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Uncertainty Estimation for Safe Human-Robot Collaboration Using Conservation Measures
We present an online and data-driven uncertainty quantification method to enable the development of safe human-robot collaboration applications....
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Evolving fuzzy neural classifier that integrates uncertainty from human-expert feedback
Evolving fuzzy neural networks are models capable of solving complex problems in a wide variety of contexts. In general, the quality of the data...
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Uncertainty Estimation
Estimating uncertainty is an important part of hydrological data modeling. They offer a measure of confidence in model predictions and aid in...
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Active Uncertainty Reduction for Human-Robot Interaction: An Implicit Dual Control Approach
The ability to accurately predict human behavior is central to the safety and efficiency of robot autonomy in interactive settings. Unfortunately,...
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Uncertainty Modelling in Performability Prediction for Safety-Critical Systems
Failure of safety-critical systems (SCSs) devastates human life and the environment and involves huge costs. So, quality assurance is essential for...
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Uncertainty Analysis in Hydrologic Modelling
Hydrologic modelsHydrologic model differ regarding hydrologic processes, their parameters, inputs and outputs. Consequently, the results of different...
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Influence of material parameter variability on the predicted coronary artery biomechanical environment via uncertainty quantification
Central to the clinical adoption of patient-specific modeling strategies is demonstrating that simulation results are reliable and safe. Indeed,...
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Entropy analysis of human death uncertainty
Uncertainty about the time of death is part of one’s life, and plays an important role in demographic and actuarial sciences. Entropy is a measure...
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Type-Reduction: Uncertainty Measures
This chapter introduces a computation called type-reduction that lets a type-2 fuzzy set (T2 FS) be projected into a type-1 fuzzy set. It does this...
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Quantifying Uncertainty in Hydrological Drought Index Using Calibrated SWAT Model
The hydrological model requires precise parameter calibration to reflect the basin characteristicsproperly. The optimum parameter values depend...
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Formal Modelling for Multi-Robot Systems Under Uncertainty
Purpose of ReviewTo effectively synthesise and analyse multi-robot behaviour, we require formal task-level models which accurately capture...
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Introduction to Handling Uncertainty in Artificial Intelligence
Uncertainty is a prevalent phenomenon in everyday interactions and many aspects of human life, particularly when dealing with information from...
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Sources of Uncertainty and Membership Functions
This chapter examines the kinds of uncertainties that motivate the use of type-2 fuzzy sets and systems and how data about words can be collected...
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Bayesian inference in the framework of uncertainty theory
Bayesian inference is one of the important topics in modern statistics. The information of the parameter in Bayesian statistics which is regarded as...
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Uncertainty-aware correspondence identification for collaborative perception
Correspondence identification is essential for multi-robot collaborative perception, which aims to identify the same objects in order to ensure...
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Time-dependent reliability of structures under consideration of epistemic uncertainty
Time-dependent reliability (TDR) is the possibility that a structure under consideration can perform the intended function under specified service...
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Epistemic Uncertainty Quantification in Human Trajectory Prediction
Human Trajectory Prediction (HTP) is a critical technology in several areas related to the development of smart cities, such as video monitoring or...
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Uncertainty and Modeling Principles
In this chapter, the types of uncertainty encountered in any scientific study are presented in terms of objective treatment procedures, especially...
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Social Influence Under Uncertainty in Interaction with Peers, Robots and Computers
Taking advice from others requires confidence in their competence. This is important for interaction with peers, but also for collaboration with...
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Uncertainty-guided dual-views for semi-supervised volumetric medical image segmentation
Deep learning has led to tremendous progress in the field of medical artificial intelligence. However, training deep-learning models usually require...
