scholarly journals SARS-CoV-2 Spread Forecast Dynamic Model Validation through Digital Twin Approach, Catalonia Case Study

Mathematics ◽  
2021 ◽  
Vol 9 (14) ◽  
pp. 1660
Author(s):  
Pau Fonseca i Casas ◽  
Joan Garcia i Subirana ◽  
Víctor García i Carrasco ◽  
Xavier Pi i Palomés
Keyword(s):  
Model Comparison ◽  
Dynamic Models ◽  
Complex Nature ◽  
Description Language ◽  
Digital Twin ◽  
Modeling Process ◽  
Lack Of Information ◽  
Comparison Approach ◽  
Nonpharmaceutical Interventions

The spread of the SARS-CoV-2 modeling is a challenging problem because of its complex nature and lack of information regarding certain aspects. In this paper, we explore a Digital Twin approach to model the pandemic situation in Catalonia. The Digital Twin is composed of three different dynamic models used to perform the validations by a Model Comparison approach. We detail how we use this approach to obtain knowledge regarding the effects of the nonpharmaceutical interventions and the problems we faced during the modeling process. We use Specification and Description Language (SDL) to represent the compartmental forecasting model for the SARS-CoV-2. Its graphical notation simplifies the different specialists’ understanding of the model hypotheses, which must be validated continuously following a Solution Validation approach. This model allows the successful forecasting of different scenarios for Catalonia. We present some formalization details, discuss the validation process and present some results obtained from the validation model discussion, which becomes a digital twin of the pandemic in Catalonia.

The Art of Model Development

1999 ◽  
Author(s):  
Ronald K. Pearson
Keyword(s):  
Discrete Time ◽  
Dynamic Models ◽  
Empirical Modeling ◽  
Model Structure ◽  
Time Dynamic ◽  
Structure Selection ◽  
Modeling Process ◽  
Class C ◽  
Model Structure Selection

The primary objective of this book has been to present a reasonably broad overview of the different classes of discrete-time dynamic models that have been proposed for empirical modeling, particularly in the process control literature. In its simplest form, the empirical modeling process consists of the following four steps: 1. Select a class C of model structures 2. Generate input/output data from the physical process P 3. Determine the model M ∊ C that best fits this dataset 4. Assess the general validity of the model M. The objective of this final chapter is to briefly examine these four modeling steps, with particular emphasis on the first since the choice of the model class C ultimately determines the utility of the empirical model, both with respect to the application (e.g., the difficulty of solving the resulting model-based control problem) and with respect to fidelity of approximation. Some of the basic issues of model structure selection are introduced in Sec. 8.1 and a more detailed treatment is given in Sec. 8.3, emphasizing connections with results presented in earlier chapters; in addition, the problem of model structure selection is an important component of the case studies presented in Secs. 8.2 and 8.5. The second step in this procedure—input sequence design—is discussed in some detail in Sec. 8.4 and is an important component of the second case study (Sec. 8.5). The literature associated with the parameter estimation problem—the third step in the empirical modeling process—is much too large to attempt to survey here, but a brief summary of some representative results is given in Sec. 8.1.1. Finally, the task of model validation often depends strongly on the details of the physical system being modelled and the ultimate application intended for the model. Consequently, detailed treatment of this topic also lies beyond the scope of this book but again, some representative results are discussed briefly in Sec. 8.1.3 and illustrated in the first case study (Sec. 8.2). Finally, Sec. 8.6 concludes both the chapter and the book with some philosophical observations on the problem of developing moderate-complexity, discrete-time dynamic models to approximate the behavior of high-complexity, continuous-time physical systems.

scholarly journals Digital Twin for Designing and Reconfiguring Human–Robot Collaborative Assembly Lines

2021 ◽  
Vol 11 (10) ◽  
pp. 4620
Author(s):  
Niki Kousi ◽  
Christos Gkournelos ◽  
Sotiris Aivaliotis ◽  
Konstantinos Lotsaris ◽  
Angelos Christos Bavelos ◽  
...  
Keyword(s):  
Production System ◽  
Assembly Lines ◽  
Flexible Assembly ◽  
Digital Twin ◽  
Collaborative Assembly ◽  
Geometrical Information ◽  
Line Level ◽  
Dual Arm ◽  
Different Levels

This paper discusses a digital twin-based approach for designing and redesigning flexible assembly systems. The digital twin allows modeling the parameters of the production system at different levels including assembly process, production station, and line level. The approach allows dynamically updating the digital twin in runtime, synthesizing data from multiple 2D–3D sensors in order to have up-to-date information about the actual production process. The model integrates both geometrical information and semantics. The model is used in combination with an artificial intelligence logic in order to derive alternative configurations of the production system. The overall approach is discussed with the help of a case study coming from the automotive industry. The case study introduces a production system integrating humans and autonomous mobile dual arm workers.

scholarly journals A Bayesian model comparison approach to test the specificity of visual integration impairment in schizophrenia or psychosis

2018 ◽  
Vol 265 ◽  
pp. 271-278 ◽  
Author(s):  
Tyler B. Grove ◽  
Beier Yao ◽  
Savanna A. Mueller ◽  
Merranda McLaughlin ◽  
Vicki L. Ellingrod ◽  
...  
Keyword(s):  
Bayesian Model ◽  
Model Comparison ◽  
Visual Integration ◽  
Bayesian Model Comparison ◽  
Comparison Approach

Subsystem selection for digital twin development: A case study on an unmanned underwater vehicle

2021 ◽  
Vol 223 ◽  
pp. 108629
Author(s):  
Demetrious T. Kutzke ◽  
James B. Carter ◽  
Benjamin T. Hartman
Keyword(s):  
Underwater Vehicle ◽  
Digital Twin ◽  
Unmanned Underwater Vehicle ◽  
Selection For

scholarly journals Definiteness Systems and Dialect Classification

Languages ◽  
2021 ◽  
Vol 6 (3) ◽  
pp. 128
Author(s):  
Mike Turner
Keyword(s):  
Binary System ◽  
Recent Work ◽  
Classification Schemes ◽  
Modeling Process ◽  
Arabic Dialects ◽  
Dialect Classification ◽  
Semantic Typology

In this article I explore how typological approaches can be used to construct novel classification schemes for Arabic dialects, taking the example of definiteness as a case study. Definiteness in Arabic has traditionally been envisioned as an essentially binary system, wherein definite substantives are marked with a reflex of the article al- and indefinite ones are not. Recent work has complicated this model, framing definiteness instead as a continuum along which speakers can locate referents using a broader range of morphological and syntactic strategies, including not only the article al-, but also reflexes of the demonstrative series and a diverse set of ‘indefinite-specific’ articles found throughout the spoken dialects. I argue that it is possible to describe these strategies with even more precision by modeling them within cross-linguistic frameworks for semantic typology, among them a model known as the ‘Reference Hierarchy,’ which I adopt here. This modeling process allows for classification of dialects not by the presence of shared forms, but rather by parallel typological configurations, even if the forms within them are disparate.

Development of a Digital Twin of a Local Road Network: A Case Study

2021 ◽  
Vol 51 (1) ◽  
pp. 20210043
Author(s):  
Wynand JvdM Steyn ◽  
André Broekman
Keyword(s):  
Road Network ◽  
Digital Twin ◽  
Local Road

scholarly journals Automated optimal flight planning based on the aircraft intent description language

2018 ◽  
Vol 233 (3) ◽  
pp. 928-948
Author(s):  
Daniel González-Arribas ◽  
Manuel Soler ◽  
Javier López-Leonés ◽  
Enrique Casado ◽  
Manuel Sanjurjo-Rivo
Keyword(s):  
Optimal Control ◽  
Traffic Management ◽  
Modular Design ◽  
Air Traffic Management ◽  
Generation Process ◽  
Trajectory Prediction ◽  
Description Language ◽  
Traffic Management System ◽  
Automated Tools

The future air traffic management system is to be built around the notion of trajectory-based operations. It will rely on automated tools related to trajectory prediction in order to define, share, revise, negotiate and update the trajectory of the aircraft before and during the flight, in some case, in near real time. This paper illustrates how existing standards on trajectory description such as the aircraft intent description language can be enhanced including optimisation capabilities based on numerical optimal control. The Aircraft Intent Description Language is a formal language that has been created in order to describe aircraft intent information in a rigorous, unambiguous and flexible manner. It has been implemented in a platform for a modular design of the trajectory generation process. A case study is presented to explore its effectiveness and identify the requirements and needs to generate optimised aircraft intents with higher automation and flexibility. Preliminary results show the suitability of numerical optimal control to design optimised aircraft intents based on the aircraft intent description language.

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