Overlapping Clustering Based Technique for Scalable Uncertainty Quantification in Physical Systems

2020 ◽  
Vol 8 (3) ◽  
pp. 827-859
Author(s):  
Arpan Mukherjee ◽  
Rahul Rai ◽  
Puneet Singla ◽  
Tarunraj Singh ◽  
Abani Patra
Keyword(s):  
Uncertainty Quantification ◽  
Physical Systems ◽  
Overlapping Clustering

Uncertainty Quantification in Models of Microfluid Systems

2003 ◽  
Author(s):  
Habib N. Najm ◽  
Bert J. Debusschere ◽  
Omar M. Knio ◽  
Roger R. Ghanem ◽  
Alain Matta ◽  
...  
Keyword(s):  
Uncertainty Quantification ◽  
Equilibrium Constants ◽  
Protein Labeling ◽  
Layer Potential ◽  
Physical Systems ◽  
Model Predictions ◽  
Model Protein ◽  
Full Coupling ◽  
Predicted Model ◽  
The Impact

Uncertainty quantification (UQ) in models of physical systems is a necessary tool for both model validation and engineering design optimization. We have applied UQ tools using stochastic spectral polynomial chaos techniques to the modeling of fluid flow in an electrokinetically driven microchannel, allowing for detailed buffer electrochemistry and finite rate analyte reactions. The model includes full coupling of wall electric double layer potential with variations in PH and local electric field. Allowing for uncertainties in species mobilities, buffer equilibrium constants, and wall properties, we have computed the resulting uncertainty in predicted model outputs, illustrating the impact of growth of uncertainty on confidence in model predictions. We present details of the computational UQ techniques with specific focus on their application in the electrochemical micro fluidic context. We also present UQ results pertaining to model protein labeling in an electokinetically-pumped microchannel flow.

Emerging Cyber-Physical Systems : An Overview

2018 ◽  
pp. 306-316
Author(s):  
Okolie S.O. ◽  
Kuyoro S.O. ◽  
Ohwo O. B
Keyword(s):  
Health Care ◽  
Economic Benefit ◽  
Physical World ◽  
Cyber Physical Systems ◽  
Cyber Physical System ◽  
Economic Sectors ◽  
Strategic Research ◽  
Physical Systems ◽  
Security Issues ◽  
Wide Range

Cyber-Physical Systems (CPS) will revolutionize how humans relate with the physical world around us. Many grand challenges await the economically vital domains of transportation, health-care, manufacturing, agriculture, energy, defence, aerospace and buildings. Exploration of these potentialities around space and time would create applications which would affect societal and economic benefit. This paper looks into the concept of emerging Cyber-Physical system, applications and security issues in sustaining development in various economic sectors; outlining a set of strategic Research and Development opportunities that should be accosted, so as to allow upgraded CPS to attain their potential and provide a wide range of societal advantages in the future.

Security of Cyber-Physical Systems: A Generalized Algorithm for Intrusion Detection and Determining Security Robustness of Cyber Physical Systems using Logical Truth Tables

2013 ◽  
Vol 9 ◽  
Author(s):  
Curtis G. Northcutt
Keyword(s):  
Intrusion Detection ◽  
Cyber Security ◽  
Logical Truth ◽  
Cyber Physical Systems ◽  
Security Model ◽  
Security Measures ◽  
Physical Systems ◽  
Multiple Signal ◽  
Security Attack ◽  
Truth Tables

The recent proliferation of embedded cyber components in modern physical systems [1] has generated a variety of new security risks which threaten not only cyberspace, but our physical environment as well. Whereas earlier security threats resided primarily in cyberspace, the increasing marriage of digital technology with mechanical systems in cyber-physical systems (CPS), suggests the need for more advanced generalized CPS security measures. To address this problem, in this paper we consider the first step toward an improved security model: detecting the security attack. Using logical truth tables, we have developed a generalized algorithm for intrusion detection in CPS for systems which can be defined over discrete set of valued states. Additionally, a robustness algorithm is given which determines the level of security of a discrete-valued CPS against varying combinations of multiple signal alterations. These algorithms, when coupled with encryption keys which disallow multiple signal alteration, provide for a generalized security methodology for both cyber-security and cyber-physical systems.

INVERSE UNCERTAINTY QUANTIFICATION OF A CELL MODEL USING A GAUSSIAN PROCESS METAMODEL

2020 ◽  
Vol 10 (4) ◽  
pp. 333-349
Author(s):  
Kevin de Vries ◽  
Anna Nikishova ◽  
Benjamin Czaja ◽  
Gábor Závodszky ◽  
Alfons G. Hoekstra
Keyword(s):  
Gaussian Process ◽  
Uncertainty Quantification ◽  
Cell Model ◽  
A Cell
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