Model Based Development of Vehicle System Using 1D-CAE

2017 ◽  
Vol 2017.30 (0) ◽  
pp. F02-5
Author(s):  
Yutaka Hirano
Keyword(s):  
Model Based ◽  
Vehicle System

Proposal of Model-based HMI Development Method for In-vehicle System

2018 ◽  
Vol 138 (11) ◽  
pp. 1435-1443
Author(s):  
Yoshitaka Atarashi ◽  
Manabu Morita ◽  
Norihisa Komoda
Keyword(s):  
Development Method ◽  
Model Based ◽  
Vehicle System

Model Based Diagnostics for Vehicle Systems

2000 ◽  
Author(s):  
Pierluigi Pisu ◽  
Giorgio Rizzoni ◽  
Ahmed Soliman ◽  
Sanket Amberkar ◽  
Brian Murray ◽  
...  
Keyword(s):  
Fault Detection ◽  
Control Systems ◽  
System Performance ◽  
Vehicle Control ◽  
Focused Attention ◽  
Vehicle Performance ◽  
Model Based ◽  
Vehicle System ◽  
Vehicle Systems ◽  
Diagnosis Method

Abstract In recent years, increasing interest and requirement for improved vehicle performance, reliability and safety has focused attention on the use of Fault Detection & Isolation when designing vehicle control systems. In order to achieve this FDI schemes, particular vehicle subsystems integrated with a controller have been proposed. This paper introduces a new Model-Based Fault Detection and Fault Diagnosis method for monitoring the overall vehicle system performance.

Representation, abstraction, and simple-minded sophisticates

2020 ◽  
Vol 43 ◽  
Author(s):  
Peter Dayan
Keyword(s):  
Decision Theory ◽  
Predictive Coding ◽  
Bayesian Decision Theory ◽  
Bayesian Decision ◽  
Model Based ◽  
Model Free

Abstract Bayesian decision theory provides a simple formal elucidation of some of the ways that representation and representational abstraction are involved with, and exploit, both prediction and its rather distant cousin, predictive coding. Both model-free and model-based methods are involved.

Quantitative Model-Based Image Analysis of NuMa Distribution Links Nuclear Organization with Cell Phenotype

2001 ◽  
Vol 7 (S2) ◽  
pp. 578-579
Author(s):  
David W. Knowles ◽  
Sophie A. Lelièvre ◽  
Carlos Ortiz de Solόrzano ◽  
Stephen J. Lockett ◽  
Mina J. Bissell ◽  
...  
Keyword(s):  
Image Analysis ◽  
Mammary Epithelial Cells ◽  
Nuclear Organization ◽  
Critical Role ◽  
Quantitative Model ◽  
Mammary Epithelial ◽  
Cell Phenotype ◽  
Proliferating Cells ◽  
Mitotic Apparatus ◽  
Model Based

The extracellular matrix (ECM) plays a critical role in directing cell behaviour and morphogenesis by regulating gene expression and nuclear organization. Using non-malignant (S1) human mammary epithelial cells (HMECs), it was previously shown that ECM-induced morphogenesis is accompanied by the redistribution of nuclear mitotic apparatus (NuMA) protein from a diffuse pattern in proliferating cells, to a multi-focal pattern as HMECs growth arrested and completed morphogenesis . A process taking 10 to 14 days.To further investigate the link between NuMA distribution and the growth stage of HMECs, we have investigated the distribution of NuMA in non-malignant S1 cells and their malignant, T4, counter-part using a novel model-based image analysis technique. This technique, based on a multi-scale Gaussian blur analysis (Figure 1), quantifies the size of punctate features in an image. Cells were cultured in the presence and absence of a reconstituted basement membrane (rBM) and imaged in 3D using confocal microscopy, for fluorescently labeled monoclonal antibodies to NuMA (fαNuMA) and fluorescently labeled total DNA.

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