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Identifikation des menschlichen Bewegungsverhaltens auf der Basis von Primitiven

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Book Series: Karlsruher Beiträge zur Regelungs- und Steuerungstechnik / Karlsruher Institut für Technologie, Institut für Regelungs- und Steuerungssysteme ISSN: 25116312 ISBN: 9783731506089 Year: Volume: 1 Pages: LII, 124 p. DOI: 10.5445/KSP/1000062214 Language: GERMAN
Publisher: KIT Scientific Publishing
Subject: Technology (General)
Added to DOAB on : 2019-07-30 20:02:02
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The consideration of discrete motor primitives in models of human motor control is essential for the realistic prediction of voluntary movements. In this book a formal movement model is derived from neurobiological findings as well as new identification and learning methods are presented for the secured determination of the model parameters. Both the model and the identification methods are demonstrated using the example of predicting human driver steering movements.

Biological Networks

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ISBN: 9783038974338 / 9783038974345 Year: Pages: 174 DOI: 10.3390/books978-3-03897-434-5 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: General and Civil Engineering --- Internal medicine --- Biology
Added to DOAB on : 2019-01-10 11:14:23
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Networks of coordinated interactions among biological entities govern a myriad of biological functions that span a wide range of both length and time scales—from ecosystems to individual cells and from years to milliseconds. For these networks, the concept “the whole is greater than the sum of its parts” applies as a norm rather than an exception. Meanwhile, continued advances in molecular biology and high-throughput technology have enabled a broad and systematic interrogation of whole-cell networks, allowing the investigation of biological processes and functions at unprecedented breadth and resolution—even down to the single-cell level. The explosion of biological data, especially molecular-level intracellular data, necessitates new paradigms for unraveling the complexity of biological networks and for understanding how biological functions emerge from such networks. These paradigms introduce new challenges related to the analysis of networks in which quantitative approaches such as machine learning and mathematical modeling play an indispensable role. The Special Issue on “Biological Networks” showcases advances in the development and application of in silico network modeling and analysis of biological systems.

Process Modelling and Simulation

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ISBN: 9783039214556 / 9783039214563 Year: Pages: 298 DOI: 10.3390/books978-3-03921-456-3 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2019-12-09 11:49:15
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Since process models are nowadays ubiquitous in many applications, the challenges and alternatives related to their development, validation, and efficient use have become more apparent. In addition, the massive amounts of both offline and online data available today open the door for new applications and solutions. However, transforming data into useful models and information in the context of the process industry or of bio-systems requires specific approaches and considerations such as new modelling methodologies incorporating the complex, stochastic, hybrid and distributed nature of many processes in particular. The same can be said about the tools and software environments used to describe, code, and solve such models for their further exploitation. Going well beyond mere simulation tools, these advanced tools offer a software suite built around the models, facilitating tasks such as experiment design, parameter estimation, model initialization, validation, analysis, size reduction, discretization, optimization, distributed computation, co-simulation, etc. This Special Issue collects novel developments in these topics in order to address the challenges brought by the use of models in their different facets, and to reflect state of the art developments in methods, tools and industrial applications.

Keywords

process model validation --- partial least square regression --- phytochemicals --- natural extracts --- wheat germ --- fluidized bed drying --- mathematical model --- moisture content --- condensation --- simulation --- Pharmaceutical Processes --- Mammalian Cell Culture --- sensitivity analysis --- parameter estimation --- Design of Experiments --- algebraic modeling language --- dynamic optimization --- model predictive control --- moving horizon estimation --- fluid bed granulation --- heat and mass balance --- population balance model --- binder dissolution --- kernel development --- robust optimization --- uncertainty --- point estimation method --- equality constraints --- parameter correlation --- barley --- simulation --- hydration --- swelling --- cooking --- porridge --- extents --- graph theory --- model identification --- observability --- optimal clustering --- parameter estimation --- state decoupling --- data-mining --- machine learning --- neural networks --- chemistry --- materials --- engineering --- energy --- grey-box model --- machine learning --- SOS programming --- process modeling --- scrap dissolution --- scrap melting --- thermodynamics --- kinetics --- dynamic converter modelling --- Combined Heat and Power --- gray-box model --- utility management --- CHP legislation --- optimization --- polyacrylonitrile-based carbon fiber --- coagulation bath --- dry-jet wet spinning process --- computational fluid dynamics --- wave resonance --- maximum wave amplitude --- reactor coolant pump --- vane --- costing stopping --- mathematical model --- idling test --- n/a

Swarm Robotics

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ISBN: 9783038979227 / 9783038979234 Year: Pages: 310 DOI: 10.3390/books978-3-03897-923-4 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Computer Science
Added to DOAB on : 2019-06-26 08:44:06
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Collectively working robot teams can solve a problem more efficiently than a single robot, while also providing robustness and flexibility to the group. Swarm robotics model is a key component of a cooperative algorithm that controls the behaviors and interactions of all individuals. The robots in the swarm should have some basic functions, such as sensing, communicating, and monitoring, and satisfy the following properties:

Keywords

3D model identification --- shape normalization --- weighted implicit shape representation --- panoramic view --- scale-invariant feature transform --- optimization --- meta-heuristic --- parallel technique --- Swarm intelligence algorithm --- artificial flora (AF) algorithm --- bionic intelligent algorithm --- particle swarm optimization --- artificial bee colony algorithm --- swarm robotics --- search --- surveillance --- behaviors --- patterns --- comparison --- swarm behavior --- Swarm Chemistry --- self-organization --- asymmetrical interaction --- genetic algorithm --- cooperative target hunting --- multi-AUV --- improved potential field --- surface-water environment --- signal source localization --- multi-robot system --- event-triggered communication --- consensus control --- time-difference-of-arrival (TDOA) --- Cramer–Rao low bound (CRLB) --- optimal configuration --- UAV swarms --- path optimization --- multiple robots --- formation --- sliding mode controller --- nonlinear disturbance observer --- system stability --- formation control --- virtual structure --- formation reconfiguration --- multi-agents --- robotics --- unmanned aerial vehicle --- swarm intelligence --- particle swarm optimization --- search algorithm --- underwater environment --- sensor deployment --- event-driven coverage --- fish swarm optimization --- congestion control --- modular robots --- self-assembly robots --- environmental perception --- target recognition --- autonomous docking --- formation control --- virtual linkage --- virtual structure --- formation reconfiguration --- mobile robots --- robotics --- swarm robotics --- formation control --- coordinate motion --- obstacle avoidance --- n/a

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