12 papers · ranked by Valyu relevance
San Dinh, Claudemi A. Nascimento, David S. Mebane, Fernando V. Lima
Implementation of Dynamic Discrepancy Reduced-Order Modeling in Advanced Process Control Authors: San Dinh, Claudemi A. Nascimento, David S. Mebane, Fernando V. Lima This paper introduces a novel framework for implementing dynamic discrepancy reduced-order modeling in advanced process control. This framework balances…
Abhisek Tiwari, Tulika Saha, Sriparna Saha, Shubhashis Sengupta + 4 more
The fundamental component of any dialogue system is the dialogue manager, which should be capable enough to pick appropriate action depending on the conversational context. These sequences of appropriate actions help the end-user to complete his/her task successfully. We propose a dynamic goal-adapted dialogue manager…
Jun Wu, Jingrui He
Dynamic transfer learning refers to the knowledge transfer from a static source task with adequate label information to a dynamic target task with little or no label information. However, most existing theoretical studies and practical algorithms of dynamic transfer learning assume that the target task is continuously…
Joseph G. Shuttleworth, Chon Lok Lei, Dominic G. Whittaker, Monique J. Windley + 3 more
'Monique J. Windley' 'Adam P. Hill' 'Simon P. Preston' 'Gary R. Mirams'] When using mathematical models to make quantitative predictions for clinical or industrial use, it is important that predictions come with a reliable estimate of their accuracy (uncertainty quantification). Because models of complex biological…
Chon Lok Lei, Sanmitra Ghosh, Dominic G. Whittaker, Yasser Aboelkassem + 13 more
Uncertainty quantification (UQ) is a vital step in using mathematical models and simulations to take decisions. The field of cardiac simulation has begun to explore and adopt UQ methods to characterize uncertainty in model inputs and how that propagates through to outputs or predictions; examples of this can be seen in…
Robin Umbra, Ulrike Fasbender
This manuscript introduces the Interaction Discrepancy Model (IDM), a theoretical framework designed to enhance our understanding of person-environment interactions. Traditional models often overlook the dynamic, iterative, and feedback-driven nature of these interactions, typically focusing on episodic and isolated…
Rebecca E. Morrison
In many applications of interacting systems, we are only interested in the dynamic behavior of a subset of all possible active species. For example, this is true in combustion models (many transient chemical species are not of interest in a given reaction) and in epidemiological models (only certain subpopulations are…
Amer Kajmakovic, Konrad Diwold, Kay Römer, Jesus Pestana + 2 more
'Nermin Kajtazovic' 'Hossam A. Gabbar'] Safety-critical automation often requires redundancy to enable reliable system operation. In the context of integrating sensors into such systems, the one-out-of-two (1oo2) sensor architecture is one of the common used methods used to ensure the reliability and traceability of…
Benjamin Engelhardt, Holger Frőhlich, Maik Kschischo
Mathematical modelling is a labour intensive process involving several iterations of testing on real data and manual model modifications. In biology, the domain knowledge guiding model development is in many cases itself incomplete and uncertain. A major problem in this context is that biological systems are open.…
Michael Goldstein, Ian Vernon, Jonathan A. Cumming
Model or structural discrepancy is an essential component in the analysis of computer simulators, representing the differences between the outputs of the simulator and the real-world system that the simulator seeks to represent. This discrepancy can arise from various sources such as simplifications of the model…
Federico Chiariotti, Chiara Pielli, Andrea Zanella, Michele Zorzi
Bike-sharing services are flourishing in Smart Cities worldwide. They provide a low-cost and environment-friendly transportation alternative and help reduce traffic congestion. However, these new services are still under development, and several challenges need to be solved. A major problem is the management of…
Ross Goutcher, Lauren Murray, Brooke Benz
Motion-in-depth perception is critical in enabling animals to avoid hazards and respond to potential threats. For humans, important visual cues for motion-in-depth include changing disparity (CD) and changing image size (CS). The interpretation and integration of these cues depends upon multiple scene parameters, such…