.8. Neumann conditions: the optimization perspective  224\u003c\/p\u003e \u003cp\u003e2.9. Charge distribution on a cord 228\u003c\/p\u003e \u003cp\u003e2.10. Stokes problem  235\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 3. Numerical Simulations of Partial Differential Equations: Time-dependent Problems  267\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1. Diffusion equations  267\u003c\/p\u003e \u003cp\u003e3.1.1. L2 stability (von Neumann analysis) and L∞ stability: convergence  269\u003c\/p\u003e \u003cp\u003e3.1.2. Implicit schemes  276\u003c\/p\u003e \u003cp\u003e3.1.3. Finite element discretization 281\u003c\/p\u003e \u003cp\u003e3.1.4. Numerical illustrations  283\u003c\/p\u003e \u003cp\u003e3.2. From transport equations towards conservation laws  291\u003c\/p\u003e \u003cp\u003e3.2.1. Introduction  291\u003c\/p\u003e \u003cp\u003e3.2.2. Transport equation: method of characteristics 295\u003c\/p\u003e \u003cp\u003e3.2.3. Upwinding principles: upwind scheme 299\u003c\/p\u003e \u003cp\u003e3.2.4. Linear transport at constant speed; analysis of FD and FV schemes  301\u003c\/p\u003e \u003cp\u003e3.2.5. Two-dimensional simulations  326\u003c\/p\u003e \u003cp\u003e3.2.6. The dynamics of prion proliferation 329\u003c\/p\u003e \u003cp\u003e3.3. Wave equation 345\u003c\/p\u003e \u003cp\u003e3.4. Nonlinear problems: conservation laws 354\u003c\/p\u003e \u003cp\u003e3.4.1. Scalar conservation laws 354\u003c\/p\u003e \u003cp\u003e3.4.2. Systems of conservation laws  387\u003c\/p\u003e \u003cp\u003e3.4.3. Kinetic schemes  393\u003c\/p\u003e \u003cp\u003eAppendices  407\u003c\/p\u003e \u003cp\u003eAppendix 1  409\u003c\/p\u003e \u003cp\u003eAppendix 2  417\u003c\/p\u003e \u003cp\u003eAppendix 3  427\u003c\/p\u003e \u003cp\u003eAppendix 4  433\u003c\/p\u003e \u003cp\u003eAppendix 5  443\u003c\/p\u003e \u003cp\u003eBibliography 447\u003c\/p\u003e \u003cp\u003eIndex  455\u003c\/p\u003e","brand":"ISTE Ltd and John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49413725618519,"sku":"9781848219885","price":125.06,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781848219885.jpg?v=1730521177"},{"product_id":"handbook-of-dynamic-data-driven-applications-systems-volume-1-9783030745677","title":"Handbook of Dynamic Data Driven Applications","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eThe Handbook of Dynamic Data Driven Applications Systems establishes an authoritative reference of DDDAS, pioneered by Dr. Darema and the co-authors for researchers and practitioners developing DDDAS technologies.\u003c\/p\u003e  \u003cp\u003eBeginning with general concepts and history of the paradigm, the text provides 32 chapters by leading experts in ten application areas to enable an accurate understanding, analysis, and control of complex systems; be they natural, engineered, or societal:\u003c\/p\u003e  \u003cp\u003eThe authors explain how DDDAS unifies the computational and instrumentation aspects of an application system, extends the notion of Smart Computing to span from the high-end to the real-time data acquisition and control, and manages Big Data exploitation with high-dimensional model coordination.\u003c\/p\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e  \u003cp\u003e\u003ci\u003eThe Dynamically Data Driven Applications Systems (DDDAS) paradigm inspired research regarding the prediction of severe storms.  Specifically, the DDDAS concept allows atmospheric observing systems, computer forecast models, and cyberinfrastructure to dynamically configure themselves in optimal ways in direct response to current or anticipated weather conditions.  In so doing, all resources are used in an optimal manner to maximize the quality and timeliness of information they provide.\u003c\/i\u003e\u003c\/p\u003e  \u003cp\u003e                                            Kelvin Droegemeier, Regents’ Professor of Meteorology at the University of Oklahoma; former Director of the White House Office of Science and Technology Policy\u003c\/p\u003e  \u003cp\u003e                                          \u003c\/p\u003e  \u003cp\u003e\u003ci\u003eWe may well be entering the golden age of data science, as society in general has come to appreciate the possibilities for organizational strategies that harness massive streams of data. The challenges and opportunities are even greater when the data or the underlying system are dynamic - and DDDAS is the time-tested paradigm for realizing this potential.\u003c\/i\u003e\u003c\/p\u003e  \u003cp\u003e                          Sangtae Kim, Distinguished Professor of Mechanical Engineering and Distinguished Professor of Chemical Engineering at Purdue University\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eThe Dynamically Data Driven Applications Systems (DDDAS) paradigm inspired research regarding the prediction of severe storms.  Specifically, the DDDAS concept allows atmospheric observing systems, computer forecast models, and cyberinfrastructure to dynamically configure themselves in optimal ways in direct response to current or anticipated weather conditions.  In so doing, all resources are used in an optimal manner to maximize the quality and timeliness of information they provide.\u003c\/i\u003e\u003cp\u003e            Kelvin Droegemeier, Regents’ Professor of Meteorology at the University of Oklahoma; former Director of the White House Office of Science and Technology Policy\u003c\/p\u003e  \u003cp\u003e             \u003ci\u003eWe may well be entering the golden age of data science, as society in general has come to appreciate the possibilities for organizational strategies that harness massive streams of data. The challenges and opportunities are even greater when the data or the underlying system are dynamic - and DDDAS is the time-tested paradigm for realizing this potential.\u003c\/i\u003e\u003c\/p\u003e  \u003cp\u003e             Sangtae Kim, Distinguished Professor of Mechanical Engineering and Distinguished Professor of Chemical Engineering at Purdue University\u003c\/p\u003e  \u003cp\u003e \u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e1 Introduction to Dynamic Data Driven Applications Systems.- 2 Tractable Non-Gaussian Representation in Dynamic Data Driven Coherent Fluid Mapping.- 3 Dynamic Data-Driven Adaptive Observations in Data Assimilation for Multi-scale Systems.- 4 Dynamic Data-Driven Uncertainty Quantification via Polynomial Chaos for Space Situational Awareness.- 5 Towards Learning Spatio-Temporal Data Stream Relationships for Failure Detection in Avionics.- 6 Markov Modeling of Time Series via Spectral Analysis for Detection of Combustion Instabilities.- 7 Dynamic Space-Time Model for Syndromic Surveillance with Particle Filters and Dirichlet Process.- 8 A Computational Steering Framework for Large-Scale Composite Structures.- 9 Development of Intelligent and Predictive Self-Healing Composite Structures using Dynamic Data-Driven Applications Systems.- 10 Dynamic Data-Driven Approach for Unmanned Aircraft Systems aero-elastic response analysis.- 11 Transforming Wildfire Detection and Prediction using New and Underused Sensor and Data Sources Integrated with Modeling.- 12 Dynamic Data Driven Application Systems for Identification of Biomarkers in DNA Methylation.- 13 Photometric Steropsis for 3D Reconstruction of Space Objects.- 14 Aided Optimal Search: Data-Driven Target Pursuit from On-Demand Delayed Binary Observations.- 15 Optimization of Multi-Target Tracking within a Sensor Network via Information Guided Clustering.- 16 Data-Driven Prediction of Confidence for EVAR in Time-varying Datasets.- 17 DDDAS for Attack Detection and Isolation of Control Systems.- 18 Approximate Local Utility Design for Potential Game Approach to Cooperative Sensor Network Planning.- 19 Dynamic Sensor-Actor Interactions for Path-Planning in a Threat Field.- 20 Energy-Aware Dynamic Data-Driven Distributed Traffic Simulation for Energy and Emissions Reduction.- 21 A Dynamic Data-Driven Optimization Framework for Demand Side Management in Microgrids.- 22 Dynamic Data Driven Partitioning of Smart Grid Using Learning Methods.- 23 Design of a Dynamic Data-Driven System for Multispectral Video Processing.- 24 Light Field Image Compression.- 25 On Compression of Machine-derived Context Sets for Fusion of Multi-model Sensor Data.- 26 Simulation-based Optimization as a Service for Dynamic Data-driven Applications Systems.- 27 Privacy and Security Issues in DDDAS Systems.- 28 Dynamic Data Driven Application Systems (DDDAS) for Multimedia Content Analysis.- 29 Parzen Windows: Simplest Regularization Algorithm.- 30 Multiscale DDDAS Framework for Damage Prediction in Aerospace Composite Structures.- 31 A Dynamic Data-Driven Stochastic State-awareness Framework for the Next Generation of Bio-inspired Fly-by-feel Aerospace Vehicles.- DDDAS: The Way Forward.      ","brand":"Springer Nature Switzerland AG","offers":[{"title":"Default Title","offer_id":49415634092375,"sku":"9783030745677","price":189.99,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9783030745677.jpg?v=1730527594"},{"product_id":"algorithms-and-solutions-based-on-computer-technology-5th-scientific-international-online-conference-algorithms-and-solutions-based-on-computer-technology-asbc-2021-9783030938710","title":"Algorithms and Solutions Based on Computer","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eThis book is a collection of papers compiled from the conference \"Algorithms and Computer-Based Solutions\" held on June 8-9, 2021 at Peter the Great St. Petersburg Polytechnic University (SPbPU), St. Petersburg, Russia. The authors of the book are leading scientists from Russia, Germany, Netherlands, Greece, Hungary, Kazakhstan, Portugal, and Poland.\u003cbr\u003eThe reader finds in the book information from experts on the most interesting trends in digitalization - issues of development and implementation of algorithms, IT and digital solutions for various areas of economy and science, prospects for supercomputers and exo-intelligent platforms; applied computer technologies in digital production, healthcare and biomedical systems, digital medicine, logistics and management; digital technologies for visualization and prototyping of physical objects.\u003cbr\u003eThe book helps the reader to increase his or her expertise in the field of computer technologies discussed.\u003cbr\u003e","brand":"Springer Nature Switzerland AG","offers":[{"title":"Default Title","offer_id":49415663124823,"sku":"9783030938710","price":134.99,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9783030938710.jpg?v=1730527700"},{"product_id":"computer-aided-systems-theory-eurocast-2022-18th-international-conference-las-palmas-de-gran-canaria-spain-february-20-25-2022-revised-selected-papers-9783031253119","title":"Computer Aided Systems Theory – EUROCAST 2022:","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eThis 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.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cb\u003eSystems Theory and Applications\u003c\/b\u003e.- Transdisciplinary Software Development for Early Crisis  Detection.- Uncertainty and Ambiguity: Challenging Layers in Model  Construction.- George J. Boole. A Nineteenth Century Man for the Modern  Digital Era.- Improvement of Electromagnetic Systems by Werner Von  Siemens.- Improvement of Electromagnetic Systems by Werner Von  Siemens.- \u003cb\u003eTheory and Applications of Metaheuristic Algorithms\u003c\/b\u003e.- Multi-criteria Optimization of Workflow-based Assembly Tasks  in Manufacturing.- Lightweight Interpolation-Based SurroImproving the Flexibility of Shape-Constrained Symbolic  Regression with Extended Constraints.- gate Modelling for MultiObjective Continuous Optimisation.- Analysis and Handling of Dynamic Problem Changes in OpenEnded Optimization.- Dynamic Vehicle Routing with Time-Linkage: From Problem  States to Algorithm Performance.- Dynamic Fitness Landscape Analysis.- A Relative Value Function Based Learning Beam Search for  Longest Common Subsequence Problem.- Multi-day Container Drayage Problem with Active and Passive  Vehicles.- On Discovering Optimal Trade-Offs when Introducing New  Routes in Existing Multi-Modal Public Transport Systems.- A Mathematical Model and GRASP for a Tourist Trip Design  Problem.- A Large Neighborhood Search for Battery Swapping Station  Location Planning for Electric Scooters.- Shapley Value based Variable Interaction Networks for Data  Stream Analysis.- Symbolic Regression with Fast Function Extraction and  Nonlinear Least Squares Optimization.- Comparing Shape-Constrained Regression Algorithms for Data  Validation.- Shape-constrained Symbolic Regression with NSGA-III.- Using Explainable Artificial Intelligence for Data Based  Detection of Complications in Records of Patient Treatments.- Identifying Differential Equations to predict Blood Glucose  using Sparse Identification of Nonlinear Systems.-Obtaining Difference Equations for Glucose Prediction by  Structured Grammatical Evolution and sparse identification.- \u003cb\u003eModel-Based System Design, Verification and Simulation\u003c\/b\u003e.- Modeling Approaches for Cyber Attacks on Energy  Infrastructure.- Simulation setup for a closed-loop regulation of neuro-muscular  blockade.- Textile In The Loop as Automated Verification Tool for Smart  Textiles Applications.- Orchestrating Digital Twins for Distributed Manufacturing  Execution Systems.- Automata with Bounded Repetition in RE2.- Integrating OSLC Services into Eclipse.- Developing an Application in the Forest for New Tourism Post  COVID-19.- GPU-Accelerated Synthesis of Probabilistic Programs.- Static Deadlock Detection in Low-Level C Code.- \u003cb\u003eApplications of Signal Processing Technology\u003c\/b\u003e.- 3D Ultrasound Fingertip Tracking.- An Artificial Skin from Conductive Rubber.- Neural Network Based Single-Carrier Frequency Domain  Equalization.- Smooth Step Detection.- Optical Preprocessing and Digital Signal Processing for the  Measurement of Strain in Thin Specimen.- Lower Limbs Gesture Recognition Approach to Control a  Medical Treatment Bed.- \u003cb\u003eArtificial Intelligence and Data Mining for Intelligent  Transportation Systems and Smart Mobility\u003c\/b\u003e.- JKU-ITS Automobile for Research on Autonomous Vehicles.- Development of a ROS-based Architecture for Intelligent  Autonomous on Demand Last Mile Delivery.- Contrastive Learning for Simulation-to-Real Domain Adaptation  of LiDAR data.- Deep Learning Data Association Applied to Multi-Object  Tracking Systems.- A Methodology to Consider Explicitly Emissions in Dynamic  User Equilibrium Assignment.- Sensitivity Analysis for A Cooperative Adaptive Cruise Control  Car Following Model: Preliminary Findings.- On Smart Mobility and Data Stream Mining.- Smart Vehicle Inspection.- \u003cb\u003eComputer Vision, Machine Learning for Image Analysis  and Applications\u003c\/b\u003e.- Impact of the Region of Analysis on the Performance of the  Automatic Epiretinal Membrane Segmentation in OCT Images.- Performance Analysis of GAN approaches in the Portable Chest  X-ray synthetic image generation for COVID-19 screening.- Clinical Decision Support tool for the Identification of  Pathological Structures Associated with Age-related Macular  Degeneration.- Deep Features-based approaches for Phytoplankton  Classification in Microscopy Images.- Robust Deep Learning-based Approach for Retinal layer  Segmentation in Optical Coherence Tomography Images.- Impact of increased centerline weight on the Joint segmentation  and classification of arteries and veins in color fundus images.- Rating the Severity of Diabetic Retinopathy on a Highly  Imbalanced Dataset.- Gait Recognition using 3D View-Transformation Model.- Segmentation and Multi-Facet Classification of Individual Logs  in Wooden Piles.- Drone Detection Using Deep Learning: A Benchmark Study.- \u003cb\u003eComputer and Systems Based Methods and Electronic  Technologies in Medicine\u003c\/b\u003e.- Continuous Time Normalized Signal Trains for a Better  Classification of Myoelectric Signals.- A Comparison of Covariate Shift Detection Methods on Medical  Datasets.- Towards a Method to Provide Tactile Feedback in Minimally  Invasive Robotic Surgery.- Reference Datasets for Analysis of Traditional Japanese and  German Martial Arts.- A Novel Approach to Continuous Heart Rhythm Monitoring for  Arrhythmia Detection.- Indoor Positioning Framework for Training Rescue Operations  Procedures at the Site of a Mass Incident or Disaster.- Designing sightseeing support system in Oku-Nikko using BLE  beacon.- \u003cb\u003eSystems in Industrial Robotics, Automation and IoT\u003c\/b\u003e.- Mixed Reality HMI for Collaborative Robots.- A Digital Twin Demonstrator for Research and Teaching in  Universities.- Robot System as a Testbed for AI Optimizations.- An Architecture for Deploying Reinforcement Learning in  Industrial Environments.- Ck-continuous Spline Approximation with TensorFlow Gradient  Descent Optimizers.- Stepwise Sample Generation.- Optimising Manufacturing Process with Bayesian Learning and  Knowledge Graphs.- Representing Technical Standards as Knowledge Graph to Guide  the Design of Industrial Systems.- Improvements for mlrose Applied to the Traveling Salesperson  Problem.- Survey on Radar Odometry.- Systems Thinking. Relevance for Technology, Science  and Management Professionals.- \u003cb\u003eSystems Thinking. Relevance for Technology, Science  and Management Professionals\u003c\/b\u003e.- Crisis Management in a Federation – Cybernetic Lessons from a  Pandemic.- Using Archetypes to Teach Systems Thinking in an Engineering  Master’s Course.- Collecting vs Sharing of Personal Data: Examining the  Implications to the Society.","brand":"Springer International Publishing AG","offers":[{"title":"Default Title","offer_id":49415701889367,"sku":"9783031253119","price":75.99,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9783031253119.jpg?v=1730527839"},{"product_id":"modelling-and-simulation-for-autonomous-systems-9th-international-conference-mesas-2022-prague-czech-republic-october-20-21-2022-revised-selected-papers-9783031312670","title":"Modelling and Simulation for Autonomous Systems:","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eThis book constitutes the thoroughly refereed post-conference proceedings of the 9th International Conference on Modelling and Simulation for Autonomous Systems, MESAS 2022, held MESAS 2022, Prague, Czech Republic, October 2022.\u003cp\u003eThe 21 full papers included in the volume were carefully reviewed and selected from 24 submissions. They are organized in the following topical sections: Modelling, Simulation Technology, methodologies and Robotics. \u003c\/p\u003e  \u003cp\u003e \u003c\/p\u003e  \u003cp\u003e \u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003eM\u0026amp;S of Intelligent Systems - R\u0026amp;D and Application.- AxS\/AI in Context of Future Warfare and Security Environment.- Future Challenges of Advanced M\u0026amp;S Technology. ","brand":"Springer International Publishing AG","offers":[{"title":"Default Title","offer_id":49415707590999,"sku":"9783031312670","price":56.99,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9783031312670.jpg?v=1730527858"},{"product_id":"3rd-international-conference-on-thermal-issues-in-machine-tools-ictimt2023-9783031344855","title":"3rd International Conference on Thermal Issues in","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eThis open access conference proceedings contains all the papers presented at the ICTIMT 2023, the 3rd International Conference on Thermal Issues in Machine Tools. The event takes place in Dresden, the capital of Saxony, from March 21-23 2023. The conference is organized by the Chair of Machine Tools Development and Adaptive Controls of the Technische Universität Dresden.\u003c\/p\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003eThermal interactions between workpiece, tool, machine.- Testing and simulation methods to identify thermal errors.- Reference workpieces and assessment.- Energy efficient compensation and correction of thermal errors.- Improving thermal robustness of machine tools through design changes.- Thermo-energetic optimization of machine tools.\u003cbr\u003e","brand":"Springer International Publishing AG","offers":[{"title":"Default Title","offer_id":49415711261015,"sku":"9783031344855","price":42.74,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9783031344855.jpg?v=1730527870"},{"product_id":"3rd-international-conference-on-thermal-issues-in-machine-tools-ictimt2023-9783031344886","title":"3rd International Conference on Thermal Issues in","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eThis open access conference proceedings contains all the papers presented at the ICTIMT 2023, the 3rd International Conference on Thermal Issues in Machine Tools. The event takes place in Dresden, the capital of Saxony, from March 21-23 2023. The conference is organized by the Chair of Machine Tools Development and Adaptive Controls of the Technische Universität Dresden.\u003c\/p\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003eThermal interactions between workpiece, tool, machine.- Testing and simulation methods to identify thermal errors.- Reference workpieces and assessment.- Energy efficient compensation and correction of thermal errors.- Improving thermal robustness of machine tools through design changes.- Thermo-energetic optimization of machine tools.\u003cbr\u003e","brand":"Springer International Publishing AG","offers":[{"title":"Default Title","offer_id":49415711293783,"sku":"9783031344886","price":33.24,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9783031344886.jpg?v=1730527869"},{"product_id":"artificial-intelligence-for-healthy-longevity-9783031351754","title":"Artificial Intelligence for Healthy Longevity","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eThis book reviews the state-of-the-art efforts to apply machine learning and AI methods for healthy aging and longevity research, diagnosis, and therapy development. The book examines the methods of machine learning and their application in the analysis of big medical data, medical images, the creation of algorithms for assessing biological age, and effectiveness of geroprotective medications.\u003c\/p\u003e\u003cp\u003eThe promises and challenges of using AI to help achieve healthy longevity for the population are manifold. This volume, written by  world-leading experts working at the intersection of AI and aging, provides a unique synergy of these two highly prominent fields and aims to create a balanced and comprehensive overview of the application methodology that can help achieve healthy longevity for the population.\u003c\/p\u003eThe book is accessible and valuable for specialists in AI and longevity research, as well as a wide readership, including gerontologists, geriatricians, medical specialists, and students from diverse fields, basic scientists, public and private research entities, and policy makers interested in potential intervention in degenerative aging processes using advanced computational tools.\u003cp\u003e\u003c\/p\u003e\u003cp\u003e \u003c\/p\u003e\u003cp\u003e \u003c\/p\u003e\u003cp\u003e \u003c\/p\u003e\u003cp\u003e \u003c\/p\u003e\u003cp\u003e \u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003eAI in longevity.- Automated reporting of medical diagnostic imaging for early disease and aging biomarkers detection.- Risk forecasting tools based on the collected information for two types of occupational diseases.- Obtaining longevity footprints in DNA methylation data using different machine learning approaches.- The role of assistive technology in regulating the behavioural and psychological symptoms of dementia.- Epidemiology, genetics and epigenetics of Biological Aging: one or more aging systems?.- Temporal relation prediction from Electronic Health Records using Graph Neural Networks and Transformers Embeddings.- In silico screening of life-extending drugs using machine learning and omics data.- An overview of kernel methods for identifying genetic association with health-related traits.- Artificial Intelligence approaches for skin anti-aging and skin resilience research.- AI in genomics and epigenomics.- The utility of information theory based methods in the research of aging and longevity.- AI for Longevity: getting past the Mechanical Turk model will take Good Data.- Leveraging algorithmic and human networks to cure human aging: Holistic understanding of Longevity via Generative Cooperative Networks, Hybrid Bayesian\/Neural\/Logical AI and Tokenomics-Mediated Crowdsourcing.\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e  \u003cp\u003e \u003c\/p\u003e","brand":"Springer International Publishing AG","offers":[{"title":"Default Title","offer_id":49415711818071,"sku":"9783031351754","price":151.99,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9783031351754.jpg?v=1730527870"}],"url":"https:\/\/bookcurl.com\/collections\/computer-modelling-and-simulation.oembed?page=5","provider":"Book Curl","version":"1.0","type":"link"}