A Model-Based Approach for User Requirements Decomposition and Component Selection

2015 ◽  
pp. 173-202 ◽  
Author(s):  
Mahin Abbasipour ◽  
Margarete Sackmann ◽  
Ferhat Khendek ◽  
Maria Toeroe
Keyword(s):  
User Requirements ◽  
Model Based ◽  
Component Selection

Automated Component-Selection of Design Synthesis for Physical Architecture with Model-Based Systems Engineering using Evolutionary Trade-off

2018 ◽  
Vol 28 (1) ◽  
pp. 1296-1310 ◽  
Author(s):  
Habibi Husain Arifin ◽  
Nasis Chimplee ◽  
Ho Kit Robert Ong ◽  
Jirapun Daengdej ◽  
Thotsapon Sortrakul
Keyword(s):  
Systems Engineering ◽  
Design Synthesis ◽  
Trade Off ◽  
Model Based ◽  
Component Selection ◽  
Model Based Systems Engineering ◽  
Selection Of

Model-Based Product Line Engineering with Genetic Algorithms for Automated Component Selection

2021 ◽  
pp. 287-310
Author(s):  
Habibi Husain Arifin ◽  
Ho Kit Robert Ong ◽  
Jie Dai ◽  
Wu Daphne ◽  
Nasis Chimplee
Keyword(s):  
Genetic Algorithms ◽  
Product Line ◽  
Product Line Engineering ◽  
Model Based ◽  
Component Selection ◽  
Line Engineering

scholarly journals A Routing Model Based on Multiple-User Requirements and the Optimal Solution

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 156470-156483
Author(s):  
Sheng Liu ◽  
Di Wu ◽  
Lanyong Zhang
Keyword(s):  
Optimal Solution ◽  
User Requirements ◽  
Model Based ◽  
Multiple User

A Taxonomy of User Requirements for Model-Based Diagnostic Systems

1999 ◽  
Vol 32 (2) ◽  
pp. 7778-7783 ◽  
Author(s):  
M.J. Chantler ◽  
T.K. Wyatt ◽  
A. Aldea ◽  
G. McGunnigle
Keyword(s):  
User Requirements ◽  
Diagnostic Systems ◽  
Model Based

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.

Model-Based Clustering and Classification for Data Science

2019 ◽  
Author(s):  
Charles Bouveyron ◽  
Gilles Celeux ◽  
T. Brendan Murphy ◽  
Adrian E. Raftery
Keyword(s):  
Data Science ◽  
Model Based Clustering ◽  
Model Based ◽  
Clustering And Classification
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