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MaxEnt 2019—Proceedings, 2019, MaxEnt 2019The 39th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering

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ISBN: 9783039284764 9783039284771 Year: Pages: 312 DOI: 10.3390/books978-3-03928-477-1 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Mathematics
Added to DOAB on : 2020-04-07 23:07:09
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Abstract

This Proceedings book presents papers from the 39th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering, MaxEnt 2019. The workshop took place at the Max Planck Institute for Plasma Physics in Garching near Munich, Germany, from 30 June to 5 July 2019, and invited contributions on all aspects of probabilistic inference, including novel techniques, applications, and work that sheds new light on the foundations of inference. Addressed are inverse and uncertainty quantification (UQ) and problems arising from a large variety of applications, such as earth science, astrophysics, material and plasma science, imaging in geophysics and medicine, nondestructive testing, density estimation, remote sensing, Gaussian process (GP) regression, optimal experimental design, data assimilation, and data mining.

Swarm Robotics

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ISBN: 9783038979227 9783038979234 Year: Pages: 310 DOI: 10.3390/books978-3-03897-923-4 Language: English
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

Multi-Sensor Information Fusion

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ISBN: 9783039283026 9783039283033 Year: Pages: 602 DOI: 10.3390/books978-3-03928-303-3 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- General and Civil Engineering
Added to DOAB on : 2020-04-07 23:07:09
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This book includes papers from the section “Multisensor Information Fusion”, from Sensors between 2018 to 2019. It focuses on the latest research results of current multi-sensor fusion technologies and represents the latest research trends, including traditional information fusion technologies, estimation and filtering, and the latest research, artificial intelligence involving deep learning.

Keywords

linear regression --- covariance matrix --- data association --- sensor fusing --- SLAM --- multi-sensor data fusion --- conflicting evidence --- Dempster–Shafer evidence theory --- belief entropy --- similarity measure --- data classification --- fault diagnosis --- Bar-Shalom Campo --- Covariance Projection method --- data fusion --- distributed architecture --- Kalman filter --- linear constraints --- inconsistent data --- user experience evaluation --- user experience measurement --- eye-tracking --- facial expression --- galvanic skin response --- EEG --- interaction tracker --- self-reporting --- user experience platform --- mix-method approach --- image fusion --- multi-focus --- weight maps --- gradient domain --- fast guided filter. --- Dempster-Shafer evidence theory (DST) --- uncertainty measure --- open world --- closed world --- Deng entropy --- extended belief entropy --- sensor data fusion --- orthogonal redundant inertial measurement units --- data fusion architectures --- sensors bias --- fire source localization --- dynamic optimization --- global information --- the Range-Point-Range frame --- the Range-Range-Range frame --- sensor array --- SINS/DVL integrated navigation --- unscented information filter --- square root --- state probability approximation --- most suitable parameter form --- deep learning --- data preprocessing --- Human Activity Recognition (HAR) --- Internet of things (IoT) --- Industry 4.0 --- trajectory reconstruction --- low-cost sensors --- embedded systems --- powered two wheels (PTW) --- safe trajectory --- data fusion --- health management decision --- grey group decision-making --- health reliability degree --- maintenance decision --- sensor system --- least-squares filtering --- least-squares smoothing --- networked systems --- random parameter matrices --- random delays --- packet dropouts --- multi-sensor system --- multi-sensor information fusion --- particle swarm optimization --- sensor data fusion algorithm --- distributed intelligence system --- multi-sensor time series --- deep learning --- machine health monitoring --- time-distributed ConvLSTM model --- spatiotemporal feature learning --- optimal estimate --- unknown inputs --- distributed fusion --- augmented state Kalman filtering (ASKF) --- soft sensor --- coefficient of determination maximization strategy --- expectation maximization (EM) algorithm --- Gaussian mixture model (GMM) --- alumina concentration --- multi-sensor joint calibration --- high-dimensional fusion data (HFD) --- supervoxel --- Gaussian density peak clustering --- sematic segmentation --- multisensor data fusion --- multitarget tracking --- GMPHD --- sonar network --- RFS --- attitude estimation --- Kalman filter --- land vehicle --- magnetic angular rate and gravity (MARG) sensor --- quaternion --- yaw estimation --- network flow theory --- multitarget tracking --- spectral clustering --- A* search algorithm --- RTS smoother --- integer programming --- Surface measurement --- multi-sensor measurement --- surface modelling --- data fusion --- Gaussian process --- multi-sensor network --- observable degree analysis --- information fusion --- nonlinear system --- hybrid adaptive filtering --- weighted fusion estimation --- square-root cubature Kalman filter --- information filter --- surface quality control --- multi-sensor data fusion --- cutting forces --- vibration --- acoustic emission --- signal feature extraction methods --- predictive modeling techniques --- attitude --- orientation --- estimation --- Kalman filter --- quaternion --- manifold --- image registration --- evidential reasoning --- belief functions --- uncertainty --- DoS attack --- industrial cyber-physical system (ICPS) --- security zones --- mimicry security switch strategy --- fixed-point filter --- extended Kalman filter --- nested iterative method --- Steffensen’s iterative method --- convergence condition --- vehicular localization --- target positioning --- high-definition map --- vehicle-to-everything --- intelligent and connected vehicles --- intelligent transport system --- image registration --- non-rigid feature matching --- local structure descriptor --- Gaussian mixture model --- aircraft pilot --- workload --- multi-source data fusion --- fuzzy neural network --- principal component analysis --- parameter learning --- drift compensation --- domain adaption --- feature representations --- electronic nose --- data fusion --- dual gating --- MEMS accelerometer and gyroscope --- cardiac PET --- out-of-sequence --- multi-target tracking --- random finite set --- gaussian mixture probability hypothesis density --- multisensor system --- Gaussian process regression --- Bayesian reasoning method --- Dempster–Shafer evidence theory (DST) --- uncertainty measure --- novel belief entropy --- multi-sensor data fusion --- decision-level sensor fusion --- electronic nose --- subspace alignment --- interference suppression --- transfer --- evidence combination --- time-domain data fusion --- object classification --- uncertainty --- multirotor UAV --- precision landing --- artificial marker --- pose estimation --- sensor fusion --- camera --- LiDAR --- calibration --- plane matching --- ICP --- projection --- data fusion --- data registration --- adaptive distance function --- complex surface measurement --- Gaussian process model --- Dempster–Shafer evidence theory --- conflict measurement --- mutual support degree --- Hellinger distance --- Pignistic vector angle --- multi-sensor data fusion --- multi-environments --- state estimation --- unmanned aerial vehicle

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