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Books > Computing & IT > Applications of computing > Computer modelling & simulation
Computer languages and computer graphics have become the primary modes of human-computer interaction. This book provides a basic introduction to "Real and Virtual Environment" computer modelling. Graphics models are used to illustrate both the way computer languages are processed and also used to create computer models of graphic displays. Computer languages have been bootstrapped from machine code, to high-level languages such as Java, to animation scripting languages. Integrating graphic and computer models takes this support for programming, design and simulation work, one step further, allowing interactive computer graphic displays to be used to construct computer models of both real and virtual environment systems. The Java language is used to implement basic algorithms for language translation, and to generate graphic displays. It is also used to simulate the behaviour of a computer system, to explore the way programming and design-simulation environments can be put together.
Simulation and Verification of Electronic and Biological Systems provides a showcase for the Circuit and Multi-Domain Simulation Workshop held in San Jose, California, USA, on November 5, 2009. The nine chapters are contributed by experts in the field and provide a broad discussion of recent developments on simulation, modeling and verification of integrated circuits and biological systems. Specific topics include large scale parallel circuit simulation, industrial practice of fast SPICE simulation, structure-preserving model order reduction of interconnects, advanced simulation techniques for oscillator networks, dynamic stability of static memories and biological systems as well as verification of analog integrated circuits. Simulation and verification are fundamental enablers for understanding, analyzing and designing an extremely broad range of engineering and biological circuits and systems. The design of nanometer integrated electronic systems and emerging biomedical applications have stimulated the development of novel simulation and verification techniques and methodologies. Simulation and Verification of Electronic and Biological Systems provides a broad discussion of recent advances on simulation, modeling and verification of integrated circuits and biological systems and offers a basis for stimulating new innovations.
Data driven methods have long been used in Automatic Speech Recognition (ASR) and Text-To-Speech (TTS) synthesis and have more recently been introduced for dialogue management, spoken language understanding, and Natural Language Generation. Machine learning is now present "end-to-end" in Spoken Dialogue Systems (SDS). However, these techniques require data collection and annotation campaigns, which can be time-consuming and expensive, as well as dataset expansion by simulation. In this book, we provide an overview of the current state of the field and of recent advances, with a specific focus on adaptivity.
The present book includes a set of selected extended papers from the 4th International Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH 2014), held in Vienna, Austria, from 28 to 30 August 2014. The conference brought together researchers, engineers and practitioners interested in methodologies and applications of modeling and simulation. New and innovative solutions are reported in this book. SIMULTECH 2014 received 167 submissions, from 45 countries, in all continents. After a double blind paper review performed by the Program Committee, 23% were accepted as full papers and thus selected for oral presentation. Additional papers were accepted as short papers and posters. A further selection was made after the Conference, based also on the assessment of presentation quality and audience interest, so that this book includes the extended and revised versions of the very best papers of SIMULTECH 2014. Commitment to high quality standards is a major concern of SIMULTECH that will be maintained in the next editions, considering not only the stringent paper acceptance ratios but also the quality of the program committee, keynote lectures, participation level and logistics.
This book includes extended and revised versions of a set of selected papers from the 3rd International Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH 2013) which was co-organized by the Reykjavik University (RU) and sponsored by the Institute for Systems and Technologies of Information, Control and Communication (INSTICC). SIMULTECH 2013 was held in cooperation with the ACM SIGSIM - Special Interest Group (SIG) on SImulation and Modeling (SIM), Movimento Italiano Modellazione e Simulazione (MIMOS) and AIS Special Interest Group on Modeling and Simulation (AIS SIGMAS) and technically co-sponsored by the Society for Modeling & Simulation International (SCS), Liophant Simulation, Simulation Team and International Federation for Information Processing (IFIP). This proceedings brings together researchers, engineers, applied mathematicians and practitioners working in the advances and applications in the field of system simulation.
Grasping in Robotics contains original contributions in the field of grasping in robotics with a broad multidisciplinary approach. This gives the possibility of addressing all the major issues related to robotized grasping, including milestones in grasping through the centuries, mechanical design issues, control issues, modelling achievements and issues, formulations and software for simulation purposes, sensors and vision integration, applications in industrial field and non-conventional applications (including service robotics and agriculture). The contributors to this book are experts in their own diverse and wide ranging fields. This multidisciplinary approach can help make Grasping in Robotics of interest to a very wide audience. In particular, it can be a useful reference book for researchers, students and users in the wide field of grasping in robotics from many different disciplines including mechanical design, hardware design, control design, user interfaces, modelling, simulation, sensors and humanoid robotics. It could even be adopted as a reference textbook in specific PhD courses.
This book describes thermal plant simulation, that is, dynamic simulation of plants which produce, exchange and otherwise utilize heat as their working medium. Directed at chemical, mechanical and control engineers involved with operations, control and optimization and operator training, the book gives the mathematical formulation and use of simulation models of the equipment and systems typically found in these industries. The author has adopted a fundamental approach to the subject. The initial chapters provide an overview of simulation concepts and describe a suitable computer environment. Reviews of relevant numerical computation methods and fundamental thermodynamics are followed by a detailed examination of the basic conservation equations. The bulk of the book is concerned with development of specific simulation models. Care is taken to trace each model derivation path from the basic underlying physical equations, explaining simplifying and restrictive assumptions as they arise and relating the model coefficients to the physical dimensions and physical properties of the working materials. Numerous photographs of real equipment complement the text and most models are illustrated by numerical examples based on typical real plant operations.
The ease of use of the programs in the application to ever more complex cases of disease and pestilence. The lack of need on the part of the student or modelers of mathematics beyond algebra and the lack of need of any prior computer programming experience. The surprising insights that can be gained from initially simple systems models.
This book constitutes the proceedings of the 14th International Conference on Transport Systems Telematics, TST 2014, held in Katowice/Krakow and Ustron, Poland, in October 2014. The 49 papers included in this volume were carefully reviewed and selected from 125 submissions. The papers provide an overview of solutions being developed in the fields of transport telematics and intelligent transport systems.
This book constitutes the refereed proceedings of the 36th German Conference on Pattern Recognition, GCPR 2014, held in Munster, Germany, in September 2014. The 58 revised full papers and 8 short papers were carefully reviewed and selected from 153 submissions. The papers are organized in topical sections on variational models for depth and flow, reconstruction, bio-informatics, deep learning and segmentation, feature computation, video interpretation, segmentation and labeling, image processing and analysis, human pose and people tracking, interpolation and inpainting.
7. 1. 1 Background Uncertainty can be considered as the lack of adequate information to make a decision. It is important to quantify uncertainties in mathematical models used for design and optimization of nondeterministic engineering systems. In general, - certainty can be broadly classi?ed into three types (Bae et al. 2004; Ha-Rok 2004; Klir and Wierman 1998; Oberkampf and Helton 2002; Sentz 2002). The ?rst one is aleatory uncertainty (also referred to as stochastic uncertainty or inherent - certainty) - it results from the fact that a system can behave in random ways. For example, the failure of an engine can be modeled as an aleatory uncertaintybecause the failure can occur at a random time. One cannot predict exactly when the engine will fail even if a large quantity of failure data is gathered (available). The second one is epistemic uncertainty (also known as subjective uncertainty or reducible - certainty) - it is the uncertainty of the outcome of some random event due to lack of knowledge or information in any phase or activity of the modeling process. By gaining information about the system or environmental factors, one can reduce the epistemic uncertainty. For example, a lack of experimental data to characterize new materials and processes leads to epistemic uncertainty.
Implicit objects have gained increasing importance in geometric modeling, visualisation, animation, and computer graphics, because their geometric properties provide a good alternative to traditional parametric objects. This book presents the mathematics, computational methods and data structures, as well as the algorithms needed to render implicit curves and surfaces, and shows how implicit objects can easily describe smooth, intricate, and articulatable shapes, and hence why they are being increasingly used in graphical applications. Divided into two parts, the first introduces the mathematics of implicit curves and surfaces, as well as the data structures suited to store their sampled or discrete approximations, and the second deals with different computational methods for sampling implicit curves and surfaces, with particular reference to how these are applied to functions in 2D and 3D spaces.
A state-of-the-art research monograph providing consistent treatment of supervisory control, by one of the world's leading groups in the area of Bayesian identification, control, and decision making.
This book deals with the analysis, the design and the implementation of the mechatronic systems. Classical and modern tools are developed for the analysis and the design for such systems. Robust control, H-Infinity and guaranteed cost control theory are also used for analysis and design of mechatronic systems. Different controller such as state feedback, static output feedback and dynamic output feedback controllers are used to stabilize mechatronic systems. Heuristic algorithms are provided to solve the design of the classical controller such as PID, phase lead, phase lag and phase lead-lag controllers while linear matrix inequalities (LMI) algorithms are provided for finding solutions to the state feedback, static output feedback and dynamic output feedback controllers. The theory presented in the different chapters of the volume is applied to numerical examples to show the usefulness of the theoretical results. Some case studies are also provided to show how the developed concepts apply for real system. Emphasis is also put on the implementation in real-time for some real systems that we have developed in our mechatronic laboratory and all the detail is provided to give an idea to the reader how to implement its own mechatronic system. Mechatronics Systems: Analysis, Design and Implementation is an excellent textbook for undergraduate and graduate students in mechatronic system and control theory and as a reference for academic researchers in control or mathematics with interest in control theory. The reader should have completed first-year graduate courses in control theory, linear algebra, and linear systems. It will also be of great value to engineers practising in fields where the systems can be modeled by linear time invariant systems.
The purpose of this volume is to provide a brief review of the previous work on model reduction and identifi cation of distributed parameter systems (DPS), and develop new spatio-temporal models and their relevant identifi cation approaches. In this book, a systematic overview and classifi cation on the modeling of DPS is presented fi rst, which includes model reduction, parameter estimation and system identifi cation. Next, a class of block-oriented nonlinear systems in traditional lumped parameter systems (LPS) is extended to DPS, which results in the spatio-temporal Wiener and Hammerstein systems and their identifi cation methods. Then, the traditional Volterra model is extended to DPS, which results in the spatio-temporal Volterra model and its identification algorithm. All these methods are based on linear time/space separation. Sometimes, the nonlinear time/space separation can play a better role in modeling of very complex processes. Thus, a nonlinear time/space separation based neural modeling is also presented for a class of DPS with more complicated dynamics. Finally, all these modeling approaches are successfully applied to industrial thermal processes, including a catalytic rod, a packed-bed reactor and a snap curing oven. The work is presented giving a unifi ed view from time/space separation. The book also illustrates applications to thermal processes in the electronics packaging and chemical industry. This volume assumes a basic knowledge about distributed parameter systems, system modeling and identifi cation. It is intended for researchers, graduate students and engineers interested in distributed parameter systems, nonlinear systems, and process modeling and control.
The book presents a peer-reviewed collection of papers presented during the 10th issue of the Artificial Economics conference, addressing a variety of issues related to macroeconomics, industrial organization, networks, management and finance, as well as purely methodological issues. The field of artificial economics covers a broad range of methodologies relying on computer simulations in order to model and study the complexity of economic and social phenomena. The grounding principle of artificial economics is the analysis of aggregate properties of simulated systems populated by interacting adaptive agents that are equipped with heterogeneous individual behavioral rules. These macroscopic properties are neither foreseen nor intended by the artificial agents but generated collectively by them. They are emerging characteristics of such artificially simulated systems.
Growth in the pharmaceutical market has slowed down - almost to a standstill. One reason is that governments and other payers are cutting costs in a faltering world economy. But a more fundamental problem is the failure of major companies to discover, develop and market new drugs. Major drugs losing patent protection or being withdrawn from the market are simply not being replaced by new therapies - the pharmaceutical market model is no longer functioning effectively and most pharmaceutical companies are failing to produce the innovation needed for success. This multi-authored new book looks at a vital strategy which can bring innovation to a market in need of new ideas and new products: Systems Biology (SB). Modeling is a significant task of systems biology. SB aims to develop and use efficient algorithms, data structures, visualization and communication tools to orchestrate the integration of large quantities of biological data with the goal of computer modeling. It involves the use of computer simulations of biological systems, such as the networks of metabolites comprise signal transduction pathways and gene regulatory networks to both analyze and visualize the complex connections of these cellular processes. SB involves a series of operational protocols used for performing research, namely a cycle composed of theoretical, analytic or computational modeling to propose specific testable hypotheses about a biological system, experimental validation, and then using the newly acquired quantitative description of cells or cell processes to refine the computational model or theory.
Requirements engineering has since long acknowledged the importance of the notion that system requirements are stakeholder goals-rather than system functions-and ought to be elicited, modeled and analyzed accordingly. In this book, Nurcan and her co-editors collected twenty contributions from leading researchers in requirements engineering with the intention to comprehensively present an overview of the different perspectives that exist today, in 2010, on the concept of intention in the information systems community. These original papers honor Colette Rolland for her contributions to this field, as she was probably the first to emphasize that 'intention' has to be considered as a first-class concept in information systems engineering. Written by long-term collaborators (and most often friends) of Colette Rolland, this volume covers topics like goal-oriented requirements engineering, model-driven development, method engineering, and enterprise modeling. As such, it is a tour d'horizon of Colette Rolland's lifework, and is presented to her on the occasion of her retirement at CaISE 2010 in Hammamet, the conference she once cofounded and which she helped to grow and prosper for more than 20 years.
In recent years fractional calculus has played an important role in various fields such as mechanics, electricity, chemistry, biology, economics, modeling, identification, control theory and signal processing. The scope of this book is to present the state of the art in the study of fractional systems and the application of fractional differentiation. Furthermore, the manufacture of nanowires is important for the design of nanosensors and the development of high-yield thin films is vital in procuring clean solar energy. This wide range of applications is of interest to engineers, physicists and mathematicians.
This book constitutes the referred proceedings of the 8th China Conference on Image and Graphics Technologies and Applications, IGTA 2014, held in Beijing, China, in June 2014. The 39 papers presented were carefully reviewed and selected from 110 submissions. They cover various aspects of research in image processing and graphics and related topics, including object detection, pattern recognition, object tracking, classification, image segmentation, reconstruction, etc.
Agent-based modeling/simulation is an emerging field that uses bottom-up and experimental analysis in the social sciences. Selected research from that presented at the Third International Workshop on Agent-Based Approaches in Economic and Social Complex Systems 2004, held in May 2004 in Kyoto, Japan, is included in this book. The aim of the workshop was to employ the bottom-up approach to social and economic problems by modeling, simulation, and analysis using a software agent. This research area is an emerging interdisciplinary field among the social sciences and computer science, attracting broad attention because it introduces a simulation-based experimental approach to problems that are becoming increasingly complex in an era of globalization and innovation in information technology. The state-of-the-art research and findings presented in this book will be indispensable tools for anyone involved in this rapidly growing discipline.
Rapid Modelling and Quick Response presents new research developments in the fields of rapid modelling and quick response linked with performance improvements (based on lead time reduction, etc., as well as financial performance measures). The papers and teaching cases in this book were presented at the second Rapid Modelling Conference: "Quick Response - Intersection of Theory and Practice". The main focus of this collection is the transfer of knowledge from theory to practice, providing the theoretical foundations for successful performance improvement. This conference volume challenges the traditional notions of rapid modelling, and offers valuable contributions to the scientific communities of operations management, production management, supply chain management, industrial engineering and operations research. Rapid Modelling and Quick Response will give the interested reader (researcher, as well as practitioner) a good overview of new developments in this field.
This book constitutes the second part of the refereed proceedings of the International Conference on Life System Modeling and Simulation, LSMS 2014, and of the International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2014, held in Shanghai, China, in September 2014. The 159 revised full papers presented in the three volumes of CCIS 461-463 were carefully reviewed and selected from 572 submissions. The papers of this volume are organized in topical sections on advanced neural network theory and algorithms; advanced evolutionary computing theory and algorithms, such as particle swarm optimization, differential evolution, ant colonies, artificial life, artificial immune systems and genetic algorithm; fuzzy, neural, and fuzzy-neuro hybrids; intelligent modeling, monitoring, and control of complex nonlinear systems; intelligent modeling and simulation of climate change; communication and control for distributed networked systems.
Decision makers in large scale interconnected network systems require simulation models for decision support. The behaviour of these systems is determined by many actors, situated in a dynamic, multi-actor, multi-objective and multi-level environment. How can such systems be modelled and how can the socio-technical complexity be captured? Agent-based modelling is a proven approach to handle this challenge. This book provides a practical introduction to agent-based modelling of socio-technical systems, based on a methodology that has been developed at TU Delft and which has been deployed in a large number of case studies. The book consists of two parts: the first presents the background, theory and methodology as well as practical guidelines and procedures for building models. In the second part this theory is applied to a number of case studies, where for each model the development steps are presented extensively, preparing the reader for creating own models.
This book constitutes thoroughly revised and selected papers from the Second International Conference on Model-Driven Engineering and Software Development, MODELSWARD 2014, held in Lisbon, Portugal, in January 2014. The 10 thoroughly revised and extended papers presented in this volume were carefully reviewed and selected from 88 submissions. They are organized in topical sections named: invited papers; modeling languages, tools and architectures; and methodologies, processes and platforms. |
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