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Motor Control and Learning
Motor Control and Learning focuses on the effects of development, aging, and practice on the control of human voluntary movement. These issues have been at the center of attention of the motor control community, but no book until now has addressed all of these issues under one cover in the context of contemporary views on the control of human voluntary movement. This book emphasizes the links between progress in basic motor control research and applied areas such as motor disorders and motor rehabilitation.
Molecular Mechanisms of Neurotransmitter Release
Within the complex neuronal network of the nervous system, neuron-to-neuron communication occurs mainly through chemical synapses, where the presynaptic nerve terminal releases neurotransmitters that control the function of postsynaptic neurons by acting on postsynaptic receptors. Recent decades have brought groundbreaking new developments and a wealth of knowledge to this field. In Molecular Mechanisms of Neurotransmitter Release, leading experts provide concise, up-to-date information on all major molecular mechanisms involved, with complete background information and figures and diagrams to further elucidate key concepts or experiments.Comprehensive and cutting-edge, Molecular Mechanisms of Neurotransmitter Release is sure to provide a learning tool for neuroscience students, a solid reference for neuroscientists, and a source of knowledge for all those who have a general interest in the ever-evolving field of neuroscience.
Molecular Gels : Materials with Self-Assembled Fibrillar Networks
Molecular gels and fibrillar networks – a comprehensive guide to experiment and theory Molecular Gels: Materials with Self-Assembled Fibrillar Networks provides a comprehensive treatise on gelators, especially low molecular-mass gelators (LMOGs), and the properties of their gels. The structures and modes of formation of the self-assembled fibrillar networks (SAFINs) that immobilize the liquid components of the gels are discussed experimentally and theoretically. The spectroscopic, rheological, and structural features of the different classes of LMOGs are also presented. Many examples of the application of the principal analytical techniques for investigation of molecular gels (including SANS, SAXS, WAXS, UV-vis absorption, fluorescence and CD spectroscopies, scanning electron, transmission electron and optical microscopies, and molecular modeling) are presented didactically and in-depth, as are several of the theories of the stages of aggregation of individual LMOG molecules leading to SAFINs. Several actual and potential applications of molecular gels in disparate fields (from silicate replication of nanostructures to art conservation) are described. Special emphasis is placed on perspectives for future developments.
Molecular Aspects of the Stress Response
We are extremely happy to present the reader this book containing a summary of a well-known research field, the phenomenon of cellular stress defense from two new angles: networks and membranes.
Modern socio-technical perspectives on privacy
This book provides researchers and professionals with a foundational understanding of online privacy as well as insight into the socio-technical privacy issues that are most pertinent to modern information systems, covering several modern topics (e.g., privacy in social media, IoT) and underexplored areas (e.g., privacy accessibility, privacy for vulnerable populations, cross-cultural privacy).
Modern Genome Annotation : The Biosapiens Network
An accurate description of current scientific developments in the field of bioinformatics and computational implementation is presented by research of the BioSapiens Network of Excellence. Bioinformatics is essential for annotating the structure and function of genes, proteins and the analysis of complete genomes and to molecular biology and biochemistry. Included is an overview of bioinformatics, the full spectrum of genome annotation approaches including; genome analysis and gene prediction, gene regulation analysis and expression, genome variation and QTL analysis, large scale protein annotation of function and structure, annotation and prediction of protein interactions, and the organization and annotation of molecular networks and biochemical pathways. Also covered is a technical framework to organize and represent genome data using the DAS technology and work in the annotation of two large genomic sets: HIV/HCV viral genomes and splicing alternatives potentially encoded in 1% of the human genome.
Modern deep learning for tabular data : Novel approaches to common modeling problems
Synthesizes and presents novel deep learning approaches to a seemingly unlikely domain - tabular data. Whether for finance, business, security, medicine, or countless other domain, deep learning can help mine and model complex patterns in tabular data - an incredibly ubiquitous form of structured data. Part I of the book offers a rigorous overview of machine learning principles, algorithms, and implementation skills relevant to holistically modeling and manipulating tabular data. Part II studies five dominant deep learning model designs - Artificial Neural Networks, Convolutional Neural Networks, Recurrent Neural Networks, Attention and Transformers, and Tree-Rooted Networks - through both their 'default' usage and their application to tabular data. Part III compounds the power of the previously covered methods by surveying strategies and techniques to supercharge deep learning systems: autoencoders, deep data generation, meta-optimization, multi-model arrangement, and neural network interpretability.
Modern Deep Learning Design and Application Development : Versatile Tools to Solve Deep Learning Problems
Learn how to harness modern deep-learning methods in many contexts. Packed with intuitive theory, practical implementation methods, and deep-learning case studies, this book reveals how to acquire the tools you need to design and implement like a deep-learning architect. It covers tools deep learning engineers can use in a wide range of fields, from biology to computer vision to business. With nine in-depth case studies, this book will ground you in creative, real-world deep learning thinking. You will: Improve the performance of deep learning models by using pre-trained models, extracting rich features, and automating optimization. Compress deep learning models while maintaining performance. Reframe a wide variety of difficult problems and design effective deep learning solutions to solve them. Use the Keras framework, with some help from libraries like HyperOpt, TensorFlow, and PyTorch, to implement a wide variety of deep learning approaches.
Models for computer aided tolerancing in design and manufacturing ; Selected conference papers from the 9th CIRP International Seminar on Computer-aided tolerancing, held at Arizona State University, Tempe, Arizona, USA, 10-12 April, 2005
Computer Aided Tolerancing (CAT) is an important topic in any field of design and production where parts move relative to one another and/or are assembled together. Geometric variations from specified dimensions and form always occur when parts are manufactured. Improvements in production systems can cause the amounts of the variations to become smaller, but their presence does not disappear. To shorten the time from concept to market of a product, it has been increasingly important to take clearances and the tolerancing of manufacturing variations into consideration right from the beginning, at the stage of design. Hence, geometric models are defined that represent both the complete array of geometric variations possible during manufacture and also the influence of geometry on the function of individual parts and on assemblies of them.
Modelling, State Observation and Diagnosis of Quantised Systems
The book concerns quantised systems which emerge from continuous-variable systems by quantising the values of all signals. It is shown how this leads to an abstract system description by means of a stochastic automaton. Based on stochastic automata, new methods for the solution to state observation and fault diagnostic problems are derived. The methods are extended to networks of stochastic automata, allowing component-oriented modelling and, thus, to deal with complex systems. The practical applicability and usefulness of the approach is shown at several examples.
Modelling, Monitoring and Diagnostic Techniques for Fluid Power Systems
Modelling, Monitoring and Diagnostic Techniques for Fluid Power Systems covers the background theory of fluid power and indicates the range of concepts necessary for a modern approach to condition monitoring and fault diagnosis in a readable and understandable fashion. The theory is constantly leavened by 15 years' worth of practical measurements by the author, working in association with major fluid power companies, and real industrial case studies – hot-strip-mill monitoring in conjunction with Corus p.l.c. being just one example. Comprising four parts, it provides: • an introduction to component behaviour. • a guide to the modelling methods employed for circuit analysis. • methods for doing condition monitoring. • common faults and breakdowns.
Modelling, Computation and Optimization in Information Systems and Management Sciences ; 2nd International Conference MCO 2008, Metz, France - Luxembourg, September 8-10, 2008. Proceedings
This book constitutes the refereed proceedings of the Second International Conference MCO 2008, Metz, France, September 2008.The 65 revised full papers presented were carefully reviewed and selected from 160 submissions. The papers are organized in topical sections on optimization and decision making; data mining theory, systems and applications; computer vision and image processing; computer communications and networks; optimization and search techniques for security, reliability, trust.
Modelling Autonomic Communications Environments ; 3rd IEEE International Workshop, MACE 2008, Samos Island, Greece, September 22-26, 2008. Proceedings
Research and development of autonomics have come a long way, and we are delighted to present the proceedings of the 3rd IEEE International Workshop on Modelling Autonomic Communications Environments (MACE 2008).Asin the last two years, this workshopwasheld aspart of Manweek, the International Week on Management of Networks and Services, which took place on the lovely Island of Samos in Greece .MACE started as anexperimentin2006,andcreatedasmallcommunitythat nowfnds it self attracted backeachyearby afeeling ofexcitement-thatthere is something new going on. Certainly, MACE is not as shiny or practiced as other well-known conferences and workshops, but we consider this a feature of the workshopitself.
Modelling and Optimization of Biotechnological Processes : Artificial Intelligence Approaches
The book begins with a historical introduction to the field of bioprocess control based on artificial intelligence approaches, followed by two chapters covering the optimization of fed-batch culture using genetic algorithms. Online biomass soft-sensors are constructed in Chapter 4 using recurrent neural networks. The bioprocess is then modelled in Chapter 5 by cascading two soft-sensor neural networks. Optimization and validation of the final product are detailed in Chapters 6 and 7. The general conclusions are drawn in Chapter 8.
Modelling and Estimation Strategies for Fault Diagnosis of Non-Linear Systems : From Analytical to Soft Computing Approaches
This monograph presents a variety of techniques that can be used for designing robust fault diagnosis schemes for non-linear systems. The introductory part of the book is of a tutorial value and can be perceived as a good starting point for the new-comers to this field. Subsequently, advanced robust observer structures are presented. Parameter estimation based techniques are discussed as well. A particular attention is drawn to experimental design for fault diagnosis. The book also presents a number of robust soft computing approaches utilizing evolutionary algorithms and neural networks. All approaches described in this book are illustrated by practical applications.
Modelling and Development of Intelligent Systems ; 6th International Conference, MDIS 2019, Sibiu, Romania, October 3–5, 2019, Revised Selected Papers
This volume constitutes the refereed proceedings of the 6th International Conference on Modelling and Development of Intelligent Systems, MDIS 2019, held in Sibiu, Romania, in October 2019. The 13 revised full papers presented in the volume were carefully reviewed and selected from 31 submissions. The papers are organized in topical sections on adaptive systems; conceptual modelling; data mining; intelligent systems for decision support; machine learning.
Modelling and Analysis of Hybrid Supervisory Systems : A Petri Net Approach
Modelling and Analysis of Hybrid Supervisory Systems introduces a modelling formalism that merges Petri nets, differential equation systems and object-oriented methods; a formalism that is adequate for modelling complex and large-scale systems. To guide the designer and conduct hybrid modelling, the book describes a method that starts from the requirements of a supervisory system and results in a proposal for such a system. The method is mainly based on Unified Modelling Language diagrams, well-known tools in both academia and industry. In order to ensure that the supervisory system will behave as expected under any operational circumstances, a validation procedure that allows verification of the formal properties of the hybrid model is presented.
Modélisation et statistique spatiales = Spatial modeling and statistics
Spatial statistics are undergoing significant development due to their use in many fields: earth sciences, environment and climatology, epidemiology, econometrics, image analysis, etc. This book presents the main spatial models used as well as their statistics for the three types of data: geostatistics (observation on a continuous domain), data on a discrete network, point data. The objective is to present in a concise but mathematically complete way the most classical models (second order and variogram; software model and Gibbs-Markov field; point processes) as well as their simulation by MCMC algorithm. Then comes the presentation of statistical tools useful for their study.
Modeling, Simulation and Optimization of Complex Processes ; Proceedings of the Third International Conference on High Performance Scientific Computing, March 6–10, 2006, Hanoi, Vietnam
This proceedings volume contains a selection of papers presented at the Third International Conference on High Performance Scientific Computing held at the Hanoi Institute of Mathematics, Vietnamese Academy of Science and Technology (VAST), March 6-10, 2006. The conference has been organized by the Hanoi Institute of Mathematics, Interdisciplinary Center for Scientific Computing (IWR), Heidelberg, and its International PhD Program ``Complex Processes: Modeling, Simulation and Optimization'', and Ho Chi Minh City University of Technology. The contributions cover the broad interdisciplinary spectrum of scientific computing and present recent advances in theory, development of methods, and applications in practice. Subjects covered are mathematical modelling, numerical simulation, methods for optimization and control, parallel computing, software development, applications of scientific computing in physics, chemistry, biology and mechanics, environmental and hydrology problems, transport, logistics and site location, communication networks, production scheduling, industrial and commercial problems.
Modeling, Simulation and Optimization of Complex Processes ; Proceedings of the International Conference on High Performance Scientific Computing, March 10-14, 2003, Hanoi, Vietnam
This proceedings volume contains a selection of papers presented at the symposium "International Conference on High Performance Scientific Computing'' held at the Hanoi Institute of Mathematics of the Vietnam National Center for Natural Science and Technology (NCST). The contributions cover the broad interdisciplinary spectrum of scientific computing and present recent advances in theory, development of methods, and applications in practice. Subjects covered are mathematical modelling, numerical simulation, methods for optimization and optimal control, parallel computing, symbolic computing, software development, applications of scientific computing in physics, chemistry, biology and mechanics, environmental and hydrology problems, transport, logistics and site location, communication networks, production scheduling, industrial and commercial problems.
