Computer modelling and simulation Books

Book SynopsisThis open access book provides a step-by-step overview on how to build a microsimulation model with SAS. It shows how to convert an already existing multistate projection by age, sex, education and region into a microsimulation model. Two new dimensions are then added, either the labor force participation and the sector of activity, and/or some examples of outputs and alternative scenarios that would not be possible with standard demographic methods. The book also describes how to adapt the model for other countries or other purposes. It also provides details on how to extend and adapt the model for other purposes as well as other use of microsimulation with SAS. The book suggests codes that are easy to understand, so they can be replicated or adapted for other purposes. As such, this book provides a great resource for people with beginner to intermediate knowledge in SAS.Table of ContentsChapter 1. Introduction.- Chapter 2. Getting Started.- Chapter 3. Converting a Cohort Component Model into a Microsimulation Model.- Chapter 4. Adding New Dimensions.- Chapter 5. Building Alternative Scenarios.- Chapter 6. Extending and Adapting the Model.- Chapter 7. Conclusion.

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Book Synopsis3D Mesh Processing and Character Animation 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. 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. Table of Contents1 Introduction.- 2 Mesh Processing Basic.- 3 Mesh Processing Algorithms.- 4 The Geometry Shader.- 5 Mesh Tessellation.- 6 Quaternions.- 7 Character Animation.- 8 Kinematics.

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Book SynopsisThis graduate-level textbook covers modelling, programming and analysis of stochastic computer simulation experiments, including the mathematical and statistical foundations of simulation and why it works. The book is rigorous and complete, but concise and accessible, providing all necessary background material. Object-oriented programming of simulations is illustrated in Python, while the majority of the book is programming language independent. In addition to covering the foundations of simulation and simulation programming for applications, the text prepares readers to use simulation in their research. A solutions manual for end-of-chapter exercises is available for instructors.Table of ContentsChapter 1: Why Do We Simulate.- Chapter 2: Simulation Programming: Quick Start.- Chapter 3: Examples.- Chapter 4: Simulation Programming with PythonSim.- Chapter 5: Three Views of Simulation.- Chapter 6: Simulation Input.- Chapter 7: Simulation Output.- Chapter 8: Experiment Design and Analysis.- Chapter 9: Simulation Optimization and Sensitivity.- Chapter 10: Simulation for Research.- References.- Index.

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Book SynopsisThis 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.The 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.The book helps the reader to increase his or her expertise in the field of computer technologies discussed.

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Book SynopsisThis 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. The 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. Overall, 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.Table of Contents1. 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.

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Book SynopsisCommissioned by the Society for Modeling and Simulation International (SCS), this needed, useful new ‘Body of Knowledge’ (BoK) collects and organizes the common understanding of a wide collection of professionals and professional associations.Modeling and simulation (M&S) is a ubiquitous discipline that lays the computational foundation for real and virtual experimentation, clearly stating boundaries—and interactions—of systems, data, and representations. The field is well known, too, for its training support via simulations and simulators. Indeed, with computers increasingly influencing the activities of today’s world, M&S is the third pillar of scientific understanding, taking its place along with theory building and empirical observation.This valuable new handbook provides intellectual support for all disciplines in analysis, design and optimization. It contributes increasingly to the growing number of computational disciplines, addressing the broad variety of contributing as well as supported disciplines and application domains. Further, each of its sections provide numerous references for further information. Highly comprehensive, the BoK represents many viewpoints and facets, captured under such topics as: Mathematical and Systems Theory Foundations Simulation Formalisms and Paradigms Synergies with Systems Engineering and Artificial Intelligence Multidisciplinary Challenges Ethics and Philosophy Historical Perspectives Examining theoretical as well as practical challenges, this unique volume addresses the many facets of M&S for scholars, students, and practitioners. As such, it affords readers from all science, engineering, and arts disciplines a comprehensive and concise representation of concepts, terms, and activities needed to explain the M&S discipline.Tuncer Ören is Professor Emeritus at the University of Ottawa. Bernard Zeigler is Professor Emeritus at the University of Arizona. Andreas Tolk is Chief Scientist at The MITRE Corporation. All three editors are long-time members and Fellows of the Society for Modeling and Simulation International. Under the leadership of three SCS Fellows, Dr. Ören, University of Ottawa, Dr. Zeigler, The University of Arizona, and Dr. Tolk, The MITRE Corporation, more than 50 international scholars from 15 countries provided insights and experience to compile this initial M&S Body of Knowledge.Table of Contents1. Preliminary.- 2. M&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&S.- 8. Ethics.- 9. Enterprise (Economics of M&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.

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Book SynopsisThis introductory textbook/reference addresses the fundamental and mostly applied kinds of models. The focus is on models of dynamic systems that move and change over time. However, the work also proposes new methods of uncertainty treatment, offering supporting examples.Topics and features: Chapters suitable for textbook use in teaching modeling and simulation Includes sections of questions and answers, helpful in didactic work Proposes new methodology in addition to examining conventional approaches Offers some cognitive, more abstract models to give a wider insight on model building The book’s readership may consist of researchers working on multidisciplinary problems, as well educators and students. It may be used while teaching computer simulation, applied mathematics, system analysis and system dynamics.Table of Contents1. Concept of Model.- 2. Continuous System Models.- 3. Differential inclusions, uncertainty and functional sensitivity.- 4. Functional sensitivity applications.- 5. Attainable sets in flight control.- 6. Discrete event models.- 7. Self-organization, dynamics and agent-based model .- 8. The space of models, semi-discrete events with fuzzy logic.- 9. Models and categories.- 10. Fuzzy time instants and time model.- 11. Reversibility and the 5th dimension.- 12. Modeling, simulation and optimization.

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Book SynopsisThis 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.Table of ContentsSystems Theory and Applications.- 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.- Theory and Applications of Metaheuristic Algorithms.- 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.- Model-Based System Design, Verification and Simulation.- 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.- Applications of Signal Processing Technology.- 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.- Artificial Intelligence and Data Mining for Intelligent Transportation Systems and Smart Mobility.- 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.- Computer Vision, Machine Learning for Image Analysis and Applications.- 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.- Computer and Systems Based Methods and Electronic Technologies in Medicine.- 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.- Systems in Industrial Robotics, Automation and IoT.- 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.- Systems Thinking. Relevance for Technology, Science and Management Professionals.- 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.

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Book SynopsisThis 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.The 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. Table of ContentsM&S of Intelligent Systems - R&D and Application.- AxS/AI in Context of Future Warfare and Security Environment.- Future Challenges of Advanced M&S Technology.

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Book SynopsisThis 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.Table of ContentsThermal 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.

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Book SynopsisThis 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.Table of ContentsThermal 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.

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Book SynopsisThis 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.The 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.The 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. Table of ContentsAI 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.

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Book SynopsisThis is the first book that sums up test-related modeling of digital circuits and systems by a new structural-decision-diagrams model. The model represents structural and functional information jointly and opens a new area of research.The book introduces and discusses applications of two types of structural decision diagrams (DDs): low-level, structurally synthesized binary DDs (SSBDDs) and high-level DDs (HLDDs) that enable diagnostic modeling of complex digital circuits and systems.Topics and features: Provides the definition, properties and techniques for synthesis, compression and optimization of SSBDDs and HLDDs Provides numerous working examples that illustrate the key points of the text Describes applications of SSBDDs and HLDDs for various electronic design automation (EDA) tasks, such as logic-level fault modeling and simulation, multi-valued simulation, timing-critical path identification, and test generation Discusses the advantages of the proposed model to traditional binary decision diagrams and other traditional design representations Combines SSBDDs with HLDDs for multi-level representation of digital systems for enabling hierarchical and cross-level solving of complex test-related tasks This unique book is aimed at researchers working in the fields of computer science and computer engineering, focusing on test, diagnosis and dependability of digital systems. It can also serve as a reference for graduate- and advanced undergraduate-level computer engineering and electronics courses.Three authors are affiliated with the Dept. of Computer Systems at the Tallinn University of Technology, Estonia: Raimund Ubar is a retired Professor, Jaan Raik and Maksim Jenihhin are tenured Professors. Artur Jutman, PhD, is a researcher at the same university and the CEO of Testonica Lab Ltd., Estonia.Table of ContentsChapter 1: Introduction.- Chapter 2: Overview of structural decision diagrams.- Chapter 3: Structurally Synthesized Binary Decision Diagrams.- Chapter 4: Fault modeling in digital circuits.- Chapter 5: Logic-level fault simulation.- Chapter 6: Test generation, fault diagnosis and testability.- Chapter 7: High-Level Decision Diagrams.- Chapter 8: Test generation for microprocessors with HLDDs.

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Book Synopsis.- M&S of Intelligent Systems R&D and Application..- Comparison of Frequency Cepstral Coefficients in Impulse Acoustic Events Detection..- Modelling and Simulation of hypersonic missile in VR-Forces environment..- Atlas Fusion 2.0 - A ROS2 Based Real-Time Sensor Fusion Framework..- UAS Flight Path Optimization Model for Effective Monitoring and Surveillance of the Buffer Zone in the UNFICYP Peacekeeping Mission..- A Model-Based Design Approach for a System of Systems based on an Integrated UAV Platform..- Practical applicability of tree spacing passability analysis on vehicle path planning..- Where to go and how to get there: Tactical terrain analysis for military unmanned ground-vehicle mission planning..- A Survey of Trajectory Planning Algorithms for Off-road Uncrewed Ground Vehicles..- Multi-physics and Multi-spectral Sensors Simulator for Autonomous Flight Functions Development..- Future Challenges of Advanced M&S Technology..- Conceptual Aspects of Counter-UAS Modelling and Simulation..- Challenges Associated with the Deployment of Autonomous Reconnaissance Systems on Future Battlefields..- The Key Challenges of SBAD M&S..- Development of Geoprocessing Tool for Wet Gap Crossing in Military Operations..- Digital Twin Modeling for Machine Vision Testing in Autonomous Systems..- A Situation Analysis Process in Computer-Generated Forces Team Behavior within Air Combat Simulations under Risk and Uncertainty: Concept and First Implementations..- A Tactical Planning Process in Computer-Generated Forces Team Behavior within Air Combat Simulations: Concept and First Implementations..- Survey on Sensing, Modelling and Reasoning Aspects in Military Autonomous Systems..- AxS/AI in Context of Future Warfare and Security Environment..- Camera based AI models used with lidar data for improvement of detected object parameters..- The Analysis of Point Cloud Registration Methods for Natural Environment in Autonomous Driving..- Hyperspectral Data Dimensionality Reduction: a Comparative Study between PCA and Autoencoder methods..- Utilizing a CNN for Automatic Detection of Military Reconnaissance and Surveillance Objects in Aerial Images: Concept and Challenges..- Multimodal Earth Observation Modeling using AI..- Statistical Evaluation of Simulation Study Data..- Mission: COMANND.  Conceptualizing an AI Assistant for Decision-Making..- Using Only Synthetic Images to Train a Drogue Detector for Aerial Refueling.

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Book Synopsis.- Applications of Signal Processing Technology..- Efficient Hardware Architecture for Random Forest Training..- Influence of Spike Encoding, Neuron Models and Quantization on SNN Performance..- Adaptive combination in Frequency Domain: An Approach for Robust Nonlinear Acoustic Echo Cancellation..- Using of a Robotic Platform to Detect Acoustic Events for Indoor Environments..- Applied Data Science and Engineering for Intelligent Transportation Systems and Smart Mobility..- Modeling Wildlife Accident Risk with Gaussian Mixture Models..- Towards a Unified Incident Detection and Response System for Autonomous Transportation..- Computer and Systems Based Methods and Electronic Tools in Clinical and Academic Medicine..- Edge-Processing of Myoelectric Signals for the Control of Hand- and Arm-Prostheses..- AI-Driven Gesture and Action Recognition for Learning Medicine through Virtual Reality..- Medical Protocols and AI-Driven Algorithms for Enhanced Monitoring of Cardiac Implantable Electronic Devices..- A Survey of Machine Learning Methods for Analyzing Synovitis Arthritis in Human Joints..- Motion tracking in Augmented and Mixed Realities for Healthcare and Medicine Applications..- Advancements and Applications of Medical Human Digital Twin Technology in Cerebral Palsy Diagnosis, Therapy, and Rehabilitation..- Systems in Industrial Robotics, Automation and IoT..- Transformation of IEC 61131-3 onto an Embedded Platform Using LLVM..- Machine Learning based Parameter Estimation of Energy Models in Digital Production Environments..- Efficient Classification of Live Sensor Data on Low-Energy IoT Devices with Simple Machine Learning Methods..- Machine Learning using a Hybrid Quantum Classical Algorithm with Amplitude Data Encoding..- Quantitative Trend Analysis of Reinforcement Learning Algorithms in Production Systems..- Using AutomationML for Advanced Simulation in Industrial Automation..- AR Digital Twin Demonstrator for Industrial Robotics Education..- Accelerating Manual Pick-and-Place Operations with AR Projected CAD Plans and AI-Assisted Object Recognition..- Systems Thinking: Applications in Technology, Science, and Management..- Variety Engineering - A Cybernetic Concept with Practical Implications..- Using a System Archetypes to Explore Business Model Challenges for Digital Textile Microfactories..- Interacting with the Water Cycle - Towards an Experimental Paradigm..- Systemic Thinking in IT Management of the Future: Where are the Benefits?..- Developing a Human Health Digital Twin for Cardiovascular Risk Assessment: Simulation Model and Dashboard..- The Human-Centered AI-DATA Model for Digital Customer Journeys in E-Commerce..- Using LLMs and Websearch in Order to Perform Fact Checking on Texts Generated by LLMs..- Data Science in Medical and Bio-Informatics..- Data Based Prediction of the Duration of the Postoperative Stay of Patients..- A Methodology to Build Spanish Trustworthy Question-Answer Datasets for Suicide Information..- Personalized ML-Assisted Respiratory Muscle Training for Patients with Paraplegia..- Modelling the Risk of Overweight and Obesity Based on the GenObiA Dataset using Genetic Programming..- Customization and Analysis of Orthopedic Aids..- Source Localization for Electrohydraulic Shockwave Devices..- Analysis of Fluorescence Images of C. elegans.

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Book SynopsisAugmented and Virtual Reality are revolutionizing present and future technologies: these are the fastest growing and most fascinating areas of technologies at present. This book aims to provide insight into the theory and applications of Augmented and Virtual Reality to multiple technologies such as IoT (Internet of Things), ML (Machine Learning), AI (Artifi cial Intelligence), Healthcare and Education.

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Book SynopsisThis 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.

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Book SynopsisThis 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.

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Book SynopsisThis book presents a comprehensive set of guidelines and applications of DIgSILENT PowerFactory, an advanced power system simulation software package, for different types of power systems studies. Written by specialists in the field, it combines expertise and years of experience in the use of DIgSILENT PowerFactory with a deep understanding of power systems analysis. These complementary approaches therefore provide a fresh perspective on how to model, simulate and analyse power systems. It presents methodological approaches for modelling of system components, including both classical and non-conventional devices used in generation, transmission and distribution systems, discussing relevant assumptions and implications on performance assessment. This background is complemented with several guidelines for advanced use of DSL and DPL languages as well as for interfacing with other software packages, which is of great value for creating and performing different types of steady-state and dynamic performance simulation analysis. All employed test case studies are provided as supporting material to the reader to ease recreation of all examples presented in the book as well as to facilitate their use in other cases related to planning and operation studies. Providing an invaluable resource for the formal instruction of power system undergraduate/postgraduate students, this book is also a useful reference for engineers working in power system operation and planning.Table of ContentsLoad Flow Calculation and its Application.- Modelling of Transmission Systems under Unsymmetrical Conditions and contingency analysis using DIgSILENT PowerFactory.- Probabilistic load flow module for PowerFactory.- Unbalanced Power Flow in Distribution Systems using TRX Matrix: Implementation using DIgSILENT Programming Language.- Primal-dual interior point algorithm applied to DC optimal power flow using DIgSILENT Programming Language.- Indices to Assess the Integration of Renewable Energy Resources on Standard Test Networks through DIgSILENT’s Programming Language.- Modelling of automatic generation control in power systems.- Gas Turbine Modelling for Power System Dynamic Simulation Studies.- Implementation of Simplified Models of DFG-Based Wind Turbines for RMS-Type Simulation in DIgSILENT Power Factory.- Parameterized modal analysis using DIgSILENT Programming Language.- Probabilistic Approach for Risk Evaluation of Power System Oscillatory Stability.- Mean-Variance Mapping Optimization Algorithm for Power System Applications in DIgSILENT Power Factory.- Application and Requirement of DIgSILENT PowerFactory to Matlab/Simulink Interface.- Advanced applications of DPL language: Simulation automation and management of results.- Interfacing PowerFactory: co-simulation, real-time simulation and controller hardware-in-the-loop applications.- PowerFactory as a software stand-in for Hardware-In-Loop Testing.- Programming of simplified models of Flexible Alternating Current Transmission System (FACTS) devices using DIgSILENT Simulation Language.- Active and Reactive Power Control of Wind Farm based on Integrated Platform of PowerFactory and Matlab.- Implementation of Simplified Models of Local Controller for Muti-terminal HVDC Systems in DIgSILENT Power Factory.- Estimation of Equivalent Model for Clusters of Induction Generators based on PMU Measurements.

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Book SynopsisThis must-read text/reference provides a practical guide to processes involved in the development and application of dynamic simulation models, covering a wide range of issues relating to testing, verification and validation. Illustrative example problems in continuous system simulation are presented throughout the book, supported by extended case studies from a number of interdisciplinary applications. Topics and features: provides an emphasis on practical issues of model quality and validation, along with questions concerning the management of simulation models, the use of model libraries, and generic models; contains numerous step-by-step examples; presents detailed case studies, often with accompanying datasets; includes discussion of hybrid models, which involve a combination of continuous system and discrete-event descriptions; examines experimental modeling approaches that involve system identification and parameter estimation; offers supplementary material at an associated website.Table of ContentsAn Introduction to Simulation Models and the Modelling ProcessConcepts of Simulation Model Testing, Verification and ValidationMeasures of Quality for Model ValidationSensitivity Analysis for Model EvaluationExperimental Data for Model ValidationMethods of Model VerificationMethods for the Invalidation/Validation of Simulation ModelsManagement Issues within Simulation Model Development and TestingCase Study: Development and Testing of a Simulation Model of Two Interconnected VesselsCase Study: Model Validation and Experiment Design for Helicopter Simulation Model Development and ApplicationsCase Study: Compartmental Models of the Gas-Exchange Processes of the Human LungsCase Study: Modelling of Elements of the Neuromuscular Systems Involved in the Regulation of Posture and Control of MovementFurther Discussion

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Book SynopsisThis 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.Table of Contents1. 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.

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Book Synopsis​This book provides a complete and comprehensive guide to Pyomo (Python Optimization Modeling Objects) for beginning and advanced modelers, including students at the undergraduate and graduate levels, academic researchers, and practitioners. Using many examples to illustrate the different techniques useful for formulating models, this text beautifully elucidates the breadth of modeling capabilities that are supported by Pyomo and its handling of complex real-world applications. This second edition provides an expanded presentation of Pyomo’s modeling capabilities, providing a broader description of the software that will enable the user to develop and optimize models. Introductory chapters have been revised to extend tutorials; chapters that discuss advanced features now include the new functionalities added to Pyomo since the first edition including generalized disjunctive programming, mathematical programming with equilibrium constraints, and bilevel programming.Pyomo is an open source software package for formulating and solving large-scale optimization problems. The software extends the modeling approach supported by modern AML (Algebraic Modeling Language) tools. Pyomo is a flexible, extensible, and portable AML that is embedded in Python, a full-featured scripting language. Python is a powerful and dynamic programming language that has a very clear, readable syntax and intuitive object orientation. Pyomo includes Python classes for defining sparse sets, parameters, and variables, which can be used to formulate algebraic expressions that define objectives and constraints. Moreover, Pyomo can be used from a command-line interface and within Python's interactive command environment, which makes it easy to create Pyomo models, apply a variety of optimizers, and examine solutions.Trade Review“This book provides a detailed guide to Pyomo for beginners and advanced users from undergraduate students to academic researchers to practitioners. … the book is a good software guide which I strongly recommend to anybody interested in looking for an alternative to commercial modeling languages in general or in learning or intensifying their Pyomo skills in particular.” (Christina Schenk, SIAM Review, Vol. 61 (1), March, 2019)Table of Contents1. Introduction.- Part I. An Introduction to Pyomo.- 2. Mathematical Modeling and Optimization.- 3. Pyomo Overview.- 4. Pyomo Models and Components.- 5. The Pyomo Command.- 6. Data Command Files.- Part II. Advanced Features and Extensions.- 7. Nonlinear Programming with Pyomo.- 8. Structured Modeling with Blocks.- 9. Generalized Disjunctive Programming.- 10. Stochastic Programming Extensions.- 11. Differential Algebraic Equations.- 12. Mathematical Programs with Equilibrium Constraints.- 13. Bilevel Programming.- 14. Scripting.- A. A Brief Python Tutorial.- Index.

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Book SynopsisThis title brings together frontier research on complex economic systems, heterogeneous interacting agents, bounded rationality, and nonlinear dynamics in economics. The book contains the proceedings of the CEF2015 (21st Computing in Economics in Finance), held 20-22 June 2015 in Taipei, Taiwan, and addresses some of the important driving forces for various emergent properties in economies, when viewed as complex systems. The breakthroughs reported in this book are a result of an interdisciplinary approach and simulation remains the unifying theme for these papers as they deal with a wide range of topics in economics. The text is a valuable addition to the efforts in promoting the complex systems view in economic science. The computational experiments reported in the book are both transparent and replicable.Complex System Modeling and Simulation in Economics and Finance is useful for graduate courses of complex systems, with particular focus on economics and finance. At the same time it serves as a good overview for researchers who are interested in the topic.Table of ContentsAgent-Based Macro Models.- Laboratory Experiments.- Expectations and Learning.- The Cross-Strait: Computational and Behavioral Approach to Economics.- Quantitative Finance.- Theory of Heterogeneous Agents.- Modelling Economic Networks.- Computational Methods.- Agent-Based Models and Policy Design.- Agent-Based Models: Econometric issues and Validation.- Machine Learning in Finance.- Systemic Risks and Network Resilience.- House Prices and Mortgage Debt.- Dynamics of limit order markets.- Asset pricing and portfolio optimization.- Measuring risks in financial assets.

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Book Synopsis1. Systemanalyse: Eine Einführung 1. 0 Überblick Unsere Wirklichkeit wird nicht so sehr geprägt durch die Einzelfunktionen ihrer vielen Bestandteile, sondern vielmehr durch deren Zusammenwirken. Manche Kom­ ponenten wirken stark aufeinander, andere nur schwach, weitere schließlich haben überhaupt nichts miteinander zu tun. Wir verwenden das Wort 'System', um damit eine Anzahl von Bestandteilen abzugrenzen, die untereinander relativ stark, mit ihrer gemeinsamen Systemumwelt aber nur relativ schwach interagieren und das so, daß man dem beobachteten Verhalten dieses Systems einen 'Zweck' zuordnen kann. Bei näherer Betrachtung ist unsere Realität voll solcher Systeme, und sogar voller Sy­ steme von Systemen: Menschen, Tiere, Pflanzen, Ökosysteme, Maschinen, Fabriken, Städte, Staaten. Um die Rolle der Systemanalyse zu diskutieren, befassen wir uns hier beispielhaft mit den komplexesten dieser Systeme: mit natürlichen Systemen (Orga­ nismen und Ökosystemen). Im Laufe der Evolution haben nur diejenigen natürlichen Systeme überleben können, denen es gelungen ist, Systemprozesse zu entwickeln, die ihre Erhaltung sichern, d. h. , die die Fähigkeit erworben haben, auch unter schwierigen und unerwarteten Bedin­ gungen zu überleben. Allerdings sind die meisten natürlichen Systeme nicht in der Lage, erfolgreich mit den schweren Störungen fertigzuwerden, die ihnen durch den hohen Ressourcenverbrauch und die Umweltbelastungen der modernen Gesell­ schaften aufgezwungen werden. Um die Zerstörung der ökologischen Basis und der natürlichen Ressourcen zu vermeiden, müssen wir lernen, diese Systeme in ihrem Verhalten besser zu verstehen und die Folgen unserer Handlungen zuverlässig abzu­ schätzen. Das Werkzeug für diese Aufgabe ist die Systemanalyse.Table of Contents0. Überblick und Vorbemerkungen.- 1. Systemanalyse: Eine Einführung.- 2. Grundwissen der Modellbildung und Simulation.- 3. Verhalten und Stabilität dynamischer Systeme.- 4. Simulationsmodelle.- 5. Anhang.- Anmerkungen zu den Programmen auf der Begleitdiskette.

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Book SynopsisDieses Buch gibt eine umfassende Einführung in die verschiedenen Aspekte der modernen Computergraphik. Neben der Diskussion grundlegender Fragestellungen (Koordinatensysteme, Rasterung, Farbmodelle) werden dabei sowohl die geometrische Modellierung dreidimensionaler Objekte als auch deren graphische Darstellung behandelt. Weiterhin wird die Rolle der Computergraphik in aktuellen Anwendungen wie Animation, Visualisierung oder Virtual Reality beleuchtet. Unterstützt durch zahlreiche, z.T. farbige Illustrationen erhält der Leser so einen Überblick über die einzelnen Arbeitsschritte und Techniken auf dem Weg zum photorealistischen Bild.Trade Review"Es ist leicht lesbar und erfordert keine besonderen mathematischen Vorkenntnisse." Monatshefte für Mathematik, 02/2003Table of ContentsGrundlagen und graphische Grundfunktionen - Geometrische Modellierung dreidimensionaler Objekte - Graphische Darstellung dreidimensionaler Objekte - Ausgewählte Themen und Anwendungen - Schnittstellen und Standards - Graphiksoftware - Aufgaben

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Book SynopsisAISB91 is the eighth conference organized by the Society for the Study of Artificial Intelligence and Simulation of Behaviour. It is not only the oldest regular conference in Europe on AI - which spawned the ECAI conferences in 1982 - but it is also the conference that has a tradition for focusing on research as opposed to applications. The 1991 edition of the conference was no different in this respect. On the contrary, research, and particularly newly emerging research dir­ ections such as knowledge level expert systems research, neural networks and emergent functionality in autonomous agents, was strongly emphasised. The conference was organized around the following sessions: dis­ tributed intelligent agents, situatedness and emergence in autonomous agents, new modes of reasoning, the knowledge level perspective, and theorem proving and machine learning. Each of these sessions is discussed below in more detail. DISTRIBUTED INTELLIGENT AGENTS Research in distributed AI is concerned with the problem of how multiple agents and societies of agents can be organized to co-operate and collectively solve a problem. The first paper by Chakravarty (MIT) focuses on the problem of evolving agents in the context of Minsky's society of mind theory. It addesses the question of how new agents can be formed by transforming existing ones and illustrates the theory with an example from game playing. Smieja (GMD, Germany) focuses on the problem of organizing networks of agents which consist internally of neural networks.Table of ContentsDistributed Intelligent Agents.- Deriving Transformers from Knowledge Organized as a Society of Agents.- Multiple Network Systems (MINOS) Modules: Task Division and Module Discrimination.- Commitments and Projects.- RR - An Intelligent Resource-Bounded Reasoner.- Situatedness and Emergence in Autonomous Agents.- A Cognitive Model of Goal-oriented Automatisms and Breakdowns.- The ‘Logical Omniscience’ of Reactive Systems.- A Connectionist Semantics for Spatial Descriptions.- Neural Networks and Visual Behaviour: Flies, Panned Eyes, and Statistics.- Specifying Complex Behaviour for Computer Agents.- New Modes of Reasoning.- Integrating Neural Network and Expert Reasoning: An Example.- An Architecture for Selective Forgetting.- Constraint Propagation in Qualitative Modelling: Domain Variables Improve Diagnostic Efficiency.- Recursive Plans.- The Knowledge Level Perspective.- Task Centered Representation for Expert Systems at the Knowledge Level.- Knowledgeable knowledge acquisition.- Formalization of the KADS Interpretation Models.- Qualitative Models for Simulation and Control of Dynamic Systems.- Tractable Rationality at the Knowledge Level.- On Problems with the Knowledge Level Perspective.- Theorem Proving.- Using Abstraction.- Sound Substitution into Modal Contexts.- Machine Learning.- Modelling Representations of Device Knowledge in SOAR.- Instance-Based and Generalization-Based Learning Procedures Applied to Solving Integration Problems.

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Book SynopsisNeural networks are a computing paradigm that is finding increasing attention among computer scientists. In this book, theoretical laws and models previously scattered in the literature are brought together into a general theory of artificial neural nets. Always with a view to biology and starting with the simplest nets, it is shown how the properties of models change when more general computing elements and net topologies are introduced. Each chapter contains examples, numerous illustrations, and a bibliography. The book is aimed at readers who seek an overview of the field or who wish to deepen their knowledge. It is suitable as a basis for university courses in neurocomputing.Trade Review"If you want a systematic and thorough overview of neural networks, need a good reference book on this subject, or are giving or taking a course on neural networks, this book is for you." Computing ReviewsTable of Contents1. The Biological Paradigm.- 1.1 Neural computation.- 1.1.1 Natural and artificial neural networks.- 1.1.2 Models of computation.- 1.1.3 Elements of a computing model.- 1.2 Networks of neurons.- 1.2.1 Structure of the neurons.- 1.2.2 Transmission of information.- 1.2.3 Information processing at the neurons and synapses.- 1.2.4 Storage of information — learning.- 1.2.5 The neuron — a self-organizing system.- 1.3 Artificial neural networks.- 1.3.1 Networks of primitive functions.- 1.3.2 Approximation of functions.- 1.3.3 Caveat.- 1.4 Historical and bibliographical remarks.- 2. Threshold Logic.- 2.1 Networks of functions.- 2.1.1 Feed-forward and recurrent networks.- 2.1.2 The computing units.- 2.2 Synthesis of Boolean functions.- 2.2.1 Conjunction, disjunction, negation.- 2.2.2 Geometric interpretation.- 2.2.3 Constructive synthesis.- 2.3 Equivalent networks.- 2.3.1 Weighted and unweighted networks.- 2.3.2 Absolute and relative inhibition.- 2.3.3 Binary signals and pulse coding.- 2.4 Recurrent networks.- 2.4.1 Stored state networks.- 2.4.2 Finite automata.- 2.4.3 Finite automata and recurrent networks.- 2.4.4 A first classification of neural networks.- 2.5 Harmonic analysis of logical functions.- 2.5.1 General expression.- 2.5.2 The Hadamard—Walsh transform.- 2.5.3 Applications of threshold logic.- 2.6 Historical and bibliographical remarks.- 3.Weighted Networks — The Perceptron.- 3.1 Perceptrons and parallel processing.- 3.1.1 Perceptrons as weighted threshold elements.- 3.1.2 Computational limits of the perceptron model.- 3.2 Implementation of logical functions.- 3.2.1 Geometric interpretation.- 3.2.2 The XOR problem.- 3.3 Linearly separable functions.- 3.3.1 Linear separability.- 3.3.2 Duality of input space and weight space.- 3.3.3 The error function in weight space.- 3.3.4 General decision curves.- 3.4 Applications and biological analogy.- 3.4.1 Edge detection with perceptrons.- 3.4.2 The structure of the retina.- 3.4.3 Pyramidal networks and the neocognitron.- 3.4.4 The silicon retina.- 3.5 Historical and bibliographical remarks.- 4. Perceptron Learning.- 4.1 Learning algorithms for neural networks.- 4.1.1 Classes of learning algorithms.- 4.1.2 Vector notation.- 4.1.3 Absolute linear separability.- 4.1.4 The error surface and the search method.- 4.2 Algorithmic learning.- 4.2.1 Geometric visualization.- 4.2.2 Convergence of the algorithm.- 4.2.3 Accelerating convergence.- 4.2.4 The pocket algorithm.- 4.2.5 Complexity of perceptron learning.- 4.3 Linear programming.- 4.3.1 Inner points of polytopes.- 4.3.2 Linear separability as linear optimization.- 4.3.3 Karmarkar’s algorithm.- 4.4 Historical and bibliographical remarks.- 5. Unsupervised Learning and Clustering Algorithms.- 5.1 Competitive learning.- 5.1.1 Generalization of the perceptron problem.- 5.1.2 Unsupervised learning through competition.- 5.2 Convergence analysis.- 5.2.1 The one-dimensional case — energy function.- 5.2.2 Multidimensional case — the classical methods.- 5.2.3 Unsupervised learning as minimization problem.- 5.2.4 Stability of the solutions.- 5.3 Principal component analysis.- 5.3.1 Unsupervised reinforcement learning.- 5.3.2 Convergence of the learning algorithm.- 5.3.3 Multiple principal components.- 5.4 Some applications.- 5.4.1 Pattern recognition.- 5.4.2 Image compression.- 5.5 Historical and bibliographical remarks.- 6. One and Two Layered Networks.- 6.1 Structure and geometric visualization.- 6.1.1 Network architecture.- 6.1.2 The XOR problem revisited.- 6.1.3 Geometric visualization.- 6.2 Counting regions in input and weight space.- 6.2.1 Weight space regions for the XOR problem.- 6.2.2 Bipolar vectors.- 6.2.3 Projection of the solution regions.- 6.2.4 Geometric interpretation.- 6.3 Regions for two layered networks.- 6.3.1 Regions in weight space for the XOR problem.- 6.3.2 Number of regions in general.- 6.3.3 Consequences.- 6.3.4 The Vapnik—Chervonenkis dimension.- 6.3.5 The problem of local minima.- 6.4 Historical and bibliographical remarks.- 7. The Backpropagation Algorithm.- 7.1 Learning as gradient descent.- 7.1.1 Differentiable activation functions.- 7.1.2 Regions in input space.- 7.1.3 Local minima of the error function.- 7.2 General feed-forward networks.- 7.2.1 The learning problem.- 7.2.2 Derivatives of network functions.- 7.2.3 Steps of the backpropagation algorithm.- 7.2.4 Learning with backpropagation.- 7.3 The case of layered networks.- 7.3.1 Extended network.- 7.3.2 Steps of the algorithm.- 7.3.3 Backpropagation in matrix form.- 7.3.4 The locality of backpropagation.- 7.3.5 Error during training.- 7.4 Recurrent networks.- 7.4.1 Backpropagation through time.- 7.4.2 Hidden Markov Models.- 7.4.3 Variational problems.- 7.5 Historical and bibliographical remarks.- 8. Fast Learning Algorithms.- 8.1 Introduction — classical backpropagation.- 8.1.1 Backpropagation with momentum.- 8.1.2 The fractal geometry of backpropagation.- 8.2 Some simple improvements to backpropagation.- 8.2.1 Initial weight selection.- 8.2.2 Clipped derivatives and offset term.- 8.2.3 Reducing the number of floating-point operations.- 8.2.4 Data decorrelation.- 8.3 Adaptive step algorithms.- 8.3.1 Silva and Almeida’s algorithm.- 8.3.2 Delta-bar-delta.- 8.3.3 Rprop.- 8.3.4 The Dynamic Adaption algorithm.- 8.4 Second-order algorithms.- 8.4.1 Quickprop.- 8.4.2 QRprop.- 8.4.3 Second-order backpropagation.- 8.5 Relaxation methods.- 8.5.1 Weight and node perturbation.- 8.5.2 Symmetric and asymmetric relaxation.- 8.5.3 A final thought on taxonomy.- 8.6 Historical and bibliographical remarks.- 9. Statistics and Neural Networks.- 9.1 Linear and nonlinear regression.- 9.1.1 The problem of good generalization.- 9.1.2 Linear regression.- 9.1.3 Nonlinear units.- 9.1.4 Computing the prediction error.- 9.1.5 The jackknife and cross-validation.- 9.1.6 Committees of networks.- 9.2 Multiple regression.- 9.2.1 Visualization of the solution regions.- 9.2.2 Linear equations and the pseudoinverse.- 9.2.3 The hidden layer.- 9.2.4 Computation of the pseudoinverse.- 9.3 Classification networks.- 9.3.1 An application: NETtalk.- 9.3.2 The Bayes property of classifier networks.- 9.3.3 Connectionist speech recognition.- 9.3.4 Autoregressive models for time series analysis.- 9.4 Historical and bibliographical remarks.- 10. The Complexity of Learning.- 10.1 Network functions.- 10.1.1 Learning algorithms for multilayer networks.- 10.1.2 Hilbert’s problem and computability.- 10.1.3 Kolmogorov’s theorem.- 10.2 Function approximation.- 10.2.1 The one-dimensional case.- 10.2.2 The multidimensional case.- 10.3 Complexity of learning problems.- 10.3.1 Complexity classes.- 10.3.2 NP-complete learning problems.- 10.3.3 Complexity of learning with AND-OR networks.- 10.3.4 Simplifications of the network architecture.- 10.3.5 Learning with hints.- 10.4 Historical and bibliographical remarks.- 11. Fuzzy Logic.- 11.1 Fuzzy sets and fuzzy logic.- 11.1.1 Imprecise data and imprecise rules.- 11.1.2 The fuzzy set concept.- 11.1.3 Geometric representation of fuzzy sets.- 11.1.4 Fuzzy set theory, logic operators, and geometry.- 11.1.5 Families of fuzzy operators.- 11.2 Fuzzy inferences.- 11.2.1 Inferences from imprecise data.- 11.2.2 Fuzzy numbers and inverse operation.- 11.3 Control with fuzzy logic.- 11.3.1 Fuzzy controllers.- 11.3.2 Fuzzy networks.- 11.3.3 Function approximation with fuzzy methods.- 11.3.4 The eye as a fuzzy system — color vision.- 11.4 Historical and bibliographical remarks.- 12. Associative Networks.- 12.1 Associative pattern recognition.- 12.1.1 Recurrent networks and types of associative memories.- 12.1.2 Structure of an associative memory.- 12.1.3 The eigenvector automaton.- 12.2 Associative learning.- 12.2.1 Hebbian learning — the correlation matrix.- 12.2.2 Geometric interpretation of Hebbian learning.- 12.2.3 Networks as dynamical systems — some experiments.- 12.2.4 Another visualization.- 12.3 The capacity problem.- 12.4 The pseudoinverse.- 12.4.1 Definition and properties of the pseudoinverse.- 12.4.2 Orthogonal projections.- 12.4.3 Holographic memories.- 12.4.4 Translation invariant pattern recognition.- 12.5 Historical and bibliographical remarks.- 13. The Hopfield Model.- 13.1 Synchronous and asynchronous networks.- 13.1.1 Recursive networks with stochastic dynamics.- 13.1.2 The bidirectional associative memory.- 13.1.3 The energy function.- 13.2 Definition of Hopfield networks.- 13.2.1 Asynchronous networks.- 13.2.2 Examples of the model.- 13.2.3 Isomorphism between the Hopfield and Ising models.- 13.3 Converge to stable states.- 13.3.1 Dynamics of Hopfield networks.- 13.3.2 Covergence proof.- 13.3.3 Hebbian learning.- 13.4 Equivalence of Hopfield and perceptron learning.- 13.4.1 Perceptron learning in Hopfield networks.- 13.4.2 Complexity of learning in Hopfield models.- 13.5 Parallel combinatorics.- 13.5.1 NP-complete problems and massive parallelism.- 13.5.2 The multiflop problem.- 13.5.3 The eight rooks problem.- 13.5.4 The eight queens problem.- 13.5.5 The traveling salesman.- 13.5.6 The limits of Hopfield networks.- 13.6 Implementation of Hopfield networks.- 13.6.1 Electrical implementation.- 13.6.2 Optical implementation.- 13.7 Historical and bibliographical remarks.- 14. Stochastic Networks.- 14.1 Variations of the Hopfield model.- 14.1.1 The continuous model.- 14.2 Stochastic systems.- 14.2.1 Simulated annealing.- 14.2.2 Stochastic neural networks.- 14.2.3 Markov chains.- 14.2.4 The Boltzmann distribution.- 14.2.5 Physical meaning of the Boltzmann distribution.- 14.3 Learning algorithms and applications.- 14.3.1 Boltzmann learning.- 14.3.2 Combinatorial optimization.- 14.4 Historical and bibliographical remarks.- 15. Kohonen Networks.- 15.1 Self-organization.- 15.1.1 Charting input space.- 15.1.2 Topology preserving maps in the brain.- 15.2 Kohonen’s model.- 15.2.1 Learning algorithm.- 15.2.2 Mapping high-dimensional spaces.- 15.3 Analysis of convergence.- 15.3.1 Potential function — the one-dimensional case.- 15.3.2 The two-dimensional case.- 15.3.3 Effect of a unit’s neighborhood.- 15.3.4 Metastable states.- 15.3.5 What dimension for Kohonen networks?.- 15.4 Applications.- 15.4.1 Approximation of functions.- 15.4.2 Inverse kinematics.- 15.5 Historical and bibliographical remarks.- 16. Modular Neural Networks.- 16.1 Constructive algorithms for modular networks.- 16.1.1 Cascade correlation.- 16.1.2 Optimal modules and mixtures of experts.- 16.2 Hybrid networks.- 16.2.1 The ART architectures.- 16.2.2 Maximum entropy.- 16.2.3 Counterpropagation networks.- 16.2.4 Spline networks.- 16.2.5 Radial basis functions.- 16.3 Historical and bibliographical remarks.- 17. Genetic Algorithms.- 17.1 Coding and operators.- 17.1.1 Optimization problems.- 17.1.2 Methods of stochastic optimization.- 17.1.3 Genetic coding.- 17.1.4 Information exchange with genetic operators.- 17.2 Properties of genetic algorithms.- 17.2.1 Convergence analysis.- 17.2.2 Deceptive problems.- 17.2.3 Genetic drift.- 17.2.4 Gradient methods versus genetic algorithms.- 17.3 Neural networks and genetic algorithms.- 17.3.1 The problem of symmetries.- 17.3.2 A numerical experiment.- 17.3.3 Other applications of GAs.- 17.4 Historical and bibliographical remarks.- 18. Hardware for Neural Networks.- 18.1 Taxonomy of neural hardware.- 18.1.1 Performance requirements.- 18.1.2 Types of neurocomputers.- 18.2 Analog neural networks.- 18.2.1 Coding.- 18.2.2 VLSI transistor circuits.- 18.2.3 Transistors with stored charge.- 18.2.4 CCD components.- 18.3 Digital networks.- 18.3.1 Numerical representation of weights and signals.- 18.3.2 Vector and signal processors.- 18.3.3 Systolic arrays.- 18.3.4 One-dimensional structures.- 18.4 Innovative computer architectures.- 18.4.1 VLSI microprocessors for neural networks.- 18.4.2 Optical computers.- 18.4.3 Pulse coded networks.- 18.5 Historical and bibliographical remarks.

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Book SynopsisIn dem Lehrbuch stellt der Autor grundlegende methodische Ansätze für den modellbasierten Systementwurf von mechatronischen Systemen in systematischer und geschlossener Form dar. Der Methodenkanon umfasst domänenneutrale Methoden zur Modellbildung und Verhaltensanalyse, der Modellkanon analytische Verhaltensmodelle für wichtige physikalisch-technische Domänen der mechatronischen Funktionsrealisierung. Mehr als 50 durchgerechnete Entwurfsbeispiele demonstrieren die dargestellten Methoden und Konzepte und unterstützen das Selbststudium.Table of ContentsElemente der Modellbildung.- Simulationstechnische Aspekte.- Funktionsrealisierung – Mehrkörperdynamik.- Funktionsrealisierung – Mechatronischer Elementarwandler.- Funktionsrealisierung – Elektrostatische Wandler.- Funktionsrealisierung – Piezoelektrische Wandler.- Funktionsrealisierung – Wandler mit elektromagnetischer Wechselwirkung.- Funktionsrealisierung – Digitale Informationsverarbeitung.- Regelungstechnische Aspekte.- Stochastische Verhaltensanalyse.- Entwurfsbewertung – Systembudgets.

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Book SynopsisShape interrogation is the process of extraction of information from a geometric model. It is a fundamental component of Computer Aided Design and Manufacturing (CAD/CAM) systems. This book provides a bridge between the areas geometric modeling and solid modeling. Apart from the differential geometry topics covered, the entire book is based on the unifying concept of recasting all shape interrogation problems to the solution of a nonlinear system. It provides the mathematical fundamentals as well as algorithms for various shape interrogation methods including nonlinear polynomial solvers, intersection problems, differential geometry of intersection curves, distance functions, curve and surface interrogation, umbilics and lines of curvature, and geodesics.Trade ReviewFrom the reviews: "... Currently there are several excellent books in the area of geometric modeling and in the area of solid modeling. The major contribution of this book lies in its skilful manner of providing a bridge between these two areas that is guaranteed to make the target audience cry out aloud with delight. Apart from the differential geometry topics covered, the entire book is based on the unifying concept of recasting all shape interrogation problems to the solution of a nonlinear system. Indeed the book is quite compulsive; No study of shape interrogation can ignore Patrikalakis and Maekawa's. Nearly 460 references to the literature make the book widely welcomed. ..." Current Engineering Practice 2002-2003, Vol. 45, Issue 3-4 "... It provides a comprehensive coverage of the fundamental concepts that shape interrogation techniques rely on as well as of the various techniques and algorithms for interrogation of shape features. ... Containing 408 pages, the book can be an indispensable reference for anybody with interest in this field of computer aided geometric design and software development. Nick Patrikalakis and Takashi Maekawa, researchers at MIT, managed to presnet all related concepts in an insightful way. The careful arrangement of the topics and the endeavor of the authors to recast all shape interrogation problem to the numerical solution of a nonlinear system of equations impressed the reviewer. ..." I. Horváth, Structural and Multidisciplinary Optimization 2003, Vol. 24, Issue 6 "…this is a very detailed and complete book on topics that are important in both the theory and practice of geometric modeling. It is a welcome addition to the literature. Reading it and experimenting with the techniques it describes should be a rewarding experience." Luiz Henrique de Figueiredo, MATHEMATICAL REVIEWS "... This book by Patrikalakis and Maekawa is the first thorough, long overdue, look at this curicial area. The book presents an original and inclusive summary of advanced computational topics that relate to the geometry of freeform shapes. Research in these computational areas has matured to a point where such a compendium is no longer nice to have on one's shelf, but a necessity for the serious investigator. The book handles computational problems that represent fundamental components in any solid modeling environment, filling a vacuum in the literature. It will serve well any researcher, either in academia or industry, working in the area of freeform design or manusfacturing. This work continues from the point where the traditional geometric design and solid modeling books stop. ... Shape interrogation and computational geometry of freeform shapes have been a part of the geometric design and manufacturing community for a long time. This book makes efforts and is likely to become the 'Bible' for this area. As a high-quality produced book, it is a must reference for any advanced researcher or developer who works with splines and freeform representations. If you consider yourself one, this book should probably be on your bookshelf. I eagerly await what the first revision of this book may yield." Gershon Elber, Computer-Aided Design 35 (2003) 1053 "‘Shape Interrogation’ in general means the process of extracting information from a geometric model. … The aim of this text is to provide an exhaustive list of tools and algorithms useful for shape interrogation of freeform curves and surfaces. Their effectivity depends on the end user’s capability of solving systems of nonlinear equations, which is one reason for the author’s focus on robust polynomial solvers." (Johannes Wallner, Zentralblatt MATH, Vol. 1035, 2004) "‘Shape Interrogation’ is the process of extracting information from a geometric model. … This book provides a bridge between the areas of geometric modeling and solid modeling. Apart from the differential geometry topics covered, the entire book is based on the unifying concept of recasting all shape interrogations problems to the solution of a nonlinear system. … The book can serve as a textbook for teaching advanced topics of geometric modeling for graduate students as well as professionals in industry." (deslab. mit.edu, October, 2003) "This book gives a detailed description of algorithms and computational methods for shape interrogation … . The book can be used in a course for advanced graduate students and also as a reference text for researchers and practitioners in CAD/CAM. … is a very detailed and complete book on topics that are important in both the theory and the practice of geometric modeling. It is a welcome addition to the literature. Reading it and experimenting with the techniques it describes should be a rewarding experience." (Luiz Henrique de Figueiredo, Mathematical Reviews, 2003 a) "Shape interrogation and computational geometry of free-form shapes have been a part of the geometric design and manufacturing community for a long time. This book makes a first triumphant attempt at summarizing these research efforts and is likely to become the ‘Bible’ for this area. As a high-quality produced book, it is a must reference for any advanced researcher or developer who works with splines and freeform representations. If you consider yourself one, this book should probably be on your bookshelf." (Gershon Elber, Computer Aided Design, Vol. 35, 2003) "The book focuses on the topic of getting shape information from the geometric models of sculptured objects. … Containing 408 pages, the book can be an indispensable reference for anybody with interest in this field of computer aided geometric design and software development. … the text is sufficiently illustrated with figures and the production of the book is of good quality. … The book can be offered as a textbook for teaching advanced topics of geometric modeling for graduate students." (I. Horváth, Structural and Multidisciplinary Optimization, Vol. 24 (6), 2003) "This book provides the mathematical fundamentals as well as algorithms for various shape interrogation methods including nonlinear polynomial solvers, intersection problems, differential geometry of intersection curves, distance functions, curve and surface interrogation, umbilics and lines of curvature, geodesics, and offset curves and surfaces. … The book will inform and enlighten professionals in industry and therefore remains essential reading for them too." (Current Engineering Practice, Vol. 45 (3-4), 2002-03)Table of ContentsRepresentation of Curves and Surfaces.- Differential Geometry of Curves.- Differential Geometry of Surfaces.- Nonlinear Polynomial Solvers and Robustness Issues.- Intersection Problems.- Differential Geometry of Intersection Curves.- Distance Functions.- Curve and Surface Interrogation.- Umbilics and Lines of Curvature.- Geodesics.- Offset Curves and Surfaces.

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Book SynopsisAn komplexe Karosserie-Blechformteile werden seitens der Automobilindustrie allerhöchste Anforderungen hinsichtlich Funktionalität und Oberflächenqualität gestellt. Um diese Anforderungen zu erfüllen, wird ein entsprechender Methodenplan entwickelt. Das geplante Werk führt zunächst in Grundlagen von Karosseriebau, Umform- und Werkstofftechnik, Werkzeugtechnik und Pressentechnik ein, soweit diese für die Herstellung von Karosserieteilen relevant sind. Auf Basis dieser Grundlagen wird im Hauptteil die Thematik der Methodenplanung behandelt, wobei der komplexe Planungsprozess zunächst auf ein sequentielles Gedankenmodell herunter gebrochen wird. Schließlich wird anhand von Praxisbeispielen aufgezeigt, wie die zuvor sequentiell behandelten Planungsschritte zum Teil gleichzeitig, zum Teil nacheinander in mehreren Iterationsschleifen in der Praxis abgearbeitet werden. Bei allen Ausführungen steht stets die Erfüllung der qualitätsmäßigen Anforderungen, die heute an moderne Karosserieteile gestellt werden, im Vordergrund.Table of ContentsEinleitung.- Karosserietechnik und Karosseriewerkstoffe.- Plastizitätstheoretische und werkstofftechnische Grundlagen.- Verfahrenstechnische Grundlagen der Karosserieteilherstellung. Werkzeugtechnik und Werkzeugherstellungsprozess.- Grundlagen der Maschinen- und Anlagentechnik.- Fertigungsplanung und Fertigungsstrategien.- Methodenplanung.- Sachwortregister.- Literaturverzeichnis.

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Book SynopsisDieses Buch richtet sich gezielt an die große Gruppe der Prozesseigner, die in ihrem Unternehmen für einen oder mehrere Geschäfts- und Produktionsprozesse verantwortlich sind. Ihre Rolle ist wichtig, damit Prozessmanagement insgesamt gelingt. Geschulte Prozesseigner ermöglichen Standards zu etablieren und dezentral erkannte Verbesserungspotenziale zu erschließen. Hierzu müssen sie Führungsverantwortung übernehmen, ohne über disziplinarische Durchgriffsmöglichkeiten zu verfügen. Dieses Buch bietet Prozesseignern praxisnah konkrete Anleitungen, wie sie ihrer Aufgabe gerecht werden.Table of ContentsWarum Unternehmen Prozessmanagement nutzen - Prozesse schrittweise entwickeln - Der Fall FULLSERVICE-STRUKTURBETRIEB - Methoden der Prozessintensivierung - Prozesse bewerten - Prozesse von Prozesseignern

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Book Synopsis​Die virtuelle Entwicklung ist als wesentlicher Bestandteil im Entwicklungsprozess neuer Produkte etabliert. Virtual Reality (VR) – ein Teilbereich der virtuellen Entwicklung – bietet die Möglichkeit, durch schnelle Visualisierung und freie Interaktion die Designfindung zu unterstützen, Ergonomie- und Montageuntersuchungen durchzuführen sowie Entwicklungsstände frühzeitig auf Fehler zu untersuchen. Martin Rademacher entwickelt ein Vorgehensmodell, mit dem sich die Einsatzfähigkeit der VR für Fragestellungen im automobilen Entwicklungsprozess in einem nutzer- und aufgabenzentrierten Kontext untersuchen lässt und wendet es auf den Aufgabenbereich „Absicherung der Anmutung und Qualität“ in einem Automobilunternehmen an.Table of Contents​Virtual Reality.- Produktentwicklungsprozess.- Akzeptanz und Usability.- Usability Engineering von Virtual Reality.- Vorgehensmodell zur Evaluation von VR-Arbeitssystemen.

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Book SynopsisHendrik Hopf entwickelt eine Methodik zur Fabriksystemmodellierung im Kontext von Energie- und Ressourceneffizienz (FSMER), welche ein planungsunterstützendes Werkzeug für die nachhaltigkeitsorientierte Fabrikplanung darstellt. Die Methodik setzt sich aus einem Metamodell, vier Fabriksystemkonzepten, einem Referenzmodell sowie einem Vorgehensmodell zusammen. Ziel ist es, die Fabrik ganzheitlich, methodisch und modellgestützt, mit Fokus auf die Zielgrößen Energie- und Ressourceneffizienz in frühen konzeptionellen Planungsphasen abzubilden, Wirkbeziehungen zu erklären sowie Potenziale zur Effizienzsteigerung aufzuzeigen. Komplexe Zusammenhänge einer Fabrik und die Auswirkungen von Planungsentscheidungen können somit in vereinfachter und grafisch orientierter Form dargestellt und beurteilt werden.Table of ContentsModellierung von Systemen.- Energie-/ressourceneffiziente Fabrik.- Fabriksystemkonzepte.- Referenzmodell des Fabriksystems.- Evaluation der Methodik.

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Book SynopsisBernhardt Lüddecke bietet einen umfassenden Einblick in Kennfeldvermessung und Berechnung von Abgasturboladern. Mit experimentellen und numerischen Untersuchungen zur Aero-Thermodynamik sowie zu Reibungsverlusten und Wärmeströmen verdeutlicht er die Eigenschaften dieser kompakten Maschinen. Mithilfe einer neuartigen Drehmoment-Messtechnik konnte der Autor erstmals kurbelwinkelaufgelöst das momentane Drehmoment einer Abgasturboladerturbine geringer Baugröße unter realen motorischen Bedingungen ermitteln. Die vorliegende Studie erlaubt es, auf ein quasi-stationäres Turbinenverhalten auch unter pulsierender Beaufschlagung zu schließen, was für aussagekräftige Simulationen aufgeladener Motoren von wesentlicher Bedeutung ist.Table of ContentsExperimentelle und numerische Untersuchungen an Verdichter- und Turbinenstufen von Abgasturboladern.- Modellierung von Wärmeströmen und Lagerreibleistung zur Kennfeldkorrektur.- Messverfahren für die Turbinenkennfeldermittlung am Heißgasprüfstand.- Motorzyklusaufgelöste, kontaktlose Messung des Turboladerwellendrehmoments mittels inverser Magnetostriktion.- Turbinenbetriebsverhalten unter stationären und pulsierenden Randbedingungen.

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Book SynopsisDas Buch vermittelt Konzepte, zeigt aktuelle Trends wie agile Methoden, stellt Anwendungsszenarien für die Modellierung und Implementierung von Geschäftsprozessen im Zeitalter der Digitalisierung vor. Das Herausgeberwerk basiert dabei auf Fragestellungen aus der unternehmerischen Praxis. Schwerpunkte sind innovative Analysemethoden, kontextsensitive und wissensintensive Geschäftsprozesse sowie aktuelle Ansätze bei der Umsetzung. Fallstudien runden das Buch ab. Es wendet sich sowohl an Berater und Projektverantwortliche als auch an Studierende und Lehrende.Table of ContentsTrends im Geschäftsprozessmanagement (GPM) - Analyse von Geschäftsprozessen - Kontextsensitive Geschäftsprozesse - Wissensintensive Geschäftsprozesse - Implementierung von Geschäftsprozessen - Fallstudien

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Book SynopsisMobilität dominiert unser Leben. Der Straßenverkehr ist sowohl Keimzelle als auch Lebensader unserer modernen Gesellschaft. Doch wie kann man diesen fassen, planen und berechnen? Während der öffentliche Nahverkehr zumeist vorgegebenen Strukturen folgt – wie zum Beispiel ein Zug seinen Schienen – wirken die Bewegungen des Individualverkehrs chaotisch für den außenstehenden Beobachter. Dieses essential bringt Ordnung in das Chaos und setzt sich mit der mikroskopischen Verkehrssimulation auseinander. Michael Moltenbrey konzentriert sich auf die Vermittlung eines sehr einfachen und rudimentären Verkehrsmodells, welches die Bewegungen einzelner Fahrzeuge abbildet. Auf den ersten Blick sind die Bewegungen der einzelnen Verkehrsteilnehmer unvorhersehbar. Auf den zweiten erkennt man wiederkehrende Strukturen und Muster, die helfen, das Gesamtkonzept Verkehr besser zu erfassen.Table of ContentsEinführung.- Was ist Verkehr?.- Welche Arten von Simulationen gibt es?.- Ein einfaches Zellularautomatenmodell.- Es geht auch schneller –Überholmanöver und Mehrspurigkeit. - Auf dem Weg zu einer Stadt – Kreuzungen und Ampeln.- Nicht nur Autos fahren – Heterogener Verkehr.- Gesamtmodell.- Diskussion und Ausblick.

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Book SynopsisDieses Lehrbuch vermittelt Grundwissen zur Lösung von Problemen der Elektrotechnik, der Antriebstechnik und der Mechatronik mit Hilfe des mathematischen Expertensystems Maple™ und des objektorientierten Simulationssystems MapleSim™. Der Autor stellt zunächst Maple™ in konzentrierter Form vor. Danach geht er ausführlich auf die Ermittlung analytischer und numerischer Lösungen von Differentialgleichungen mit Maple™ ein. Der Modellierung und Analyse elektrischer und mechanischer Systeme mit Unterstützung durch Maple™ sowie komplexeren Anwendungsbeispielen sind die folgenden Kapitel des Buches gewidmet. Ausführlich beschrieben werden auch das objektorientierte Modellieren und Simulieren mit MapleSim™ und die Zusammenarbeit von Maple™ mit MapleSim™, Matlab™ und Scilab™.Table of ContentsEinführung in Maple™.- Lösen von Differentialgleichungen.- Modellierung und Analyse elektrischer und mechanischer Systeme.- Laplace-Transformation.- Netzwerkberechnung.- Ortskurven.- Ausgleichsvorgänge.- Schwingungsberechnung.- Analyse und Simulation von Antriebssystemen.- Modellierung von Nichtlinearitäten, diskrete Approximation.- Objektorientierte Modellierung und Simulation mit MapleSim™.- Brücken von Maple™ zu Matlab®/Simulink® und Scilab™/Xcos.

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Book SynopsisStrukturbildung ist Modellbildung. Durch Strukturen können technische Systeme wie mit einem Teststand simuliert, dimensioniert und optimiert werden. Das ist ein unschätzbarer Vorteil, denn Fehler werden schon in der Entwurfsphase erkannt und korrigiert.In der Reihe ‚Strukturbildung und Simulation technischer Systeme‘ werden die Grundlagen und Anwendungen anhand vieler Beispiele anschaulich, praxisnah und relativ leicht verständlich vermittelt. So erhält der Leser die Kenntnisse und Fertigkeiten, die er im Studium, bei der Systementwicklung und bei der Beschaffung von Komponenten benötigt.Die angegebenen Strukturen können mit allen gängigen Simulationsprogrammen berechnet werden. Das hier verwendete Programm SimApp ist leistungsfähig, preiswert und einfach zu erlernen. Im Band 1 wurden im Kapitel 1 die zur Modellbildung nötigen statischen Grundlagen gelegt. Im Kapitel 2 wurden sie zuerst auf elektrostatische Systeme angewendet.Der zweite Band legt die Grundlagen und Anwendungen zur dynamischen Systemanalyse. Im ersten Teil lag der Schwerpunkt auf linearen elektrischen Systemen.In diesem zweiten Teil liegt der Schwerpunkt auf nichtlinearen und mechanischen Systemen. Sie werden hochauflösend im Frequenzbereich simuliert und im Bode-Diagramm dargestellt.Mit dem Wissen der Bände 1 und 2 verfügt der Leser über die Kenntnisse, die ihn zur Analyse und Modellbildung eigener Systeme befähigen. Die damit erzeugten Daten und Diagramme ermöglichen durch den Vergleich mit realen Messungen die Überprüfung der Strukturen auf Richtigkeit.Table of ContentsElektrische Dynamik - Teil 2.- Mechanische Dynamik.

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Book SynopsisDieses Buch behandelt die mathematischen Aspekte der modernen Bildverarbeitungsmethoden. Besonderer Schwerpunkt liegt dabei auf der Präsentation von Grundideen und Konzepten. Es werden eine Vielzahl moderner mathematischer Methoden behandelt, welche zur Lösung wichtiger, grundlegender Probleme der Bildverarbeitung eingesetzt werden. Die Grundprobleme umfassen zum Beispiel Entrauschen, Scharfzeichnen, Kantenerkennung, Inpainting. Neben elementaren Methoden wie Punktoperationen, linearen oder morphologischen Filtern stellt das Buch insbesondere neuere Methoden wie partielle Differentialgleichungen und Variationsmethoden vor. Trade Review"[...] it belongs to the bookcase of any office where someone is doing research/application in image processing. It has the virtues of a good and handy reference manual." Zentralblatt MATH, 1220-2011Table of ContentsEinleitung: Was sind Bilder? Problemstellungen der klassischen Bildverarbeitung - Grundlegende Werkzeuge: Grauwerttransformationen. Glättungs- und Schärfungsmethoden. Lineare Filter. Morphologische Filter - Diskrete und kontinuierliche Betrachtungsweise: Interpolation. Die kontinuierliche Fourier-Transformation. Fourier-Reihen. Gefensterte Fourier-Transformation. Kontinuierliches Filtern und die Wärmeleitungsgleichung - Axiomatische Bildverarbeitung: Skalenraum-Axiome. Beispiele für Multiskalen-Analysen. Grundlegende Theorie. Die Standard PDE-Modelle - Variationsmethoden: Motivation und Vorbemerkungen. Anwendungen

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Book SynopsisComputational Creativity, Concept Invention, and General Intelligence in their own right all are flourishing research disciplines producing surprising and captivating results that continuously influence and change our view on where the limits of intelligent machines lie, each day pushing the boundaries a bit further. By 2014, all three fields also have left their marks on everyday life – machine-composed music has been performed in concert halls, automated theorem provers are accepted tools in enterprises’ R&D departments, and cognitive architectures are being integrated in pilot assistance systems for next generation airplanes. Still, although the corresponding aims and goals are clearly similar (as are the common methods and approaches), the developments in each of these areas have happened mostly individually within the respective community and without closer relationships to the goings-on in the other two disciplines. In order to overcome this gap and to provide a common platform for interaction and exchange between the different directions, the International Workshops on “Computational Creativity, Concept Invention, and General Intelligence” (C3GI) have been started. At ECAI-2012 and IJCAI-2013, the first and second edition of C3GI each gathered researchers from all three fields, presenting recent developments and results from their research and in dialogue and joint debates bridging the disciplinary boundaries. The chapters contained in this book are based on expanded versions of accepted contributions to the workshops and additional selected contributions by renowned researchers in the relevant fields. Individually, they give an account of the state-of-the-art in their respective area, discussing both, theoretical approaches as well as implemented systems. When taken together and looked at from an integrative perspective, the book in its totality offers a starting point for a (re)integration of Computational Creativity, Concept Invention, and General Intelligence, making visible common lines of work and theoretical underpinnings, and pointing at chances and opportunities arising from the interplay of the three fields.Table of ContentsStakeholder Groups in Computational Creativity Research and Practice.- Weak and Strong Computational Creativity.- Theorem: General intelligence entails creativity, assuming.- The Computational Creativity Complex.- How Models of Creativity and Analogy Need to Answer the Tailorability Concern.- On the role of computers in creativity-support systems.- A computational theory of creativity as everyday reasoning from learned information.- Accounting for creativity within a psychologically realistic cognitive architecture.- E pluribus unum - Formalisation, Use-Cases, and Computational Support for Conceptual Blending.- Creating Meaningful and Poetic Instances of Rhetorical Forms.- Open-Ended Elaborations in Creative Metaphor.- Poetry generation with PoeTryMe.- From MEXICA to MEXICA-impro: the Evolution of a Computer Model for Plot Generation.- Handle: Engineering Artificial Musical Creativity at the "Trickery" Level.- A Culinary Computational Creativity System.- Interactive Meta-Reasoning: Toward a CAD-like environment for designing game-playing agents.- Collective Discovery Events: Web-based Mathematical Problem-solving with Codelets.- A Personal Perspective Into the Future for Computational Creativity.

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